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In pediatric patients, respiratory viruses (RVs) are considered important pathogens in acute respiratory tract infections, resulting in hospitalization and acute care visits [1] [2] [3] for which diagnostic evaluations for RVs are frequently performed [4] . However, diagnostic evalua-tions for RVs are rarely performed in adult patients because such viruses cause only benign respiratory tract infections [4] . Recently, with the advent of more sensitive molecular techniques, clinical cases of pneumonia associated with variable RVs have been reported with increasing frequency in adult patients [5, 6] . The importance of RVs in adult patients has also been emphasized www.kjim.org http://dx.doi.org/10.3904/kjim.2015.30. 1.96 with the emergence of severe acute respiratory syndrome, avian influenza A (H5N1), and pandemic influenza H1N1 in 2009 [3] . In the near future, RV detection tests may be considered an essential part of the diagnostic work-up for adult patients with acute respiratory tract infections. However, physicians treating adult patients are not yet familiar with RV detection tests. We investigated the current utilization of a multiplex reverse transcription-polymerase chain reaction (RT-PCR) test for RVs in adult patients in clinical practice. The multiplex RT-PCR test allows the detection of a large number of RVs simultaneously with a higher sensitivity than viral culture [7] . We hypothesized that utilization data and results from current multiplex RT-PCR tests would be helpful in identifying the benefits and problems associated with multiplex RT-PCR utilization in adult patients.
This study was performed at Chung-Ang University Hospital, an 850-bed, tertiary care teaching hospital in Seoul, Republic of Korea. Adult patients (> 16 years of age) who underwent multiplex RT-PCR testing between January 2012 and April 2013 were identified and their electronic medical records and chest radiographs reviewed. Demographic characteristics, underlying diseases, multiplex RT-PCR results, the presence of respiratory symptoms, and clinical outcomes were investigated.
An upper respiratory infection (URI) was defined as the presence of ≥ 1 of the following respiratory symptoms: cough, sputum production, rhinorrhea, sore throat, and dyspnea. Pneumonia was defined as the presence of a new or progressive infiltrate on chest radiography plus two or more of the following symptoms or signs: fever, sputum production, rhinorrhea, sore throat, dyspnea, and the attending physician's diagnosis of pneumonia. A nonrespiratory infection (NRI) was defined as neither a URI nor pneumonia. If a patient had an episode of acute infection within 2 days after admission and underwent multiplex RT-PCR testing for the episode, he or she was considered to have received a test for a community-acquired infection. The flu season was defined as between January and April in 2012 and between January and April in 2013. The flu season was determined based on the Weekly Surveillance Reports for Influenza and Other Respiratory Viruses of the Korea Centers for Disease Control and Prevention [8] .
During the study period, nasopharyngeal specimens obtained using a flocked swab were submitted in Universal Transport Medium (COPAN, Brescia, Italy). Nasopharyngeal specimens were submitted for RV7 detection between January 2012 and December 2012 and for RV16 detection between January 2013 and April 2013.
Nucleic acids were extracted from 300-μL specimens using a Viral Gene-Spin Viral DNA/RNA Extraction Kit (iNtRON Biotechnology, Seongnam, Korea). cDNAs were synthesized from the extracted RNAs with cDNA Synthesis Premix (Seegene, Seoul, Korea) and a GeneAmp PCR System 9700 thermal cycler (Applied Biomaterials, Foster City, CA, USA).
RV7 testing was performed to detect the following viruses: adenovirus, influenza viruses A and B, respiratory syncytial virus (RSV), human metapneumovirus (HMPV), and human rhinovirus (HRV) A. PCR was performed using a Seeplex RV7 Detection Kit (Seegene) according to the manufacturer's instructions with a GeneAmp PCR System 9700 thermal cycler (Applied Biomaterials). The products were separated on 2% agarose gels containing 0.5 g of ethidium bromide/mL in Tri-borate-EDTA buffer and were visualized under ultraviolet light. PCR, according to the manufacturer's instructions. An Anyplex II RV16 Detection Kit (Seegene) was used to detect fourteen types of RNA viruses and two types of DNA viruses, according to the manufacturer's instructions. Briefly, the assay was conducted in a final volume of 20 μL containing 8 μL of cDNA, 4 μL of 5 × RV primer, 4 μL of 8-methoxypsoralen solution, and 4 μL of 5 × master mix with the CFX96 real-time PCR detection system (Bio-Rad Laboratories Inc., Hercules, CA, USA).
Statistical analyses were performed using SPSS version 18.0 (SPSS Inc., Chicago, IL, USA). Continuous variables were compared using Student t test or the Mann-Whitney U test. Categorical variables were compared using a chi-square test or Fisher exact test.
During the study period, multiplex RT-PCR testing was performed for 291 respiratory samples from 282 adult patients. During the same period, rapid influenza antigen detection tests were performed for 5,890 nasopharyngeal swab samples and bacterial cultures were performed for 38,195 respiratory samples in the study hospital. Thus, the frequency of multiplex RT-PCR testing was only 4.9% of rapid influenza antigen detection tests and 0.8% of respiratory bacterial cultures. The mean turnaround time for the 81 positive multiplex RT-PCR tests was 66.1 hours (SD, 24.2; range, 20.4 to 119.7). A turnaround time of < 48 hours was observed in 25.9% (21/81) of the 81 positive tests. The characteristics of the 291 cases are summarized in Table 1 . The mean patient age was 59.5 years and more than half were male (176, 60.5%). The most common underlying disease was diabetes mellitus (17.9%), followed by chronic lung disease (7.9%), solid tumor (7.6%), hematologic malignancy (5.2%), and chronic renal failure (3.8%). Multiplex RT-PCR testing was performed most frequently in cases of pneumonia (58.4%), followed by URI (21.3%) and NRI (20.3%). The majority of multiplex RT-PCR tests were performed for admitted patients (97.9%) with community-acquired infections (84.2%) during the flu season (82.5%). Patients who underwent multiplex RT-PCR for an NRI had the following diseases: urinary tract infections, acute gastroenteritis, acute hepatitis, febrile neutropenia, meningitis, mediastinitis, pulmonary tuberculosis, mumps, chickenpox, acute cholangitis, Escherichia coli bacteremia of unknown origin, enteric fever, Clostridium difficile infection, acute appendicitis, cellulitis, cervical lymphadenitis, hemorrhagic cystitis, cerebrovascular accidents, seizure, hyperventilation syndrome, and angina. In patients with an NRI, multiplex RT-PCR testing was performed due to the presence of a fever of unknown origin during the flu or nonflu season. The list of detected RVs is presented in Table 2 . RVs were identified in 81 of 291 samples (27.8%), with influenza as the most commonly identified (47/81, 58.0%). Influenza (27.4% vs. 14.1%, p = 0.02) and human coronavirus (6.4% vs. 1.2%, p = 0.04) were more frequently detected in patients with a URI than in those with pneumonia. The rates of RV positivity were not different between patients with community-and hospital-acquired infections (28.6% vs. 23.9%, p = 0.52). For any individual RV, there was no difference between the rates of RV positivity in community-and hospital-acquired infections. Of 59 patients with an NRI, 12 (20.3%) had positive multiplex RT-PCR results for influenza (6) , adenovirus (2), parainfluenza virus (2), human enterovirus (2), HRV (1), and RSV (1).
The characteristics of the 166 patients with pneumonia (four duplicates excluded) who underwent multiplex RT-PCR testing were compared according to pathogen type (Table 3) . Approximately one quarter of these patients had an RV infection (26.5%, 44/166) and a bacterial infection (24.1%, 40/166), respectively. Nine patients (5.4%, 9/166) had bacterial/viral coinfections. The remaining 91 patients (54.8%) had no identified pathogen. In patients with an RV infection, 20 had RVs other than influenza (20/44, 45.4%). Patients with a single RV infection and those without an RV infection did not differ in terms of their baseline characteristics, underlying diseases, symptoms, and in-hospital mortality, except that rhinorrhea was more frequently observed in patients with a single RV infection during the flu season. In pa- tients coinfected with an RV and a bacterium, RSV and hematologic malignancy were more common features than in patients infected with a single RV. The in-hospital mortality rates were higher in patients with a bacterial/viral coinfection (88.9%) than in those without an RV infection (16.4%) and with a single RV infection (11.4%).
Multiplex RT-PCR testing was performed primarily for adult patients with community-acquired respiratory infections admitted to a tertiary care center during the flu season, and especially for patients with pneumonia. The test was performed infrequently and the test results were often reported late. The RV-positive rate (28.6%) for community-acquired infections was not different from that for hospital-acquired infections (23.9%, p = 0.52). RVs were identified in more than a quarter (26.5%) of the 166 patients with pneumonia. Nearly half of the patients with RV-associated pneumonia had RVs other than influenza (20/44, 45.4%). In our hospital, multiplex RT-PCR testing was most frequently performed for adult patients with community-acquired respiratory infections admitted during the flu season. Thus, the test was primarily used to diagnose influenza in adult patients, especially those with pneumonia. For clinicians who experienced the influenza A (H1N1) pandemic in 2009, the use of multiplex RT-PCR as a diagnostic test for influenza infection is understandable. At other hospitals, the perception of multiplex RT-PCR testing by physicians may be similar, given the predominance of influenza among RVs and the presence of effective anti-influenza therapies [9] . Therefore, the multiplex RT-PCR test should be performed to diagnose influenza during the flu season, especially considering the low sensitivity of rapid influenza antigen detection tests [9] . However, in our hospital, the multiplex RT-PCR test was performed infrequently compared to rapid influenza antigen detection tests. Additionally, the test was rarely performed in outpatient departments at the study hospital. These findings are understandable given that the test results are not available on-site, unlike the rapid influenza antigen detection test. Moreover, the test is not covered by National Health Insurance of South Korea and is relatively expensive (more than 100,000 KRW) compared to the cost of a respiratory bacterial culture (21,619 KRW) or the rapid influenza antigen detection test (18,000 to 28,000 KRW). Consequently, infrequent ordering resulted in less routine PCR testing in the clinical laboratory (not every day, but three times a week at our hospital). This may explain why a turnaround time of < 48 hours was observed in only 25.9% of the positive tests. Forty-eight hours is the most appropriate time period for the introduction of anti-influenza drugs after the onset of symptoms [9] . Considering these problems and the continuous threat of influenza infection, our current utilization of multiplex RT-PCR testing requires improvement, which may increase the diagnostic sensitivity for influenza and decrease the number of patients who receive delayed thera py.
In our study, the RV positivity rate for community-acquired infections did not differ from that for hospital-acquired infections. There were no differences in viral pathogens between community-and hospital-acquired infections. In a recent study of viral infections in patients with severe pneumonia requiring intensive care unit admission, patients with community-acquired pneumonia and healthcare-associated pneumonia had similar rates of RV positivity (40.6% vs. 34.3%) and similar RV pathogens [6] . Regarding these findings, experts suggest that RV infections are not directly influenced by previous healthcare interventions or exposure to antimicrobial agents, but rather they mirror circulating viruses in the community [10] . Although hospital-acquired infections and healthcare-associated infections are different, a similar explanation may be applied to our findings. Considering the frequent detection of RVs in our patients with a hospital-acquired infection, multiplex RT-PCR testing should not be limited to patients with community-acquired respiratory infections. The test may be required for patients with serious hospital-acquired respiratory infections of unknown cause. Based on our study findings, the test may be needed for hospital RV infection control [4] , although the turnaround time may not be optimal for that purpose.
The causal role of RVs other than influenza has not been determined in adult patients with pneumonia, and effective treatment with antiviral agents is largely unavailable in clinical practice. Thus, the detection of RVs other than influenza may be regarded as unnecessary for adult patients with pneumonia, especially during the non-flu season considering the fact that the multiplex RT-PCR test represented only 0.8% of sputum bacterial culture tests. However, clinical studies of pneumonia associated with RVs other than influenza have reported increased infection rates in both immunocompromised and non-immunocompromised patients [3, 5, 6, [11] [12] [13] [14] . Additionally, a few antiviral agents are recommended for severe pneumonia caused by RVs other than influenza, especially in immunocompromised patients [3, 15] . In this study, although most of the tests were performed for the diagnosis of influenza infection during the flu season, RVs other than influenza were found in 45.4% (20/44) of the patients with RV-associated pneumonia. Furthermore, in more than half (6/9) of the patients with a bacterial/viral coinfection, RVs other than influenza, including RSV, HMPV, and HRV, were detected. This group of coinfected patients had higher rates of mortality than either the group with a single RV infection or the group without an RV infection. Although the association with higher mortality may be due to more serious underlying diseases such as hematologic malignancy (22.2%) and the impact of bacterial infections in this group, the significance of RVs other than influenza should not be neglected. The clinical significance of RSV, HMPV, and HRV in adult patients with pneumonia has recently been reported [16] [17] [18] [19] . Our study suggests that RVs other than influenza should be considered in adult patients with pneumonia, and that the clinical impact of these RVs should be evaluated in future clinical studies.
In our study, 20.3% of patients with an NRI had positive multiplex RT-PCR test results. The clinical presentation of an RV infection may vary according either to the pathogenic potential of the RV or the degree of host immunity against RVs, and respiratory symptoms or signs in some patients with an RV infection may be minimal or absent. Asymptomatic carriers of RVs are another possible explanation, as suggested in a previous study [11] .
This study has several limitations. First, it was not designed to compare the clinical management, outcomes, and medical costs of patients who underwent multiplex RT-PCR testing with patients who did not. Thus, our study does not include direct evidence for the clinical usefulness of the multiplex RT-PCR test for RVs. Prior studies have shown conflicting results for the cost-effectiveness of the multiplex RT-PCR test [4] . Additional studies are required before the multiplex RT-PCR test for RVs can be strongly recommended in South Korea. Second, the platform for multiplex RT-PCR testing was changed during the study period, which might have affected the multiplex RT-PCR results and the positivity rates. However, the RV7 test was performed only in 24.0% of 291 cases. Third, clinical data were retrospectively collected. Unrecognized clinical factors may have resulted in biases in the study analysis. Fourth, our data cannot be generalized to other centers with different characteristics.
In conclusion, the multiplex RT-PCR test was performed most frequently for adult patients admitted for community-acquired respiratory infections during the flu season at a tertiary care center. The test was performed infrequently, and reporting of the test results was often delayed. The utilization of multiplex RT-PCR testing should be encouraged to more effectively diagnose infections with influenza and other RVs, both inside and outside the hospital.
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F eline infectious peritonitis (FIP) is an uncommon, fatal, progressive, and immune-augmented disease of cats caused by feline coronavirus (FCoV) infection. Although FCoV is common in most domestic, feral, and nondomestic cat populations worldwide (seroprevalence 20%-100%), FIP will develop in <10% of FCoV seropositive cats (1) (2) (3) (4) . FIP tends to occur most frequently in cats <2 years of age or, less commonly, in geriatric cats (4, 5) . The clinical manifestations of FCoV infection can be either a pathogenic disease, FIP (cases infected with feline infectious perito-nitis virus [FIPV] ) and, more commonly, a benign, or mild enteric infection (feline enteric coronavirus [FECV] asymptomatic) (6, 7) . Specific genetic determinants of these clinical outcomes have yet to be discovered. There is no effective treatment, vaccine, or diagnostic protocol that can discriminate the avirulent FECV from FIPV.
FIP pathology is characterized typically by severe systemic inflammatory damage of serosal membranes and widespread pyogranulomatous lesions, which occurs in the lungs, liver, lymph tissue, and brain (8) . Evidence suggests that the host immune system is crucial in this pathogenesis; profound T-cell depletion from the periphery and lymphatic tissues and changes in cytokine expression are observed in end-stage FIP (9, 10) . The clinical finding of hypergammaglobulinemia-associated FIP is indicative of virus-induced immune dysregulation (11) .
Viral genetic determinants specifically associated with FIPV pathogenesis have yet to be discovered. An in vivo mutation transition hypothesis postulated that de novo virus mutation occurs in vivo, giving rise to virulence (12, 13) . The precise nature of the mutation responsible for pathogenesis has not been identified, although studies have suggested sequence differences in the spike protein (14) , nonstructural protein (NSP) 7b, and NSP3c (13) as disease determinants. Together with in vitro studies describing the FIPV strains affinity for macrophages in contrast to FECV strains (15) , the hypothesis was extended to propose that the enteric coronavirus (FECV) undergoes a mutational shift in the gastrointestinal system, thus allowing infection of macrophages, systemic dissemination, and fatal disease manifestation (12, 13) . However, attempts to use engineered chimeric viruses designed to identify the operative virulence determinants have been unsuccessful (16) . Furthermore, circulating FCoVs found in different tissues of FCoV-infected asymptomatic cats were indistinguishable (17, 18) .
The in vivo mutation hypothesis of FIPV pathogenesis is widely cited, although it has never been explicitly confirmed. Mutational transition of HIV-1 has been demonstrated in AIDS patients, in which mutation of envelope residues alters coreceptor use from CCR5 to CXCR4, a prelude to the collapse of the CD4-bearing lymphocyte population (19) . Similarly, key amino acid changes in the porcine coronavirus spike gene lead to increased virulence in the coronavirus transmissible gastroenteritis virus, a fatal disease causing high rates of illness and death in young pigs (20) (21) (22) .
An alternative circulating virulent-avirulent FCoV hypothesis of viral pathogenesis suggests that distinctive benign and pathogenic strains of FECV circulate in a population, and that the disease will develop only in those persons infected by the virulent strains. Dengue virus may offer an example because it has been shown that 4 distinctive viral strains circulate worldwide, and severe hemorrhagic fever develops in persons exposed sequentially to distinct strains (23) . Zoonotic equine Venezuelan encephalitis virus also displays circulating virulent and avirulent strains, which through interaction with ecologic and epidemiologic factors, contribute to or constrain the disease incidence (24) .
This study aimed to systematically test evolutionary predictions of the in vivo mutation hypothesis versus the circulating virulent/avirulent hypothesis in the pathogenicity of FIP in the cat. We developed a study of naturally occurring FECV and FIPV using molecular genetic tools by collecting samples from field cases of FIP (cases) and FECV-positive but asymptomatic cats (controls). Cases were infected with feline coronavirus (FCoV) and had the clinical disease of feline infectious peritonitis (FIP). Controls were also infected with FCoV, but were clinically asymptomatic (FECV-asymptomatic). The prediction was that phylogenetic analysis of viral gene sequences would demonstrate paraphyly for FIP case-cats and FECV-asymptomatic cats if the in vivo mutation hypothesis was supported, and monophyly of the 2 if the circulating virulent/ avirulent hypothesis was supported ( Figure 1 ). Additionally, we surveyed the viral genetic diversity and dynamics and determined genetic signatures associated with pathogenesis in FIP.
A total of 56 live, euthanized, or recently deceased domestic cats were clinically examined and sampled in Maryland veterinary hospitals during 2004-2006 (online Appendix Table 1 , available from www.cdc.gov/EID/ content/15/9/1445-appT1.htm). Blood (3-6 mL) was collected routinely by venipuncture from manually restrained or anesthetized domestic cats. Feces were obtained from the rectum by cotton swab and frozen in 0.5 mL of phosphatebuffered saline. Cats from 1 (Weller Farm) of 6 farms were micro-chipped (AVID, Folsom, LA, USA) for identification for repeat sampling of individual cats. Samples were collected in full compliance with specific federal permits (Convention on International Trade in Endangered Species; Endangered and Threatened Species) issued to the National Cancer Institute by the US Fish and Wildlife Service of the Department of the Interior.
For euthanized and recently deceased cats, gross necropsy examination and sample collection were performed within 2 hours of death. Samples from liver, spleen, mesenteric lymph node, kidney, jejunum, and colon were taken, fixed in 10% buffered formalin, and routinely embedded in paraffin. Sections (5 μm) were stained with hematoxylin and eosin (HE). Tissues were also flash frozen in liquid nitrogen (-220°C) for RNA extraction and stored at either -220°C or -70C°.
For complete blood counts, fresh (<12 hours) wholeblood samples were assessed by Antech veterinary diagnostic laboratory by using an automated cell counter A) The in vivo mutation transition hypothesis predicts paraphyly of feline infectious peritonitis (FIP) cases and feline enteric coronavirus (FECV) asymptomatic feline coronavirus (FCoV) isolates). B) The circulating virulent/avirulent strain hypothesis predicts reciprocal monophyly of FIV-cases versus FECV asymptomatic. Numbers represent individual cat (or locale), which is either FIPV case (red) or FECV asymptomatic (blue). Evidence presented in this article supports the circulating dual virulent and avirulent strains. USA), and coronavirus (Virachek CV, Synbiotics Corp., San Diego, CA, USA) antibodies were also performed.
HE-stained slides of spleen, liver, lymph node, intestine, and kidney sections were evaluated for evidence of granulomatous and pyogranulomatous lesions (National Cancer Institute Laboratory Animal Sciences Program, Frederick, MD, USA). Formalin-fixed sections (3 μm thick) were cut from paraffin blocks and placed on glass slides for immunohistochemical (IHC) testing, as previously described, with CoV p56, a cross-reacting antibody for the demonstration of feline coronavirus (FECV and FIPV biotypes) (9,10) (Washington Animal Disease Diagnostic Laboratory, Pullman, WA, USA) ( Figure 2 ).
RNA from 160 μL ascites fluid or frozen feces suspended 10% in phosphate-buffered saline was extracted by using the QIAamp virus RNA mini kit (QIAGEN, Valencia, CA, USA) following the manufacturer's instructions. RNA from tissue was extracted from ≈60 mg of frozen liver, lung, spleen, colon, jejunum, or lymph node by using RNAeasy (QIAGEN) following the manufacturer's instructions. Extracted RNA was eluted in 35 μL of RNase-free water and stored at -70ºC. cDNA was reverse transcribed using 9 μL of eluted RNA (10 pg-5 μg) in an initial 12-μL reaction mixture containing 50 ng of random hexamers and 0.5 mmol/L of dNTPs. After incubation at 65ºC for 5 min to denature the RNA, 10 mmol/L of dithiothreitol, 5× Synthesis Buffer, 40 U of RNaseOUT, and 15 units of Thermoscript RT were added on ice (Invitrogen, Carlsbad, CA, USA). Reaction mixtures were incubated in thermocycler at 25ºC for 10 min, followed by 50ºC for 30 min. cDNA was stored at -20ºC.
Primers amplifying 7b (736 bp), membrane protein (575 bp), polymerase (386 bp), and spike-NSP3 (1,017 bp) ( Figure 3 ) were designed based on available feline coronavirus sequence (1, 12, 13) . PCR was performed by using 2 μL of cDNA in a 50-μL reaction containing 50 mmol/L KCl, 10 mmol/L Tris-HCl (pH 8.3), 1.5 mmol/L MgCl 2 , 0.25 mmol/L concentrations of dNTPs (dATP, dCTP, dGTP, and dTTP), 2 mmol/L concentrations of each primer, and 2.5 units of Platinum Taq DNA polymerase (Invitrogen). PCR was conducted on a geneAmp PCR system 9700 thermocycler (Applied Biosystems, Foster City, CA, USA) with the following touchdown conditions: 2 min at 94ºC then a touchdown, always starting with 20 sec at 94ºC, then 30 sec at 60ºC (3 cycles), 58ºC (5 cycles), 56ºC (5 cycles), 54ºC (5 cycles), 52ºC (22 cycles), and then 1 min at 72ºC for extension, and with a final extension at 72ºC for 7 min and a hold at 4ºC. PCR products were visualized by electrophoresis on a 1% agarose gel and primers and unincorporated dNTPs were removed by using Microcon YM (Millipore, Billerica, MA, USA).
Representative PCR products were cloned and sequenced ( Figure 3 , panel B). Cloning was performed by using a TOPO-TA cloning kit (Invitrogen) according to the manufacturer's instructions. Plasmid DNA was isolated from 1-47 clones from each reaction product (Agencourt CosMCPrep; Agencourt Bioscience Corporation, Beverly, MA, USA). The presence of the correct sized insert was verified by restriction enzyme digestion (EcoRI), and sequences were obtained from clones with the correct insert by using standard ABI BigDye terminator reactions (Applied Biosystems). Anticontamination measures were taken at all steps of reverse transcription-PCR (RT-PCR) amplification and post-PCR processing.
Sequences from pol 1a, spike-NSP3, membrane, and NSP7b were analyzed separately. Nucleotide sequences were compiled and aligned for subsequent phylogenetic analysis by using ClustalX (25) and verified visually (26). Analyses involved producing a phylogenetic tree of viral gene sequences based upon the following approaches: minimum evolution, maximum parsimony, and maximum likelihood in PAUP (27) . Modeltest was used to estimate the optimal model of sequence evolution, and these settings were incorporated into subsequent analyses (28) . Minimum evolution trees were constructed from models of substitution specified by Modeltest, with starting trees obtained by neighbor joining followed by application of a tree-bisection-reconnection (TBR) branch-swapping algorithm during a heuristic search for the optimal tree. Maximum parsimony analysis employed a heuristic search of starting trees obtained by stepwise addition followed by TBR. Maximum-likelihood parameters specified by Modeltest selected the general time-reversible model of substitution, included empirical base frequencies, and estimated rate matrix and corrected for among-site rate variation (gamma distribution). A bootstrap analysis using 1,000 iterations was performed for maximum parsimony and minimum evolution and 100 iterations by using the nearest neighbor interchange branch-swapping algorithm for maximum likelihood. Amino acid residue alignments were generated using MacClade 3.05 (26) and ClustalX (www.softpedia. com/get/Science-CAD/Clustal-X.shtml).
Variable sites and parsimoniously informative sites were computed in MEGA version 3.0 (29) . Pairwise comparisons of genetic distances were performed in PAUP and the mean and range of genetic distances were calculated in Excel (Microsoft, Redmond, WA, USA). The sequences of FCoV pol 1a, membrane, NSP 7b, and spike-NSP3 were deposited in GenBank under accession nos. EU663755-EU664317.
During 2004-2006, fifty-six domestic cats with suspected FIP or exposure to infected FIP cats from Maryland farms and veterinary hospitals were sampled (online Appendix Table 1 ). All samples producing RT-PCR products were from cats positive for antibodies against FCoV (titers >25). Thirty-six sampled cats were from the Weller farm where several individual cats were sampled once per year for the 3-year study period. Healthy and recently deceased or euthanized cats were included from the Ambrose farm (n = 7), Palmer Veterinary Hospital (n = 3), Frederick County Animal Shelter (n = 7), Seymour farm (n = 1), and the New Market Animal Hospital (n = 2). Fca-4590 from the Weller farm is an important FIP case because samples were obtained on May 20, 2004, when the cat was clinically healthy (predisease) and again on December 22, 2004, when FIP developed in the cat and it died (postdisease).
Necropsies were performed on 23 cats that died or were euthanized due to suspected FIP. Most of the necropsied cats were FCoV antibody positive (online Appendix ( Figure 2 ; online Appendix Table 1 ). The presence of pyogranulomatous lesions at histology evaluation was sufficient for designation of an FIP case. Additionally, 5 of the 8 FIP cases were evaluated by IHC testing. Multiple tissues were positive by IHC in each of these cats. One cat (Fca-4561) was IHC positive only in the jejunum and negative by histopathologic analysis on all tissues, therefore it was classified as FECV asymptomatic. The FCoV-seropositive necropsied cats with no characteristic FIP histopathologic changes and IHC lesions were classified as FECV asymptomatic (online Appendix Table 1 ; Figure 2 ). Healthy cats were classified as FECV asymptomatic if they had normal results on physical examinations, were FCoV antibody positive (titer >25) but not lymphopenic (<1.5 cells/μL), or were monitored until 2007 and known to be free of FIP disease (online Appendix Table 1 ). RT-PCR was attempted with 4 primer pairs designed from FCoV genes for all cats (Figure 3, panel B) . Of the 82 samplings from 56 cats, 42 samplings amplified virus with at least 1 primer pair yielding a 51% rate of recovery of viral sequence (online Appendix Table 1 ). From 8 cats with clinical FIP and 23 FECV-asymptomatic cats, amplification from the 4 viral regions produced 735 cloned viral gene segments that resulted in 501 unique gene sequences (online Appendix Table 2 , available from www.cdc.gov/ EID/content/15/9/1445-appT2.htm; Figure 3, panel B) .
Phylogenetic analysis of the cloned virus sequences from 3 Maryland locales sampled during 2004-2006 showed specific patterns of viral dynamics. First, gene sequences from healthy cats infected with FECV displayed a monophyletic cluster pattern that was generally distinctive from cats diagnosed with FIP in the membrane, NSP 7b, and spike-NSP3 gene segments (Figure 4 ). For example, every FCoV gene sequence for the membrane gene from FIP cases fell within a major cluster consisting of 3 principal clades (Figure 4 ). By contrast, 127/154 (82%) virus gene sequences from FECV-asymptomatic cats sorted in 2 separate clades that were distinct (100 bootstrap statistical support) from the viral gene sequences of FIP cases ( Figure 4 ). Similar reciprocal monophyly of 140 NSP7b sequences was obtained for FIP cases versus FECV-asymptomatic cats (Figure 4) . A consistent disease driven phylogeographic sorting was also observed for the 1,017-bp sequence spanning the spike-NSP3 genes, albeit with less statistical resolution, likely because of evolutionary constraints on gene divergence in this region (Figure 4 ). Together the remarkable reciprocal monophyly in these 3 genes supports the predictions of the circulating virulent-avirulent strain hypothesis illustrated in Figure 1 .
Samples from 1 cat, Fca-4590, were particularly informative. The virus was isolated from the cat predisease, and then again 7 months later postdisease. Fca-4590 was asymptomatic but infected with FECV in May 2004. FCoV sampling from that month showed strong (high bootstrap) affiliation with the FECV-asymptomatic clades for the membrane and the NSP7b genes. However, virus isolated
Fca-4590 fell within the FIP-case clades (also with high bootstrap), and was indistinguishable from FCoV isolated from other cats with FIP. This finding suggested that the pathogenic FIP-case type of FCoV infected this cat subsequent to its infection with an avirulent FECV and apparently replaced it.
Tissue-specific differentiation within each cat was minimal (Figure 4 ). By contrast, there were notable localespecific distinctions within the sick and healthy cats (Figure 4) . For example, the FECV strains in asymptomatic cats from the Weller household were associated together in a major FECV subclade; strains in cats from the Frederick Animal Shelter were classified in a different subclade, nested within the FECV-asymptomatic clade (Figure 4) . The archival FCoV virulent strain (Aju-92), isolated from cheetahs in Oregon in 1982 (30) , defined a phylogenetic lineage distinctive from the FIP and FECV-asymptomatic clades resolved in the Maryland domestic cats (Figure 4) .
Nucleotide sequences of membrane and NSP 7b generated in this study were translated to amino acid sequences (online Appendix Figure 1 , available from www. cdc.gov/EID/content/15/9/1445-appF1.htm). Relative to pathogenesis, 5 informative amino acid sites were found in the membrane protein at positions 108, 120, 138, 163, and 199 (based on reference sequence for TGEV GenBank no. NP058427) (22) , giving rise to 6 composite genotypes potentially diagnostic of FIP cases versus FECV-asymptomatic cats (online Appendix Table 2 ). Among the 8 cats with FIP, 19 FECV-asymptomatic cats, and 1 cheetah with FIP, 6 composite genotypes were identified based on these 5 diagnostic sites (online Appendix Table 2 ).
All domestic cats with FIP diagnosed by pathologic or immunohistochemical changes displayed the amino acid signature of either YIVAL (I) or YIIAL (II); infected cats without clinical FIP had the HIIVI (III), HIIVL (IV), HVI-AL (V), YVVAL (VI), or YIVAL (I) haplotype. No FIP cases had haplotype III, IV, V, or VI, whereas 3 FECVasymptomatic cats carried the YIVAL signature found predominately in FIP cases (Fca-4594, 4624, and 4657; online Appendix Table 2 ). Of these, 2 cats (4624 and 4657) were euthanized at the time of sampling (all euthanized FECVasymptomatic cats are highlighted in light green in online Appendix Although a strong phylogenetic signal differentiating FIP cases from FECV-asymptomatic cats was seen in NSP 7b (Figure 4) , no diagnostic amino acid changes specific to FIP cases vs. FECV-asymptomatic controls were found in the NSP 7b nucleotide or amino acid alignments. In contrast to the monophyletic findings in the membrane, NSP 7b, and spike-NSP3 genes, cloned viral sequences of pol 1a, were paraphyletic in terms of disease phenotype (online Appendix Figure 2 , available from www.cdc.gov/EID/ content/15/9/1445-appF2.htm).
Infection with FCoV is common in cats throughout the world, although in most cats the virus causes no clinical signs. However, in some cats, FCoV infection is associated with the development of the progressive and fatal disease manifestation of FIP. This disease is among the most serious viral infections in cats, not only because of its fatal nature, but also because of the difficulties in diagnosing FIP antemortem and controlling the spread of FCoV. We have presented a molecular virologic study of naturally occurring FCoV infection and phylogenetic analysis of the cloned virus sequences obtained from the membrane, NSP 7b, spike-NSP3, and pol 1a genes isolated from domestic cats located in Maryland households infected with FCoV during 2004-2006. We observed predominately monophyletic clustering of strains correlating with disease phenotype in membrane and NSP 7b genes consistent with the circulating virulent/ avirulent strain hypothesis of FIP pathogenesis, which calls into question the in vivo mutation hypothesis.
The amino acid alignments presented in online Appendix Figure 1 clearly demonstrate that in the FIPV cases included in this study the genotypes correlated with disease phenotype are ancestrally derived and not the result of a few de novo mutations. Given the clear genetic differentiation between viruses from FIP cases and FECV asymptomatic cats in multiple gene segments, we infer that cats become reinfected with new strains of FCoV from external sources, rather than by in vivo mutations. Cats in our study were not co-infected with multiple strains of FECV and FIPV at the same time and were generally infected with one predominant virus strain. Two exceptions to this finding in our study were cats with cases of FIPV (Fca-4662 and 4664) that from which distinct gastrointestinal (feces or intestine) and systemic (liver and/or ascites fluid) viral isolates were obtained, which indicates that in vivo superinfection does occur (Figure 4 ; online Appendix Table 2 ).
A role of the membrane protein in FIP pathogenesis seems likely, given its known functions in other coronaviruses. The membrane protein is the most abundant structural protein with important functions in virus budding and with cell-mediated host immunity (31) . The specific functions of the membrane protein amino acid sequences have been determined in severe acute respiratory syndrome (SARS)-CoV (32) . Aligning the sequences from this study with SARS-CoV, the first diagnostic amino acid site 108 aligns to a site just upstream from the second transmembrane helix (online Appendix Figure 1) . A tyrosine at position 108, which is found in all FIPV biotypes and shared among SARS-CoV, has a neutral polarity (in contrast to a histidine there, found in most FECV biotypes, which have a positive polarity) and may play a role in the stability of the virus within the membrane. Site 120 aligns within the third transmembrane helix, site 138 aligns just downstream to the transmembrane helice, site 163 aligns within the Cterminus, which projects inside the virus particle, and site 199, also within the C-terminus domain, aligns within a defined SARS-immunodominant epitope (32) (Figure 5 ).
The demonstration of 6 naturally occurring composite genotypes based on 5 variable sites in the membrane protein amino acid alignment that are highly correlative with disease phenotype (online Appendix Table 2 ) offers specific opportunities for developing diagnostics and for the preventive management of this disease. By extending this study to additional cat populations in disparate geographic locations, designing chimeric FCoV challenge experiments, and investigating host genetic correlations with pathogenesis, we will be able to further discern the causative factors in FIP pathogenesis. Fca-4594, which was infected with the diseaseassociated genotype composite without succumbing to FIP, suggests additional requirements for viral pathogenesis. As has been suggested in the outbreak of FIP in a colony of captive cheetahs (33) , host immune genetics may play a role.
Both the viral strain and host immune genes contribute to disease progression and virus-related death, such as AIDS progression in HIV infection. With the recent publication of the full cat genome sequence (34) and the viral genotype composites described here, new genomic tools are now available to proceed with both viral and host genetic association studies in the pathogenesis in FCoV infection, a model for coronavirus infection in humans, such as SARS-CoV. Table 2 ) as determined by sequence comparison to severe acute respiratory syndrome coronavirus (32) . Amino acid residue, polarity, and hydrophobicity or hydropholicity is stated.
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Since the beginning of the coronavirus disease 2019 (Covid-19) crisis, the lockdown has been considered a key policy response in many countries to prevent the further spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which causes the disease. The implementation of the lockdown order, however, has varied in countries and territories around the world, thanks to the unpredictable situation of the pandemic [1]. Vietnam is one of the few countries achieving effective control of Covid-19 outbreak after the implementation of lockdown strategy [2] . Under Directive No. 16/CT-TTg issued in March 31, 2020, a "stay-at-home" order was imposed nationwide to curb the spread of the contagion, limit the number of infections and casualties, and alleviate the pressure on the health service providers. The effectiveness of such outbreak control was evidenced by the fact that there were only 59 new infected cases confirmed during the first 14-day nationwide social distancing (from April 1 to 14, 2020) , equaled to 40% of the two weeks prior to the national lockdown [3] . Of these, there were 30 confirmed cases in isolation zones and 29 confirmed cases in the community [3] . Within 99 days since April 15, Vietnam had confirmed no community transmission despite extensive testing. While in many regions of the world strict Covid-19 lockdown orders had still been in effect, the Government of Vietnam relaxed social distancing rules for almost all provinces and cities on 23 April [4] . The early success in Vietnam' epidemic control has mainly attributed to the national emergency response across the whole sociopolitical system, in particular, 22-day nationwide lockdown.
However, the strike of no Covid-19 community transmission has been broken on July 25 when a new case were reported in Da Nang City [5] . This disruption made the Covid-19 pandemic in Vietnam more unforeseeable than ever [6] , [7] , [8] . Immediately, contact tracing efforts as well as epidemiologic investigations have been strengthened under the strong guidance of the Vietnamese Prime Minister, yet the source of the infection is not known in several new cases [8] , . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted September 1, 2020. . https://doi.org/10.1101/2020.08.27.20183616 doi: medRxiv preprint [9] . With the estimation of the reproduction ratio (R 0 ) for 257 first Covid-19 patients in Vietnam (between 23/1/2020 and 10/4/2020), a Huy G. Nguyen' early analysis revealed the downward trend of the epidemic in this country [10] . However, the potential SARS-CoV-2 transmission in the community is not reflective of current reality in each stage under Government' strict restrictions. An initial understanding of the characteristics of Covid-19 patients detected before and after lockdown end in Vietnam is needed to suggest prompt and efficient actions in the worst-case scenarios for in Vietnam. Given the Covid-19' rapid spread, an updated analysis of cases was conducted to examine the differences of characteristics of Covid-19 patients before versus after lockdown end in Vietnam.
In this paper, we collected data of Covid-19 patients who were confirmed SARS-CoV-2 infection from 23 January to 31 July, 2020. We divided Covid-19 situation timeline from 23 January to 31 July 2020 into two main periods, before lockdown end (23 January -22 April, 2020) and after lockdown end (23 April -31 July, 2020). We selected cut-off point of Covid-19 situation timeline in Vietnam on 23 April, 2020 (23 April, 2020 is the day that the Vietnam Government decided to loosen the national lockdown [4] ).
Analysis data in this paper was extracted from two sources, official database of the Ministry of Health of Vietnam (MOH) (https://ncov.moh.gov.vn/) and the website of Our World in Data (https://ourworldindata.org/coronavirus#coronavirus-country-profiles) [11] . A total of 569 Covid-19 confirmed patients were consecutively detected from 23 January to 31 July, 2020 ( Figure 1 ).
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The copyright holder for this preprint this version posted September 1, 2020. [13] .
Covid-19 recovered case before and after lockdown end was defined that, a patient who recovered from Covid-19 and discharged from the health facility met the following criteria: 1) no fever for at least three days; 2) a good general health condition; (3) two samples taken at least 1 day apart having negative test results for SARS-CoV-2 [12], [13] .
Covid-19 death case is a patient with confirmed Covid-19 infection whose death resulted from clinically compatible illness, unless there is an other certain cause of mortality that cannot be related to Covid-19 disease (e.g., trauma). No period of full recovery was recorded between the illness and death.
The variables in this analysis were selected on the basis of the availability of above official databases. The variables related to the Covid-19 patient characteristics were divided into subgroups as following: mean age, age group (0-10 years/11-20 years/21-30 years/31-40 years/41-50 years/51-60 years/60 years and over), gender (male/female), nationality (Vietnam/others), the history of returning from China (yes/no), the history of returning from other countries (excluding China) (yes/no), and treatment status (under treatment/ discharged/ died).
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Vietnam' Covid-19 situation timeline was considered as a variable with two main values: (code 1) before lockdown end and (code 2) after lockdown end. We used both descriptive and analytical method. While age data was expressed as mean ± standard deviation (SD) with interquartile ranges (IQR), categorical variables were presented as frequency with percentage (%). We estimated the overall proportion of Covid-19 confirmed cases and its percentage before and after lockdown end according to selected demographic and epidemiological characteristics.
Chi-square tests and Mann-Whitney U tests were utilized to compare patient' characteristics between two periods. All statistical analyses in this paper were conducted by Stata® 15 (StataCorp LLC, USA). The level of statistical significance was set at 0.05. Table 1 .
Patients had a median age of 38.56 (SD 16.61) years, and the patients in the time after lockdown end were older than those in the period before lockdown end by a median of 5 years. Overall, those aged 21-30 years are recorded with the highest number of Covid-19 confirmed cases in both periods (35.82% (n = 96) vs. 27.91% (n = 84)). Almost 90% (n = 241) of patients aged 59 years or younger before lockdown, while this figure after lockdown end was nearly 85% (n = 254). There was significant difference in the patient gender between two periods, 45.52% male before lockdown and 61.79% male after lockdown.
Of 10 Covid-19 patients returned from China, 9 patients (3.36%) were in the first period and 1 (0.33%) was in the second period, while no difference between two periods was observed . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted September 1, 2020. . https://doi.org/10.1101/2020.08.27.20183616 doi: medRxiv preprint according to the number of patients returned from other countries. Besides, the Covid-19 patient' nationality between two periods was also significantly varied (Table 1) .
Compared to the phase before lockdown with 268 discharged Covid-19 patients (100%) and no Covid-19 death, post lockdown period had only 34.88% patients cured and discharged from the facilities with 5 fatalities (1.66%) and 191 those being under treatment (63.46%) ( Table 1) .
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The copyright holder for this preprint this version posted September 1, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted September 1, 2020. .
It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted September 1, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted September 1, 2020.
At the time of writing this article, the first 569 consecutive confirmed cases of Covid-19 through 31 July 2020 are utilized to compare according to two stages, before and after lockdown end in Vietnam. Among the 569 patients, the a median age was 38.56 years, which was significantly lower compared to recent reports in other countries such as 62.2 years in 393 patients in New York City, U.S [14] and 50.1 years in 198 patients in Shanghai, China [15] . Age structure of each country may be the best explanation for the difference in the confirmed case number through two phases. The age distribution of cases was revealed with strong and important role on Covid-19 case fatality [16] . In Vietnam, as compared to before lockdown end, the stage after lockdown had a higher proportion of elder patients. The Covid-19 patient distribution in general is quite similar amongst age groups and those aged 21-30 years are recorded with the highest number of Covid-19 confirmed cases in both periods, implying that SARS-CoV-2 infection risk considerations are not focused solely on any age group. Those in later stage are also patients having pre-existing comorbidities, contributing to the partial explanation of 5 first fatality cases before 31 July. In this analysis, it was observed that significant difference in the gender was shown between two stages (45.52% male patients before lockdown end vs 61.79% male patients after lockdown end).
Despite the more and more increasing global Covid-19 patient number with the overload of the health system, Vietnam has still been responding well to the Covid-19 pandemic with the mobilization of the entire political system. Significant difference was observed in the nationality of Covid-19 patients between two phases. During the initial phase of the study timeline, 17.91% patients (n=48) were residents of other countries, which decreased to 7.64% patients (n=23) during phase after the lockdown end. This point is mainly because, in the time after lockdown . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted September 1, 2020. . end, most of them are Vietnamese citizens flown home from abroad [17] . In our analysis, the Vietnamese cases increase in the community after lockdown may be associated with the reopening of domestic tourism in the "new normal" condition after the first Covid-19 wave and the illegal border entry [4] , [18] , [19] . Current situation requires that, Vietnam' proactive efforts in Covid-19 control will be effective when volume, speed, and reach of travel in tourism are well managed and the measures to closely control and monitor repatriation and immigration via its borders are prioritized. Despite having a long borderline with China, Vietnam only recorded 9 confirmed patients returned from China at the time before lockdown end and only a case after lockdown who had illegally immigrated to Vietnam. On the other hand, we found, the number of Covid-19 patients who returned from other countries (excluding China) slightly increased through two stages, however, this difference was not statistically significant. This result partially shows that the continuous volume of people returning Vietnam from abroad during the Covid-19 epidemic. Such the detection of the Covid-19 cases from overseas is the effort of not only the entire political system in immigration control and management of people returning from abroad in general and but also the Vietnam Border Defense Force in particular. The more clear proof is that, over 16,000 people illegally entering Vietnam have been prevented by the Vietnam Border Defence Force since the beginning of 2020 and, particularly, over 2,400 people have been arrested in July once trespassing on the trail [19] .
Our study showed that the difference in the treatment status of Covid-19 patients between before and after lockdown end. Vietnam' early success in the Covid-19 patient treatment was proved by the absolute figure of 268 discharged Covid-19 patients (100%) before lockdown end. Although the number of the recovered patients, overall, continued to slightly increase from 23 April to 25
July after lockdown end, yet the number of new cases in this phase gradually decreased within . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted September 1, 2020. . three months before Covid-19 outbreak point documented in the community in Da Nang on 25
July. Importantly, all new Covid-19 instances from 23 April to 25 July after lockdown were Vietnamese people who returned from abroad and this risk group was then required to isolate for 14 days [20] . When Vietnam was retaining 99 days without any cases in the community, various countries across the world have been faced a rapid growth in the number of new and fatal cases of Covid-19 [21] . Since 25 July after lockdown, almost patients being treatment in Vietnam have been confirmed SARS-CoV-2 infection, which known as the second wave of Covid-19. In such emerging Covid-19 situation, the community transmission cases reported to be linked to the hospitals in Da Nang where the elder patients with chronic severe diseases such as cancer, chronic kidney disease and dialysis, heart failure, diabetes, or hypertension were being treated [22] . Therefore, compared to the phase before lockdown end (all discharged Covid-19 patients (100%) and no death), the post-lockdown time recorded the worse situation with mostly patients being treated (n = 191, 63.46%) and first 5 fatalities (1.66%). It should be noted that five fatal cases were identified at the moment of Vietnam' second Covid-19 outbreak after the national lockdown implementation for three months. After synthesizing current analysis data, two main reasons associated with Vietnamese Covid-19 deaths were suggested by the Vietnamese experts.
Firstly, the new coronavirus strain detected in second wave of Covid-19 infections there had a faster speed of infection compared to the earlier strain. However, many uncertainties have remained concerning the virus-host interaction and the evolution of the epidemic, and its harmfulness compared to the strain previously existed in Vietnam has been not yet known [22] , [23] . Secondly, the presence of multiple coexisting severe illness was reported in Covid-19 fatalities [24] .
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The copyright holder for this preprint this version posted September 1, 2020. .
The present results should be viewed with the limitations. First, because the paper' secondary analysis data was collected from two publicly available datasets, the information of the exposure history, clinical symptoms or signs, radiologic assessments, laboratory testing as well as the other risks could be unknown. Second, the challenges in national large-scale coronavirus testing resulted in the underestimated true number of Covid-19 infections. Finally, due the ongoing Covid-19 pandemic with the more complicated situation in Vietnam, the current estimates are temporary at the time of this writing.
Our short communication illustrated demographic and epidemiological disparity of Covid-19 patients before versus after loosening the national lockdown in Vietnam. The Covid-19 patient distribution in general is quite similar amongst age groups and these patients were largely recorded in the 21-30-year-old group in both periods. Most of the Covid-19 patients are residents of Vietnam and Vietnamese patient number has still increased rapidly during phase after the lockdown end. Importantly after the lockdown period, Vietnam' proactive efforts in Covid-19 control after lockdown end will be effective when the measures to closely control and monitor repatriation and immigration via its borders are strictly enforced.
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The copyright holder for this preprint this version posted September 1, 2020. Available from: https://ncov.moh.gov.vn/web/guest/-/gs-ts-nguyen-van-kinh-chungvirus-moi-gay-covid-19-lay-lan-nhanh-nhung-oc-luc-khong-oi-.
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Early detection of acute pulmonary embolism (PE) in patients with SARS-CoV-2 infection is integral 2 to the clinical management of these patients. Many recently published studies have evaluated incidence of PE 3 in hospitalized patients with COVID-19 1-9 , however there is relatively limited data describing patients with 4 SARS-CoV-2 infection and concomitant diagnosis of acute PE upon initial presentation. Therefore, the purpose 5 of this study is to (i) evaluate the incidence of acute pulmonary embolism (PE) in patients undergoing 6 computed tomography pulmonary angiography (CTPA) in the emergency department (ED) across six hospitals 7 in New York City during the height of the COVID-19 pandemic compared to a non-pandemic period, and (ii) 8 compare the characteristics and early outcomes of patients presenting with PE during the pandemic (n=87) to 9 patients presenting with PE during a non-pandemic period (n=34).
This retrospective review was approved by the institutional review board and informed written consent 11 was waived. No authors had any conflicts of interest to declare.
The inclusion criteria included all patients 18 years of age who underwent CTPA in the emergency 13 department. Data was collected for all patients who underwent imaging between April 1 st and May 1 st , 2019, 14 and April 1 st and May 1 st , 2020, representing studies performed during non-pandemic and pandemic times, 15 respectively. Demographic information was manually extracted from the electronic medical record with and 16 each record was reviewed by two independent authors for accuracy. Date of testing for SARS-CoV-2 infection 17 by reverse transcriptase polymerase chain reaction (RT-PCR) was recorded. For the purposes of classifying 18 patients as positive, negative, or not tested, the following criteria were used. Patients were classified as COVID 19 positive if the patient had a documented positive test from an encounter prior to presenting to the ED with PE 20 or if the patient had a positive test obtained within 2 days of CTPA. If a patient was not tested or tested 21 negative within 2-days of the CTPA, the patient was classified as not-tested, or negative, respectively. Patients 22 who >2 days after CTPA tested positive, were classified according to results available within 2 days of PE 23 detection.
Outcomes data on each patient was recorded for 14-days following hospital discharge. Patients 25 transferred to an outside hospital after admission were excluded from the short-term outcomes analysis. For the 26 patients diagnosed with PE between April 1 st and May 1 st 2020, date of symptom onset was recorded, with any 27 described symptom of SARS-COV2 infection recorded as day 1 of symptoms 10 .
Axial images from the thoracic inlet to the iliac crests were obtained of the chest during IV 29 administration of an intravenous contrast bolus timed for pulmonary arterial opacification. 3-D and thin section 30 reformats were performed on a separate workstation. Dose reduction techniques were utilized including 31 kVp/mA dose modulation based on patient size and iterative reconstruction. Reports of PE-protocol CTAs 32 performed were queried from the radiology information system using Montage (Montage Health, Monterey, Accepted Article 34 performed in 2020 were additionally evaluated for commonly reported imaging features of COVID-19 35 pneumonia 11 . 36 To compare continuous data between the 2019 and 2020 group a Mann-Whitney U test was used for non-37 normally distributed data, and a student's t -test was used for normally distributed data. Pearson's Chi-squared 38 test was used to compare categorical variables between groups. Normality of continuous data was determined 39 by the Shapiro-Wilk test. Normally distributed data was reported and means with standard deviations, and non-40 normally distributed data was reported as medians with interquartile ranges. All statistical tests were
There was no significant difference in number of patients who underwent intensive care unit (ICU) 66 admission, length of hospital stay, 14-day readmission, or disposition of the patients between the groups. 67 Detailed characteristics of the cohorts and short-term outcomes are described in the Table. 68 Our study demonstrated that 18.8% of studies performed during the height of the pandemic were 69 positive for PE, which is significantly higher than the year prior in which 7.6% of CTPA studies performed in 70 the ED were positive for PE. Notably, a prior study performed by a single-center in France, reported an 71 incidence of PE of 18.0% in patients presenting to the ED with COVID-19 pneumonia 12
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On 30th of January 2020, WHO declared a Public Health Emergency of International Concern after the first clusters of people infected by COVID-19 were diagnosed in China (WHO, 2020) . The day after, the Italian Government started to define the first containment measures, such as checking people entering the country from China, in order to prevent the expansion of the contagion in the country (Government, 2020) . However, from the second half of February the number of Italian cases increased, especially in Northern Italy. This led the Government to announce on February 21st the first restrictive measures in what was defined as the first Red Zone, including defined territories in the regions of Lombardia and Veneto, the areas most affected by the infection. Since the pandemic kept spreading around the country, the Prime Minister issued on March 9th a decree which extended to the entire national territory the restrictions already in force locally. The rules were supposed to last until April 3rd, but were extended by two more decrees firstly until April 13th and, later, until May 3rd (Government, 2020) . At the time of writing (April 26th, 2020), there were in Italy 199,000 confirmed cases and 26,977 deaths, more than half of which occurred only in Lombardia and Veneto. When the data of the present study were collected (between the 2nd and the 7th of April), those numbers were still increasing, showing that the end of the pandemic is still a long way off.
The measures, known as #Iamstayingathome (#IoRestoaCasa), include the closure of shops, except those selling crucial necessities, the cancellation of all sports events, and the shutdown of schools and universities across the country (Government, 2020) . With schools, all the educative supporting services directed to children of all ages were closed, with teachers from primary grade onwards providing online lectures. Quarantine began for the entire population; everyone was banned from leaving home except for non-deferrable and proven work or health reasons, or other urgent matters. Smart working has been incentivized, but since most activities are closed many people lost their job or went through a severe reduction of their income.
The life condition of families suddenly and deeply changed. In the home environment, the educational role of parents for children has become even much crucial than before. Children have only their parents around them, to provide support with homework when necessary and promote a positive development and new learning experiences for toddlers and preschoolers . Parents have been left alone not only in taking care of home-schooling their children, but also in general in the management of their children and of the home environment. All other educational services are closed, babysitters and grandparents are not available, and contact with peers is not allowed. Many parents also must do smart-working, and handling time and spaces to work with children around may be very problematic. Though quarantine means that time that can be shared with loved ones has increased, it also poses a major burden on parents' shoulders, as they are called to take an educational role while also trying to live their own lives and get on with their everyday job commitments. This situation has significantly increased the risk of experiencing stress and negative emotions in parents, with a potentially cascading effect on children's wellbeing (Sprang and Silman, 2013) .
Hence, despite its positive effect in reducing the number of new infected cases, the mobility restriction and social isolation Abbreviations: SDQ, Strengths and Difficulties Questionnaire; PSI, Parenting Stress Index Short form. associated with quarantine are major concerns for families' psychological wellbeing. Related to this, the health care situation of the country is fragile, calling for attention. Hospitals are overcrowded, and the number of deaths is still increasing, as well as the number of infected people and those recovering in hospitals (Government, 2020) . It is becoming very common to know at least one person who tested positive to COVID-19 or was hospitalized, and, most regretfully, to have experienced the loss of a person due to COVID-19. This might generate fear and preoccupation in parents and children, even for families who do not have to face health problems . Literature concerning previous experiences all over the world that may have some aspects in common with the COVID-19 situation reported a high presence of psychological distress such as depression, stress, irritability, and post-traumatic stress symptoms associated with quarantine (Hawryluck et al., 2004; Brooks et al., 2020) with long-lasting effects continuing for years after the event (Liu et al., 2012) .
The majority of studies conducted during previous pandemics and from the beginning of the COVID-19 outbreak examined psychological consequences on the general population, leaving the study of effects on parents and children mainly unexplored, with few exceptions (Brooks et al., 2020) . One study found that levels of post-traumatic stress were four times higher in children who had been quarantined than in those who were not (Sprang and Silman, 2013) . A preliminary study conducted in China reported the presence of psychological difficulties in children during the COVID-19 pandemic, with fear, clinging, inattention, and irritability as the most severe symptoms for younger children (Jiao et al., 2020) . Still, mechanisms that might explain what specific COVID-19 related risk factors put children more at risk of negative outcomes, and what is the interplay between COVID-19 lockdown and parents' wellbeing on children's adjustment, have not been investigated yet. A deeper understanding of family processes, protective factors, and risk factors in the home environment might be important if the wellbeing of children is to be promoted in these difficult times .
The present study wants to shed light on families' well-being during the COVID-19 outbreak in Italy, by exploring parents' and children's individual and dyadic adjustment after one month of quarantine. Understanding parents' and children's reactions and emotions, and identifying risk and protective factors, is essential to properly address their needs to tailor present and future intervention programs (Sprang and Silman, 2013) .
In general, little is known about which factors may be associated with protection against child behavioral and emotional problems during a health emergency. In order to fill this gap, the main aim of the present study was to explore how pandemicrelated variables, structural aspects of the home and family environment, and parental subjective experience of stress and adjustment to the quarantine, affect the wellbeing of parents and children, and how in turn the well-being of parents and children are associated. Specifically, we explored both individual parent stress and dyadic perception of stress since it is well-know that both levels of stress may impair children's well-being (Belsky, 1984; Abidin, 1992; Madigan et al., 2018; Martin et al., 2019) . We expected that implications of the COVID-19 outbreak might increase parents' psychological difficulties, particularly stress both at the individual and the dyadic level, with a consequent negative impact on children's emotional and behavioral wellbeing (Dalton et al., 2020) .
Parents filled out an anonymous online survey, after reading the written consent form and explicitly agreeing to take part in the study. The survey was shared via social media for a limited time (from April 2nd to 7th, 2020), targeting parents of children aged 2-to 14-years-old. In the case of multiple children, the parent was asked to report on one child only. All the questionnaires, both parent-and child-related, were completed by the parent. There was no monetary compensation for participating. The final sample providing information on all study variables consisted of 854 parents living in Italy, of which 797 were mothers (Mage = 38.96(6.02) (49% of whom had a high school degree or less, 37% a bachelor's or master degree, and 21% a higher education degree) and 57 were fathers (Mage = 41.9(6.75) (41% of whom had a high school degree or less, 33% a bachelor's or master degree, and 26% a higher education degree). Children's mean age was 7.14 (3.38); 427 were boys. A total of 271 parents were resident in the north of Italy where most COVID-19 cases, were registered i.e., Lombardia and Veneto (from now on defined as the Red Area). Data reported in this study are part of a wider longitudinal research project designed with multiple purposes related to the investigation of the psychological impact of the COVID-19 outbreak in Italian parents and children. The study was approved by the ethical commitment of the Department and was conducted according to the American Psychological Association guidelines in accordance with the 1964 Helsinki Declaration.
An ad-hoc index was computed to evaluate the amount of contact the parent had with people directly affected by the virus, following the assumption that the greater the number of contacts, and the closer the people affected by COVID-19 that the parent knows are to the parent, the greater the impact on psychological wellbeing would be. One point was given for each of the following if present: the parents tested positive for the virus, a familiar or close friend tested positive, a familiar/close friend was hospitalized, a familiar/close friend died. A half=point each was given if the parent knew a person (not familiar or close friend) who tested positive, was hospitalized, or died.
An ad-hoc risk index was computed to evaluate the house and family situation, including factors supposed to be related to the quality of life condition. One point was given for each of the following: loss of job due to the pandemic, absence of external spaces (balcony or garden), total family income less than 1250 e per month, only one adult in the house in charge of the child, no Wi-Fi, no pets. To compute the index, this score was summed with the number of rooms/number of people ratio in the house.
Difficulties experienced by parents during the quarantine were investigated with a newly developed pool of 13 items. Parents were asked to indicate, using a 7-point Likert scale, how difficult they were perceiving, during the last week, dealing with several aspects related to the quarantine such as finding a relaxing space alone to unplug, time for the partner and for kids, and to do activities such as sport, reading, cooking, etc. (see Appendix 1 for the full list of items). Cronbach's alpha was 0.84, with 95% CIs [0.83-0.84].
Perception of parent's stress in the parent-child interaction was investigated using the 15 items Parent/Child Dysfunctional interaction domain of the Parenting-Stress Index Short Form (PSI) (Abidin, 1995) . The scale investigates with a 5-point rating scale the extent of parents' agreement or disagreement with statements describing the parent-child relationship as difficult to manage. Cronbach's alpha in the current study was 0.86, 95% CIs [0.86-0.86].
Parent's individual perception of stress was investigated using the 7 items from the Stress subscale of the Depression Anxiety Stress Scale-Short form (DASS) (Lovibond and Lovibond, 1995) . The scale provides on a 5-point rating scale a measure of individual symptoms indicating stress i.e., irritation and agitation. To obtain the total score, items are summed. Cronbach's alpha in the current study was 0.88, 90% CIs [0.88-0.89].
Behavioral and psychological problems in children were investigated using the parent-report form of the Strengths and Difficulties Questionnaire (SDQ) (Goodman, 2001) . The current study focuses specifically on the following subscales: emotional symptoms, hyperactivity-inattention, and conduct problems. Each subscale is measured by 5 items, rated on a 3-point scale. To obtain the total scores, items are summed. Cronbach's alpha in the current study were as follow: 0.
First, descriptive statistics and bivariate correlations among study variables were presented. Afterwards, two multivariate mediation models were tested, including as a predictor relevant quarantinerelated risk factors (derived from the correlational analysis), as a mediator parents' stress (in one model dyadic parenting stress was explored as the candidate mediator, in the other model it was individual stress) and as outcomes children's psychological problems at the SDQ. Mediation models were compared with a with a null model and a main effect model, including only quarantine-related risk factors as the predictor. Akaike weights, providing the probability of a model to support new data conditional on the set of models considered, were used for model comparison (Wagenmakers and Farrell, 2004) . Parameters were investigated for the best fitting model. Finally, as a followup analysis, we explored whether results were comparable distinguishing between parents' living in the Red Area (including Lombardia and Veneto regions) with the rest of the sample. To this aim, we performed a multi-group analysis. Analyses were run using the statistical software R (Team, 2018) , lavaan package (Rosseel, 2012) . Plots were depicted using package ggplot2.
Means, SDs, and correlation values among variables of interest are reported in Table 1 . Due to the large sample size, correlation values above 0.06 (i.e., trivial in effect size) were significant at p < 0.05; thus, for interpreting effects, we considered the strength of the association (namely Pearson's r) as an effect size. Results showed that overall there were no relevant associations of COVID-contact risk index and Home environment risk index with dyadic parenting stress (PSI), parent's individual stress (DASS), and children's psychological problems (SDQ).
Because the only risk factor associated with parent's individual and dyadic stress and children's psychological problems was the Quarantine parent risk index, we did not include in the model the Home and COVID risk indices. Thus, models tested had as a predictor the Quarantine parent risk index, as the candidate mediator parent stress (dyadic and individual), and as outcomes children's emotional and behavioral problems. For both the model including dyadic parenting stress as a mediator and individual stress as a mediator, the mediation model outperformed the null and main-effect regression model. Specifically, for the model including dyadic parenting stress as a mediator, Akaike weights were lower than 0.001 for both the null and the main effect model, and very close to 1.00 for the mediation model. The same weights were obtained for the comparison with the mediation model including individual stress. Standardized estimates of the two mediation models are reported in Figures 1, 2 . Parameters for indirect effects and proportion of variance explained for each outcome variable for the investigated models are reported in Table 2 .
Because of the significant association between study variables and age, we ran the analyses again, including the effect of the child's age on the mediator and outcome variables. Results remained stable overall. With a multi-group analysis, we finally explored whether results were comparable for residents in the Red Area (Lombardia and Veneto) vs. other regions. No relevant differences were identified. Results are available upon request to the corresponding author.
The COVID-19 outbreak is a completely new and unexpected situation currently affecting many countries. Italy was, after China, the second most highly affected country at the time, with the pandemic spreading very fast. In just a few weeks, the population found itself from thinking that the pandemic was happening far away, to being directly involved (Government, 2020) . The closure of schools and the decision to keep children locked at home was obvious, but the consequences of all this for families' well-being were barely considered.
Our study is the first to examine the impact of the COVID-19 outbreak on parents' and children's wellbeing. We explored bivariate associations among the environment, family, and COVID-19 outbreak-related factors on parents' stress and children's psychological problems, and the interplay among these variables. Results showed that factors such as living in a more at-risk contagion zone or being in closer contact with the virus' effects do not relevantly affect parents' and children's well-being. This confirms findings from a preliminary study in China, where the difference in children's symptoms between areas identified by different levels of epidemic risk was not statistically significant (Jiao et al., 2020) . Similarly, the quality of the environment, such as the physical characteristics of the living space, is not associated with parents' and children's psychological symptoms. Yet, it is the parents' individual perception of the situation, and more specifically how difficult they find it dealing with the many stresses the quarantine imposes, that is significantly associated with parent's stress and children's psychological problems, and that indirectly impacts on children's behavioral and emotional problems through the mediating role of parent's stress. Parents who report finding taking care of their children's learning, finding space and time for themselves, the partner, the children, and for the activities they used to do before the lockdown more difficult, are more stressed. This confirms studies that found an effect of the limitations associated with quarantine on the well-being of adults (Brooks et al., 2020) . We further add to the literature that this stress is experienced both at the individual (e.g., being over-reactive, feeling nervous and irritated) and at the dyadic level (e.g., finding it difficult to enjoy interactions with the child, and child behavioral and emotional expressions). In addition, we pointed out that it is this stress that significantly impacts on children's well-being. Hence, it is mainly when the strains of quarantine affect the ability of the parent to enjoy and appreciate the parent-child relational experience that the consequential negative impact on the child's well-being is stronger, a result with important implications for informing intervention programs that target the family and the child. Moreover, this impact is present at every age, even though our age range is quite wide. This underlines that the impact of the lockdown on parents and children is present with similar mechanisms for families with children younger than 14 years. The effect we identified in our study may be explained in many ways. More stressed parents find it more difficult to understand their child's needs and to respond in a sensitive way (Abidin, 1992; Scaramella et al., 2008) . Stress is often associated with rude behaviors and difficulties in explaining limits and discipline. Thus, children in these families may feel less understood by their parents and may react in more negative and aggressive ways (Pinquart, 2017) . Moreover, we know that children have lower personal resources to deal with the many changes the pandemic is imposing on their life and guidelines suggest parents should discuss and explain the situation with them, since correct information about what is happening and the reasons for the restrictions children have to face is crucial to prevent negative psychological consequences (Dalton et al., 2020) . However, how and when to do that is completely left up to the parents' choice. We can speculate that more stressed parents may be too overwhelmed by the situation to find appropriate ways to be a supportive figure for their children and to find the best ways to address children's questions and fears (DiGiovanni et al., 2004) . When children do not find responsive answers to their preoccupations from adults, they may show more distress, evidenced by more emotional and behavioral problems as well as inattention and difficulties in concentrating.
These results suggest many interesting implications that should be addressed in the present and in the future in Italy, and in all countries involved in the pandemic, if we want to promote children's wellbeing, and prevent the onset of more severe behavioral and emotional problems. The pandemic and the quarantine associated with it require using personal resources to deal with everyday life and fears and worries. Correct information and guidelines have to be given to adults about how this stressful situation may affect their personal and children's wellbeing. Public health should provide parents with knowledge about, for instance, how children at different ages express distress and the importance of sharing and talking about fears and negative emotions (Dalton et al., 2020) . In this way even less resilient and more stressed parents may be helped in finding ways to understand and support their children (Belsky, 1984) .
The closure of schools may have also contributed to this phenomenon. Firstly, because parents are left alone dealing with their children's education and learning, this may be a very challenging duty. Moreover, teachers have a role not only in delivering educational materials but also in offering an opportunity for children to interact, and to receive from them support and explanations. Organizing online courses in a way to also improve the possibility for children to interact with their teacher about things outside of the learning context should be a priority especially if school closures are to be prolonged. Moreover, the Government should take into consideration the impact of school closures on parents by finding ways to help them deal with the learning experience of children and with having children at home 24/7, while parents also have to manage homeworking and childcare. This is going to be even more relevant if, during the second phase of the emergency, job activities will re-open, and parents will be asked to go back to work, but schools will be kept closed. How are parents supposed to deal with this?
Some limitations of the present study should be addressed. Firstly, this is a correlational study; a longitudinal exploration of the effects of quarantine on parents and the cascading effects on children over time would help in better understanding the phenomenon. Moreover, we have collected children's psychological symptoms from parent reports; although this data collection method is widely used it may be less informant than child reports or direct evaluation of children's well-being made by experts. Lastly, we may expect that quarantine risk is higher for more at-risk families i.e., families of separated parents, families with children with disabilities, very poor families, etc. The exploration of the phenomenon with those in at-risk situations would help in developing more tailored interventions.
If properly supported by healthcare professionals and other social connections, including the school environment, parents and children can appropriately overcome this critical period of distress and avoid severe long-term consequences. Quarantine and social distancing are efficient ways to deal with the pandemic, but these experiences may have consequences on people's wellbeing. However, the media and public institutions concentrate primarily on physical health to recommend steps for the prevention and containment of the disease, leaving the impact on mental health undiscussed. Indeed, stable mental health is one of the keys to fight this ongoing pandemic and to restore a post-pandemic society; the well-being of parents and children must be under surveillance since problems on this side may have long-lasting implications.
As Bowlby suggested 30 years ago, "Man and woman power devoted to the production of material goods counts a plus in all our economic indices. Man and woman power devoted to the production of happy, healthy, and self-reliant children in their own homes does not count at all. We have created a topsy-turvy world" (Bowlby, 1988) .
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
The studies involving human participants were reviewed and approved by Department of Neuroscience, Imaging and Clinical Sciences. The patients/participants provided their written informed consent to participate in this study.
MS, FL, and MF conceptualized the study and organized the data collection. MS and FL wrote the first draft of the manuscript. FL and MP run the analyses and wrote the results section. All authors contributed to revision of the final version of the manuscript.
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The recent outbreak of novel coronavirus 2 (SARS-CoV-2)associated disease (COVID-19) has quickly gained pandemic status transforming healthcare delivery worldwide. Nationwide lockdowns and prioritization of healthcare for acute care have disrupted and delayed the delivery of care to patients with cancer. It is reported that patients with cancer are already at an increased risk of infection [1] . Cancer patients who contract COVID-19 have more than triple the risk for severe health events including admission to the intensive care unit for invasive ventilation and rapid clinical deterioration [2] . An Italian study assessing the case fatality of COVID-19 reported that 72 (20.3%) among 355 patients who died had active cancer [3] .
As the COVID-19 pandemic deepens and widens, hospitals are bracing up for challenging times as the crisis significantly reduced the outpatient department (OPD), hospital inpatient care (IPD), and operating room (OR) footfalls. The oncology community is striving profoundly to reorganize the oncological care in order to reduce in-person clinical appointments, prioritizing treatment strategies, educational activities, and staff management and rescheduling cancer surgeries without compromising cancer outcomes. It has been advised that hospitals discontinue elective surgery and work on triage of nonemergent surgical procedures during the pandemic [4] . On the contrary, in the absence of treatment, cancer may spread or develop resistance to treatments causing multiple complications or, in some instances, death. We may see a drop in the proportion of early detected malignancies due to delayed presentation which could have cascading effects on cancer patients. Hence, it is imperative to design and implement clinically relevant SOP-driven changes that are required to resume cancer surgeries and guide the decision-making for appropriate surgical care. World Health Organization (WHO) and Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) have also emphasized to create, review, and update a clinical policy rapidly for preventing COVID-19 infection [5] .
The article reports consensus from the virtual platform meeting among the core expert group from the public and high volume private hospitals across India. Experts navigated through a set of questions and elaborated on their practice changes and new SOP development. The domain expertise of the expert group and the outcome of their discussion were used to bring together consensus recommendations that can be adapted by other oncology treatment centers in India during the COVID-19 crisis. The discussion was carried about the situation and operational challenges, patient prioritization and safety measures, changes in disease behavior and treatments, measures for the operating room, surgery and staff safety, potential challenges on different surgical approaches, and medical device usage changes. The discussion outlines many commonalities but also important local differences in specific implementation strategies, which have been documented and captured as an algorithm paving the way forward for different healthcare setups pinpointing critical practical approaches to enable evidence-based remodeling of cancer care during the COVID-19 pandemic. By sharing the joint experiences, this report aims to mobilize the global research community to publish the consensus guidelines/sharing best practices and views on the resumption of care and safety for operating rooms [OR] and surgical procedures that are critically needed to offer the best possible care to cancer patients (Table 1) .
In public and private institutions, the general policy has been to attempt to stay COVID-19 free by establishing designated facilities or separate block within existing facilities to provide COVID-19-related services [filter/fever clinics and dedicated COVID health center] to individually screen and triage people and staff before permitting entry into the facilities [ Fig. 1 ]. In addition, the centers forced strict restrictions on the number of visitors [6] accompanying patients when admitted to the hospital or during infusions or radiation treatment, as visitors could potentially be [unknowingly] COVID-19 positive. Institutes who are at the forefront in combating COVID-19 have had to deal with admissions for patients without cancer that has included suspected and positive cases of COVID-19 in separate facilities while limiting the admissions to emergency cancer patients. Hence, the priority at these institutes was given to workforce allocation, personal protective equipment [PPE] acquisition, and creation of capacity for ICU's and ventilators. Given the high transmissibility rate of SARS-Cov-2, all centers have facilitated face-to-face consultations, whenever possible, taking place via web consulting or by telephone calls to avoid overcrowding of hospitals and to ensure patients are not exposed to SARS-CoV-2 virus during travel or in health facilities. For survivor groups, online meetings have been organized through teleconferencing software platforms. There were no specific changes in treatment and noted changes in disease behavior observed during the pandemic phase. The crisis is said to affect the clinical outcomes adversely due to delayed presentation and prolonged time before treatment initiation. No significant increase in hospital length of stay has been reported except in a few cases.
Priority setting for the delivery of cancer therapies in the context of a pandemic will be strongly influenced by several factors, including the patient's location and resource allocation-from protective gear, hospital beds, and to nursing and doctor time. Few guidelines are currently available for different surgical considerations and prioritization [7, 8] ; however, the prioritization process should be adjustable to local, regional, and national epidemiological trends and changes in COVID-19 care. The prioritization process should also take a facility's resources, priorities, and patient needs into account [9] . The prioritization process, principles, and framework should be transparent to hospitals, healthcare workers, and the public. The benefits of transparency include reducing ethical dilemmas. There are multiple considerations in developing the prioritization process, including a list of canceled and delayed procedures, a strategy for a phased opening of ORs, PPE availability, and issues related to increased OR volume. Priority allocation of resources and staff to COVID-19 care, a continuation of emergency, semi-urgent essential care, and gradual resumption of withheld elective clinical activities need to be balanced and should now continue side by side considering that the COVID-19 pandemic is here to stay for a longer period. Though this would be guided by local COVID-19 situation and the extent to which hospital infrastructure is occupied by COVID-19 patients, it is gradually being realized that delays in non-COVID-19 care can be equally if not more devastating and this cannot be postponed indefinitely [10] . Figure 2 depicts prioritization (Priority A has highest and C being lowest) considerations based on factors like the chances of cure, availability of effective non-surgical treatment options or effective of upfront non-surgical treatments, and risk for progression.
COVID-19 appears to affect people of all ages; however, cancer patients who are usually characterized by lower immunity and immuno-depressed state because of their chemotherapy or surgery are at higher risk for serious medical complications and increased mortality once infected with COVID-19 compared with the healthy population [2] . Hence, more attention should be paid to cancer patients as the effective prevention of cross-infection of COVID-19 and the rational arrangement of Second, multiple on-site temperature tests are performed in the triage tent at the entrances of the hospital authorized by a multidisciplinary triage team. Strict screening strategy with a standard questionnaire scoring system designed by ICMR has been implemented for all patients, visitors, and medical staff presenting to the hospital. Patients who do not pass the scoring track are restricted to enter OPD and were dealt separately in the clinics outside. Furthermore, some hospital initiatives such as code green have been taken to restrict the free movement of high-risk patients. These reported safety measures may be of great value to help guide patients with cancer smoothly and safely through the crisis.
The overarching goal in cancer care during the COVID-19 crisis is to provide compassionate and high-quality cancer care while continuing to look after patient and staff safety. SARS-CoV-2 is considered most contagious when the patient is symptomatic, and the evidence suggests that it is transmitted by asymptomatic individuals as well [11] . Transmission before the onset of symptoms has been reported [12, 13] and has contributed to spreading among residents of a nursing facility in Washington, USA [14] . Transmission of SARS-CoV-2 within healthcare facilities to healthcare workers has been documented in China where 3.8% of COVID-19 cases were reported in healthcare workers leading to five deaths [15] . Italy reported 15,314 infections among healthcare workers, representing 11% of all infections as of 10 April 2020 [16] . The World Health Organization reported 22,073 cases of COVID-19 among healthcare workers from 52 countries as of 8 April 2020 [17] ; however, due to lack of systematic reporting, the actual number is underrepresented.
Due to the lockdown imposed by the government responding to this crisis, public and private institutes developed the outbreak response administrative measures such as modification of workflow and processes, management, coordination and movement of staff, the introduction of personal protective equipment for staff, and strengthening of the screening tests. Institutes formulated self-institutional guidelines for safety protocols based on the ASA and APSF, SSO, IASO, and AMASI guidelines. To deliver universal high-quality care through multidisciplinary medical guidance to cancer patients, virtual tumor boards were launched and department meetings have been initiated. One important consideration even in routine work is that all ORs should consider all patients as COVID-19 positive and must be accommodated in negative pressure operation rooms based on availability. Other measures include minimizing patient-provider encounters.
When compared with the flow of surgeries with pre-COVID-19 phase, public institutes reported a 50-60% drop in numbers of oncosurgeries but reported no change in emergency surgeries. To cope with the anticipated increased influx of COVID-19 patients, private institutes decided to continue with only emergency surgeries as normal during phase 1 lockdown. All priority oncosurgeries in private institutes were resumed back during the phase 2 lockdown and were made possible due to the development of a few internal policy changes specified above. There is an agreement that managing rotation of staff is a key issue in resuming services and minimizing exposure. One such strategy adopted was 2 weeks on and 2 weeks off considering the incubation period can be as long as 14 days. Another strategy adopted at private institutes suggests 3 days on and 3 days off duty for medical and radiation oncologists, encouraging every clinician to visit alternate day for 2-3 h.
Perioperative COVID-19-positive status confers a very high risk of perioperative pulmonary complications and mortality. Risk is higher for patients undergoing major cancer surgery [18] . Many guidelines strongly recommend testing for SARS-COV-2 prior to the operation [7] and emphasized on RT PCR testing to all patients. This can be resource exhaustive and may not be completely practical at this moment for universal application considering the limited number of test kit availability and rising incidence across the country. Also, RT PCR is only 70% sensitive, and the risk of false negativity is significant [19] . Whether universal screening can be mandated for every patient undergoing surgery based on the available resources is yet unanswered. This is currently being governed by recommendations released from time to time by authorized national and local government health agencies. The process however is dynamic, and we will probably see routine preoperative testing to for COVID-19 in times to come considering the risk to the patient and healthcare workers both in absence of definitive treatment and immunity.
Cancer surgery and other surgeries that cannot be avoided should be continued with adequate precautions as far as possible, and surgical approaches should be selected judiciously. A small but definite risk of transmission exists irrespective of the surgical approach [open, laparoscopic, or robotic]; however, one needs to take all the possible precautions to minimize it. It is well established that laparoscopy has not only a favorable impact on respiratory function but also less pain and reduced length of stay for patients. However, safety precautions are necessary when performing laparoscopy due to the risk of exposure and infection to the staff personnel [20]. Many emergency laparoscopic procedures will still be required during this pandemic, yet very little is known regarding the uptake of these procedures during the COVID-19 crisis surrounding SARS-CoV-2 virus transmission. There are concerns relating to COVID-19 transmission arising from the potential generation of SARS-CoV-2-contaminated aerosols from CO 2 leakage during laparoscopic surgery, although there are no data to support it. Intubation and extubation remain one of the highest risk aerosol-generating procedures due to the high viral load in respiratory secretions [21] . However, performing minimally invasive robotic and laparoscopic surgery is not contraindicated if provided with certain modifications. Few hospitals have modified all the trocars and cannula with an external evacuator which goes through an undersealed double chamber sodium hypochlorite and the third chamber with a buffalo filter.
Laparoscopy allows for a self-contained operative field with less and possibly no spillage of fluids and tissues, thus minimizing risk to the operative staff. All institutes agreed that laparoscopic surgery can be continued where clear benefits have been evident but emphasized avoiding experimental laparoscopy during the current crisis. On the other hand, at some hospitals, all minimally invasive surgeries were suspended initially but have resumed especially in patients with prostate and lower rectum cancers where the benefit over open surgery is well established [22] . The temporary suspension was observed at institutes due to available infrastructure, patient number, surgery time, and staff availability. It is advisable to evaluate risk of COVID-19 in patients before any surgery, rather its high time to emphasize and follow infection control with the utmost care.
As laparoscopy is known to result in the earlier discharge of patients from hospitals and less dealing with surgical wounds and surgical site infections (SSIs), few guidelines have been established providing recommendations regarding laparoscopic surgical response to COVID-19 [23] . It is reported that the aerosol can contaminate personnel and all the furniture and surfaces in the room via airborne particles when released during laparoscopic surgery [leaks] or after the operation (exsufflation) [24] . Smoke evacuators used at the time of laparoscopy offer the unique advantage of being able to reduce the surgical plume in the abdominal cavity [20] . However, there is no compelling data to support the notion that COVID-19-a novel virus-is transmitted through the surgical plume or aerosolized laparoscopic gas. To disseminate knowledge and provide guidelines for minimally invasive surgery procedures, a recent study suggested the usage of lowpressure peritoneum, the use of balloon trocars, evacuating all pneumoperitoneum before trocar removal, or specimen extractions [25] . On emphasizing the importance of using smoke evacuators, hospitals should consider the use of new modalities such as suction devices placed near the electrosurgical site, to further decrease the aerosolization that could improve smoke evacuation beyond the simple vacuum and filter system [26] . However, there are no claims reporting any changes in surgical technique practices or use of any surgical devices including usage of energy devices, but adequate safety precautions must be taken.
Temporary halt on non-COVID-19 healthcare services has caused anxiety and confusion among cancer patients [27] . It is possible that the stress related to this pandemic may exacerbate other treatment-related effects and the psychosocial impact of the pandemic may disproportionately affect the cancer patients. It is important that clinicians directly acknowledge patients' concerns about their individual risks and anxieties. To address these psychosocial needs of the patients, institutions have started providing psychosocial counseling not just to patients but also to the staff personnel for empowerment and control during this pandemic.
During the COVID-19 crisis, physicians are providing competent care by placing patient welfare above other interests, catering the information to enable patients to make wellconsidered decisions and promoting continuity of care, while respecting patient privacy and confidentiality. Hospitals implemented teleconsultations to patients by strictly adhering to the requirements of Telemedicine Practice Guidelines published by the Indian government [28] . Few hospitals have integrated a teleconsultation software with the institutes HIS system, and a separate teleconsultation team is established to provide personalized telehealth advice electronically. Patients were encouraged to consent for teleconsultation, and identification was confirmed through a government ID while providing safeguards to protect the patient's privacy and security and documenting the prescription and clinical evaluation.
Informed consenting is a fundamental step in clinical practice. A small early study from China suggested that cancer patients who underwent surgery or chemotherapy in the month preceding the appearance of the virus had a higher risk (75%) of developing a severe episode compared with those who had not undergone surgery or chemotherapy (43%) [2] . Further evidence described the high mortality rate and poorer outcomes associated with COVID-19 in cancer patients with older age [18, 29] . Hence, it is crucial to include the data about the effect of cancer and cancer treatment risks in the wake of the COVID-19 crisis and communicated in a clear and detailed manner to the patients during the informed consenting process by the treating oncologist. All institutes involved in this discussion have already adapted to this measure to support individual autonomy to patients about their treatment decisions.
In the wake of the COVID-19 pandemic, we recommend rigorous preparations in terms of internal administrative measures. These measures include the modification of infrastructure and processes, management of staff and patients, strict screening and triage strategies, establishment and frequent updating of protocols, and clinical recommendations and infection prevention strategies. Appointments of patients on follow-up should be managed through telemedicine or web consulting to reduce the possibility of hospital visits and eliminating the risk of spreading the virus. All treatment decisionmaking should follow standard guidelines and must be taken in the context of a multidisciplinary tumor board. The informed consenting process must include recent data about the risk and benefits of treatment in the context of the specific COVID-19 pandemic status.
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study central nervous system (CNS) diseases including both encephalitis and demyelination. Different strains of MHV induce disease with varying degrees of severity. The A59 strain induces acute encephalitis during the first week of infection and a strong CD8+ T-cell response is observed in the brain coinciding with virus clearance. Despite efficient clearance of infectious virus, demyelination is evident four weeks postinfection (p.i.). The JHM strain (also referred to as MHV-4 or JHM.SD in the literature) 1 induces lethal encephalomyelitis within the first week of infection and virus is typically not cleared. In this study, we investigate the CD8+ T-cell responses induced during infections with A59 and JHM.
Virus specific CD8+ T cells play a protective role against MHV strain A59 and are essential for clearance of infectious virus from the central nervous system (CNS). We have previously found that only early transfer, prior to 3 days postinfection (p.i.) with RA59-gfp/gp33, of gp33-specific CD8+ T cells (obtained from P14 transgenic mice) resulted in accumulation of activated epitope-specific CD8+ T cells within the brain. 2 We observed that P14 splenocytes did not accumulate in the brains of RA59-gfp/gp33 infected mice when the transfers were performed on day 3 or 5 p.i. In order to determine if this was due to a defect in trafficking or priming during the infection, we examined the expansion of transferred CFSE-labeled gp33-specific CD8+ T cells in the draining cervical lymph nodes following infection with RA59-gfp/gp33. In addition, we sought to determine why activated, virus-specific CD8+ T cells are detected at very low levels in the spleen and brain after infection with RJHM.
Four-week-old male mice were used in all experiments; B6 or B6-LY5.2/Cr (CD45.1) mice were obtained from the National Cancer Institute. P14 mice 3 were bred at the University of Pennsylvania. Recombinant MHV strain A59 expressing enhanced green fluorescent protein (EGFP) or expressing the gp33 epitope as fused to EGFP are described elsewhere. 4 Recombinant A59 (RA59), recombinant JHM (RJHM) and the recombinant chimeric virus expressing the JHM spike with A59 background genes (SJHM/RA59) have been described elsewhere. 5,6 .
Spleens were removed from P14 mice and suspensions were prepared by homogenizing in a nylon bag (64 µm diameter) in RPMI 1640 medium supplemented with 1% fetal calf serum. Red blood cells were lysed with 0.83% ammonium chloride and the lymphocyte suspension was washed twice in 1 x PBS and resuspended in 1 x PBS for transfer. Cells (at a concentration of 5 x 10 7 cells/ml) were labeled with 1 µl of 5 mM CFSE/ml. The total number of cells transferred was 2 x 10 7 cells in 0.5 ml.
Mice were perfused with 10 ml 1 x PBS and organs removed. Brain lymphocytes were isolated as previously described. 7, 8 Cells were harvested from spleens and lymph nodes as described above. Intracellular IFN-γ was assayed as previously described.
Demyelination was analyzed in at least 10 sections of spinal cord from each animal and five to eight mice were examined in each of two separate experiments. Percent demyelination was calculated by counting quadrants of cross-sectioned spinal cord that was stained with the myelin specific dye, luxol fast blue. A neuropathologist examined the spinal cords to determine the severity score which was from 0 to 5 with 5 being the most severe demyelination. 2
Transfer of naïve, gp33-specific CD8+ T cells one day prior to infection with RA59gfp/gp33 protected against acute encephalitis and, importantly, virus spread to the spinal cord was markedly reduced. This correlated with a dramatic reduction in the quantity and severity of demyelination seen 28 days p.i. However, mice that received adoptive transfers of gp33-specific CD8+ T cells on days 3 or 5 p.i. were not protected from acute disease, which was assessed by virus replication, viral antigen spread and encephalitis. Importantly, only the mice receiving the early transfer that were protected from acute disease had significantly reduced chronic demyelination as observed on day 28 p.i. (Table 1) . We observed that the early transfer, performed one day prior to infection, resulted in protection from acute and chronic disease. In addition, we observed that the transferred (CD45.2 positive) cells were activated and secreted IFN-γ in response to gp33 peptide and accumulated to high percentages within the brains by day 7 p.i. However, the transferred cells did not accumulate in the brain on day 7 p.i. when the transfers were performed on days 3 or 5 p.i. Thus, we examined the brain-derived mononuclear cells from transfer recipients at later time points, days 10 and 12 p.i. As is evident from the data shown in Table 2 when transfers were performed on days 3 or 5 p.i. significantly fewer transferred cells accumulated at the site of infection as compared to the transfer recipients that received the transfer prior to infection. Whereas nearly half of the CD8+ T cells were the transferred cells in the early transfer recipients on day 10 p.i., only about 10.0% and less than 1.0% of the CD8+ T cells were the transferred cells in the day 3 and day 5 transfer recipients, respectively. Furthermore, on day 12 p.i. the total numbers of both CD8+ T cells as well as the transferred CD45.2-positive cells decreased as compared to day 10 p.i. We concluded that the cells transferred on days 3 or 5 p.i. were defective in their activation and/or ability to traffic into the CNS. However, when transfers were performed in RAG-/-, we observed the accumulation of gp33-specific IFN-γ-secreting cells in the brain and the later the transfer was performed the higher the percentage of gp33-specific cells observed in the brain. RAG-/-do not contain endogenous T cells capable of lytic activity, thus, it is assumed that antigen presentation is prolonged. Thus, we predicted that when we transferred P14 splenocytes into B6 mice on days 3 or 5 the cells were not activated or recruited into the brain due to a lack of antigen presentation at that time point.
In order to determine whether there was a block in the ability for the gp33-specific CD8+ T cells to traffic into the brain or if there was a defect in priming of the transferred cells, we developed an adoptive transfer model to trace the expansion of transferred cells. P14 splenocytes were labeled with CFSE and transferred prior to infection or on day 3 post infection.
As previously been reported in the literature, 9 we observed that RJHM elicits a surprisingly weak CD8+ T-cell response and a poor epitope specific IFN-γ response. In order to rule out the possibility that RJHM causes destruction of the brain parenchyma that prevents recruitement of CD8+ T cells, animals were inoculated intranasally (i.n.) with their LD 50 dose of 100 or 1000 pfu of RJHM or SJHM/RA59 (recombinant A59 expressing the JHM spike in place of the A59 spike), respectively. Intranasal infection results in a slower course of disease with most animals dying after the first week of infection allowed the analysis of recruitment of T cells into the brain. Mice were sacrificed at 7 days p.i. in order to analyze the epitope specific CD8+ T-cell response at the site of infection. Whereas 21.9% of the cells isolated from the brains of SJHM/RA59 infected animals were CD8+, only 0.8% of the cells isolated from the brains of RJHM infected animals were CD8+. Furthermore, the specific IFN-γ response to the two epitopes within the spike protein was much higher in the SJHM/RA59 infected animals (Fig. 2) . This also indicates that the low CD8+ T-cell response is not due to the RJHM spike.
In order to determine if RJHM was capable of suppressing the immune response we coinfected mice with RJHM and RA59. Interestingly, the coinfected animals had a strong CD8+ T cell response to the subdominant S598 epitope that is present in both viruses, however, there was still no response to S510, the immunodominant epitope that is only present in RJHM.
In this study we define the window of antigen presentation during a CNS infection with RA59-egfp/gp33 to be within the first 72 hours of infection. When splenocytes were transferred on day 3 p.i., they were not activated to proliferate and, thus, did not accumulate within the brain. This provides more evidence that in order for CD8+ T cells to traffic to the site of infection they must undergo several rounds of division in the lymphoid organs. Furthermore, consistent with the idea that antigen presenting cells are destroyed by cytotoxic T lymphocytes as limiting determinant of immune activation we observed that transfers performed on days 3 and 5 p.i. in RA59-gfp/gp33 infected RAG-/did result in the accumulation of virus-specific CD8+ T cells within the brain 7 days post transfer ( Table 2) . The neurotropic strains of MHV, A59, and JHM induce different courses of disease with JHM resulting in lethal encephalitis within the first week of infection. In addition, the brains of infected animals. Following coinfection with JHM and A59, we observed that JHM is not capable of suppressing the CD8+ T-cell response but fails to elicit a CD8+ T-cell response. The weak CD8+ T-cell response induced during infections with JHM is not spike-determined as a chimeric virus expressing the JHM spike with the background genes derived from A59 results in a strong CD8+ T-cell response to both the S510 and S598 epitopes.
We thank Peter T. Nelson for analyzing and scoring demyelination. This work was supported by NIH grant no.AI-47800.
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Diabetes is a non-infectious metabolic disorder. It is characterized by hyperglycemia contingent on a shortage in secretion or resistance to insulin action and β-cell dysfunction (Adedara et al. 2019) . Epidemiological studies revealed that the incidence of diabetes is on the rise around the world, with an estimation of approximately 387 million people. This figure is predicted to rise to 590 million by 2035 (Guariguata et al. 2014 ). This rise in the incidence of diabetes is of global concern, as it has been linked to immunocompromise that could exacerbate viral infections like COVID-19. Therefore, studies on mechanisms and new pharmacological agents with hypoglycemic potentials to enhance the well-being of people with diabetes are warranted.
Among the complications associated with diabetes are damage of vital organs functions, including the brain (Banks et al. 2012; Ascher-Svanum et al. 2015) . Neurological disorders owing to diabetes have been confirmed in both clinical and experimental studies (Erbaş et al. 2016; Bădescu et al. 2016) . Several studies have shown that diabetes-related alterations in brain function could aggravate neurological ailments, for instance, impaired cognitive function, depression, anxiety, and altered locomotor function (Kodl and Seaquist 2008; Patel and Udayabanu 2017) . Earlier reports revealed a noticeably higher frequency in anxiety among diabetic subjects in comparison with their non-diabetic counterparts (Maia et al. 2014; Castellano-Guerrero et al. 2018) . The vulnerability of the brain to diabetes can be ascribed to its high level of peroxidizable polyunsaturated fatty acids (PUFAs) constituent, which is the principal target of peroxidative attack under conditions of oxidative stress. Oxidative stress could occur in diabetes owing to increased production of free radicals, which prevail over the body's inherent endogenous antioxidant systems (Patel and Udayabanu 2017) . Altered pancreatic β-cells function and insulin resistance are the main features of diabetes (Kodl and Seaquist 2008; Adedara et al. 2019) and are triggered by oxidative stress owing to the continual high glucose level in the system (Asmat and Abad 2016; Ebokaiwe et al. 2019) .
Metformin is the most commonly used oral regimen in diabetic treatment. The role of metformin in the treatment of neurodegenerative diseases apart from the known hypoglycemic effect has garnered attention in recent times (Markowicz-Piasecka et al. 2017) . Results of several experimental and clinical studies indicate that metformin treatment improves cognitive function (Markowicz-Piasecka et al. 2017 ) and protect the brain against the oxidative imbalance imposed by diabetes (Correia et al. 2008) . Alteration in selenium homeostasis is one of the various mechanisms proposed for the pathogenesis of diabetic complications. Earlier studies showed that there were increased risks of diabetes and its accompanying complications owing to deficient selenium levels in the brain (Ozkaya et al. 2009; Rayman and Stranges 2013) . Thus, selenium plays a vital role in brain functions.
The emerging influence of nanotechnology as well as reported biological activities of nano-sized materials by ameliorating several metabolic disorders (Al-Quraishy et al. 2015; Abdulmalek and Balbaa 2019; Ebokaiwe et al. 2019 Ebokaiwe et al. , 2020a prompted the current study on SeNPs. Also, recent developments in nanotechnological advancement have resulted in the nano-sizing of dietary trace elements with proven biological significance such as Se nanoparticles (SeNPs). These have garnered recognition in the management of metabolic disorders owing to their functions as composites of some enzymes and proteins in the biological system (Rayman and Stranges 2013; Abdulmalek and Balbaa 2019; Ebokaiwe et al. 2019 Ebokaiwe et al. , 2020a .
In this study, the basic features of diabetes were mimicked in rats using fructose to induce insulin resistance and a low dose of STZ to induce partial dysfunction in pancreatic β-cell per earlier protocol (Wilson and Islam 2012) . Hence, this study is the first designed to assess the potential influence of SeNPs and/or Met treatment against diabetes-associated brain inflammatory/ oxidative injury and behavioral impairments in rats.
Selenium was procured from Thermo Fisher Acros Organics (Geel, Belgium). Anti-parvalbumin was purchased from Novus Biologicals (USA), anti-Nrf2 primary antibody from Abcam (USA), and anti-caspase 3 from Cell Signaling (USA), and β-actin antibody from Santa Cruz Biotechnology (USA). All chemicals/reagents were of analytical grade.
The nanoparticle was produced, lyophilized, and characterized by following the methods in our earlier reports (Ebokaiwe et al. 2019 (Ebokaiwe et al. , 2020a .
Male adult Wistar rats weighing 165 g ± 5 g were selected for this study. Animals, obtained from the Animal House, Alex Ekwueme Federal University, Ndufu-Alike Ikwo, Nigeria, and kept under the 12 h light-dark cycle. Animals handling was with humane care and standard rat chow diet with water provided ad libitum.
Following the protocol described by Wilson and Islam (2012) , diabetes in animals was induced after a 1-week acclimatization period, by replacing the drinking water with 10% fructose solution ad libitum for 2 weeks to induce insulin resistance, while the normal control (NC) was given only drinking water. Intraperitoneal injection of STZ (40 mg/kg bwt) in citrate buffer (pH 4.5) at day 0 was administered to rats to induce partial pancreatic β-cell dysfunction. NC rats were administered the same quantity of citrate buffer. A week after induction of diabetes, the non-fasting blood glucose (NFBG) level was determined in the blood collected from the tail vein of all rats using an Accu-chek glucometer (Roche Diagnostics GmbH, Mannheim, Germany). Animals with NFBG level higher than 230 mg/dL were considered as diabetic and selected for the study.
As shown in Fig. 1 five groups of eight (8) rats each were maintained throughout the investigation period and administered as follows:
Group I, NC rats were orally administered water/citrate buffer (2 mL/mg bwt);
Group II: Diabetic control (DC) rats were orally administered with citrate buffer (2 mL/kg bwt);
Group III: Diabetic rats treated with metformin (M) orally at 50 mg/kg; Group IV: Diabetic rats treated with SeNPs (0.1 mg/kg) orally;
Group V: Diabetic rats treated with SeNPs and M (0.1 and 50 mg/kg) orally.
Selected doses of SeNPs and M were chosen based on our earlier studies (Ebokaiwe et al. 2019 (Ebokaiwe et al. , 2020a . Animals were monitored all through the 6-week intervention period for non-fasting blood glucose levels and body weight. Animals were sacrificed by cervical dislocation, 24 h after the last treatment, and the blood collected from the retro-orbital venous plexus. Serum samples were obtained by centrifuging blood cells for 10 min at 3000g. This was stored frozen and used later for the determination of insulin levels. Brain tissues were quickly excised, weighed, and some fixed in 10% neutral buffered formalin for immunohistochemistry. All others were frozen at − 80°C until further biochemical estimations.
Rat Insulin ELISA kit-#90,010 (Crystal Chem, Zaandam, Netherlands) was used to quantify levels of rat insulin in serum. Homeostatic model assessment (HOMA-IR and HOMA-β) were evaluated with serum insulin levels and fasting blood glucose (FBG) concentrations taken at the end of the experiment using the following expression:
Tests were conducted after the last administration using the Ymaze, open field test (OFT), and tail suspension test (TST), following protocols from earlier studies (Mori et al. 2014; Ijomone et al. 2015 Ijomone et al. , 2018 . All behavioral tests were videotaped and later scored by two independent observers who were blinded to the experimental protocol. All apparatuses used for the tests were cleaned with 10% ethanol to remove possible bias due to smell left by previous animal.
The Y-maze was performed as previously described (Ijomone et al. 2015) . This test evaluates short-term spatial memory as a measure of cognitive abilities using spontaneous alternating behaviors that is common in rats. Here, a three-armed Yshaped maze was used. Rats were placed on a predetermined start arm and allowed to roam freely for 8 min. Arm entry (hind limbs completely in arm) was scored. Entering all 3 arms in the overlapping triplet sets is defined as spontaneous alternation. The percentage of spontaneous alternation was calculated as: [spontaneous alternation / (total number of arm entries -2)] × 100.
This assesses locomotor and exploratory activities in rats using protocols previously described (Ijomone et al. 2015 (Ijomone et al. , 2018 . Here, an apparatus consisting of a box (72 × 72 × 36 cm) with the floor divided into 18 × 18 square units was used. Rats were placed in the center of the box and allowed to roam freely for 5 min. Locomotion frequency (number of crossings from one square to the other), rearing frequency (number of times the animals stood on their hind paws), rearing against the wall (number of times the animals stood on their hind paws against the wall), and hinding (calculated by adding the rearing frequency to rearing against the wall) are among the parameters scored.
Biochemical/molecular analyses of the brain tissue 10 % fructose (2 weeks) Fig. 1 Schematic illustration of the protocol depicting the experimental groups, treatment period with SeNPs and/or M as well as the neurobehavioral and the biochemical endpoints evaluated
This test assesses depressive or despair-like behavior in rats. The idea is based on the fact that rats will develop an immobile posture when exposed to unavoidable stress of being suspended by their tail (Ijomone et al. 2015 (Ijomone et al. , 2018 . Here, rats were suspended individually by their tail from a retort stand with an adhesive tape for 6 min, and the amount of time each rat spent immobile was recorded.
Determination of antioxidant/oxidative stress, proinflammatory biomarkers, and acetylcholinesterase activity in rat brain
The supernatants from the brain samples were analyzed for antioxidant activities and oxidative stress biomarkers by following earlier protocols, superoxide dismutase (SOD) activity (Misra and Fridovich 1972) , catalase (CAT) activity (Clairborne 1995) , levels of reduced glutathione (GSH) (Jollow et al. 1974) , glutathione-S-transferase (GST) activity (Habig et al. 1974) , the activity of glutathione peroxidase (GSH-Px) (Rotruck et al. 1973) , and levels of lipid peroxidation (LPO) (Garcia et al. 2005) . To determine the level of proinflammation, the supernatants were analyzed for myeloperoxidase (MPO) activity (Eiserich et al. 1998) [31] and acetylcholinesterase (AChE) activity (Ellman et al. 1961 ).
Cell lysates from brain homogenates were prepared in the lysis buffer (50 mm Tris, pH 7.4 containing 0.15 M NaCl,10% glycerol (v/v), 1% NP-40 (v/v), 1 mM sodium fluoride, 1 mM sodium orthovanadate, 1 mM PMSF, 1 mM EDTA, 150 mM bestatin, 1 mM leupeptin, and 1 mM aprotinin) using a tissue:buffer ratio of 1:5. Protein concentration was estimated with BCA kit and equal amounts of protein were loaded on each lane and subjected to 10% sodium dodecyl sulfate polyacrylamide gel electrophoresis (Mini Protean II System, Bio-Rad, Berkeley, CA) as described by Kim (2017) for anti-parvalbumin (#NB120-11427; Novus Biologicals, USA), anti-Nrf2 (#ab31163; Abcam, USA), and cleaved caspase 3 (#9664 Cell Signaling, USA).
A total of 5 μm thick sections of routine paraffin embedded brain tissues were used. Anti-Nrf2 (#ab31163; Abcam, MA, USA) proteins were analyzed following protocols from earlier studies (Ebokaiwe et al. 2019 (Ebokaiwe et al. , 2020a .
Data were reported as mean ± SEM. Data comparisons were carried out using one-way ANOVA and subsequently by Newman-Keuls multiple comparison test. GraphPad Prism (version 5.03; GraphPad Software, La Jolla, CA, USA) was utilized in plotting charts and analyzing data. Statistical significance was set at p < 0.05.
Blood glucose levels, body weight gain, organ weight, and survival rate Blood glucose concentrations were significantly higher in all diabetic groups when compared with the normal group post-STZ injection. However, blood glucose levels were reduced in some groups of diabetic rats when treated with SeNPs and the standard of care drug metformin in comparison with untreated groups throughout the intervention period ( Table 2 ). It decreased after 2 weeks of treatment and continued to reduce steadily throughout the study period. Significant lower brain weight was observed in the DC group compared with that of the NC and treated groups at the end of the study period (F 4,30 = 78; p < 0.0001) ( Table 2) . Also observed was a higher mortality rate in the DC group after day 14 than the NC and treated groups (Table 2) .
Serum insulin concentration as well as HOMA-IR and HOMA-β scores in various animal groups at the end of the study period Insulin concentration was lower in DC group when compared with the NC and treated groups (F 4,30 = 366; p < 0.0001) ( Table 3) . A corresponding higher HOMA-IR in the serum of the DC was observed than that of the NC and treated groups, whereas, a lower level of HOMA-β was observed in the DC than that of the NC and the treated groups (Table 3 ).
SeNPs and/or M improved locomotor activities and exploratory profile in diabetic rats Figure 2 shows the results of endpoint analyses of locomotor activities and exploratory profile in various groups during the 8 min trial in the novel environment. A significant reduction in total time immobile, total distance traveled, average speed, and spontaneous alternation (angle of an absolute turn and total body rotation) was observed in the DC group when compared with treated groups and NC.
The evidence of improved locomotor activities and exploratory profile are shown in Fig. 2a ; the Y-maze test revealed a significant decline in percentage of spontaneous alternation in DC than that of the NC and treated rats (F 4,30 = 208; p < 0.0001). (Fig. 2b) The TST revealed a significant increase in immobility time in DC compared to the NC and treated groups (F 4,30 = 35; p < 0.0001). Activities in the OFT ( Fig. 2c and d) SeNPs and/or M improved antioxidant enzyme activities and GSH levels in the brain of diabetic rats
The antioxidant activities are shown in Fig. 3 a, SOD; b, CAT; c, GST; d, GSH-Px; and e, levels of GSH in the brain of NC and experimental rats. We observed a noticeable decline in the activities of SOD, CAT, and glutathione enzymes (GST and GSH-Px), as well as GSH levels, in the brain of DC rats when compared with the NC and treated groups (SOD [F 4,30 effects in reversing brain injury associated with diabetes by improving the antioxidant system.
The dynamics of the levels of lipid peroxidation, activities of myeloperoxidase, and acetylcholinesterase in the brain of NC and experimental groups of rats are presented in Fig. 4a SeNPs and/or M regulate Nrf2, caspase 3, and parvalbumin, expression in diabetic rats the NC and experimental groups. The expression and immunoreactivity of Nrf2 protein was significantly lower in the brain of DC rats compared with that of the NC. Interestingly, treatment with SeNPs and/or M significantly restored these alterations relative to NC (F 4,30 = 151; p < 0.0001) (Fig. 5) . Parvalbumin (PV) expression decreased while caspase 3 expression increased following induction of diabetes. SeNPs and/or M groups showed significant attenuation of low PV and high caspase 3 expression in the brain (PV
The use of STZ to induce diabetes in vivo and in vitro to understand the complications associated with diabetes and the possible modulatory efficacy of known drugs and new compounds is of interest to researchers, following the global rise in diabetes conditions (Kamat et al. 2016 ). Neurotoxicity of STZ exposure involves altered glucose metabolism, insulin signaling, oxidative stress, and apoptosis (Kamat et al. 2016; Biswas et al. 2016 ). The two key pathological conditions of diabetes which are insulin resistance and partial pancreatic βcell dysfunction was successfully exhibited in the experimental animals in this study. Although normal functioning of the brain requires high glucose demand, the brain cells cannot cope with persistent glucose uptake under diabetic conditions due to hyperglycemia-a trend referred to as glucose neurotoxicity (Tomlinson and Gardiner 2008; Bahniwal et al. 2017) . Consequently, the prevention or attenuation of diabetic neurotoxicity is of vital interest to the clinician in order to improve the health of diabetic patients.
Previous studies demonstrated that low doses of selenium could exhibit antidiabetic and insulin-mimetic activities in animal models (Steinbrenner et al. 2011; Al-Quraishy et al. 2015; Abdulmalek and Balbaa 2019; Ebokaiwe et al. 2019 Ebokaiwe et al. , 2020a . However, clinical interventions using selenium as a drug are contradictory, as low doses acute exposure show efficacy whereas high doses and long-term usage worsen diabetes by increasing insulin resistance (Thomson 2004; Steinbrenner et al. 2011; Fontenelle et al. 2018 ). An earlier study by Steinbrenner (2013) reported that high doses of selenium contributed to the induction of insulin resistance as a result of its role in the metabolism of carbohydrates and lipids. In another study elsewhere, Wang et al. (2014) demonstrated that high doses of selenium (200 mg/kg) exacerbated hyperglycemia by promoting the expression of carboxykinase phosphoenolpyruvate and glucose 6-phosphatase enzymes involved in gluconeogenesis. The study by Jablonska et al. (2016) demonstrated that low doses of selenium improve homeostasis of glucose and the expression of genes related to glucose metabolism at different levels of regulation, linked to insulin signaling, glycolysis, and pyruvate metabolism. NFBG levels are a vital parameter in comprehending the severity of type 2 diabetes (Group 1998) . We measured the NFBG from day 7 of the intervention and fasting blood glucose (FBG) at the end of the intervention. From our results, SeNPs and/or M exhibited potent blood glucose-lowering activity in the treated rats, starting from the second week and throughout the intervention. Potential mechanisms that may account for the blood glucose-lowering activity of SeNPs and/ or M include enhancement of insulin action (Hwang et al. 2007 ) and pancreatic β-cell stimulation (Al-Quraishy et al. 2015) . Earlier study by Deeds and colleagues have established significant weight loss and mortality of rodents as accomplices of STZ toxicity and complications of hyperglycemia. The noticeable reduction in body weight and high mortality in the DC group in this study corroborates earlier reports (Deeds et al. 2011) as part of the toxicology impact of STZ. However, bodyweight gain and blood glucose were significantly improved to levels comparable with the NC after treatment with SeNPs and/or M indicating an improvement in metabolic condition and attenuation of tissue damage associated with hyperglycemia in the treated groups.
Maintaining glucose homeostasis is undoubtedly significant to lower the risk of micro or macro-vascular complications in diabetes condition (Chawla et al. 2016) . Treatment with SeNPs and/or M enhanced insulin concentration in diabetic rats compared to DC. This activity is due to lower NFBG and FBG levels observed in the treated groups, as a result of enhanced glucose uptake by the peripheral tissues. Furthermore, SeNPs and/or M reduced HOMA-IR index (for insulin resistance) and also improved the HOMA-β (for β-cell function) score. This technique (HOMA) is utilized in the estimation of insulin resistance and β-cell function from fasting blood glucose levels and insulin concentration (Wallace et al. 2004) . The reduction in the HOMA-IR scores by SeNPs and/or M treatment has further strengthened their potent antidiabetic activities.
Diabetes is accompanied by altered cognitive and motor functions, as evidenced by a significant decrease in spontaneous alternation, reduced locomotion frequency, increased immobility time, and decreased hinding and forelimb grip, reflecting altered short-term memory, depression, and impairment in the coordination between the nervous and muscular junctions (Sharma et al. 2010; Adedara et al. 2019) . We observed a similar trend in this study; however, the observed tendency to reverse impaired neurobehavioral parameters in diabetic rats following treatment with SeNPs and/or M is a further confirmation of metabolic improvement in the treated rats.
Reactive oxygen species (ROS) generation, oxidative stress, and altered levels of inflammatory mediators have been strongly implicated in tissue damage due to hyperglycemia (Newsholme et al. 2016) . Estimation of antioxidant defense along with LPO provide insight into the brain redox status (Valko et al. 2016 ) since membranes within the brain are known to be rich in peroxidizable fatty acids, thus they undergo peroxidation under oxidative insult (Shichiri 2014) . The current study demonstrated the efficacy in the treatment of diabetic rats with SeNPs and/or M, evidenced in their conspicuous ability to attenuate LPO by decreasing MDA level in treated rats. Accordingly, SeNPs and/or M not only lowered the LPO level but also increased both first and second line of antioxidant defense mechanisms. The present investigation showed that DC rats exhibited heightened MPO activity in the brain samples, which indicates the induction of inflammatory response in diabetic neurotoxicity. Acetylcholinesterase hydrolyzes acetylcholine, an essential neurotransmitter in the regulation of motor function and locomotion (Day et al. 1991) . The observed decrease in MPO and AChE activity by SeNPs and/or M treatment indicates amelioration of inflammation and consequently, improving cholinergic neurotransmission and restoring locomotor functions. Several reports have implicated Nrf2 as the main transcription factor of antioxidative stress (Zhang et al. 2018; Ebokaiwe et al. 2019 Ebokaiwe et al. , 2020a . Also, activation of Nrf2 expression decreases secondary brain damage and improves functional recovery after traumatic brain injury (Chandran et al. 2017; Zhang et al. 2018; Ebokaiwe et al. 2019) . In this study, the observed significant reduction in Nrf2 expression in DC animals is an indication of oxidant stress. Administration of SeNPs and/or M restored Nrf2 expression to basal levels, which could be one of the mechanisms/pathways involved in attenuating diabetes mediated neurobehavioral dysfunction.
The antioxidant activity of selenoproteins in the CNS is well recognized, and deficiency of Se elicits brain injury (Fang et al. 2013) . In addition to the role of Se as an essential component of the antioxidant system in the brain, studies have further demonstrated that Se can assuage oxidative stress in the brain through the regulation of Ca 2+ channels, mitochondrial biogenesis, and apoptosis (Steinbrenner and Sies 2013; Dominiak et al. 2016) .
Altered calcium homeostasis could lead to severe brain damage in diabetic conditions. The reduction in levels of calcium-binding protein-parvalbumin in the brain samples has been reported under diabetic conditions (Park and Koh 2017) . Parvalbumin, a known calcium-buffering protein that is structurally similar to calmodulin (Cates et al. 2002; Koh 2012) has an affinity for Ca 2+ -binding domains, thus playing a vital function in the maintenance of Ca 2+ homeostasis. Hence, this protein is an important Ca 2+ -buffering protein (Silver and Erecińska 1990; Lindholm et al. 2002) . During our investigation, DC rats showed reduced expression of parvalbumin in the whole brain lysate. The observed enhancement in the expression of parvalbumin following SeNPs and/or M treatment corroborates their beneficial neuro-therapeutic effects by modulating calcium homeostasis via regulation of parvalbumin protein expression, hence, another possible pathway that is involved in SeNPs and/or M attenuating influence against diabetes-induced brain damage. Hyperglycemia, hypoxia, and ischemic conditions have been reported to enhance intracellular Ca 2+ levels as well as apoptotic and necrotic cell death in the rat brain (Lindholm et al. 2002; Park and Koh 2017) . In neurodegenerative diseases, cellular dysfunction and cell death are usually mediated by increased cytoplasmic Ca 2+ concentrations (Park and Koh 2017) . In the present study, caspase 3 protein-apoptotic biomarker was estimated. Elevated expression of caspase 3 in the brain of DC animals was significantly attenuated in the SeNPs and/or M treated groups, an indication of apoptosis regulation.
According to the findings from this study, the restorative impact of SeNPs and/or M against diabetes-induced alterations in neurobehavioral and biochemical/molecular indices is attributed to the enhancement of endogenous antioxidant systems, reduced lipid peroxidation, suppression of oxidative/ inflammatory stress, acetylcholinesterase, and most importantly regulation of molecular markers of oxidant stress and tissue damage, Nrf2, caspase-3, and parvalbumin proteins.
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The Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV)-2 pandemic is ongoing, with nearly 36 2.6 million cases and over 128,000 deaths reported from Coronavirus disease (COVID)-19 in the United States 37 to date. 1,2 Transmission models of SARS-CoV-2, based on numerous inferences of other immune responses to 38 viral infections, suggest that infection may provide some immunity to reinfection. 1,3 If true, the utility of 39 serological tests to identify those who have acquired antibodies against SARS-CoV-2 (seroconversion) and the 40 frequency of seroconversion in the population (seroprevalence) is a powerful tool with which to guide public 41 health policies. 4,5 It is critical to determine how many individuals have had COVID-19 and are thus likely to be 42 immune, and differentiate them from those who have not been infected. These data are necessary to inform 43 modeling projections and policy making that will allow an optimal approach to "reopening" a country, state, or 44 region, and furthermore, these data must be accurate and reliable. 45
Serological assays rely on accurate recognition and ideally quantification of antibodies that recognize 46 viral antigens specific to SARS-CoV-2. Optimal test characteristics include high levels of sensitivity and 47 specificity. Coronaviruses have four major structural proteins; spike (S) protein (containing the S1 domain and 48 RBD motif), nucleocapsid (N) protein, membrane (M) protein, and envelop (E) protein. 6 Research conducted on 49 2005 SARS-CoV-1 and Middle East respiratory syndrome Coronavirus (MERS-CoV), which are highly related 50 to SARS-CoV-2, found that recovered individuals produced the strongest immunogenic antibodies against 51 antigens of the S-and N-proteins. 7 Thus, the development of serological tests for SARS-CoV-2 antibodies has 52 focused heavily on the detection of antibodies against these viral proteins. Antibody-based tests vary in both 53 technology (platform) and target antigen (design). In May of 2020, the FDA announced a reversal in its 54 emergency use authorization (EUA) and approval policies in order to help ensure that reliable tests are used to 55 accurately measure seroconversion in a population. Some tests have received EUA but limited data is available. 56
Considerable variability in test characteristics, particularly sensitivity, implies that there may not yet be an ideal 57 test design and instrument platform. This also can lead to variability and potential bias in the estimation of the 58 level of immunity in various locales or subpopulations. 8,9 59 Multiple serological assays have been developed to detect SARS-CoV-2 antibodies from whole blood, 60 plasma and serum. Essentially, three platforms of serological testing have been adopted: 1) in-house enzyme 61 linked immunosorbent assays (ELISA), 2) high-throughput serological assays (HTSA) and 3) lateral flow 62 assays (LFA). ELISAs offer wide flexibility for research laboratories to select virtually any antigenic protein of 63 interest and assay patient sera to provide highly sensitive, quantitative results. HTSAs are more suitable to 64 clinical laboratories processing large volumes of samples. Although HTSAs offer a narrower selection of 65 antigen choices, these platforms offer high-throughput capacity, high sensitivity and can be integrated into 66 clinical lab testing facilities. LFAs also offer limited antigen diversity, but function with small volumes of 67 whole blood, plasma or sera (1 drop, ~20uL) and require short test development times (≤30 minutes) allowing 68 administration and test results at the point of care. As reagent supply, testing capacity and affordability vary 69 across the country, the clinical community will undoubtedly resort to using multiple platforms to fill the 70 demand. 71
Underreporting of COVID-19 cases may be occurring, which could inaccurately reflect the morbidity 72 and mortality of SARS-CoV-2. 10 The objective of this study was to assess the seroprevalence in a sample of 73 blood donors in Rhode Island using commercially available serology tests . 11 To this end, consecutive blood 74 donors were enrolled though the Rhode Island Blood Center (RIBC) into a pilot study with the goal of 75 estimating seroprevalence for the population represented by those who donate blood on a regular basis. This 76 pilot is part of a larger statewide effort to estimate seroprevalence, including a statewide community survey and 77 testing on specific populations of interest. 78
From April 27, 2020 -May 11, 2020, consecutive Rhode Island Blood Center (RIBC) donors (n=2,008) 81 received a 2-question survey and completed a blood or plasma donation. Donor blood samples were then tested 82 using two commercially available serology tests and an in-house ELISA, described below. Plasma or serum was 83 isolated from whole blood samples collected in silica clot activator tubes. Samples were extracted, aliquoted to 84 minimize future freeze-thaw cycles, and stored at -80°C. 85
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Flat-well, nickel-coated 96 well ELISA plates (Thermo Scientific; USA) were coated with 2 ug/mL of 99 recombinant S1 spike protein, nucleocapsid protein, or Receptor Binding Domain (RBD) spike protein specific 100 to SARS-CoV-2 in resuspension buffer (1% Human Serum Albumin in 0.01% PBST) and incubated in a 101 stationary humidified chamber overnight at 4°C. On the day of the assay, plates were blocked for 30 min with 102 ELISA blocking buffer (3% W/V non-fat milk in PBST). Standard curves for both S1 and RBD assays were 103 generated by using mouse anti-SARS-CoV spike protein monoclonal antibody (clone [3A2], ABIN2452119, 104
Antibodies-Online) as the standard. Anti-SARS-CoV-2 Nucleocapsid mouse monoclonal antibody (clone [7E1B], 105 bsm-41414M, Bioss Antibodies) was used as a standard for nucleocapsid binding assays. Monoclonal antibody 106 standard curves and serial dilutions of donor sera were prepared in assay buffer (1% non-fat milk in PBST) and 107 added to blocked plates in technical duplicate for 1 hr with orbital shaking at room temperature. Plates were then 108 washed three times with PBST and incubated for 1 hr with ELISA assay buffer containing Goat anti-Human IgA, 109
IgG, IgM (Heavy & Light Chain) Antibody-HRP (Cat. No. ABIN100792, Antibodies-Online) and Goat anti-110
Mouse IgG2b (Heavy Chain) Antibody-HRP (Cat. No. ABIN376251, Antibodies-Online) at 1:30000 and 1:3000 111 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted July 26, 2020. . https://doi.org/10.1101/2020.07.20.20157743 doi: medRxiv preprint dilutions, respectively. Plates were then washed three times, developed with Pierce TMB substrate for 5 min, and 112 quenched with 3 M HCl. Absorbance readings were collected at 450 nm. Standard curves were constructed in 113 Prism 8.4 (Graphpad Software Inc.) using a Sigmoidal 4PL Non-Linear Regression (curve fit) model. 114
For each assay, seroprevalence was estimated using a Bayesian statistical method that adjusts for 116 sensitivity and specificity of the specific test. The operating characteristics for the Ortho assay were obtained 117 from the technical report distributed by the manufacturer; for SD Biosensor we relied on local validation data. 118
Details described in supplemental methods. 119 120
A total of 2,008 donor samples were collected for this study between April and May of 2020, just as the 122 daily new case rates peaked in RI (https://ri-department-of-health-covid-19-data-rihealth.hub.arcgis.com/). We 123 compared age, sex and race/ethnicity of the sample group to values reported for Rhode Island from the 2010 124 U.S. Census. The median age of donors was 56 years, significantly older than the Rhode Island median age of 125 39.4 years (Fig. 1A, Table 1 ). The sample had ~47% female donors compared to 52% statewide (Fig. 1B , 126 (Fig. 1C, 1D) . Thirteen donors were identified as convalescent plasma or whole blood 132 donors that were aware of their seroconversion status prior to enrollment in the study and were removed from 133 the analysis, which adjusted the total donors analyzed to 1,996. 134
To quantify seroprevalence in this sample, donor samples were tested with an HTSA platform (Ortho 135
Clinical Diagnostics VITROS Total Ig Test) and an LFA platform (SD Biosensor IgM/IgG test). The IgM-only 136 LFA assay yielded 68 positive tests for a 2.7% (95% CI 1.7 to 3.8%) seroconversion ( Fig. 2A, Table 2 ). In 137 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted July 26, 2020. . https://doi.org/10.1101/2020.07.20.20157743 doi: medRxiv preprint contrast, the IgG-only LFA assay yielded 13 positive tests for 0.6% seroconversion (95% CI 0.3 to 1.1%) and 138 was in agreement with the Ortho HTSA assay, which had 14 positives for a 0.6% seropositivity (95% CI 0.2 to 139 1.1) ( Fig. 2A, Table 2) . 140
In total, 3.9% of all samples (77 seropositive donors) were reactive for at least one test. To report 141 overlap between test results, we constructed a Venn diagram (Fig 2B, Table 2) sensitivity and specificity. Importantly, the reliance on self-reported data must be interpreted with caution, and 152 there was no ability to account for the time since infection, which could impact the sensitivity calculations. 153
The gold-standard in antibody quantification is the ELISA assay for its flexibility in antigen diversity 154 and quantification methodology using monoclonal antibodies to generate standard curves. We designed in-155 house ELISA assays against S1 and NP specific to SARS-CoV-2 antibodies, since these antigens have been 156 described to elicit the most immunogenic response to infection based on SARS-CoV and MERS research. We 157 analyzed all 77 samples that were positive for any serological assay and 30 random samples that were negative 158 for all serological assays as controls for S1 and NP antibodies. Surprisingly, S1 antibody quantification showed 159 a median value of 73.8µg/mL for seropositive samples compared to 45.8µg/mL for seronegative controls (Fig. 160 2C) indicating moderate antibodies against S1 epitopes. Similarly, NP antibody quantification showed a median 161 value of 46.6ng/mL for seropositive samples compared to 31.9ng/mL for seronegative controls, also indicating 162 moderate antibodies against NP epitopes. However, there was ≥100-fold range of antibody values for 163 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted July 26, 2020. . https://doi.org/10.1101/2020.07.20.20157743 doi: medRxiv preprint seropositive samples in each ELISA test, suggesting that some of the seropositive samples, but not all, were 164 significantly reactive in S1 and NP ELISA, which is highly predictive of neutralizing activity. Correlation 165 analysis of all five tests showed a high degree of positive association between ELISA, HTSAs and IgG LFA 166 tests while IgM LFA test was negatively correlated (Fig. 2E) To investigate this, we subdivided seropositive samples into "IgG/Ortho" or "IgM-only" groups. As 170 expected, the median Ortho HTSA value was 10 4 higher for the IgG/Ortho group than the IgM-only group 171 (134A.U. vs 0.02A.U., respectively) (Fig. 2E) . Similarly, both S1 and NP ELISAs showed significantly higher 172 median antibody concentrations for the IgG/Ortho group than for the IgM-only group (S1; 424.2µg/mL versus 173 60.5µg/mL and NP; 210.1ng/mL versus 39.4ng/mL) (Fig. 2F, 2G) . Importantly, these results conclude that IgG 174 LFA and Ortho HTSA assays, but not the IgM LFA assay, correlate with immunogenic antibodies specific to 175 SARS-CoV-2 as detected by ELISA. 176
Discussion 178 This is among the first studies to evaluate statewide seroprevalence using blood donations. COVID-19 179 antibody testing has entered public discourse as an important metric in determining the population 180 seroprevalence of SARS-CoV-2. Ultimately, the application of antibody testing could be clinically informative 181 as to the degree of immunity afforded incurred by recovered patients or to that of future vaccinated individuals. 182 However, we recognize the limitations of the current study include generalizability and limited demographic 183 and other data of the blood donors that may be important. In fact, seroprevalence has been suggested to be 184 higher in specific racial/ethnic communities based on recent studies. 13 Thus, more inclusive and complete 185 seroprevalence studies will need to be performed in the future. 186
The application of antibody testing could be clinically informative as to the degree of antiviral activity 187 incurred by recovered patients or to that of future vaccinated individuals. Seroprevalence studies have the 188 ability to provide two important metrics: 1) the seroprevalence within a given population and 2) semi-189 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted July 26, 2020. . https://doi.org/10.1101/2020.07.20.20157743 doi: medRxiv preprint quantification of specific antibodies to SARS-CoV-2 that may correlate with immunity. However, the latter 190 estimation requires that an accurate methodology be adopted at the onset of the study. We recently completed a 191 comprehensive analysis of SARS-CoV-2 serological test characteristics and comparison to antiviral 192 neutralization activity using pseudoviral models. 14 In that investigation, HTSAs were shown to have superior 193 performance characteristics and correlation with neutralizing activity compared to LFAs. It should be noted that 194 the LFAs used in the prior study were different from the LFAs used in this study. 195
Among Rhode Island blood donors, we found the SD Biosensor IgG LFA and the Ortho HTSA assays 196 both reported a ~0.6% estimated seroprevalence rate. This is in agreement with a recent study showing 197 relatively low seroprevalence in many metropolitan areas. 15 It is tempting to speculate that low rates of 198 seroprevalence is a logical result to the social distancing and mitigation policies that have been adopted by 199 virtually the entire world. However, the SD Biosensor IgM LFA assay had very different performance 200 characteristics, did not correlate with ELISA assays and reported a higher seroprevalence rate. The latter 201 approximation would be similar to the Santa Clara seroprevalence rate reported in April of 2020, which found a 202 seroprevalence rate of 2.5-4.2% using LFA assays. 16 However, since the IgM LFA assay correlated poorly with 203 the Ortho HTSA assay, which we have previously shown to associate with neutralization activity and antiviral 204 antibody effectiveness to prevent reinfection of cells with pseudovirus , 14 we conclude the SD Biosensor IgM 205 LFA assay is not informative as to a specific adaptive immune response to SARS-CoV-2. It should be noted 206 that a concurrent SARS-CoV-2 serology study comparing the SD Biosensor LFAs to another LFA and a 207 chemiluminescent assay concluded that the SD Biosensor IgM LFA had limited clinical utility, while the SD 208
Biosensor IgG LFA performed very well across several distinct population sets and compared to the other 209 assays (Dr. Shaolei Lu et al.; manuscript submitted). Our results caution that seroprevalence rates could be 210 miscalculated by as much as 5-fold depending on the type of serology test employed. Only assays that show 211 significant correlation to neutralization activity, a metric of specific adaptive immunity, should be employed to 212 report rates of seroprevalence. 213
LFAs offer the convenience of rapid test results at the point of care and utilization of either whole blood, 214 plasma or serum which makes deployment simple. In this study, we found that the SD Biosensor IgG LFA test 215 provided reliable sensitivity to report seroprevalence. We found in this study that the SD Biosensor IgG LFA 216 test also provided reliable sensitivity to report seroprevalence. However, LFAs do not yield semi-quantitative 217 results which could be used to further understand the immunological range of responses within a study 218 population. Therefore, HTSA platforms are better suited to quantify a wide range of antibody levels in a 219 population while LFAs are suitable for low-cost, rural or studies designed for a limited interpretation of 220 seroprevalence. 221
In conclusion, we find the estimated seroprevalence of Rhode Island blood donors to be relatively low, 222 approximately 0.6%. Thus, we predict undiagnosed and asymptomatic infections are also likely to be low. 223
Considering the possibility that this may be an underestimate of the statewide population, these conclusions 224 draw important findings as it suggests that in the absence of a vaccine, "background" or "herd" immunity to 225 also be low, now four months into the US pandemic, and thus the susceptible population remains at 95% or 226 greater. 227 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
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. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
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. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
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The current COVID-19 pandemic has once again reminded us that international travel plays a central 2 role in the rapid spread of epidemics around the world [1] [2] [3] [4] . It is therefore of utmost importance that, 3 before international air travel gradually returns to normal, measures are taken to mitigate the risks of 4 spreading infections associated with such travel, especially since COVID-19 is unlikely to be globally 5 eradicated before travel increases. Furthermore, border control measures such as screening for 6 symptoms in travellers are unlikely to be effective for infections like COVID- 19 [5] , where there is a 7 high likelihood of asymptomatic transmission [6, 7] . Hence, there is an important role in ensuring that 8 travellers take adequate precautions during their travel, to reduce the risk that they will be infected 9 during their travel, and also potentially facilitate the spread of the virus. 10
Adequate pre-travel preparations and suitable precautionary behaviour during travel can reduce the 11 risk of acquiring infectious diseases during travel [8] . Travellers visiting friends and relatives (VFR) 12 are one important and often overlooked group of travellers in this context. A study found that only a 13 minority of Australian GPs were aware that VFR travellers are a high risk group [9] . It is known that 14 VFR travellers in general often do not undertake adequate pre-travel preparations [10] [11] [12] [13] . A lack of 15 knowledge of health risks and low rates of accessing pre-travel health services [10, [14] [15] [16] contribute 16 to low uptake of appropriate precautions [12, 17] . Furthermore, VFR travellers also often reside in 17 local family settings during travel, have prolonged close contact with the local population, have a 18 prolonged duration of travel, and have eating habits similar to the local population [17] [18] [19] . All these 19
factors place them at increased risk of acquiring infectious diseases during travel [18, 20, 21] which 20 can in turn facilitate the global spread of infections [22, 23] . 21
While some aspects of VFR traveller behaviour have been found to be generalisable to VFR travellers 22 of multiple ethnicities, each ethnic group also has culture-specific health behaviours, for example, the 23 use of Chinese medicine among ethnic Chinese. Ethnic Chinese are one of the largest cultural groups 24 in many Western countries, including Australia, and account for a substantial proportion of VFR 25 travel in these countries [24] . However, data remains lacking on the travel health knowledge, attitudes 26 J o u r n a l P r e -p r o o f 3. Results 1
A total of 51 respondents participated in five focus groups. Participants had undertaken an average of 3 5.5 trips to China since migrating to Australia. The demographic characteristics of the focus group 4 participants are presented in Table 1 . 5 Reported' means the participant did not answer that question.
4 Participants generally believed that China was a low-risk destination for travel-associated infectious 5 diseases and a number of reasons were given for this perception. Familiarity with the destination, 6 including spending their childhood in China, was commonly perceived by participants. However, even among participants who see travel to China as low risk for themselves, concern for the 11 potential travel risks for children who did not grow up in China was raised by participants. One 12 participant mentioned that they were worried about their son, and had previously consulted their GP 13 to vaccinate him against hepatitis A and B before travelling to China. 14 Accompanying a low perception of risk was a low awareness of potential infectious disease risks 1 during travel to China, including during travel to rural and regional areas. For example, although 2 regions in southern China are endemic for dengue, and parts of China are endemic for vector-3 transmitted Japanese encephalitis [26] , participants' general awareness and concern about vector-4 borne diseases was poor. Proffered responses to potential infectious risks in China did not include 5 diseases endemic in many parts of China or with a higher incidence than in Australia, such as hand, 6 foot and mouth disease, chikungunya, typhoid, or malaria [26] . However, some participants identified 7 rural travel as posing a higher risk than travel to cities in China, including the perceived need to carry 8 "a little bit more medicine" as preparation for rural travel. Few participants were concerned about 9 sanitary conditions in rural areas. 10 11
Participants were generally concerned about outbreaks in China, whether they were planning to travel 13
to China or not. Some participants said they worry about their relatives in China when outbreaks 14 happen, and, in general, participants appeared more concerned about outbreaks than about other 15 infectious risks during travel. Sources of information about disease outbreaks included Chinese 16 newspapers and websites, and family and friends who live in China. Few participants would consult 17 their GP for advice before travel when there is an outbreak. 18
Some participants did not perceive themselves to be at risk because of their behavioural patterns, or 19 their beliefs in adequately reducing their risks through certain behavioural changes. 20
If we were to go out I'd wear masks, but it really isn't that big an issue. We're old 21 anyway, it's not like we would go anywhere, we usually stay at home. The most we 22
do is just to gather together with relatives or friends. (Participant 106, regarding 23 a potential respiratory outbreak) 24
Another participant, when specifically asked, said they would not see a GP before VFR travel even if 1 there was an avian influenza outbreak. Instead they "might eat healthily and do more exercise". 2 Several other participants also mentioned similar ideas. 3
Opinions differed in the discussion of cancelling or changing travel plans in the event of an outbreak. 4
Many participants stated that they would not cancel travel to China. Circumstances around the need to 5 travel, such as visiting sick relatives, were considered by many participants in their decision not to 6 cancel travel during an outbreak. Otherwise, the decision to cancel the trip or not may depend on the 7 severity of the outbreak or the level of perceived risk. Some participants would only cancel non-8 essential travel when they perceived the outbreak to be severe. However, the risks of both actual and 9 potential travel during outbreaks were often underestimated by participants. One participant described 10 their travel to China during the Severe Acute Respiratory Syndrome (SARS) pandemic. Information 11 from Chinese relatives prior to travel described life as normal in China and a perception that the risk 12
was not serious. The seriousness of the outbreak was only discovered after returning to Australia. Familiarity with the travel destination and perceptions that VFR travel to China carried negligible 8 health risks were important factors in participants' perception that pre-travel health preparation and 9 seeking advice from a travel health provider on minimising infectious disease risks were not 10 necessary. In contrast, many participants said they would seek pre-travel health advice if they were to 11 travel to other developing countries. 12
Participants expressed a range of views on the need for pre-travel advice from a medical professional. 13
There was a perception among many participants that if you are not sick, you do not need to see a 14 doctor, or that there is no point in seeing a doctor for travel. On the other hand, a minority of 15 participants had consulted a GP for one or more of their previous trips to China, including several 16 participants who did so before every trip. Participants who consulted a GP before trips to China, either 17 for some or all trips, tended to be female, had tertiary education and had migrated to Australia 10 or 18 more years ago. Reasons provided for consulting their GP before travel included vaccination, the need 19
for prescription medications and a perception of a change in their immunity after an extended 20 residence in Australia. Some also reported obtaining a prescription from their GP in case they needed 21 to use it in China. for long, normally aware because our immune system is different, we've been in 2 this country for so long, we're not used to those environment, that kind of 3 environment, so the chance of getting any sickness is higher than here. 4 (Participant 711, lived in Australia for more than 10 years) 5 I guess being healthy is very important, and before I going to China it's necessary 6 to avoid disease or illness in China, so I guess I will seek some advice from the 7 professional doctor. (Participant 703) 8
Only one participant was aware of the availability of specialist travel health clinics. After receiving 9
information on the activities of travel clinics, many participants were interested. However, the cost 10 associated with clinic visits remained a major concern for many participants and many were reluctant 11 to use them for future trips to China. 12 13
Participants generally felt that vaccination was not specifically needed for travel to China and many 15 had never received a vaccine for the purpose of protecting against travel-associated diseases. 16
However, many participants were willing to receive a vaccine during an outbreak to protect them 17 against the disease involved. One participant said they had a hepatitis B vaccine before going to China 18 3 years ago because there was a hepatitis B outbreak, and another had an influenza vaccine before 19 their trip because there was an influenza outbreak. Some participants would be willing to receive a 20 vaccine during serious outbreaks, even if they otherwise would not consider vaccinations for travel. 21
For example, one participant said they would in general refuse vaccines recommended by their GP for 22 travel because they were worried about vaccine safety, but when asked specifically about whether 23 they would have had a SARS vaccine during the pandemic if there had been one, they said they 24
Apart from vaccines specifically for an outbreak illness, when asked if they would be willing to 1 receive a vaccine for travel if recommended by their doctor, many participants said it would depend 2 on other factors, including the seriousness of the condition, vaccine side effects and safety; others 3
were not willing to receive travel vaccines at all. Other barriers to low uptake of pre-travel vaccination included the lack of recommendations from 7 their GP, not having enough time to obtain such vaccinations for those travelling on short notice, and 8 fear of allergies to vaccines affecting their ability to travel. 9
A few participants did assess their vaccination status prior to travel. As a consequence of the focus 10 group discussion, several other participants have also indicated that they may ask their GP about 11 vaccinations before their next trip. Several participants also reported a habit of getting their yearly 12 influenza vaccines before travel. Such participants tended to be older. 13
Many participants demonstrated significant misconceptions about vaccination in general. Several 14 participants thought that if they were healthy or had a strong immune system they did not need to get 15 vaccinated, or that getting vaccinated too often would adversely affect the immune system. Some 16 participants also had misunderstandings about particular vaccines. For example, one participant 17 thought the influenza vaccine offers protection for SARS as well. Some participants felt that they 18
were not well-informed about vaccines in general. 19 20
Respiratory illness was a major health concern during travel to China. For the participants, the issue One participant from Hong Kong thought that there was a higher risk of getting influenza in mainland 7
China than in Hong Kong. Some participants believed that 'keeping healthy' (i.e. maintaining good 8 general health by sleeping well, eating well and exercising) can prevent regular respiratory infections. 9
Participants frequently associated respiratory infections with crowded areas. China is a very populous 10 country, and many participants reported visiting crowded areas during their trips, including shopping 11 centres. Although some participants mentioned avoiding crowded areas as a possible way to reduce 12 the risk of respiratory infections, it was mentioned that in Hong Kong this was difficult because 13 'everywhere is crowded'. 14 Participants had mixed attitudes to face masks as a method of reducing the risk of acquiring 15 respiratory infections. Several reasons were given for the use of face masks, including poor air 16 quality, cold weather and outbreaks of respiratory infections. Others preferred not to use masks 17 because they look "weird" or were uncomfortable but noted that wearing masks in public was more 18 socially acceptable in China than in Australia. 19
Most participants were willing to wear masks during outbreaks of infectious diseases, including many 20 of those who would not wear masks outside the context of an outbreak. One participant said they 21 carry masks in their luggage when they travel to China in case of an outbreak. Another participant 22
said they took masks with them wherever they went when they were in China during the SARS 23
We did it when SARS was going on, when we travelled. (Participant 101, when 25 asked whether they had ever worn a mask when in China) 26
Several other participants, however, were not convinced about the effectiveness of masks. 1
Some participants noted that they would not wear masks if nobody around them was wearing masks. 3
However, they would be more likely to use masks if everyone around them also wore masks, for 4 example, during an outbreak. Some participants said they would go to China for elective dental work because it is cheaper there, 18 even if they were aware that hygienic standards of dentists in China may not be up to Australian 19 standards. 20
Most participants reported no animal contact during their previous trips to China, apart from the 1 animals being sold in the wet markets. Visiting wet markets and food preparation were not commonly 2 reported either. 3 4 3.8 Behavioural changes during outbreaks 5 Some, but not all, participants reported they would change their behaviour during trips where there 6 was an outbreak. Participants said they would avoid crowded areas, be particularly vigilant about 7 personal hygiene and washing hands, refrain from eating certain foods, or wear masks during an 8 outbreak. Some participants also said they would consider not going out. 9
Actually, this time when we go to Shanghai, there's the period of chicken flu. So 10 we were very careful, and many of our time stay at the hotel, and we meet our 11
There was a common idea expressed by many participants that, during outbreaks, one should 'keep
Many participants reported self-medicating, using both Chinese and Western medicine, for what they 21 perceived to be minor illnesses. Some said they would take medications to China for use as part of 22 their travel preparations. One participant said they took antibiotics, given to them by their son, before 23 going to China. Another participant said they took some Chinese medicine before meals "to avoid 24 food poisoning". Some participants also said they would purchase medicines in China and bring them 1 to Australia to use. Mostly, this involved Chinese medicine but some participants bought antibiotics in 2
China and brought them to Australia. 3
Food safety was a particular concern for many participants. Since participants spent a lot of time with 4 family and friends, their eating habits and food choices were influenced by their family and friends. 5
Participants reported that their family and friends in China would consciously choose restaurants they 6 perceive to be lower risk for them. Participants were divided over whether it is safe to eat street food 7 in China. Attitudes and practices related to street food appeared to be influenced by family and 8 friends. travellers in general [10, 12, 17, 18, 27] , most participants in the focus groups rarely undertook travel 5 health preparations for VFR travel, due to both multiple barriers to health care access and a generally 6 low risk perception of VFR travel. Among focus group participants, there was a general perception of 7 VFR travel as low risk which was due to multiple factors, including a perception of familiarity, 8 knowledge deficits and misconceptions. Health promotion campaigns should highlight and explain 9 that there are still substantial risks in VFR travel, even though they have lived in their country of 10 origin for extended periods and are 'familiar' with the country. In the context of the COVID-19 11 pandemic, it is also essential to highlight the importance of seeking medical attention immediately if 12 one experiences respiratory symptoms [28, 29] , and not just assume that it is due to the air quality. Participants' sources of information about outbreaks include Chinese newspapers and websites, their 20 general practitioner, and family and friends who live in China. This finding is consistent with a 21 previous study conducted in the Netherlands and the UK which found that Chinese immigrants often 22 sought information regarding emerging infectious diseases from family and friends and Chinese 23 language media [33] . Informal sources of information may give an underestimated or inaccurate 24 account of the risks associated with an outbreak. This becomes a particularly important concern for 25 the many participants who rely solely on such information, and as a result undertake inadequate 26 precautionary behaviours. Also of concern was the common belief that the risk for acquiring the 1 infectious agent during an outbreak was low if they 'keep healthy' or used certain Chinese medicines. 2
Underestimating the risks or severity of an outbreak sometimes meant that participants undertook 3 VFR travel for non-essential reasons, for example during the SARS outbreak, when according to 4 WHO advice, they should have cancelled the trip. These findings correlate with the Australian Bureau 5 of Statistics international departures data, which show that the decline in travel episodes during the 6 SARS pandemic was lower for VFR travellers compared with business and holiday travellers [34]. It 7 is crucial that travellers understand the importance of following the advice of authorities like the 8 WHO and the Australian government to cancel non-essential travel during outbreaks. Educational 9
interventions should be provided ongoingly to potential VFR travellers to impress upon them the 10 importance of cancelling all non-essential travel during the COVID-19 pandemic. Such education 11
should raise awareness regarding the serious risks of travelling during an outbreak and the need to be 12 careful about any outbreak even if it seems contained and/or not severe, and to dispel misconceptions 13 like 'keeping healthy' or taking Chinese medicine being adequate measures to prevent one from 14 getting sick. 15
Many participants were willing to receive vaccination specifically for an outbreak or pandemic, which 16 may be relevant for a future COVID-19 vaccine. Given that this study found some confusion about 17 whether the influenza vaccine also prevents SARS, there is a real risk that some Chinese VFR 18 travellers may mistake the influenza vaccine to be also effective for COVID-19, which could lead to a 19 misguided sense of complacency. It is therefore important to proactively correct this misconception. 20
On the other hand, where Chinese VFR travellers are aware that the influenza vaccine is not effective 21 for preventing COVID-19, they may refuse to receive it, as among study participants, there was 22 widespread reluctance to be vaccinated for VFR travel other than for outbreaks, due to a lack of 23 perceived need, even among those in the high risk category due to their age. This is consistent with 24 published quantitative studies which show that VFR travellers have low rates of accepting vaccination 25 and complying with other prophylactic measures for travel, and compare unfavourably to other 26 travellers in this regard [13, [35] [36] [37] . Importantly and encouragingly, the vast majority of participants 27
were not strongly anti-vaccination. Specific education on the benefits of vaccination prior to VFR 1 travel, supported by evidence of vaccine efficacy and safety, are needed to address the problem of 2 under-vaccination. Highlighting the benefits of influenza vaccination could still encourage its uptake, 3 despite not being specifically protective for the current pandemic. 4
The study revealed the impact of social norms on willingness to wear masks, with participants not 5 comfortable wearing a mask in settings where no-one else was wearing one. This finding is especially 6 important in the context of recent reports of ethnic Chinese experiencing racially charged attacks in 7
Australia and other Western countries while wearing masks [38, 39] , which could make them even 8 more reluctant to go against social norms. Community-wide education on the importance of ensuring 9 adequate self-protection during outbreaks, and the protection of others if infectious, despite societal 10 concerns, appears to be needed. Among focus group participants, there were mixed attitudes towards 11 face masks. In contrast, a survey conducted during the SARS pandemic in Hong Kong found that 12 75.8% of respondents were willing to wear a mask [40] . The focus groups were conducted shortly 13 after the 2013 H7N9 outbreak, which, unlike COVID-19, usually required contact with birds or 14 poultry for infection [41] . The participants' mixed responses may be a reflection of their views 15
regarding the then-current outbreak, and general attitudes towards masks during a pandemic like 16 COVID-19 may differ. However, the selective uptake of preventative measures by VFR travellers is a 17 concern. Because of their low risk perception, VFR travellers may be particularly prone to 18 underestimating the risks posed by outbreaks. 19
This study found that cultural factors are important barriers that can prevent optimal travel health 20 practices. A major factor in the failure of study participants to attend for pre-travel health 21
consultations was a strong belief that there is no need to see a doctor if one is not sick. This may 22 reflect a lack of understanding among parts of the Chinese community in Australia about the role of 23 healthcare providers in disease prevention in the Australian healthcare system. Furthermore, there was 24 a widespread lack of awareness of specialist travel health clinics. This is consistent with published 25 literature regarding VFR travellers in general, which reports very low rates of using travel health 26 services [11, 14] . Specialist travel health services are usually provided in English in Australia which 27 creates a language barrier for some VFR travellers. Linguistic and cultural appropriateness is needed 1 to improve access to and the effectiveness of health care for migrant groups [42] [43] [44] . This study also 2 found that those who have lived for longer in Australia were more willing to seek professional pre-3 travel health advice. This is consistent with other studies showing that access to health services and 4 preventive health care increases with increasing acculturation [45, 46] , and highlights the special 5 importance of reaching out to newer migrants. 6
The use of complementary or alternative medicines for health issues was commonly raised by 7 participants, including in the context of outbreaks. In particular, despite many participants having 8 resided in Australia for more than 10 years, they commonly used Chinese medicine for both curative 9
and preventive or health maintenance purposes. This shows their continued ties to Chinese culture 10 despite acculturation, and highlights the need for culturally relevant educational interventions even for 11 long-term migrants. 12
This study also found that Australian Chinese VFR travellers share many important characteristics 13
with what is previously known about other VFR travellers, regarding their activities during travel. 14 These include close and prolonged contact with the local population, consumption of food that is not 15 often consumed by tourists, using local health and social facilities, and the potential for visits to 16 remote destinations [12, 17, 19] . In this study, the context in which these factors arise was also 17 explored. The influence of family and friends was found to be a major common factor behind all these 18 behaviours. VFR travellers living with local families by definition have prolonged close contact with 19 the local population, which is a known risk factor for acquiring many infections, including respiratory 20 viruses like COVID-19. Furthermore, because the family and friends of VFR travellers are likely to 21 generally have a lifestyle similar to the rest of the local population, VFR travellers spending a lot of 22 time with family and friends would be expected to be more similar to the local population in terms of 23 activities, the places they go and the food they eat compared with tourist travellers. They are therefore 24 particularly exposed to diseases that may be circulating in the local population. 25
This was the first study of Chinese VFR travellers living in a Western country. The study found that 26
Chinese VFR travellers share many issues with other VFR travellers, while it was also able to explore 27 beliefs and behaviour that are specifically related to Chinese culture. Moreover, the use of qualitative 1 methodology has allowed the in-depth exploration of how Chinese VFR travellers actually perceive 2 various situations, and many potential enablers and barriers influencing appropriate travel health 3 preparation were identified. Misconceptions and knowledge deficits were also more thoroughly 4 explored. This rich and in-depth information can inform the development of education interventions, 5
and compliments the quantitative data on VFR traveller enablers and barriers. The focus groups were 6 conducted in English, but participants could also converse in Cantonese or Mandarin if they wished 7 to, which reduced the language barrier. During transcription, conversation was translated verbatim 8 into English, and random sections of the transcripts were checked by a third transcriber, which 9 ensured accuracy. Demographic information was collected from participants, who were found to have 10 a reasonable diversity in age, educational background, and length of residence in Australia. Some 11 participants did not provide all the demographic details requested, however the amount of missing 12 data in each category was less than 10%. There were more female than male participants, which could 13 have influenced the observation that participants who consulted a GP before travel tended to be 14 female. However, most findings in this study were not observed to be associated with gender. Finally, 15 the travel health behaviour of VFR travellers in the context of outbreaks has not been previously 16 explored in detail. The in-depth focus on outbreak-related attitudes and behaviour in this study thus 17 represents a novel contribution to the understanding of VFR travel health. informed of the latest outbreaks, but some appear to underestimate the risks posed by an outbreak 25 especially in the early stages, and may thus undertake non-essential travel during outbreaks. During 26 VFR travel, their willingness to undertake preventive behaviours varied. Low risk perception, 1 misconceptions and other issues need to be addressed to encourage proper preventive behaviour, 2 including pandemic awareness and application of public health messages during pandemics [47, 48] . 3
While this research was not conducted specifically in relation to a pandemic situation like COVID-19, 4 its findings are useful in informing educational interventions for Chinese VFR travellers as part of the 5 ongoing pandemic response.
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"The global economy could suffer between $5.8 trillion and $8.8 trillion in lossesequivalent to 6.4% to 9.7% of global gross domestic product (GDP) -as a result of the novel coronavirus disease pandemic" estimated by the Asian Development Bank (ADB), May 2020.
The COVID-19 was first identified in China in December 2019, but the virus has spread rapidly across the globe. As of 20 May 2020, the number of confirmed coronavirus infections worldwide approached 5 million across more than 200 countries and territories, with over 90% of reported cases currently located outside China. The ongoing pandemic not only represents a worldwide public health emergency, but also has imposed massive and far-reaching economic cost globally. The spread of the virus itself and the containment measures attempting to mitigate it can bring production and consumption to a standstill (Boone et al., 2020) . For example, high mortality and morbidity rates of COVID-19 reduce the labour supply which, in turn, hinders production. In a similar vein, social distancing policies and lockdown measures (e.g., store and factory closures, quarantine, and mobility limitations) aiming to reduce the transmission rate and curb the spread of the disease, J o u r n a l P r e -p r o o f may also result in a sharp and immediate decline of production in the economy. Moreover, when workers lose their income due to the mass layoffs, they tend to cut back on spending or reduce their 'postpone-able' social consumption (e.g., restaurants, movie theatres, pubs and clubs, travel and tourism). Firms may also delay their investments owing to heightened uncertainty associated with While the spread in the US and Europe is attracting considerable media coverage, the COVID-19 pandemic could have more devastating effects on the world's most vulnerable populations in low-and middle-income countries, since emerging economies tend to lack the resources and capacity to cope with a precipitous increase in infections as well as the socioeconomic consequences of containment measures (Loayza and Pennings, 2020) . For example, they have poor health infrastructure to deal with the influx of patients; they rely heavily on commodity exports and tourism which are severely hit by border lockdowns; and they have less effective policy measures with which to fight the COVID-19-driven recession (Hevia and Neumeyer, 2020) . A high degree of informality is a key feature in developing countries: a large share of the labour force is either self-employed or employed in small and medium-sized businesses. These low-income, self-employed or informally employed individuals have limited access to unemployment insurance, health insurance and paid leave, and, thus, are particularly vulnerable to COVID-19 disruptions. In developing and highly informal economies, microfinance institutions (henceforth MFIs) play an important role in providing financial support to poor and low-income households and microenterprises who have been excluded from mainstream financial services traditionally. For example, as of November 2019, Grameen Bank has provided collateral-free loans of more than $20 billion to around 9 million the poorest of the poor in rural Bangladesh, including 97% of women borrowers, and covering 93% of the total villages in Bangladesh. 1 Although a rapidly growing body of research investigates the impact of the COVID-19 crisis on the macroeconomy and stock market (see e.g., Eichenbaum et al., 2020; Guerrieri et al., 2020; Lewis et al., 2020; Gormsen and Koijen, 2020; Baker et al., 2020) , almost no research to date has attempted to analyse empirically how COVID-induced economic damage influences the performance of MFIs. The minimal attention to the impact of the COVID-19 epidemic on MFIs is unfortunate though, because MFIs serve hundreds of millions of poor and vulnerable people in developing countries. The goal of this article is to fill this gap in the literature.
To test the effects of the COVID-induced decline in economic activity on the financial and social efficiency of MFIs empirically, we use a dataset from the MIX Market, which covers 73 unique MFIs operating in 11 developing Asian countries and contains individual MFI's financial and outreach data. Additionally, we collect COVID-19 economic impact data from the Asian Development Bank (ADB), which proposes four scenarios: best case, moderate case, worse case, and hypothetical worst case; and estimates drops in 2018 nominal GDP and employment under each scenario. By way of preview, our main findings are summarized as follows. The GDP and employment impact from COVID-19 reduces MFI financial efficiency but increases MFI social efficiency, indicating that, while the economic slowdown lowers MFI financial performance, the role of creating a social impact is seemingly prioritized during COVID-19. Furthermore, we examine the specific channels through which efficiency is influenced using both the lending rate and the funding rate. We find that the lending rate plays a mediating role between the impact of COVID-19 and MFI efficiency. In particular, the potential GDP and employment impact from COVID-19 on financial efficiency is completely mediated by the lending rate, whereas a partial mediation of the lending rate is found between the impact of COVID-19 and social efficiency. This suggests that the influence from the impact of COVID-19 on MFI efficiency is transmitted indirectly through the lending rate; however, we find that a mediating effect through the funding rate is not pronounced, suggesting that the channel between the GDP and employment impact from COVID-19 and MFI efficiency is rather direct.
Our study offers two important contributions to the literature. First, this is the first study examining how MFI financial efficiency and social efficiency are affected by COVID-19. While the extant literature generally investigates the effects of the macroeconomic environment on MFI performance or efficiency (e.g., Hartarska and Nadolnyak, 2007; Ahlin et al., 2011; Bogan, 2012) , limited research focuses on how the pandemic-induced economic slowdown may affect MFI performance, particularly with respect to financial and social efficiency, differently. Second, to the best of our knowledge, this is the first study to provide empirical evidence that enhances the understanding of the mechanisms underlying the association between the impact from COVID-19 and MFI efficiency by testing the mediation effect of the supply and demand side of funding, through the channels proposed by Baron and Kenny (1986) 's method and the Sobel test (Sobel, 1982) . Accordingly, we explore the relationship between the impact of COVID-19 and MFI efficiency successfully by considering proxies for MFI funding supply and demand using lending rate, funding rate, deposits, and donations as potential mediators.
J o u r n a l P r e -p r o o f 4 The structure of the paper is as follows: Section 2 reviews the existing literature and develops the hypotheses. Section 3 describes the data and defines our variables. Section 4 reports the results of the regression analyses. Section 5 concludes the paper.
MFIs are special financial institutions and differ fundamentally from commercial banks, mainly in that they pursue the double bottom-line objectives of financial sustainability and social outreach. MFIs are socially oriented organizations that provide noncollateralized microcredit to low-income families and microentrepreneurs, who are otherwise unable to access to formal financial services (Zamore et al., 2019) . Since MFIs serve hundreds of millions of poor and vulnerable borrowers, they play a pivotal role in alleviating poverty in developing countries. Apart from their social mission, MFIs have a profit nature. Financial viability is a major concern for the microfinance industry; thus, MFIs behave like other profit-driven firms, aiming to be profitable or at least break even (Zamore et al., 2019) . In line with their dual objectives, MFIs are generally evaluated with respect to social impact considerations and profit implications. While there is a substantial literature that examines the key determinants of MFI success, previous empirical evidence regarding the impact of macroeconomic conditions on MFI performance is mixed and inconclusive. Against this background, we examine the effects of the COVID-induced economic slowdown, as measured by decline in GDP and employment, on MFI social and financial performance in developing Asian countries. Given the conflicting objectives documented in the literature (Galema et al., 2012) , that is, there may be a trade-off between serving the poorest segments and remaining financially viable, we formulate two competing hypotheses on the effects of the macroeconomic environment on MFI performance.
The previous literature suggests that a pandemic-induced economic downturn will put pressure on banks' loan portfolios and can lead to a large withdrawal of deposits, particularly in poor and developing countries (Lagoarde-Segot and Leoni, 2013; Beck, 2020) . In line with this view, we expect that the socioeconomic damage caused by COVID-19 should deliver a negative effect on MFI financial performance. First, MFI may experience a deterioration in performance as small and medium-sized businesses (SMEs) and vulnerable households, which are among the most exposed to the COVID-19, have been struggling to meet their debt obligations. Businesses are likely to generate insufficient cash flow to service their debt owing to factory shutdowns, supply chain disruption, and a sudden fall in demand for goods and services during the pandemic. Also, a strong decline in economic activity usually J o u r n a l P r e -p r o o f translates to an increase in the unemployment rate (Skoufias, 2003) . Mass layoffs and closures undermine MFI performance because the laid-off workers are financially fragile, and they may not be able to make mortgage payments on time owing to income shortfalls, thus, increasing the likelihood of non-performing loans. Second, the excessive build-up of nonperforming loans arising from the COVID-19 shock will affect sentiment negatively, so a wider decline in confidence in banks by depositors may result in large-scale withdrawals of deposits (Beck, 2020 ).
Yet another strand of related research has highlighted that MFI performance is expected to improve under poor economic conditions (Ahlin et al., 2011) . Consistent with this line of argument, we predict that COVID-19-induced economic slowdown could affect MFI social performance positively for two possible reasons. First, MFIs with a strong internalized social mission can be incentivized by reaching out to the poor and low-income households and microenterprises active in the informal economy. Ahlin et al. (2011) suggest that a decline in economic growth may increase demand for products produced by microenterprises, as consumers substitute away from imports or higher quality goods. Hence, these microenterprises will be in desperate need of credit to expand their production capacity.
Commercial banks are reluctant to lend to SMEs that are already indebted in times of economic downturn, since small and informal entrepreneurs may not be able to cope with any additional loans during the pandemic. By contrast, MFIs share a commitment to make financial services available to fragile and vulnerable clients. Therefore, MFIs may prioritize their social mission during recessions, allowing loans to become delinquent and taking losses (Ahlin et al., 2011) . Second, microfinance unique business models, like group lending technology, make MFIs less sensitive to economic shocks, and more cost-efficient, than traditional banks (Schulte and Winkler, 2019; Zamore et al., 2019) . 2 It is, thus, expected that MFIs may be able to provide smaller loans to more underserving micro-entrepreneurs during a recession. In other words, the breadth (i.e., the number of active borrowers) and the depth (i.e., the provision of small loans) of MFIs' outreach are likely to be enhanced. Based on the above competing arguments, we posit the following hypotheses:
Hypothesis 1: COVID-19 induced economic slowdown is associated negatively with MFI financial performance Hypothesis 2: COVID-19 induced economic slowdown is associated positively with MFI social performance
In this paper, we assess MFI performance with respect to financial and social efficiency by utilizing a Data Envelopment Analysis (DEA) framework. DEA is a nonparametric linear programming method that calculates the quantity of output produced, given certain levels of input, and allows for multiple comparisons between a set of homogeneous units (Gutiérrez-Nieto et al., 2007) . Previous literature suggests that DEA is an appropriate technique for the assessment of MFI performance (e.g., Gutiérrez-Nieto et al., 2009 ). The advantage of using DEA to calculate MFI efficiency is that it can incorporate the outputs of both social impact and financial viability along with other inputs into a single framework without any assumption on data distribution (Basharat et al., 2015) . The input and output data for the DEA framework are obtained from the global database of MFIs collected by the MIX Market information platform. This database contains the best publicly available cross-country data for MFI-specific social and financial indicators. It has been widely used in the microfinance literature (see Assefa et al., 2013; Ahlin et al., 2011 ; and among many others).
Following Basharat et al. (2015) , in our main empirical estimation, we use ace_lr as a general specification for financial efficiency, where assets (a), operating expense (c), and personnel (e) are taken as inputs; gross loan portfolio (l) and financial revenue (r) as outputs. Similarly, we use ace_wp as a general specification for social efficiency, where inputs (ace) are the same as those in financial efficiency; number of active female borrowers (w) and an indicator of benefit to the poorest (p) are taken as outputs. To address the concerns that our results may be sensitive to the selection of inputs and outputs, we calculate alternative measures of social and financial efficiency based on a different input and output selection using a robustness check.
We obtain the economic impact of COVID-19 data from the Asian Development Bank (ADB). The COVID-19 induced economic slowdown is measured based on the percentage of decline in both 2018 GDP and employment in all sectors. ADB estimates four scenarios based on tourism and travel bans affected by the COVID-19 situation in China -"best case", "moderate case", "worse case", and "hypothetical worst case", and it assesses the impact conditional on the realization of these scenarios. Appendix B lists the full set of scenario assumptions. The estimated GDP and employment impact of COVID-19 is based on the expected duration of travel bans, and the magnitude of the drop in domestic demand, in J o u r n a l P r e -p r o o f China. For instance, under the "best case", the duration of travel bans in China is expected to be two months, which would subsequently lead Chinese outbound tourism to drop by 50% within the two months, and no economies that impose travel bans would have tourism receipts from China. The estimated impact also includes the fall in inbound Chinese tourism and receipts, as well as tourism from outside Asia to non-China East and Southeast Asia by analogy with the pandemic period of SARS. As such, ADB expects a 0.7% decline in consumption from China relative to a no-outbreak scenario for the "best case" scenario. In comparison, the "hypothetical worst case" would see the expected duration of travel bans and decline in domestic demand in China of six months plus an extra three months for economies with COVID-19 outbreaks. Consequently, the Chinese outbound tourism would be expected to drop by 50% during the travel ban period, and inbound Chinese tourism would be expected to fall by an additional 30% relative to the best case. Tourism from outside Asia to non-China East and Southeast Asian economies would also be expected to fall by an additional four months relative to the best case. Due to these impacts, ADB expects a 2% drop in consumption and investment in China, as well as a 2% decline in domestic consumption in selected economies. In our study, gdp_chg_1, gdp_chg_2, gdp_chg_3, and gdp_chg_4 denote the magnitudes of the effects on GDP due to the potential economic impact of the COVID-19 outbreak under the "best case", "moderate case", "worse case", and "hypothetical worst case" scenarios respectively, measured as percentage drop in total 2018 nominal GDP. emp_chg_1, emp_chg_2, emp_chg_3, and emp_chg_4 denote the magnitudes of the effects on employment due to the potential economic impact of the COVID-19 outbreak under the "best case", "moderate case", "worse case", and "hypothetical worst case" scenarios respectively, measured as percentage drop in employment among all sectors as of 2018.
In addition, we include MFI-specific and macro-economic control variables that prior literature suggests as affecting MFI performance. Data on MFI-specific controls are sourced from the MIX Market database, including the ratio of capital to total assets (ca); the impairment loss allowance to total assets ratio (allow); the ratio of cash and cash equivalents to total assets (liq); the ratio of deposits to gross loan portfolio (dp); the lending rate, measured by financial revenue over average loan portfolio (lendingrate); and the funding rate, measured as total finance expense over total debt. (fundingrate). Country-level macroeconomic data, GDP growth rate and population density, are taken from the World Bank's World Development Indicators database. GDP growth rate (gdpgr) is defined as annual percentage growth rate of GDP at market prices based on constant local currency (aggregates are based on constant 2010 U.S. dollars). Population density is measured as J o u r n a l P r e -p r o o f midyear population divided by land area in square kilometres. We use the natural logarithm of population density in this paper (lnpopden). The variable definition is shown in Appendix A.
After merging all data sources together, we obtain 73 MFIs in 11 Asian developing countries for which complete information is available. All the data correspond to the year 2018. As seen from Table 1 , we note that the MFIs included in our samples are higher for Philippines and Cambodia than the other economies, whereas Mongolia and Fiji have the least observations. J o u r n a l P r e -p r o o f Table 3 Multicollinearity diagnostics a, b ace_lr ace_wp gdp_chg_1 gdp_chg_2 gdp_chg_3 gdp_chg_4 emp_chg_1 emp_chg_2 emp_chg_3 emp_chg_4 cap allow liq dep gdpgr
To examine our H1, we develop the following model to investigate the association between the impact from COVID-19 on MFI financial efficiency: (1) where ace_lr i is our financial efficiency measure for firm i; COVID i is a vector, which contains eight measures of the impact of COVID-19 for firm i, including gdp_chg_1 i , Table 4 shows the results for Equation (1). As seen from Column (1), the impact from COVID-19 by nominal GDP decreases MFI financial efficiency under the "best case" measured by
The results are consistent across Columns (2), (3) and (4) for gdp_chg_2 (β 1 = -0.319, p<0.01), gdp_chg_3 (β 1 = -0.185, p<0.01), and gdp_chg_4 (β 1 = -0.164, p<0.01), respectively, suggesting that the potential GDP impact of COVID-19
generally lowers MFI financial efficiency in all scenarios. Likewise, for the impact from COVID-19 by employment, Column (5) shows that under the "best case", emp_chg_1
significantly lowers ace_lr (β 1 = -0.886, p<0.01). The results remain consistent across Columns (6), (7) and (8), where they show that financial efficiency is decreased by emp_chg_2 (β 1 = -0.587, p<0.01), emp_chg_3 (β 1 = -0.318, p<0.01) and emp_chg_4 (β 1 = -0.374, p<0.01). Interestingly, the marginal effect of the potential GDP and employment impact from COVID-19 on financial efficiency tends to be descending as the scenario evolves from the best to hypothetically the worst. For instance, under the "best case", the marginal effect of gdp_chg_1 on ace_lr is -0.397, which is lowered gradually as the scenario worsens. A similar effect is also noted among the impacts on employment. For control variables, MFIs that are high in deposits to loan ratio but low in capital ratio and growth rate of GDP are more likely to exhibit high financial efficiency. The results in Table 4 show that COVID-19 induced economic slowdown is associated with MFI financial performance negatively; hence, we accept H1.
J o u r n a l P r e -p r o o f -0.319*** (-4.14)
We then develop the following model to examine H2 on the impact from COVID-19 on MFI social efficiency: (2) where ace_wp i is our social efficiency measure for firm i; COVID i is a vector, which contains eight measures of the impact of COVID-19 for firm i. Our control variables are cap, allow, liq, dep, gdpgr, and lnpopden. The results for Equation (2) are presented in Table 5 . The impact from COVID-19 generally shows a positive influence on MFI social efficiency. More specifically, under the "best case" in Column (1) That is, the coefficient estimates of our COVID-19 impact variables generally decrease from "best case" to "hypothetically worst case". For the control variables, we find that MFIs with higher liquidity, GDP growth rate, population density and lower deposits ratio exhibit high levels of social efficiency. The results in Table 5 show that COVID-19 induced economic slowdown is associated with MFI social efficiency negatively. Thus, we accept H2.
Having established that COVID-19 induced economic downturn affects MFI financial and social efficiency, we now turn our attention to the potential channels through which this effect operates. From the perspective of uses of funding (demand for microfinance) and
Literature generally shows that the most important financial service provided by MFIs to poor household and microenterprises is lending (Postelnicu and Hermes, 2018) . Since
MFIs are subjected to relatively higher administrative costs than other types of financial institutions owing to the small and short-term loans that are not secured by collateral (Cull et al., 2009) , they usually charge a high interest rate to cover the cost of lending (Hartarska and Nadolnyak, 2007) . The outbreak of COVID-19 may expose MFI clients like SMEs, to bankruptcy risk owing to the pandemic-induced economic slow-down, so many businesses are not able to meet their debt obligations. Under these circumstances, the higher the interest rate MFIs charge, the more likely that vulnerable borrowers will default on their loan repayments. Given that non-performing loans are the direct source of financial fragility (Beck, 2020) , we expect that the higher lending rate charged by MFIs during the pandemic will undermine their financial efficiency. Therefore, we argue that the impact from COVID-19 on MFI financial efficiency is mediated by their lending rates. Related, the relationship between the COVID-19 economic impact and MFI social efficiency is also mediated by lending rates.
The demand for credit from MFIs during crises tends to increase for microenterprises, because commercial banks are reluctant to lend to SMEs (Ahlin et al., 2011) . The extant literature also shows firms in poor countries have limited access to financial markets (Loayza and Pennings, 2020; Hevia and Neumeyer, 2020) . As such, we predict that microentrepreneurs and low-income borrowers will rely heavily on MFIs and are willing to pay the high interest rate charged by MFIs, as this may be their only obtainable source of funding during the pandemic. We, therefore, posit that during the COVID-19 outbreak, high lending rates enhance the MFIs' ability to expand their outreach and serve poor clients.
To examine the role of lending rate on MFI efficiency, we undertake a mediation test based on the basic four-step Baron and Kenny (1986) approach, using the following equations:
where Efficiency i is a vector containing the financial efficiency and social efficiency measures, which are ace_lr and ace_wp for firm i. COVID is a vector containing the potential GDP and employment impact of COVID-19 and lendingrate is MFI lending rate, which is measured as financial revenue divided by average loan portfolio. The control variables J o u r n a l P r e -p r o o f include cap, allow, liq, dep, gdpgr, and lnpopden. To test the mediation effect through lending rate, we adopt the classic mediation test from Baron and Kenny (1986) , jointly with the Sobel test (Sobel, 1982) . Based on the definition of a mediator by Baron and Kenny (1986) , we test the following conditions to show lending rate can be considered as a mediator.
First, the potential impact of COVID-19 is correlated with MFI financial and social efficiency ( ≠ 0). This is shown in Equation (3-1) , and the results from our baseline models show that COVID-19 decreases financial efficiency but increases social efficiency. Second, the potential impact of COVID-19 is correlated with lending rate, which shows the mediator as through it were an outcome variable ( ≠ 0). This is tested in Equation ( Note: a The first row (number) represents the estimated coefficient, the second row (number in parentheses) represents the t-value of significance. b We winsorized all continuous variables at the 1st and 99th percentiles to moderate the possible effects of extreme outliers. c * if p < 0.10; ** if p < 0.05; *** if p < 0.01. All tests are two-tailed. Note: a The first row (number) represents the estimated coefficient, the second row (number in parentheses) represents the t-value of significance. b We winsorized all continuous variables at the 1st and 99th percentiles to moderate the possible effects of extreme outliers. c * if p < 0.10; ** if p < 0.05; *** if p < 0.01. All tests are two-tailed.
J o u r n a l P r e -p r o o f
On the supply side of funding, literature has identified various sources of external financing to support MFIs. Initially, MFIs rely primarily on donors, subsidies from charitable or governmental agencies, and concessional funds to keep afloat (Assefa et al., 2013) . With the rapid development of commercialization, MFIs are allowed to take deposits from the public and to operate like "traditional bank-like MFIs" (Schulte and Winkler, 2019) . In addition to donation and deposits, MFIs have recently obtained private funding from commercial investors, like commercial banks, pension funds, insurance companies, private equity firms, etc., who consider MFIs as a socially responsible investment (Postelnicu and Hermes, 2018) .
During the pandemic, we expect funding rates to have ambiguous (i.e., positive or negative) effects on the financial and social efficiency of MFIs for reasons explained below.
First, higher funding rates imply higher costs of capital, which may undermine MFI financial performance; but higher funding rates also mean MFIs can attract long-term investment, since long-term capital providers usually require higher rates of return to compensate for their opportunity costs. This stable source of financing may result in improved financial efficiency in the long run. Second, higher funding rates that MFIs offer to depositors and other lenders could encourage more savings and investment with the MFIs. This will, in turn, enable MFIs to reach out to more low-income households and underserved microbusinesses. Hence, MFI social performance (i.e., the breadth and depth of outreach) will be enhanced. However, because of the heightened uncertainty and loss of confidence in banks (Beck, 2020) , depositors may withdrawal their deposits, and risk-averse investors may become extremely cautious about investing in MFIs. As such, even a higher funding rate cannot attract funding during a pandemic, and restricted availability of funding will translate into less outreach to the poorest clients.
Following the literature (e.g., Basharat et al., 2015) , the funding rate (fundingrate) is defined as total finance expense over total debt. We undertake the following equations to examine the mediation effect of funding rate: We then examine the mediation effect of the funding rate on social efficiency as affected by COVID-19. The results are shown in Table 9 . As seen from Panel A, we note that on their loan repayments. Therefore, we expect that higher lending rates result in lower financial efficiency. However, as microentrepreneurs and low-income borrowers will rely heavily on MFIs, and are willing to pay the high interest rates charged by MFIs, i.e. the demand for smaller loans is increased during COVID-19, we predict that higher lending rates lead to higher social efficiency. We also examine the effect of the MFI funding rate, but no statistical significance is obtained from our analyses.
Our study adds to the growing literature on the role of the macroeconomic environment on MFI performance. Specifically, we focus on how a pandemic is related to MFI efficiency with new evidence based on a recent and on-going COVID-19 outbreak. Our findings provide important implications for MFIs who want to manage their efficiency during the pandemic period. One point to note is that the results of this study should be viewed in light of their limitations, considering the estimation of the COVID-19 economic impact is based on the GDP and employment data for 2018 only. An avenue for future research could be to explore our hypotheses in a much larger sample as new data is released and to challenge our findings.
J o u r n a l P r e -p r o o f Panel A: Financial efficiency and social efficiency ace_lr Financial efficiency specification where assets (a), operating expense (c), and personnel (e) are taken as inputs; gross loan portfolio (l) and financial revenue (r) as outputs; see Panel D in this table for the definition of inputs and outputs. ace_wp Social efficiency specification where assets (a), operating expense (c), and personnel (e) are taken as inputs; number of active female borrowers (w) and indicator of benefit to the poorest (p) as outputs. see Panel D in this table for the definition of inputs and outputs. Panel B: Impact from COVID-19 gdp_chg_1
The magnitudes of the effects on GDP due to the potential economic impact of the COVID-19 outbreak under the "best case" scenario, measured as percentage decline in total 2018 nominal GDP. gdp_chg_2
The magnitudes of the effects on GDP due to the potential economic impact of the COVID-19 outbreak under the "moderate case" scenario, measured as percentage decline in total 2018 nominal GDP. gdp_chg_3
The magnitudes of the effects on GDP due to the potential economic impact of the COVID-19 outbreak under the "worst case" scenario, measured as percentage decline in total 2018 nominal GDP. gdp_chg_4
The magnitudes of the effects on GDP due to the potential economic impact of the COVID-19 outbreak under the "hypothetical worst case" scenario, measured as percentage decline in total 2018 nominal GDP. emp_chg_1
The magnitudes of the effects on employment due to the potential economic impact of the COVID-19 outbreak under the "best case" scenario, measured as percentage decline in employment among all sectors as of 2018. emp_chg_2
The magnitudes of the effects on employment due to the potential economic impact of the COVID-19 outbreak under the "moderate case" scenario, measured as percentage decline in employment among all sectors as of 2018 emp_chg_3
The magnitudes of the effects on employment due to the potential economic impact of the COVID-19 outbreak under the "worst case" scenario, measured as percentage decline in employment among all sectors as of 2018. emp_chg_4
The magnitudes of the effects on employment due to the potential economic impact of the COVID-19 outbreak under the "hypothetical worst case" scenario, measured as percentage decline in employment among all sectors as of 2018. Panel C: Other variables lendingrate
Lending rate, calculated as the ratio of financial revenue to average loan portfolio. fundingrate
Funding rate, calculated as the ratio of finance expense to average assets. cap
The ratio of capital to total assets. allow
The ratio of impairment loss allowance to total assets. liq
The ratio of cash and cash equivalents to total assets. dep
The ratio of deposits to gross loan portfolio. gdpgr
Annual percentage growth rate of GDP at market prices based on constant local currency (aggregates are based on constant 2010 U.S. dollars). lnpopden Natural logarithm of population density (population density is measured as midyear population divided by land area in square kilometres). Panel D: Variables for efficiency calculation input a Total assets: total value of resources controlled by the financial institution as a result of past events and from which future economic benefits are expected to flow to the financial institution. input c
Operating expense: includes expenses not related to financial and credit loss impairment, such as personnel expenses, depreciation, amortization and administrative expenses. input e Personnel: the number of individuals who are actively employed by an entity. This number includes contract employees or advisors who dedicate a substantial portion of their time to the entity, even if they are not on the entity's employees roster. output w Number of active women borrowers; the number of female individuals who currently have an outstanding loan balance with the financial institution or are primarily responsible for repaying any portion of the gross loan portfolio.
Indicator of benefit to the poorest: this output is measured as (1-(K i -min(K))/range(K))×number of active borrowers, where K is the average loan balance per borrower divided by Gross National Income (GNI) per capita; i is an indicator associated with a particular MFI; min(K) is the minimum value of K over all i; range(K) is the maximum value of K over all i minus the minimum value of K over all i. output l Gross loan portfolio: all outstanding principals due for all outstanding client loans. This includes current, delinquent, and renegotiated loans, but not loans that have been written off. output r
Financial revenue: includes all financial income and other operating revenue which is generated from non-financial services.
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| pISSN 2586-6052 | eISSN Acute and Critical Care
Dear editor: The coronavirus disease-19 (COVID-19) pandemic has severely strained intensive care unit (ICU) resources worldwide. It is estimated that a country like India with a population of 1.3 billion, has one doctor for every 1,457 individuals, 1.7 nurses per 1,000 people, approximately 1.9 million hospital beds, 95 thousand ICU beds, and 48 thousand ventilators. As the cases of severe acute respiratory syndrome (SARS) increase rapidly, finding ICU beds, ventilators, intensivists, and critical care nurses remains a big challenge. The need for mechanical ventilation in COVID-19 patients, however, remains a subject of debate. A Chinese study reported that invasive ventilation was required in only 2.3% of 1,099 COVID-19 positive patients [1] . In contrast, noninvasive ventilation (NIV), including bilevel positive airway pressure and continuous positive airway pressure, is being advocated for early/mild disease [1] . Patients needing mechanical ventilation were sicker and had a higher mortality rate, as compared to those receiving NIV. Additionally, the PaO2/FiO2 ratio was worse among nonsurvivors [2] . A metaanalysis that included 1,084 patients from eight selected studies showed that high-flow nasal cannula (HFNC) treatment could reduce the rate of endotracheal intubation and ICU mortality [3] . A more recent review concluded that HFNC and NIV should be reserved for patients with mild acute respiratory distress syndrome until further data are available [4]. Although aerosolization risk exists for both HFNC (up to 62 cm around the face) and NIV (within 92 cm distance), the former has been recommended by surviving sepsis guidelines [5,6]. NIV must be delivered with a well-fitted full-face non-vented mask, delivered in negative pressure (or single) rooms, and by adding a viral filter between the mask and the expiratory leak or tubing. Besides face masks, NIV may also be provided by nasal pillows (aerosolization risk up to 33 cm distance) and helmet masks (aerosolization risk up to zero to 27 cm distance) [5].
Potentially, HFNC and NIV have the advantage of being provided even outside the ICU and can be managed by trained paramedical staff which conserves ICU resources for more severe patients [7] . Further, recent research has shown an emerging role for awake prone HFNC and NIV [8]. Awake prone positioning improves the mismatch between ventilationperfusion and opens the atelectatic lungs by promoting adequate sputum drainage. Many patients will immediately improve their oxygenation while others show signs of exhaustion or excessive respiratory effort. High tidal volumes (breathing spontaneously or on HFNC/ NIV), may expose diseased lungs to swings of trans-pulmonary pressures and may lead to patient self-inflicted lung injury. Any undue delay in switching to invasive ventilation may worsen outcomes [9]. A recent study has shown that maximal level of interleukin-6 (IL-6), followed by C-reactive protein (CRP) level, was highly predictive of the need for mechanical ventilation suggesting the possibility of using IL-6 or CRP level to guide escalation of treat-ment in patients with COVID-19-related hyperinflammatory syndrome [10] .
With medical facilities severely stretched out, especially in resource-limited regions like India and other developing nations with large population clusters, selective use of HFNC or NIV may reduce the need for ventilated ICU beds while achieving desired clinical results. The decision to switch from HFNC/ NIV to invasive ventilation could be a tricky one with several factors and co-morbidities to be taken into account. However, in the absence of randomized controlled trials (RCTs) and lack of clear guidelines, the clinical judgment of physicians and the availability of necessary resources in their respective hospitals will largely determine the ventilation techniques employed. Large RCTs or well-designed observational studies are needed to define stratification of COVID-19 patients for the best choice of initial respiratory support keeping in mind the resources available and the judicious and timely use of invasive ventilation.
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Immunotherapy of cancer has moved from preclinical development into clinical practice [1, 2] . For example, prophylactic vaccination using 'non-self' antigens such as virusderived proteins from human papilloma viruses reduce the incidence of virus-induced tumors [3, 4] . Moreover, the description of tumor-associated 'self' antigens [5, 6] has opened new avenues for vaccination approaches that target eradication of established tumors cells. Indeed, recent phase III trials have shown that patient-specific cellular vaccines containing tumor antigens can improve survival of patients even with advanced disease [7, 8] . However, since the production of tailored vaccines for individual patients requires laborious and expensive routines, generation of simple and efficient off-theshelf reagents should be fostered.
Biological factors that make the development of therapeutic antitumor vaccines cumbersome include the immunosuppressive microenvironment within the tumor tissue itself [9, 10] and remote inhibitory effects such as the preferential differentiation of T regulatory (Treg) cells [11, 12] . It has been proposed that a combination of tumor antigens with immune-modulatory cytokines can overcome tumor-induced immunosuppression and/or -deviation [13] . Cytokines that foster activation of lymphocytes such as IL-2 or IL-15 have been evaluated in preclinical models and are currently tested in clinical studies [14] [15] [16] to augment tumor-specific immunity. Likewise, cytokines that act mainly on myeloid cells such as granulocyte macrophage colony-stimulating factor (GM-CSF) or Fms-like tyrosine kinase 3 ligand (Flt3L) have been shown to improve the efficacy of cancer vaccines [17, 18] . However, cytokines generally exhibit a wide range of functions. For example, IL-2 is a potent stimulus for the activation of naïve T cells, but fosters at the same time activation-induced cell death of CD8 + effector T cells [19] and induces Treg cells in tumor patients [20] . Likewise, GM-CSF can foster generation and survival of myeloid suppressor cells [21, 22] . Hence, it is important that cancer vaccines deliver such pleiotropic cytokines to those cells that optimally induce and maintain anticancer immune responses.
Dendritic cells (DCs) sample antigen in peripheral organs, and transport the immunogenic material to secondary lymphoid organs to initiate and maintain T and B cell responses [23] . DCs have to be appropriately stimulated to achieve full differentiation of T cells [24] and to overcome potential tolerizing stimuli within the microenvironment of secondary lymphoid organs [25] . Notably, it is important the DCs are directly activated through pattern-recognition receptors to achieve full maturation [26] and to successfully induce rejection of tumors [27] .
Attenuated viral vectors exhibit several important advantages that make them attractive vaccine vehicles for antitumor vaccination. First, viral vaccines can be produced in large quantities and stored as off-the-shelf reagents. Second, viruses generally infect professional antigen presenting cells such as DCs, and third, viral infection triggers DC maturation [28] . We have recently suggested to utilize attenuated coronaviruses as vaccine vectors because (i) these positive-stranded RNA viruses replicate exclusively in the cytoplasm without a DNA intermediary, (ii) recent technological advances permit heavy attenuation without loss of immunogenicity, (iii) their large RNA genome offer a large cloning capacity, and (iv) both human and murine coronaviruses efficiently target DCs [29] . In a previous study, we found that murine coronavirus-based vectors can deliver multiple antigens and cytokines almost exclusively to CD11c + DCs within secondary lymphoid organs [18] . Moreover, induction of CD8 + T cells directed against human tumor antigens and efficient transduction of human DCs with tumor antigen-recombinant human coronavirus 229E [18] indicate that coronavirus-mediated gene transfer to DCs should be considered as a versatile approach for antitumor vaccination.
In the present study, we evaluated the impact of Flt3L or lymphoid cytokines co-expressed with a GFP-tagged model antigen in murine coronavirus vectors on antitumor immunity. We found that DCs transduced in vivo with vectors encoding for Flt3L efficiently activated tumor-specific CD8 + T cells, broadened the epitope repertoire, and secured therapeutic tumor immunity. Interestingly, IL-2 and IL-15 showed a significantly lower adjuvant effect on CD8 + T cell priming and failed to protect against established tumors indicating that coronavirus-mediated in vivo targeting of DCs in conjunction with the myeloid cell-stimulating cytokine Flt3L is well-suited to generate therapeutic antitumor immunity.
Coronavirus-based multigene vaccine vectors were designed on the basis of the mouse hepatitis virus (MHV) genome ( Figure 1A ). To achieve propagation deficiency and to maintain at the same time replication competence, MHV-encoded accessory genes (NS2, HE, gene4, gene5a) were deleted and the non-structural protein 1 (nsp1) was truncated by introducing a mutation that reduces MHV pathogenicity, but retains immunogenicity [30] . Moreover, the structural gene E was deleted to further hinder virion formation [31] . As surrogate tumor antigen, we used a fusion protein of the enhanced green fluorescent protein (EGFP) and the gp33 CD8 + T cell epitope derived from the lymphocytic choriomeningitis virus (LCMV) glycoprotein. To compare the adjuvant effects of cytokines acting mainly on myeloid cells versus lymphocytes, the genes encoding for murine Flt3L, IL-2 or IL-15 were inserted between the replicase and spike genes ( Figure 1A ). Propagation of MHV-based vectors was achieved in 17Cl1 packaging cells that provide the E protein in trans ( Figure 1B) . Importantly, the vectors failed to propagate in primary macrophages ( Figure 1C) and DCs (not shown) in vitro, but efficiently delivered their antigen to DCs resulting in transduction rates of 20 -40% ( Figure 1D ). In vitro transduced peritoneal macrophages and DCs rapidly produced Flt3L or IL-2 following transduction with the respective vector ( Figure 1E ), whereas IL-15 could not be detected following transduction with MHV-IL15/gp (not shown). Notably, IL-15 is known as a cytokine that is trans-presented by IL-15Rα [32] and hence can usually not be measured using conventional detection systems. Furthermore, we found that neither transduction with MHV-gp vector induced any of the three cytokines nor did the cytokine-expressing vectors elicit non-specific cytokine production (not shown). Thus, coronavirus vectors can specifically deliver antigen and different immune-modulatory cytokines to their major target cells.
We have shown previously that the murine coronavirus preferentially infects macrophages and DCs in vivo [33] . Moreover, severe attenuation of MHV further focusses its target cell range to CD11c + DCs [18] . This pronounced DCspecificity was not altered by insertion of Flt3L or lymphoid cytokines. Following i.v. application of 10 6 vector particles into C57BL/6 (B6) mice, EGFP expression was detectable mainly in MHCII (IA b ) high CD11c + DCs (Figure 2A ) whereby the cytokines roughly doubled in vivo transduction efficacy ( Figure 2B ). In vivo delivery of IL-2 ( Figure 2C ) and Flt3L ( Figure 2D ) resulted in high cytokine production after 48 h, whereas IL-15 could neither be detected in serum nor in spleen (not shown). Importantly, comparable to the transient elevation of GM-CSF levels following coronavirus-mediated delivery [18] , both IL-2 and Flt3L levels had normalized at day 4 post application (not shown). Since maturation of DCs is critical for induction of protective immunity [23] , we determined expression of the maturation markers CD40 and CD86 on in vivo transduced, EGFP + DCs. As shown in Figure 2E , only the Flt3L-encoding vectors led to upregulation of both maturation markers. Interestingly, enhanced expression of CD40 and CD86 was restricted to those DCs that expressed EGFP ( Figure 2F ) indicating that the presence of the viral vector within DCs and direct production of the myeloid cell-stimulating cytokine Flt3L led to optimal DC maturation.
To compare the adjuvant effects of the different cytokines encoded by the coronavirus vectors, we first assessed magnitude and duration of transgene-specific CD8 + T cell activation. In addition, to determine cytokine-mediated changes in epitope usage, we monitored CD8 + T cell responses against the H2-D b -binding gp33-41 [34] and the H2-K b -binding gp34-41 [35] epitopes which are both present in the gp33-EGFP transgene. Using i.v. application of 10 5 pfu of each vector, we found that induction of gp34-specific CD8 + T cells responses was best supported by Flt3L leading to superior expansion of tetramer-binding CD8 + T cells and differentiation towards IFNγ-producing effector T cells ( Figure 3A ). Importantly, initial expansion of gp34-specific CD8 + T cells following vaccination with MHV-GP/Flt3 was comparable to the responses induced by the fully replication-competent LCMV ( Figure 3B and 3C) . Surprisingly, although IL-2 and IL-15 have been described as cytokines that support generation of memory T cells [36] , the Flt3L-encoding vector better supported the persistence of transgene-specific CD8 + T cells ( Figure 3B and 3C). As shown previously [18] , MHV-gp vectors failed to raise a substantial response against the H2-D b -binding gp33 epitope ( Figure 3D ). Likewise, the vectors encoding for IL-2 or IL-15 did not elicit a pronounced CD8 + T cell response against the gp33 epitope, whereas vector-encoded Flt3L promoted a broadening of the antigen reactivity towards gp33 ( Figure 3D ). This finding was corroborated using adoptive transfer of gp33-specific P14 TCR transgenic T cells one day before application of the vectors. Again, Flt3L very efficiently supported the expansion of gp33specific CD8 + T cells ( Figure 3E ) indicating that this cytokine functions as an optimal adjuvant for DC-specific targeting approaches.
Induction of potent CD8 + T cell responses against tumor antigens is critical to establish and maintain tumor immunity [37] . To assess the impact of lymphoid versus Flt3L-mediated adjuvant effects on protective tumor immunity, we utilized two different tumor models which provide compatibility with the LCMV-GP system due to the expression of a gp33 minigene [38, 39] . In the first model, we assessed metastatic growth of murine B16F10 melanoma cells. To this end, 5×10 5 B16F10-GP or parental B16F10 cells were applied to B6 mice which resulted in metastatic growth of tumor cells in lungs ( Figure 4A ). Vaccination of recipient mice on day 7 before tumor challenge with 10 5 pfu of the different coronavirus vectors had completely blocked growth of B16F10-GP tumor cells, whereas formation of metastatic foci in lungs by parental B16F10 cells was not affected ( Figure 4A ). Moreover, prophylactic vaccination with 10 2 pfu of IL-2 or IL-15 encoding vectors reduced the tumor burden, whereas the same dose of Flt3L vector completely prevented tumor growth ( Figure 4A ). Careful titration of the cytokine-encoding vector doses and compilation of several series of experiments in the prophylactic vaccination setting revealed that indeed only 10 2 viral particles of MHV-gp/ Flt3L were sufficient to completely protect the mice from tumor challenge ( Figure 4B ). To assess whether cytokine-encoding vectors can elicit therapeutic tumor immunity, mice were first inoculated with B16F10-GP tumors and vaccinated 10 days later with 10 5 pfu of the different coronavirus vectors. Again ten days later, i.e. at day 20 post tumor inoculation, melanoma cells had almost completely covered the whole lung surface in control and MHV-gp vaccinated mice, whereas therapeutic vaccination with cytokine-encoding vectors had reduced the tumor load ( Figure 4C ). Importantly, determination of affected lung surface revealed that only vaccination with the Flt3Lencoding vector was able to significantly reduce the tumor load ( Figure 4D ).
Clearance of rapidly growing metastatic tumors is certainly a challenge for the immune system. However, metastatic tumors such as the B16 melanoma cells can reach secondary lymphoid organs and thereby contribute -most likely due to their MHC class I expression -to the amplification of antitumor CD8 + T cells [40] . In contrast, tumors which arise in peripheral tissues can escape immune surveillance in the absence of appropriately activated T cells [41] . To assess whether coronavirus vector-based vaccination can prevent growth of such peripherally growing tumors, we applied 5×10 5 LCMV-GP recombinant Lewis lung carcinoma (LLC) cells s.c. into prophylactically vaccinated B6 mice. As shown in Figure 5A , all coronavirus-based vectors were able to protect the animals under these conditions. However, when we assessed the efficacy of the vaccines in a therapeutic approach, i.e. applying the vaccines on day 4 post tumor inoculation, only FLt3Lencoding vectors achieved an almost complete block of tumor growth ( Figure 5B ). Taken together, these results indicate that different cytokines can improve immunogenicity of coronavirus vectors. However, maturation of DCs through vector-encoded cytokines that preferentially activate myeloid cells is essential for the generation of therapeutic tumor immunity.
Recent clinical trials have shown that viral vector-based vaccination against cancer is feasible, safe and suitable to achieve protective tumor immunity [42] . For example, a randomized, placebo-controlled study in patients suffering from castration-resistant prostate carcinoma (n=125) showed that a heterologous prime-boost regimen with different poxvirus vectors delivering prostate-specific antigen increased the median survival by 8.5 months [43] . Notably, this approach using an off-the-shelf vaccine yielded an efficacy comparable to the personalized cellular vaccine Sipuleucel which increases survival of patients suffering from incurable prostate cancer by 4.1 months [7] . Nonetheless, the high immunogenicity of viral vectors results in the induction of antiviral immunity which makes heterologous prime-boost schemes necessary to guarantee repeated exposure to the target antigen [44] . Hence, coronavirus vectors based on human DC-targeting common cold viruses [18] , represent a potential asset for future clinical trials that utilize heterologous prime-boost approaches. Importantly, vaccination with attenuated murine coronavirus vectors permits usage of the vectors even in homologous prime-boost schemes hence leading to the maintenance of effector T cells at high frequencies [18] . Since human coronaviruses causing common cold frequently re-infect their hosts [45] , it is possible that this human viral vector family may be utilized as well in homologous prime-boost approaches.
The ability of DCs to induce antigen-specific tumor immunity can be enhanced by immunological adjuvants such as toll-like receptor (TLR) ligands which lead to optimal immune activation only when DCs are stimulated directly through their TLRs [26, 27] . Likewise, cytokines that stimulate the myeloid compartment such as the granulocyte-macrophage colonystimulating factor (GM-CSF), facilitate DC maturation and foster their survival [46] . Our previous study revealed the importance of DC-specific GM-CSF delivery for both DC maturation and prolongation of antigen presentation through improved DC survival leading to sustained CD8 + T cells immunity against viral infection and tumors [18] . Here, we found that a second myeloid cell-stimulating cytokine very efficiently enhanced the immunogenicity of coronavirus vectors. Notably, the Flt3L vectors were even more effective than the GM-CSF vectors in preventing metastatic growth of melanoma cells [18] . Moreover, MHV-Flt3L/gp vectors, but not GM-CSFencoding vectors [18] , elicited a broadening of the epitope repertoire with presentation of two epitopes from the gp33 minigene. Thus, the iterative approach of coronavirus vector optimization using a single model antigen and standardized read-out methods facilitates the definition of cytokines that display optimal adjuvant effects for this vaccine.
In this study, we also evaluated the adjuvant effect of cytokines that act more downstream in the immune activation cascade. The lymphocyte-stimulating cytokines IL-2 and IL-15 are known to enhance proliferation of T cells, to foster differentiation of CD8 + T cells and to control formation of T cell memory [36] . However, despite sharing two out of three of their receptor units (common gamma chain and IL-2/IL-15β-R) these cytokines impact differently on T cell differentiation. IL-2 is most important for the early expansion of T cells and via activationinduced cell death, the limitation of the T cell overshoot [47] . IL-15, on the other hand, is essential for survival of high-affinity T cells during the memory phase [48] and ensures thereby the maintenance of protective T cell memory responses. It is important to note that both IL-2 and IL-15 are highly efficient adjuvants that have been shown to enhance tumor-specific T cell responses [36] . Our data confirm that IL-2 and IL-15 improve CD8 + T cell activation and induction of prophylactic tumor immunity, also when incorporated in a coronavirusbased vaccine that delivers the cytokines directly to DCs in vivo.
It is interesting to note that neither the secreted and systemically acting IL-2 nor the more locally acting, transpresented IL-15 reached the efficacy of the DC-stimulating Flt3L. Flt3L is a highly immunostimulatory cytokine that supports, for example, control of parasitic infections both in mice and humans [49] . Moreover, Flt3L efficiently mobilizes DC precursors, for example in humans with metastatic colon cancer [50] . The results of the present study suggest that high vaccine immunogenicity can be achieved through direct transduction of DCs via a coronavirus vector with concomitant delivery of a potent DC maturation factor such as Flt3L. Clearly, further analyses are warranted to reveal the molecular events involved in Flt3L-mediated adjuvant effects in this system. In addition, it is possible that a combination of different cytokines delivered by coronavirus vectors in homologous prime-boost regimen, e.g. Flt3L followed by IL-15 vectors or vice versa, will result in a further improvement of coronavirus vector-induced antitumor immunity.
In conclusion, incorporation of cytokines into coronavirus vectors substantially improves their performance. Since these vectors almost exclusively target DCs, expression of cytokines that facilitate DC maturation and foster their survival such as GM-CSF or Flt3L, is highly efficient and facilitates generation and maintenance of antitumor CD8 + T cells. Therefore, coronavirus-based vectors that express DC-stimulating cytokines should be further developed for their utilization in therapeutic cancer vaccination.
Experiments were performed in accordance with federal and cantonal guidelines under permission numbers SG09/92, SG11/06, and SG11/10 following review and approval by the Cantonal Veterinary Office (St. Gallen, Switzerland).
C57BL/6 mice were obtained from Charles River Laboratories (Sulzfeld Germany). P14 TCR transgenic mice were obtained from the Swiss Immunological Mutant Mouse Repository (Zurich, Switzerland). All mice were maintained in individual and ventilated cages and were used between 6 and 9 weeks of age. 17Cl1 cells were a kind gift from S. G. Sawicki (Medical University of Ohio, Toledo, OH). The LCMV WE strain was obtained from R. M. Zinkernagel (Universität Zürich, Switzerland). Titration of MHV vectors has been performed as described previously [33] .
Generation of recombinant MHV vectors is based on reverse genetic systems established for MHV-A59 [51] . Molecular cloning and production of recombinant coronavirus particles was performed as previously described [18] .
Bone marrow-derived DCs were generated by culturing erythrocyte-depleted bone marrow cells for 6 to 7 days in the presence of GM-CSF containing supernatant from the cell line X63-GM-CSF (kindly provided by Antonius Rolink, University of Basel, Basel, Switzerland) as described previously [33] . DCs were further purified using Optiprep density gradient centrifugation. Splenocytes were obtained from spleens of B6 mice following digestion with collagenase type II for 20 min at 37°C and resuspended in RPMI/5% FCS. For isolation of the low density cells, splenocytes were resuspended in PBS supplemented with 2% FCS, 2 mM EDTA and overlaid on 20% Optiprep density gradient medium (Sigma-Aldrich Co. Basel, Switzerland). After centrifugation at 700×g for 15 min, low density cells were recovered from the interface and resuspended in RPMI/5% FCS. Cells were stained with different lineage markers and analyzed for EGFP expression with a FACSCanto flow cytometer using the FACS Diva software (BD Biosciences). Antibodies used in this study were purchased from BD Biosciences Pharmingen (CD11c-PE), or Biolegend (CD40-APC, CD86-APC, IA b -Alexa fluor 647 ).
Enumeration of virus-specific CD8 + T cells and ex vivo production of IFN-γ were determined by tetramer staining and intracellular cytokine staining, respectively, as described previously [30] . Organs were removed at the indicated time points following immunization with MHV-based vectors. Tetramers were synthesized and applied for staining of blood and spleen samples as previously described [52] . For intracellular cytokine staining, single cell suspensions of 10 6 splenocytes were incubated for 5 h at 37°C in 96-well roundbottom plates in 200 μl culture medium containing Brefeldin A (Sigma). Cells were stimulated with phorbolmyristateacetate (PMA, 50 ng/ml) and ionomycin (500 ng/ml) (both purchased from Sigma, Buchs, Switzerland) as positive control or left untreated as a negative control. For analysis of peptide-specific responses, cells were stimulated with 10 -6 M of the indicated peptides. Cells were further surface-stained with CD8-APC (eBiosciences), permeabilized with Cytofix-Cytoperm (BD Biosciences) and intracellularly-stained with IFN-γ-PE. The percentage of tet + CD8 + T cells and CD8 + T cells producing IFNγ was determined using a FACSCanto flow cytometer using the FACS Diva software (BD Biosciences). GP33 (KAVYNFATC) and GP34 (AVYNFATC) peptides were purchased from Neosystem (Strasbourg, France).
B16F10-GP melanoma cells expressing the LCMV gp33 epitope [38] and parental B16F10 cells were kindly provided by Dr. H. Pircher (University of Freiburg, Germany). The B16F10-GP melanoma cells were cultivated under G418 (200 µg/ml) (Life Technologies, Gaithersburg, MD) selection. For prophylactic vaccination experiments, mice were immunized with MHV-based vectors seven days before i.v. tumor challenge with 5×10 5 tumor cells. Protection was determined as numbers of metastasic foci per lung on day twelve post tumor inoculation. For therapeutic vaccination, mice received 5×10 5 tumor cells i.v. and were immunized ten days later with the indicated vectors. Tumor clearance was determined on day twenty and recorded as percentage of affected lung surface.
LLC cells expressing H-2D b -restricted peptide 33-41 of the LCMV glycoprotein [39] were kindly provided by Dr. Franca Ronchese (University of Wellington, New Zealand). Efficacy of prophylactic vaccination was assessed by immunizing B6 mice i.v. with 10 5 pfu coronavirus vectors seven days before s.c. challenge with 5×10 5 tumor cells in the left flank. Therapeutic vaccination was done using i.v. application of 10 5 pfu coronavirus vectors in B6 mice which had received 5×10 5 tumor s.c. in the left flank four days previously. At the indicated time points, tumor volume was recorded as V=π x abc/6, whereby a, b and c are the orthogonal diameters.
Statistical analyses were performed with Graphpad Prism 5.0 using non-paired, two tailed Student's t test. Comparison between different groups was done using one way ANOVA with Tukey's post test or with Bonferroni multiple comparison test as indicated. Statistical significance was defined as p < 0.05.
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As the COVID-19 pandemic continues, people worldwide are warned to take necessary precautions to avoid infection. With changing statistics every day, it is clear that certain groups of individuals are at increased risk of severe infection. In particular, the groups at risk are the elderly, individuals with chronic health conditions such as diabetes, cancer, and cardiovascular diseases. Most cases of COVID-19 are classified as mild or moderate. However, some cases are severe and may lead to acute respiratory distress syndrome (ARDS) and even death in those infected (Velavan and Meyer, 2020) . Therefore, it is crucial to understand the mechanism by which this virus causes organ injury and, in particular, the immune system, which is mounted in response to the infection. A few studies have now identified other risk factors for severe complications and death due to COVID-19, namely smoking and obesity (Lighter et al., 2020; Patwardhan, 2020) . The findings related to obesity are plausible since obese individuals tend to be more difficult to intubate, and excess body weight may contribute to increased pressure on the diaphragm, which may make breathing more difficult during infection. Moreover, it is well established that obesity leads to chronic meta-inflammation even in the absence of infection, which has detrimental effects on the immune system such as polarization of macrophages toward a pro-inflammatory phenotype termed M1 macrophages (Li et al., 2018) . Other effects of obesity on the immune system include polarization of T cells toward a pro-inflammatory Th17 phenotype through the accumulation of dendritic cells in the adipose tissue (Woltman et al., 2007) and release of superoxide ion by neutrophils in the adipose tissue (Brotfain et al., 2015) . In addition, obesity is associated with dysregulated lipid synthesis and clearance, which can initiate or aggravate pulmonary inflammation. It has also been shown that antiviral medication and vaccines are less effective in obese individuals (Painter et al., 2015) . In relation to the influenza virus, obesity may have a role in the viral life cycle, which, along with a dysregulated immune system, could lead to severe complications (Honce and Schultz-Cherry, 2019) . During the H1N1 pandemic in 2009, obesity was classified as an independent risk factor for hospitalization, need for mechanical ventilation, and death (Morgan et al., 2010) . These observations are concerning since over one-third of the world population are classified as overweight or obese (Hruby and Hu, 2015) . Therefore, in the ongoing COVID-19 pandemic, it is important to understand the molecular mechanisms through which obesity increases the complications related to COVID-19 to hopefully be able to design more appropriate therapies. Moreover, understanding the effects of obesity on COVID-19 may shed light on the pathogenicity of SARS-CoV-2.
The mode of cellular entry of the novel severe acute respiratory syndrome coronavirus, SARS-CoV-2, is through its binding to the angiotensin-converting enzyme 2 (ACE2) and is similar to SARS-CoV responsible for the 2003 pandemic (Lake, 2020) . Specifically, the spike glycoprotein on the virion binds to the peptidase domain of ACE2. Moreover, it has been shown that the serine protease TMPRSS2 is used by SARS-CoV-2 for the S protein binding (Hoffmann et al., 2020) . Physiologically, ACE2 is part of the renin-angiotensin system (RAS) and serves as a key regulator of systemic blood pressure through the cleavage of Angiotensin (Ang) I to generate the inactive Ang 1-9 peptide, and it directly metabolizes Ang II to generate Ang 1-7 limiting its effects on vasoconstriction and fibrosis. Other than serving as a functional receptor for SARS-CoV, ACE2 has been shown to be implicated in cardiovascular pathologies, diabetes, and lung disease. It is expressed by cells of the heart, kidney, and more specifically in lung epithelial cells (Oudit et al., 2009) . Although ACE2 expression correlates with susceptibility of SARS-CoV infection, the relationship between ACE2 and SARS-CoV-2 is yet to be fully elucidated. In fact, studies have suggested a protective role for ACE2 where overexpression of ACE2 attenuates lung inflammation (Gu et al., 2016) . Current research is focusing on the regulation and role of this receptor in relation to SARS-CoV-2. The aim of this study was to identify mechanisms, through re-analysis of publicly available transcriptomic data, by which SARS-CoV-2 dysregulates the lipid mechanism pathways and investigate the effect of dysregulated lipogenesis on the regulation of ACE2, specifically in obesity.
In order to identify essential differentially expressed genes (DEGs) in SARS-CoV-2 infected versus non-infected epithelial cells, we re-analyzed the publicly available transcriptomic dataset (GSE147507) recently uploaded to the Gene Expression Omnibus (GEO) (Blanco-Melo et al., 2020) . Independent biological triplicates of primary human lung epithelium (NHBE) were mock-treated or infected with SARS-CoV-2 (USA-WA1/2020), then subjected to whole transcriptomic analysis using RNA-Sequencing on Illumina Next Seq 500. The Raw Read Counts were retrieved and filtered from non-expressing genes that showed zero counts in the six samples. Out of the original 23,710 genes, only 15,487 were expressed and selected for further analysis. The filtered gene expression was uploaded to AltAnalyze software for Comprehensive Transcriptome Analysis (Emig et al., 2010) . Principle component analysis and Heatmap clustering were generated, and DEGs were identified using LIMMA algorithm built-in AltAnalyze software. The genes that made the optimal hierarchal cosine clustering were identified, and the common pathways shared by these genes are listed according to their significance. Graphical visualization of the gene was made using the Metascape online tool for gene ontology 1 (Zhou et al., 2019) .
Normal human primary bronchial epithelial (NHBE) cells from non-obese (BMI < 30 kg/m 2 ) and obese (BMI ≥ 30 kg/m 2 ) subjects were purchased from a commercial source (MatTek, MA, United States) or obtained from the Biobank of the Quebec
Extraction of total RNA from NHBE cells was performed using a phenol-chloroform extraction (RiboZol RNA extraction reagent, VWR, Leicestershire, United Kingdom), as directed in the manufacturer's instructions. Contaminating DNA was removed from 500 ng of total RNA using the AccuRT Genomic DNA Removal Kit (Applied Biological Materials, Richmond, BC, Canada), following manufacturer's protocol. Reverse transcription was performed using the 5× All-In-One Reverse Transcriptase Mastermix (ABM). Expression of ACE2 mRNA and GAPDG (house keeping gene) were measured using EvaGreen qPCR Mastermix (ABM). Table 2 shows forward, and reverse primers used. The reaction was as follows: 5 µl of EvaGreen Mastermix, 2 µl of diluted cDNA (1/5), 0.6 µl of forward and reverse primers (10 µM) and 2.4 µl of nuclease free H 2 O. Each sample was tested in duplicates and the quantitative reverse transcription polymerase chain reaction (qPCR) amplification was performed using CFX96 thermal cycler (BioRad, Hercules, CA, United States) and cycler conditions were performed according to manufacturer's protocol. The CT method was used to measure gene expression: amount of target = 2 − CT .
A total of 121 DEGs in infected versus non-infected cells were identified, and they clustered the two groups separately (Figure 1 ). As expected, the top pathways where the DEGs by SARS-CoV-2 are involved were related to inflammatory, immune, cytokines, and antiviral responses. Of note, as shown in Figure 1 , genes involved in lipid storage and high-density lipoprotein particles were among the top upregulated genes by the virus. To have a detailed analysis of the pathways where the top DEGs in infected versus non-infected epithelial cells are involved, we uploaded the 121 DEGs to metascape online tool. Again, most of the DEGs were involved in immune response-related such as Interleukin (IL)-17 signaling pathway. This result was expected and validated our bioinformatics analysis (Wu and Yang, 2020) . IL-10 signaling pathway, acute inflammatory response, metal sequestration by antimicrobial proteins, defense response to another organism, negative regulation of apoptotic signaling pathway, acute-phase response, cellular response to tumor necrosis factor, response to antibiotic and modulation by a host of the viral process (Figure 2 and Table 3) were also involved. Other sets of enriched pathways are related to cell and tissue homeostasis like positive regulation of cell migration, blood vessel morphogenesis, regulation of bone resorption, activation of matrix metalloproteinases, and regulation of smooth muscle cell proliferation. The third set was related to metabolic pathways like negative regulation of ion transport, regulation of glucose metabolic process, the release of cytochrome c from mitochondria, and regulation of fat cell differentiation.
De novo cellular lipogenesis, if disturbed, can change cell deformability as it influences the phospholipid composition of cellular membranes and, as a consequence, can disturb transmembrane receptors like growth factor receptor needed for cell survival (Stoiber et al., 2018) . Based on that we were interested in deciphering the effect of viral infection on epithelial cells lipid metabolism pathways and how the disturbed lipid metabolism, like in obesity and diabetes, might worsen the condition of COVID-19.
In this study, IL6, MMP11, ZC3H12A, PTPRQ, and EGR2 were found to share a common pathway related to the regulation of fat cell differentiation. Of interest, PTPRQ and EGR2 showed CSF2, CSF3, CXCL3, IL6, CXCL8, MMP9, MMP13, S100A7, S100A8, CCL20, CXCL5, TNFAIP3, C3, CAMP, ICAM1, MAOB, IL36G, PGLYRP4, ZC3H12A, KLHL6, GSDMA, SSC5D, SERPINA3, LTB, MMP11, TNFSF14, SEMA3G, C1QTNF1, ADAM32, S100A7A, CSF1R, IFI6, IFI27 significant downregulation in infected cells compared to mockinfected epithelial cells, as shown in Figure 3 . PTPRQ is protein tyrosine phosphatases (PTPs) that regulate tyrosine phosphorylation in signal transduction, and the encoded protein is a negative regulator of mesenchymal stem cell differentiation into adipocytes (Hale et al., 2017) . It is synthesized in the lung and kidney and is downregulated in the early stages of adipogenesis (Thiriet, 2012) . Recent studies linked downregulated PTPs like PTPRQ to lower weight gain, food intake, and leptin resistance (Shintani et al., 2017) .
Next, we tried to look for the trend of changes in the expression of genes involved in lipid metabolism (although the differences were not statistically significant), but this data can give us an idea about the deranged lipid-related pathways.
To visualize the leptin signaling pathways, the filtered gene expression was uploaded to PathVisio pathway analysis and drawing software (Kutmon et al., 2015) . As shown in Figure 4 , there is derangement of a leptin signaling pathway in terms of upregulation or downregulation of genes involved, of note the SOCS3, STAT1, NFKB1, and IL1B were the top upregulated genes. Most individuals with obesity have leptin resistance by leptin and its receptor inhibitor SOCS-3 (suppressor of cytokine signaling-3), leading to dysfunction of leptin biological function (Lubis et al., 2008) .
We then questioned whether disturbed lipid metabolism in obesity could affect the major players' host genes involved in virus binding and entry, namely ACE2. Apart from the circulating RAS, the local lung-based RAS plays a specific role in the injury/repair response (Marshall, 2003) and recently was documented to have a pro-fibrotic effect independent of the known blood pressure effect (Wang J. et al., 2015) . Recently, it was noted that COVID-19 can induce RAS imbalance that drives acute lung injury (Kickbusch and Leung, 2020) . In vitro results showed that continued viral infection would reduce membrane ACE2 expression, leading to unstoppable activation of RAS in the lungs, which further induce local inflammation by recruited neutrophils after LPS stimuli (Vaduganathan et al., 2020) . In COVID-19, ACE2 showed opposite harmful effects as an entry point, and beneficial effect by counteracting the overstimulated RAS as it degrades AngII to angiotensin 1-7 (Ang1-7) (Kuster et al., 2020) . Interestingly Ang1-7 is shown to block high-fat diet-induced obesity, which increased ACE2 expression in adipose tissue (Patel et al., 2016) . Therefore, our hypothesis was that induced obesity can upregulate ACE2 in the lung in response to a high-fat diet, which makes the lung more susceptible to viral entry but can regulate the overstimulated RAS. To examine that, we explored publicly available transcriptomics data, of studies where lungs were examined after inducing obesity, to look for the ACE2 expression changes. GSE38092 dataset was found with eight regular weight mice versus eight diet-induced obese mice where their lungs were extracted for microarray gene expression profiling (Tilton et al., 2013) , as shown in Figure 5C . Interestingly, lung Ace2 expression was significantly upregulated in obese mice compared to lean. Sterol-response element-binding proteins (SREBP) are transcription factors that have been associated with lipogenesis, adipogenesis, and cholesterol homeostasis to prevent lipotoxicity. Studies have shown differential expression of SREBP-1 in regard to obesity. Figures 5A,B shows a decrease in Srebf1 and Srebf2, the genes that code for the different proteins, namely SREBP-1 and SREBP-2.
The increased level of Ace2 in the lungs of obese mice using publicly available datasets led us to investigate which cell type in the lung has the highest expression of Ace2. We explored LungGENS web-based tool that can map single-cell gene expression in the lung (Du et al., 2015) . Among all cells in the human lungs, Ace2 was expressed exclusively by epithelial cells, as shown in Figure 6 .
The next question is how diet-induced obesity mechanistically can upregulate ACE2 in the lung, to answer this question, another dataset (GSE31797) was explored where the dynamics of lung lipotoxicity was examined by manipulating SREBP (Plantier et al., 2012) . SREBPs regulate the expression of genes involved in lipid synthesis and function by their actions as transcription factors (Shimano and Sato, 2017) . It was shown previously that the deletion of ACE2 in the liver and skeletal muscles could induce lipogenesis by inducing SREBPs, indicating the role of the ACE2/Ang1-7 axis in lipid metabolism (Cao et al., 2016 (Cao et al., , 2019 .
In this dataset, alveolar type 2 cell RNA from Insig1/2 / (activated SREBP1 levels) and Insig1flox/flox/Insig2−/− (suppressed SREBP1 levels) mice were profiled by microarray. Interestingly, activating SREBP1, coded by Srebf1, downregulated the expression of Ace2 gene, as shown in Figure 7 . This data indicates that Ace2 expression might be under the control of SREBP1.
In order to prove the effect of diet-induced changes in ACE2 expression, we used a publicly available subcutaneous adipose tissue transcriptomics dataset (GSE77962), where 25 males and 28 females (BMI = 28-35 kg/m 2 ) followed a very-low-calorie diet (weight-loss period) for 5 weeks and a subsequent stable period for an additional 4 weeks (Johansson et al., 2012) . Interestingly, we found in this dataset that there was a significant decrease in ACE2 (p = 0.02) in FIGURE 5 | Ace2, Srebf1, and Srebf2 expression are differentially expressed in obese mice. Srebf1, Srebf2, and Ace2 mRNA normalized gene expression in response to a high-fat diet in obese compared to regular weight mice extracted from publicly available transcriptomic dataset GSE38092.
FIGURE 6 | Expression of ACE2 is highest in lung epithelial cells. mRNA expression of ACE2 was examined in different cell types within the lung using LungGENS web-based tool.
individuals after weight loss compared to baseline (Figure 8) . Moreover, this decrease was maintained when weight loss was stable. This data indicates a correlation between ACE2 expression and diet.
qPCR Validation of in silico Analysis: ACE2 Expression Is Increased in Lung Epithelial Cells of Obese Subjects Lung epithelial cells from non-obese and obese subjects were used to validate the in silico findings. Subjects selected had no other co-morbidities as to study the effect of obesity directly. Table 1 presents the data on the lung epithelial cells obtained from non-obese and obese subjects. ACE2 (p = 0.0005) and SREBP1 (p = 0.0015) expression were significantly increased in obese subjects as described in the in silico data (Figure 9) . We were also interested to see the expression of TMPRSS2, a serine protease which is used by SARS-CoV-2 for S protein binding (Hoffmann et al., 2020) . Following the trend of ACE2, TMPRSS2 was highly increase in obese lung epithelial cells as compared to lung epithelial cells obtained from non-obese subjects. To date, there are no in vitro studies on the expression of ACE2 in lung epithelial cells in the context of obesity.
This study, which uses publicly available data, demonstrates that SARS-CoV-2 infection induces changes in lipid FIGURE 7 | Ace2 expression is regulated by SREBP. Normalized mRNA expression of Ace2 gene probes used in the publicly available dataset (GSE31797) comparing SREBP activated with SREBP inhibited alveolar cells.
FIGURE 8 | ACE2 expression is decreased in subcutaneous adipose tissue after weight loss. The following publicly available transcriptomic dataset (GSE77962) was explored (25 males; BMI: 28-35 kg/m 2 ), and 28 females (BMI: 28-35 kg/m 2 ) were placed on a very low-calorie diet for 5 weeks and a subsequent weight stable period for 4 weeks.
profile in healthy hosts as demonstrated in infection of healthy epithelial cells. This is important when obesity is at play as the lipid profile is already disrupted, which may lead to increased susceptibility to infection which if occurs will further alter the lipid profile inducing hyper-inflammation.
Furthermore, our re-analysis of the publicly available transcriptomic datasets also demonstrated that SARS-CoV-2 infection of healthy epithelial cells compared to mock-infected cells clusters the genes involved in inflammatory, immune and viral responses (Figure 1) . In particular, the IL-17 and IL-10 signaling pathways were heavily impacted. Symptoms of severe COVID-19 have been associated with a cytokine storm with high levels of IL-17, IL-10, IL-1β, IL-2, IL-7, IL-8, IL-9, among many other pro-inflammatory cytokines (Huang et al., 2020; Wu and Yang, 2020) . IL-17, with its many proinflammatory effects, has been suggested as a potential target for the treatment of COVID-19. This is of interest as obesity is associated with high levels of immune cells producing IL-17 (Chehimi et al., 2017) . IL-10, an anti-inflammatory cytokine with antiviral properties, is usually downregulated in infections. However, severe cases of COVID-19 have been associated with high levels of IL-10.
Obesity is a major health problem associated with an increased risk of developing diabetes, hypercholesteremia, and hypertension. Alterations in the metabolic pathways are seen, such as increases in leptin and insulin secretion and a decrease in adiponectin. Leptin stimulates fatty acid oxidation and may lead to lipotoxicity through decreased lipid accumulation in non-adipose tissue. As metabolic regulation and immune responses seem to be integrated with the function of one is dependent on the other, obesity is associated with high levels of pro-inflammatory mediators (Hotamisligil, 2006) . Therefore, we focused our study on metabolic pathways in conjunction with inflammatory pathways. In silico analysis revealed that among the pathways that were differentially expressed were the regulation of glucose metabolic process and regulation of fat cell differentiation (Figure 2) . PTPRQ and EGR2 genes were significantly downregulated in SARS-CoV-2 infected healthy epithelial cells. Although they have been described to have roles in lipogenesis, their exact role in viral infection remains unknown and warrants further investigation.
The upregulation of LEPR and LEP and associated SOC3 in response to SARS-CoV-2 infection was in line with mechanisms that are dysregulated in the state of obesity. This finding is of interest as it has been previously shown that viruses such as the West Nile Virus hijack cellular cholesterol to redistribute it and allow completion of its replication cycle (Mackenzie et al., 2007; Zhang et al., 2017) . Previous studies have shown that obesity is associated with leptin resistance and increased blood levels of leptin with concomitant increases in SOC3, which plays a role in inhibiting signal transduction of leptin and other cytokines (Wunderlich et al., 2013) .
Having established that SARS-CoV-2 infection and obesity share common pathways associated with dysregulation of lipid metabolism, we were interested to see if obesity, which has been described as a risk factor of COVID-19, is associated with higher susceptibility to infection. SARS-CoV-2 uses the ACE2 as a receptor for viral entry, so we hypothesized that obesity might lead to higher expression of ACE2. We first analyzed a dataset using a high-fat diet animal model of obesity, results revealed a higher expression of Ace2 among diet-induced obese mice compared to lean mice. The data also suggests that ACE2 is largely expressed in epithelial cells of the lung. Previous studies with SARS-CoV have shown that the infection state correlates with the state of cell differentiation and expression of ACE2 (Jia et al., 2005) .
To validate these findings, lung epithelial cells were used from non-obese and obese subjects. To our knowledge, this is the first FIGURE 9 | ACE2, TMPRSS2, and SREBP1 expression are increased in lung epithelial cells of obese subjects. Lung epithelial cells from non-obese (n = 4) and obese (n = 3) were used to assess mRNA expression of ACE2 (A), TMPRSS2 (B), and SREBP1 (C). **p < 0.01, ***p < 0.001. study to show that ACE2 and TMPRSS2, two entry points for SARS-CoV-2, are highly upregulated in lung epithelial cells from obese subjects using in vitro experiments.
The present study focused on the relationship between ACE2 expression and dysregulation of lipid metabolism. Therefore, we were interested to see how dysregulation of lipid metabolism could affect ACE2 expression. SREBPs are a family of transcription factors that control lipid synthesis and adipogenesis by controlling enzymes required for cholesterol, fatty acid, triacylglycerol, and phospholipid synthesis. In cholesterol deprivation, they translocate from the endoplasmic reticulum to the Golgi apparatus, where they are then targeted to the nucleus following cleavage. In the nucleus, they proceed to induce the expression of fatty acid and sterol synthesis (Bertolio et al., 2019) . SREBP family is composed of SREBP-1 and SREBP-2. SREBP-1 exists as two isoforms: SREBP1-a and SREBP1-c. These isoforms are controlled by independent regulatory proteins and appear to respond differently to different states of lipid factors. In silico data suggests that suppressing SREBP1 leads to the upregulation of ACE2 expression. Of interest, analysis of another dataset revealed changes in ACE2 expression in adipose tissue of overweight or obese individuals who underwent a weight loss program. This result further emphasizes the relationship between ACE2 and weight and shows the modulation of ACE2 expression. De Macedo et al. (2015) showed that activation of ACE2 using diminazene aceturate had a significant effect on lipogenesis. In vitro, we found that SREBP1 expression is also upregulated in lung epithelial cells of obese subjects compared to non-obese subjects. In studies in chronic kidney disease it has been shown that angiotensin II activates SREBP1 which mediates angiotensin II-induced profibrogenic responses (Wang T.N. et al., 2015) . In the present study, we have used a single cell model (lung epithelial cells) and it would be of future interest to study the FIGURE 10 | Summary of the proposed mechanism of SARS-CoV-2 infection in obese individuals. (1) ACE2 expression is increased in obese subjects due to dysregulation in lipid metabolism. (2) Increased ACE2 expression leads to an increase in the viral entry of SARS-CoV-2, which utilizes ACE2 as a receptor. (3) Upon entry of the virus, dysregulation in lipid metabolism leads to an increase in SREBP, which subsequently leads to a decrease in ACE2 (4). (5, 6) Inhibition of ACE2 activity results in increased lipotoxicity and inflammation. This mechanism demonstrates the dual function of ACE2 in viral infection. effects of other factors such the role of immune cells in the regulation of these genes. Therefore, the relationship between ACE2 and SREBP1 remains to be fully understood and warrants further investigation.
In summary, our findings from the publicly available transcriptomic data show that SARS-CoV-2 infection has significant effects on pathways involved in lipid metabolism. The proposed mechanism is illustrated in Figure 10 . In silico and in vitro results suggest that ACE2 expression is increased in obese subjects which may be due to dysregulation in lipid metabolism. Increased ACE2 expression leads to an increase in the viral entry of SARS-CoV-2, which utilizes ACE2 as a receptor. Upon entry of the virus, dysregulation in lipid metabolism leads to an increase in SREBP, which subsequently leads to a decrease in ACE2. Inhibition of ACE2 activity results in increased lipotoxicity and inflammation. This mechanism demonstrates the dual function of ACE2 in viral infection. This is of importance as dysregulation of lipid metabolism is a feature of obesity, one of the risk factors of COVID-19. More importantly, our data reveal that this increased susceptibility may be due to an increase in ACE2 expression in the lung. These findings may potentially aide us in understanding the increased susceptibility in relation to other risk factors such as diabetes and hypercholesteremia.
Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/geo; IDs: GSE147507, GSE38092, GSE31797, and GSE77962.
Ethical review and approval was obtained from McGill University Health Centre Research Ethics Board (2021-6961). Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.
SA, MH, AS, and MG designed the experiments, analyzed the samples, and contributed to data interpretation and manuscript preparation. AA, RH, AA-A, and QH contributed to data interpretation and manuscript preparation. All authors read and approved the final version of the manuscript.
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So Ri Kim https://orcid.org/0000-0002-6074-9158
There are no financial or other issues that might lead to a conflict of interest.
with severe asthma suppress immunity; therefore, biologics can also be continued. A new biologic treatment is initiated after the balance between therapeutic benefit and risk is assessed thoroughly explored. 6 It is recommended that routine pulmonary function tests (PFTs), including spirometry be postponed and limited to inevitable tests for immediate treatment decision, because such tests can disseminate viral particles and staff and patients are exposed to risk of infection. If necessary, adequate infection control measures should be taken. 6 Given the benefits of not doing routine PFTs in severe asthmatic patients, it seems appropriate to postpone the test only when COVID-19 peaks with community infection in each region. In several medical centers in this country, while COVID-19 incidence has peaked, spirometry has been postponed until patients with respiratory symptoms have negative results on reverse transcription polymerase chain reaction (RT-PCR) tests for COVID-19.
In addition, all asthmatic patients should be instructed to follow their personalized asthma action plans (AAPs). If an AE arises, an SCS can be used as specified in their AAP. 6 In the regions with low use of AAP such as South Korea, it is not only necessary to establish a personalized AAP, but a specialized clinical plan should be designed to provide asthmatic patients with safe, immediate medical services. Thus, ICSs and biologics can be continued, while SCS use should be minimized.
Among the patients with COVID-19 reported to the Centers for Disease Control and Prevention of the United States, higher percentages of patients with chronic lung diseases, including asthma and chronic obstructive pulmonary disease, were admitted to hospital or to an intensive care unit than those without. 10 However, asthma does not seem to have a significant effect on COVID-19 deaths. 4, 11 These results are consistent with those from South Korea. 12 Moreover, COVID-19 does not appear to cause AEs, although there is no direct evidence on it. Data from 3 university hospitals including, 2 hospitals in Daegu, the epicenter of the outbreak in South Korea, show that 45 asthmatic patients with suspected AEs or pneumonia underwent COVID-19 RT-PCR tests, only 2 of whom were confirmed to have COVID-19. Both of these patients had pneumonia, but there were no obvious signs of AE. They had been well controlled with low-to medium-dose ICS treatment before being affected by COVID-19. During hospitalization for treatment of COVID-19 pneumonia, treatment with ICS and long-acting β 2 agonists successfully controlled their asthma symptoms. We infer carefully from our limited observations that COVID-19 does not have a significant impact on AE in asthmatic patients, particularly those with well-controlled non-severe asthma. It remains unclear whether SCS use to treat AEs caused by or combined with COVID-19 is beneficial or harmful in COVID-19. Clinical guidelines suggest careful use of SCSs for AE associated with COVID-19 in: (1) critically ill patients with COVID-19 pneumonia, (2) those with hypoxemia due to underlying disease or who regularly use SCSs for their disease, (3) those whose dosage should be low-to-moderate (≤ 0.5-1 mg/kg/day methylprednisolone or equivalent), and (4) those whose duration is as short as ≤7 days. 13 Although COVID-19 does not seem to cause AE, the longer the pandemic duration, the greater the cumulative frequency of AEs due to aggravating factors such as seasonal/perennial allergens and other respiratory infections during the pandemic. 14 Guidelines recommend that patients with AE not caused by COVID-19 should receive a short course of SCS prescription by their attending physicians to prevent serious consequences. 6 As described above, many patients with asthma are reluctant to visit medical institutions in fear of exposure to COVID-19 and to discontinue medications, which can be significant risk factors of AE. Therefore, it is important to establish a specialized clinical plan to provide asthmatic patients with proper treatment to prevent serious AE during the COVID-19 pandemic.
During the ongoing COVID-19 pandemic while maintaining a social distance of 2 m during daily activities has been proposed, many regular visits to medical centers and health care could be delayed or handled through telemedicine. However, patients with asthma, especially severe asthma, need to continue face-to-face visits to the medical institutions even during the COVID-19 pandemic to maintain control of their asthma. However, there is no consensus on how to prioritize medical services for patients. The government of South Korea has designated 'Public Relief Hospitals' during the period of the COVID-19 pandemic to guarantee general medical services and to prevent the virus from spreading. The purpose of this system is to separate areas for general patients from those for respiratory patients to prevent infection in hospital. Therefore, general patients without risk of COVID-19 or any suspicious symptom of COVID-19 could be permitted to visit medical institutions. Ironically, under the Public Relief Hospitals system, although patients with asthma, especially when they have AEs, should be prioritized for face-to-face care, optimal medical services cannot be provided until a negative result of the COVID-19 RT-PCR test is confirmed because they usually present respiratory symptoms such as cough, sputum, and dyspnea, which are difficult to distinguish from COVID-19. For appropriate management of patients with asthma, experts suggest specialized clinical plans based on updated clinical guidelines and state-of-the-art information on COVID-19. 15 Such plans should include the following: (1) patients with well-controlled asthma or stable mild-to-moderate asthma in the past 6 to 12 months may postpone routine face-to-face visits, and use telemedicine or care by proxy to ensure continuity of care; (2) patients with severe asthma are encouraged to visit the medical institutions for face-to-face care and prescriptions; (3) asthmatics with AEs or in poor asthma control status need to follow COVID-19 screening protocols in order to determine their risk of COVID-19 infection and need for testing at a designated facility; and (4) in cases of severe asthma with COVID-19 risk, face-to-face treatment is carried out by medical staffs wearing personal protective equipment (PPE) in the negative pressure isolation ward while waiting for test results (Figure) .
Specifically, the designated hospitals for the treatment of COVID-19 in Daegu, Korea's largest COVID-19 outbreak area, follow a specialized clinical plan for patients visiting the emergency department with suspicious symptoms of AE: (1) COVID-19 risk evaluation at the initial triage─major symptoms including fever, cough, and dyspnea─and epidemiological risk evaluation such as contact history with a confirmed or suspected case and travel history; (2) COVID-19 RT-PCR test and chest X-ray imaging in an isolated room under negative pressure by medical staff wearing PPE; (3) general management of AEs after release of quarantine for patients with negative COVID-19 testing─treating with systemic corticosteroids and shortacting bronchodilators using metered-dose inhalers with spacers instead of nebulizers, since the use of nebulizers inside healthcare facilities including the emergency department may increase the risk of aerosol spread of virus particles. 6 In terms of personal quarantine, asthmatic patients are also advised to maintain general personal hygiene including wearing a face mask and to maintain a social distance of 2 m. In some patients with asthma, wearing a face mask can lead to further difficulty in breathing, but it is important to wear a mask when visiting medical facilities and enclosed public space such as locker rooms and elevators, or when new respiratory symptoms occur. However, it is better to choose a mask type that is easy to breathe, depending on the respiratory condition. Most of all, optimal asthma control is expected to be the best protective strategy for all asthmatic patients against AE caused by COVID-19 or other factors.
In conclusion, there have been few studies to demonstrate a specifically increased risk for COVID-19 in patients with asthma, and it cannot be ruled out that COVID-19 may cause AE. Thus, based on up-to-date information, we should prepare effective strategies for the prevention and treatment to protect patients with asthma. To maintain health, patients with severe asthma should maintain their controller medications including, ICSs, SCSs, and biologics, continue visits to medical facilities, and prepare an immediate clinical management plan for severe AE, including a COVID-19 RT-PCR test. Under physicians' supervision, SCSs can be used for the control of AEs. Importantly, the plans should also follow personal quarantine guidelines.
In human history, outbreaks of infectious diseases have repeatedly occurred. The process of overcoming COVID-19, a new infectious disease that can be fatal due to damage to the respiratory tract, can be an opportunity to learn more about asthma management. Figure. Specialized clinical plan for the management of asthmatic patients during the COVID-19 pandemic. COVID-19, coronavirus disease-19; RT-PCR, reverse transcription polymerase chain reaction; CS, corticosteroids; AE, asthma exacerbation; PPE, personal protective equipment. *In South Korea, telemedicine is temporarily allowed only during the COVID-19 pandemic.
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Coronavirus disease 2019 (COVID-19) is a clinical syndrome, caused by a mutational RNA virus named as Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2). After initially occurring in China in December 2019, it spread all over the world and accepted as a pandemic by the World Health Organization (WHO) in March 11, 2020 . SARS-CoV-2, is a beta-coronavirus, similar to two other coronaviruses causing deadly infections during the last two decades, i.e. Severe Acute Respiratory Syndrome Corona Virus (SARS-CoV) and the Middle East Respiratory Syndrome Corona Virus (MERS-CoV) [1] .
Although SARS-CoV-2 infections may be asymptomatic or cause only mild symptoms in the majority of the cases and less lethal than MERS-CoV infections, it may progress to interstitial pneumonia and acute respiratory distress syndrome (ARDS) in nearly 10-20% of the cases, especially in those having older age and co-morbidities. This subgroup of patients is notable with having very high levels of serum ferritin and D-dimer levels, hepatic dysfunction, thrombotic tendency, and disseminated intravascular coagulation (DIC) implicating occurrence of macrophage activation syndrome (MAS), also known as secondary hemophagocytic lymphohistiocytosis (sHLH) [2, 3] . Similar clinical and laboratory findings were also reported in patients with SARS-CoV and MERS-CoV infections [1, 2] .
In this context, we aimed to review COVID-19 infection, with special reference to its relationship with cytokine storm. For this purpose, PubMed and Google Academic were searched from April 11 to 26, 2020. Original data in all studies (including case reports and case series) that addressed the definition, causes, and classification of COVID-19 and hemophagocytosis, MAS, hemophagocytic lymphohistiocytosis, and cytokine storm, published in the English language in peer-reviewed journals, were included. An additional search for fulltext articles with the same keywords was performed in the databases, subscribed by Altınbaş University.
Results of our search were outlined as follows: firstly we discussed the pathogenesis and immunologic features in COVID-19 infection, followed by normal interactions between innate immune system and viruses, background for cytokine storm secondary to COVID-19 infection, and finally the management of the immunologic complications.
Fever, dry cough, shortness of breath, myalgia, fatigue, a tendency for leucopenia, and radiological signs of progressive pneumonia, which may cause ARDS, are similar clinical and laboratory findings seen in COVID-19, SARS-CoV, and MERS-CoV infections. This may suggest that their pathogenesis may also be similar [2] . We believe that any hypothesis covering COVID-19 pathogenesis should explain very high serum levels of both ferritin and D-dimer levels disproportionate with the severity of infection, as well as a tendency for monocytosis, rather than lymphocytosis, including a low number of natural killer (NK) and cytotoxic T cells, and finally tendency for DIC. Indeed, these striking features mainly reflect the presence of MAS and cytokine storm.
Spike glycoproteins are the most immunogenic parts of the coronaviruses, which may bind to angiotensin-converting enzyme-2 (ACE-2) receptors to enter the host cell. Similarities were shown between spike glycoproteins of SARS-CoV and SARS-CoV-2. Distribution of ACE-2 receptor expression intensely on the surface of alveolar epithelial type II cells, cardiac, renal, intestinal, and endothelial cells is consistent with the target organs involved and the clinical picture in COVID-19 infection [2, 4] .
SARS-CoV-2 spreads primarily with direct contact through droplets of saliva or discharge from the respiratory tract, when an infected person coughs or sneezes [1] . Following binding to the cell surface receptor of ACE-2 by the spike glycoprotein, it enters the cell cytoplasm, where it releases RNA genome and replicates, resulting in the formation of new viral particles. Then, the cell disintegrates and the virus spreads to other cells.
As the immune system recognizes the viral antigens, antigen-presenting cells process these antigens and present them both to the natural killer and CD8-positive cytotoxic T cells in the context of major tissue histocompatibility (MHC) antigens as usual. This presentation activates both innate and adaptive immunity causing the production of large amounts of pro-inflammatory cytokines and chemokines. In some patients, this activation becomes so massive that cytokine storm develops, resulting in thrombotic tendency and multi-organ failure, and eventually causing death [5, 6] .
Another pathogenic mechanism independent from binding to cell surface ACE-2 binding was also speculated, claiming that the virus might bind to the beta chain of porphyrins inside the erythrocytes, resulting in disturbance of heme metabolism and release of iron. However, this speculation needs further investigation and remains elusive [7, 8] .
Zhang at al. reported that the number of T lymphocytes including both CD4 and CD8 subtypes and especially NK cells are much lower than expected in patients with severe disease course [9] . The number of regulatory T cells is also very low. Severe lymphopenia is a very early sign of the disease, preceding pulmonary problems, and tends to normalize as the patient improves. Lymphopenia is included among diagnostic criteria in China. Despite low numbers, both CD4 and CD8 positive lymphocytes express the high amount of HLADR4 and CD38, showing hyperactivity. Additionally, CD8 T cells harbor high concentrations of cytotoxic granules; i.e., 31.6% were perforin positive, 64.2% were granulysin positive, and 30.5% were both granulysin and perforin positive. Total leukocyte and neutrophil counts and neutrophil/lymphocyte ratio (NLR) are increased especially in severe cases; NLR may be used as a follow-up parameter in patients with COVID-19 infection [10, 11] . Generally, the number of CD8 T lymphocytes recovers in 2-3 months, whereas it may take nearly a year for the memory CD4 T lymphocytes to recover in SARS CoV infection [9] [10] [11] [12] [13] .
Besides low numbers of peripheral lymphocytes, there is striking atrophy of the secondary lymphoid organs including the lymph nodes and spleen, confirmed by autopsy findings. Necrosis-associated lymph node and spleen atrophy, significant splenic cell degeneration, focal hemorrhagic necrosis, macrophage proliferation, and increased macrophage apoptosis in the spleen have been reported. Immunohistochemical staining showed decreased numbers of CD4 positive and CD8 positive T cells in the lymph nodes and spleen [14, 15] .
On the other hand, monocytes and macrophages are increased, which may explain elevated levels of proinflammatory cytokines such as interleukin (IL)-6, IL-1, tumor necrosis factor (TNF)α, and IL-8, which in some patients turn out to be a cytokine storm, as discussed more in detail later.
The great majority of the inflammatory cells infiltrating the lungs are monocytes and macrophages. Autopsy findings showed the presence of monocytes and macrophages and a moderate amount of multinucleated giant cells associated with a diffuse alveolar injury. However, pulmonary infiltrating lymphocytes were scarce and mostly CD4 positive. These findings were not different than those reported for patients with SARS-CoV and MERS-CoV infections [14] .
In patients with COVID-19, elevated D-dimer levels are important and persistent elevation confers to poor prognosis. Development of DIC is another problem, characterized by prolongation of prothrombin time and activated partial thromboplastin time, high fibrin degradation products, and severe thrombocytopenia, which may be life-threatening [16] .
Thrombotic tendency in COVID-19 patients is probably caused by endothelial cell activation or damage due to viral binding to the ACE-2 receptor. The presence of traditional risk factors for venous thromboembolism was found to be high among COVID-19 patients. High levels of inflammatory mediators and immunoglobulins may lead to higher blood viscosity; mechanical ventilation and vascular interventions such as central venous catheterization may further induce vascular endothelial damage in severe or critically ill patients. Anticardiolipin antibody levels were also found to be high in small groups reported. The combination of all these factors may lead to deep vein thrombosis or even possibly to lethal pulmonary thromboembolism. Therefore, COVID-19-infected patients, whether hospitalized or ambulatory need early and prolonged prophylaxis with low molecular weight heparin [9, 16] . On the other hand, ischemic changes in the fingers and toes mimicking vasculitis have been reported in patients with severe COVID-19 [13] .
The quick interpretation of these issues outlined above shows that the disease starts as a simple viral infection but goes out of control after a while and progresses towards a deadly result with development of the cytokine storm and serious organ damage. To understand why and how this process occurs, and what we can do to control this process, we need to know further details of the pathogenesis of COVID-19 and cytokine storm.
In the context of the normal innate immune system, macrophages, monocytes, dendritic cells, and neutrophils express a variety of pattern recognition receptors (PRRs) that detect pathogen-associated molecular patterns (PAMPs), which are expressed by infectious agents. Among PRRs, the membranebound family of toll-like receptors (TLRs) recognizes mainly the PAMPs in the extracellular and to a lesser account in the intracellular milieu. The triggered signaling process leads to the expression of proinflammatory cytokine-inducing transcription factors, such as NF-kB, as well as to activate interferon regulatory factors that mediate the type I interferondependent antiviral response [17] . The second set of pathogen recognition sensors is present in the cytosol and includes another family of nucleotide-binding domain leucine-rich repeat (NLR) proteins (NLRP1, NLRP3, NLRP7, and NLRC4), the protein absent in melanoma 2 (AIM2), and pyrin. These sensors are essential for the detection of endogenous dangerassociated molecular patterns (DAMPs) expressed inside the cell. Binding of DAMPs activates NLRs, triggering the formation of multiprotein cytoplasmic complexes called inflammasomes, which convert procaspase-1 to active caspase-1. Then, caspase-1 converts proIL-1β to active IL-1β, which is a very important proinflammatory cytokine [17, 18] (Fig. 1 ). It should be noted that if these signaling activation processes are kept under control, they serve for the benefit of the human body.
For the viruses, PAMPs are generally their nucleic acids. Viral RNA binds to endosomal TLR-3, TLR-7, and cytosolic receptors including RIG-I like receptors (RLR's). RLR family consists of three members, namely, retinoic acid-induced gene I (RIG-I), Melanoma Differentiation-Associated Gene 5 (MDA5), and Laboratory of Genetics and Physiology 2 (LGP2) [19, 20] . Additionally, RIG-I and MDA5 have two CARDs (N terminal caspase activation and recruitment domains). Upon binding of RNA with RLR, CARD interacts with MAVS (mitochondrial adaptor antiviral signal) protein, leading to activation of the gene coding type 1 interferons (IFNs). Type 1 IFNs play important roles in coordinating cellular immunity reactions to viral infections, thereby contributing to normal antiviral immunity [21] .
In normal conditions, virus-infected cells are destroyed by NK cells of the innate immunity and CD8 positive cytolytic T cells of the adaptive immunity, using perforin-mediated granulysin secretion. This leads to apoptosis of antigenpresenting cells and relevant cytotoxic T cells to avoid unnecessary activation after the antigenic activity is over. However, if a defect occurs in lymphocyte cytolytic activity, whether due to genetic problems or acquired conditions, this may lead to the inability of NK and cytolytic CD8 T cells to lyse infected and activated antigen-presenting cells, resulting in prolonged and exaggerated interactions between innate and adaptive immune cells. In this case, many pro-inflammatory cytokines, including TNF, interferon-γ, IL-1, IL-6, IL-18, and IL-33, are secreted in an unrestrained way causing a cytokine storm. The whole pathologic process starting with defects in lymphocyte cytolytic activity, going on with increased macrophage activity and whole immune system activation, resulting in a cytokine storm, ARDS, and multiorgan failure, is also called as MAS [3, 22, 23] . This life-threatening condition is one of the major causes of death in COVID-19 patients.
There is no consensus or suggestion on which terminology should be used: cytokine storm, MAS, or sHLH? We chose to use the term cytokine storm secondary to COVID-19; however, it would not be irrefutable for anyone to use MAS or sHLH terminology.
Among patients initially reported in Wuhan, the occurrence of MAS, cytokine storm, and ARDS were heralded by very high levels of serum pro-inflammatory cytokines and ferritin. In the past, significantly higher serum levels of IL-6, IFN-α, CCL5, CXCL8, and CXCL-10 were also detected in patients with severe SARS-CoV or MERS-CoV infections compared to those with milder infections [24] .
Clinical and laboratory features of MAS include sustained fever, elevated serum ferritin, and triglyceride levels, pancytopenia, fibrinolytic consumptive coagulopathy, liver dysfunction, and splenomegaly. Besides, low or absent NK cell activity, elevated serum levels of sCD25 and sCD163, and the presence of hemophagocytosis, which is defined as the engulfment of blood cells, including Fig. 1 Generation of inflammasome and IL-1 activation pathway eryhrocytes, leucocytes, or platelets by phagocytic cells, support the diagnosis of MAS [3] .
Proposed predisposing factors for MAS and cytokine storm secondary to COVID-19 infection are discussed below:
(1) Impaired viral clearance
The main problem in COVID-19 infection is impaired viral clearance, like SARS-CoV and MERS-CoV infections. These viruses have some strategies to combat against host defense mechanisms. SARS-CoV and MERS-CoV could produce vesicles having double membranes without PRRs, and to replicate inside these vesicles [25] . These strategies lead to impaired antiviral immune response and viral clearance. Although the PCR test is negative, the presence of virus inclusion bodies in pulmonary alveolar cells and macrophages at least for 2 weeks still supports the possibility of a failure of virus clearance [14] .
(2) Low levels of type I interferons Another contributing factor is low levels of type I interferons, which are indeed very important in anti-viral response and viral clearance [21] . Cellular proteins that recognize viral nucleic acids are mediated by stimulating interferons during viral infections. Recognition of viral RNA by MDA5 is essential for anti-viral immunity, and deficiency of MDA5 causes a tendency for viral infections in humans [26] . An accessory protein of MERS-CoV called as 4a, binds to doublestranded RNA, thereby blocking MDA5 activation and IFN induction [27] . It should be noted that people who died during the 1997 H5N1 influenza outbreak showed lymphoid tissue atrophy associated with high titer circulatory cytokines, including IL-6 [28] . Similar upregulation of pro-inflammatory cytokines together with downregulation of antiviral cytokine was observed in MERS-CoV infection [29] .
(3) Increased neutrophil extracellular traps (NETs) Neutrophils may kill the invading pathogens including viruses not only through engulfment of microbes, the formation of reactive oxygen species, degranulation, and secretion of antimicrobials but also through formation of NETs. NETs are networks of extracellular fibers, primarily composed of DNA from neutrophils that bind and kill extracellular pathogens while minimizing damage to the host cells [30] . Barnes et al. suggested that neutrophils may contribute to COVID-19 pathogenesis utilizing NETs, based upon autopsy findings. They also suggested that dornase alpha treatment may be beneficial for the management of this infection [31] . Transfer of DNA fragments to extracellular space may be due to the release of mitochondrial DNA together with disruption of the plasma membrane or caused by a process known as NETosis. NETosis is a type of programmed cell death distinct from apoptosis and necrosis. Viral RNA and proinflammatory cytokines may stimulate the formation of both NETs and NETosis. Although the exact role of NETs in anti-viral immunity has not been elucidated yet, they might contribute to COVID-19 pathogenesis [30] [31] [32] .
(4) Miscellaneous other mechanisms:
Pyroptosis is a highly inflammatory and Caspase-1dependent form of programmed cell death that occurs most frequently upon infection with intracellular pathogens and is part of the antimicrobial response. It has been postulated that pyroptosis with rapid plasma-membrane rupture and release of proinflammatory intracellular contents may also play a role in COVID-19 pathogenesis. Rapid viral replication that causes increased pyroptosis may lead to a massive release of inflammatory mediators [33, 34] .
Liu et al. emphasized the importance of antibodies against spike glycoprotein (anti-S-IgG) as promoters of proinflammatory monocyte/macrophage accumulation in the lungs. They suggested that viral-specific antibody response may cause pathological changes, which may be responsible for virusmediated lung injury [35] . Golonka et al. speculated that glycoprotein S protein on coronaviruses may undergo a conformational change and enter the host cells through the Fc region of IgG. In other words, they proposed a mechanism permitting antibody-dependent enhancement of viral entrance to host cells [32] .
As discussed above, the corruption of hem metabolism may be one of the causes of high serum free iron levels and may contribute to inflammation [8] . Recently, iron-mediated cell death, known as ferroptosis, was reported to play a role in pathogenesis miscellaneous diseases [35, 36] . The role of ferroptosis in COVID-19 pathogenesis and its place as a treatment target should be investigated.
Taken together, viral escape mechanisms to avoid anti-viral immunity, together with genetic or acquired defects in host defense, may impair viral clearance, resulting in MAS and inappropriate immune activation, causing ARDS and multiorgan failure. Why disease course is variable ranging from asymptomatic to lethal may be explained by genetic and host factors [37] . This may also explain why the number of deaths may be high in some families. Given that genetic factors also play a role in primary HLH/MAS cases, a meta-analysis was performed to analyze both the countries where HLH/MAS cases are frequently reported and where the frequency of severe and lethal COVID-19 infections are high [38] . Interestingly, geographical distributions were found to be similar. Genetic mutations causing a tendency for primary HLH may constitute a risk factor for severe disease course in COVID-19. Just the opposite, familial Mediterranean fever (FMF)-associated genetic mutations may be speculated to confer milder disease course, based upon the historical hypothesis claiming that such mutations may confer resistance to some viral and bacterial pathogens. Indeed, lower death ratios in COVID-19 infections reported from Turkey and Israel may support this speculation (based on https:// covid19.who.int/accessed in 25.04.2020). Interestingly, MAS occurrence is not frequent in FMF despite being an autoinflammatory disease [39] .
Besides anti-viral agents, treatment of immunologic complications including cytokine storm using appropriate immunosuppressive and immunomodulatory drugs is essential [40, 41] . Currently, there is no specific anti-viral agent or vaccine available for COVID-19. However, there are many drugs, most of which are familiar to rheumatologists, which are used based on their pharmacological properties. Corticosteroids (CS), chloroquine (CQ), hydroxychloroquine (HCQ), IL-6R antagonists including tocilizumab (TCZ), IL-1 antagonists including anakinra, TNF inhibitors, and Janus kinase inhibitors are among those agents used for this purpose [5, 9] , On the other hand, non-steroidal anti-inflammatory agents, especially ibuprofen, are not recommended in the treatment of COVID-19 infection because of the observations that they may exacerbate the symptoms by increasing the ACE-2 expression [42] .
These two antimalarial agents are commonly used in rheumatology practice for treating patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and Sjögren's syndrome, based upon their immunomodulatory effects. Besides anti-malarial effects, CQ and HCQ have been reported to have anti-viral activity against many viruses such as dengue, Ebola, SARS, and H5N1 in the past. Recently, they were reported also to be useful for COVID-19 and were included in the guidelines of many countries including China and Italy [43] [44] [45] [46] [47] [48] [49] .
CQ and HCQ accumulate in lysosomes and raise the pH level of the endosome, which may interfere with virus entry and/or exit from host cells [48] . Besides, these two agents may interfere with the ACE-2 receptors, which SARS-CoV-2 upregulate their expression and enter the cell by binding to these receptors. CQ and HCQ may reduce glycosylation of ACE-2 receptors, thereby preventing SARS-CoV-2 from effectively binding to host cells [48, 49] . Recently, Wenzhonget al. claimed that antimalarials might block the binding of the SARS Cov-2 virus to porphyrins and thus prevent the entering of the virus to the cell [8] . Finally, they might block the production of pro-inflammatory cytokines including IL-6, thereby blocking the pathway that subsequently leads to ARDS. Whatever the mechanisms are, multicenter studies performed in China reported beneficial effects of these agents among patients with COVID-19 [49] . Although there are some opposite reports, it seems that CQ and HCQ will remain as main drugs for COVID-19.
One may wonder whether rheumatology patients already receiving HCQ may be protected from COVID-19 infections. Recently, 22 patients with rheumatic diseases and receiving HCQ treatment were reported to have COVID-19 infection and one of them died. Although the results of this study have not been reported yet, it seems that prophylactic treatment with HCQ may not prevent COVID-19 infection (Twitter trial) (https://twitter.com/rheum_covid). We also observed that some of our patients developed COVID-19 while receiving HCQ. But rheumatic patients frequently have co-morbidities and use many other drugs as well. Also, the usual daily dose of HCQ is 200 mg, which is below the recommended dose for COVID-19. Therefore, we do not recommend prophylactic use of HCQ to prevent COVID-19 infection.
COVID-19 may enter inside the cell by endocytosis and invade the cell. AP2-associated protein kinase I (AAK1) is a member of the numb-associated kinase (NAK) family, which serves as a clathrin-mediated endocytosis regulator, and AAK1 inhibitors may prevent viral entry into the cell [40, 50] . Baricitinib is an inhibitor of the JAK-STAT pathway, which is used for suppressing proinflammatory cytokine production and systemic inflammation in RA. Baricitinib is also a NAK inhibitor, with a particularly high affinity for AAK [40, 51] . Based upon this basic data, Stebbing J et al. suggested that baricitinib2-4 mg daily may be combined with antiviral treatment in severe COVID-19 infections [40] ; however, inhibition of IFN production as a result of concomitant JAK-STAT pathway blockage may cause impairment of anti-viral immunity [52] . On the other hand, tofacitinib cannot inhibit AAK1 and is not recommended for this purpose [40] . The tendency for general infections and the possibility of diverticulitis are other disadvantages of JAK inhibitors [50] .
As mentioned above SARS and COVID-19 infections may cause MAS and cytokine storm. T lymphocytes are hyperactivated, and there is an enormous amount of proinflammatory cytokines including IL-6 and IL-1, which contribute to vascular permeability, plasma leakage, and DIC, thereby causing pulmonary damage and ARDS, as well as multi-organ failure [22] . Cytokine storm and related similar problems are also observed after the chimeric antigen receptor T cell (CAR-T) treatment [53] .
TCZ is a humanized anti-IL-6 receptor antibody, inhibiting IL-6. TCZ is currently used not only for therapy of RA, temporal arteritis, and many other autoimmune rheumatic diseases [54] but also for the treatment of the cytokine storm, which may be induced by CAR-T treatment [53] .
Based on these observations, TCZ treatment was also tried in patients with severe SARS-CoV-2 infection complicated with cytokine storm and ARDS. Retrospective studies from China reported the resolution of fever and hypoxemia and improvement in serum CRP levels and pulmonary CT findings [40, 41, [55] [56] [57] . Our own experience is also consistent with these reports. For the treatment of cytokine storm, the recommended TCZ dose is 8 mg/kg IV as single or divided two doses by 12-24 h intervals(maximum dose 800 mg). Tendency for general infections, hepatotoxicity, hypertriglyceridemia, and the possibility of diverticulitis are the main disadvantages of TCZ treatment [58] .
As mentioned above, IL-1 is another proinflammatory cytokine playing a dominant role in a cytokine storm, and SARS-CoV-2 may cause pyroptosis by IL-1β [5] . Anakinra is a recombinant IL-1R antagonist (rHIL-1Ra) and is the first IL-1 blocking biologic agent produced. Anakinra blocks the binding of both IL-1α and IL-1β to IL-1R, thereby inhibits the proinflammatory effects of IL-1 [59] . Anakinra was found to be beneficial in patients with severe sepsis without significant adverse effects based upon the data of phase 3 randomized clinical trial [60] . The recommended SC adult dose of anakinra ranges from 100 to 200 mg daily to 100 mg three times weekly; the pediatric dose is 1 mg/kg daily. The bioavailability of SC injections is 95%with a half-life of 4-6 h. In the presence of renal failure (GFR < 30 ml/min), it should be given in every 2 days. Hepatic disease does not require dose adjustment. Unlike TCZ, anakinra does not inhibit CRP synthesis directly; therefore, serum CRP levels can be used to follow up systemic acute phase response [59] . Another molecule produced for IL-blockage is canakinumab, which is a high affinity, fully humanized, monoclonal anti-IL-1β antibody with IgG1/κ isotype. Following SC injection of 150 mg, peak serum concentration is achieved in 7 days. The recommended dose interval is every 2 months [59] . The third molecule developed for IL-1 blockade is Rilonacept, which is a recombinant soluble IL-1 receptor. The half-life of rilonacept is 6.3-8.6 days. The recommended loading dose is 2.2 mg/kg, with the maximum dose of 160 mg; the maintenance dose is half of the loading dose weekly [61] . The use of canakinumab or rilonacept for severe COVID-19 infections has not been reported yet.
TNF-α is a key proinflammatory cytokine contributing to various acute and chronic inflammatory pathologies, including some autoimmune diseases and septic shock. Anti-TNF agents are commonly used for the treatment of rheumatoid arthritis, ankylosing spondylitis, and psoriatic arthritis. While serum TNF-α levels were moderately elevated in patients with SARS, much higher serum levels were observed in patients with COVID-19 infection, positively correlated with disease severity. Although anti-TNF treatment was suggested as a potential treatment for COVID-19, there is no sufficient data [40, 41] .
Systemic corticosteroid (CS) treatment is controversial in severe ARDS; nevertheless, many physicians use this treatment in patients with severe viral ARDS. Its use is not recommended for patients with COVID-19, based on the data from patients with H1N1, SARS, and MERS [5] . International guidelines recommend using moderate doses of systemic CS treatment for a short time, only when hemodynamic parameters are not improved following fluid replacement and vasopressor support [40, 41] . Current use of systemic corticosteroid treatment during COVID-19 infection is limited to patients having lethal complications related to cytokine storm such as ARDS, acute cardiac injury, renal failure, and to those patients with higher serum levels of D-Dimer. Since, there is no positive evidence coming from randomized clinical trials, WHO guideline dated March 13, 2020 does not recommend using systemic CS treatment for patients with COVID-19 routinely [62] . In our opinion, methylprednisolone 40 mg once daily for 4-5 days, in addition to TCZ treatment, may be helpful during cytokine storm and may also help to avoid rebound after TCZ.
IVIG contains the pooled polyclonal immunoglobulin G (IgG) supplied from the plasma of approximately a thousand or more healthy blood donors. In clinical practice, IVIG is used in patients with immune deficiencies for the treatment of infectious diseases, as well as in treatment-resistant patients with autoimmune diseases as an immunomodulatory agent. Previous favorable experience from patients with SARS and MERS suggested the use of a high dose of IVIG (0,3-0,5 g/kg) in patients with serious COVID-19 infection in the early phase of the disease [63, 64] . Anticoagulation and hydration should not be overlooked for increased tendency to thrombosis during IVIG treatment for COVID-19 patients.
Colchicine is an anti-inflammatory and immunomodulatory agent, commonly used for the treatment of gout, FMF, and Behçet's syndrome for a long time. Colchicine was suggested to be useful for the treatment of some complications of COVID-19 infection, based on its ability to inhibit IL-1 production [41] . COLCORONA (Colchicine Coronavirus SARS-CoV2) trial is a phase 3, multi-center, randomized, double-blind, placebo-controlled multicenter study to evaluate the efficacy and safety of colchicine in adult patients diagnosed with COVID-19 infection and have at least one highrisk criterion. Currently, the results of this study have not been reported yet (ClinicalTrials.gov Identifier: NCT04322682).
Many other drugs and interventions were also proposed for the treatment of COVID-19 and its complications. The use of low molecular weight heparin (LMWH) or unfractionated heparin, at doses indicated for prophylaxis of venous thromboembolism, strongly advised in all COVID-19 patients hospitalized. If patients have a contraindication for anticoagulation, they should be treated with lower limb compression [65] .
For the prevention and treatment of cytokine storm and possible lung fibrosis after COVID-19 pneumonia, mesenchymal stem cells (MSCs)-based immunomodulation treatment has been proposed as a suitable therapeutic approach. For this purpose, many studies are currently ongoing [66] . Leng et al. concluded that IV transplantation of MSCs was safe and effective in patients with COVID-19 pneumonia, especially for those in critically severe conditions [67] . However, currently, there are no approved MSC-based approaches for the prevention and/or treatment of COVID-19 patients, but the first results of clinical trials seem promising.
Immune plasma transfusion, which is a passive immunization way, is an old method used in the treatment of many infections. Experience with SARS-CoV infection showed that this treatment could work when given to the appropriate patient or even to family members caring for COVID-19 patients at home [68] . However, based upon the experience from SARS-CoV and MERS-CoV infections, there is a risk of antibody-mediated disease enhancement after hyperimmune globulin transfusion [69] .
In this short review, the relation between pandemic COVID-19 infection and its immunologic complication MAS was briefly debated. The mechanisms involved in cytokine storm development and why this complication occurs in some patients during COVID-19 infection were discussed and possible therapies reviewed. This study has some limitations. Firstly, the literature about COVID is changing at great speed and the Chinese literature could not be included in the manuscript. The lack of standard published studies and the differences in the treatment approaches between Chinese and Western sources (such as Chinese medicine) remained an obstacle for making correct recommendations.
Although SARS-CoV-2 infections may be asymptomatic or cause only mild symptoms in most of the cases, immunologic complications such as MAS and cytokine storm may occur in some cases. Impairment of SARS-CoV-2 clearance due to genetic and viral features, lower levels of interferons, increased neutrophil extracellular traps and NETosis, and increased pyroptosis create a background for such complications. The presence of genetic mutations causing a tendency for primary HLH may constitute a risk factor for severe disease course in COVID-19.
Once, immunologic complications like MAS/HLH occur, anti-viral treatment alone is not enough and should be combined with appropriate anti-inflammatory treatment. Early recognition and appropriate treatment of MAS and cytokine storm will decrease the morbidity and mortality in COVID-19 infection, which requires the collaboration of infectious disease, lung, and intensive care unit specialists with other experts such as immunologists, rheumatologists and, hematologists.
Author contributions As of April 11, 2020, data were started to be collected by Mehmet Soy and turned into article. The article reviewed by Gokhan Keser, Pamir Atagündüz, Fehmi Tabak, Isik Atagündüz, and Servet Kayhan and structured as last version. The data were carefully reviewed hematologically by Isik Atagündüz, and additional contributions were made to the article with literature recommendations. Data availability Resource scanning was done in Google Academic and Pubmed with appropriate keywords. Original data in all studies (including case reports and case series) that addressed the definition, causes, and classification of COVID-19 and hemophagocytosis, MAS, hemophagocytic lymphohistiocytosis, and cytokine storm, published in the English language in peer-reviewed journals, were included.
Code availability No code or software.
Ethics approval It is a review article we have no ethical approval and we declared that all procedures performed in presents study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Consent to participate All of the authors accepted last version of the article and signed the author's disclosure.
Consent for publication All of the authors accepted last version of the article for publication and signed the author's disclosure.
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The coronavirus disease 2019 (COVID- 19) pandemic represents an unprecedented global healthcare emergency with more than 20 million laboratory-confirmed cases and 730,000 deaths between February and July 2020. 1 The COVID-19 which is caused by the novel acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been the first time reported in Wuhan, China on December 31, 2019. 2 Since December 2019, the outbreak continues to spread exponentially worldwide due to the high virulence and prevalence of asymptomatic cases. 3, 4 By March 2020, COVID-19 has spread globally with more than 400,000 confirmed cases which prompted the World Health Organization (WHO) to declare the COVID-19 as a global pandemic. 5 As of August 10, 2020, COVID-19 has affected more than 227 countries and territories with more than 7 million active cases and the number is still exponentially rising. 1, 6 South Asia is one of the leading COVID-19 affected regions with more than 20 million (28.57 % of global cases) confirmed cases as of August 2020. India, Pakistan, and Bangladesh were the most COVID-19 affected countries in the South Asia region with 1695988, 278305, and 237661 confirmed cases, respectively. 6 Over the last few years, with availability and usage increased worldwide, the internet has become the main source of information particularly for healthcare-related concerns. 7, 8 With over 4.5 billion active internet users around the world, millions of people worldwide search online for health-related queries which make Web search queries a valuable source of public health infoveillance. 9, 10 Understanding about Web search trends can provide valuable information about public interest and awareness in health emergencies as a proxy for public health risk perception. 8, 11 Prior studies used internet search queries to model the outbreak of infectious disease (e.g., dengue, and influenza), track substance usages, and monitor public behavior. 12, 13 Subsequently, internet search queries also used to investigate public interest, health awareness, and mental health in the COVID-19 pandemic situation. [14] [15] [16] However, most of the studies so far focused on China, the United States, and other European countries. To our knowledge, there is no Infodemiology study till now have explored the association of web queries to the COVID-19 public internet and lawlessness in South Asian countries. With more than 880 million (18.87% of global users) internet users in South Asia, tracking Web search queries can be a real-time health informatics tool to strengthen the public health surveillance in health emergencies such as . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted August 26, 2020. . https://doi.org/10.1101/2020.08.24.20180943 doi: medRxiv preprint COVID-19 pandemic. 9, 10, 17 Therefore, this study explored the potential use of internet search trends for monitoring public interest and preventive health awareness towards COVID-19 infections in South Asia.
Daily data on confirmed COVID-19 cases were obtained from the data repository managed by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. 6 Data were retrieved for worldwide total new cases as well as for the following individual countries namely the United States (US), Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka from the 22nd January 2020 to 29th July 2020.
The Google Trends analytics platform was utilized to explore internet user search activities related to COVID-19 pandemic public interest and population health literacy. Google Trends is an online tracking system of internet hit search volumes, which enables the researchers to study trends and temporal patterns of the popular search queries. 18 Google trend determines the proportion of the searches for user specified terms among all web queries on the Google Search website and other affiliated Google sites for a given location and time. 19 Google trend then normalized the proportion by the highest query share of that term over the time-series and reports search interest as a unit of relative search volume (RSV) index. The retrieved RSV index values range from 0 to 100, with a value of 50 representing half the public interest as a value of 100. 20 This RSV indices have been used previously used to analyze public interest in various healthrelated issues as well as passive health surveillance and disease monitoring. 13, 14, 21 The search term "Coronavirus (Virus)" was used to retrieve Worldwide and nation-specific RSV indices in Google Trend as a representation of public interest on COVID-19 information. Also, a combination of the popular search phrases "hand wash", "face mask", "hand sanitizer", "face shield" and "gloves" were used to retrieve RSV indices as a surrogate of public interest on the practice of personal hygiene and other COVID-19 preventive measures.
Changes in temporal trend of public interest and number of COVID-19 cases were analyzed graphically for nation-specific major events and policy initiatives (e.g., first coronavirus cases,1000 cumulative deaths, nationwide lockdown). Temporal association in public interest in COVDI-19 and the number of new confirmed cases were analyzed using time-lag correlations measures. The lag correlation assesses whether the increases in GT data were correlated with the . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted August 26, 2020. . https://doi.org/10.1101/2020.08.24.20180943 doi: medRxiv preprint subsequent increase in COVID-19 cases and how far (days) the two series are offsets. 22 Pearson correlation coefficient was used to correlate between public interest and COVID-19 cases for a time lag between 30 and +30 days. Data of south Asian countries were also compared with the United States which was one of the most affected countries by the COVID-19 pandemic to investigate whether these searching terms objective for other communities or not. For the general worldwide interest and confirmed new case data, the period was set from January 22 to March 17, 2020, while for the countries it was set from February 15 to March 17. For the South Asian countries' time lag and correlation analysis, case data from February 22 to March 17 were used.
Each country's data was examined individually, and no direct comparison was made between countries in COVID-19 data or RSV index data. For each time frame, a new google trend dataset for was retrieved and matched with the official COVID-19 confirmed case data for further analysis. All the statistical analyses were performed using R studio and p value less than 0.05 was considered significant. IRB approval was not required because this study did not involve human subjects.
Worldwide public interest in coronavirus started to increase from January 22nd,2020 and reached its first peak on January 31, 2020, when WHO declared Covid-19 as a national healthcare emergency ( Figure 1 ). Then COVID-19-related worldwide searches remain low for some time and continuously increased after the word was spread on the outbreak in Wuhan, China. Worldwide COVID-19 related searches. COVID-19-related worldwide public interest continued to expand and reached a peak on March 16, 2020, as worldwide coronavirus cases and related death were reported and right after the WHO announcement to declare the coronavirus outbreak as a pandemic. Worldwide COVID-19 related searches remained steadily high for 1
week and again reached a peak on March 22, 2020, after the massive spread of coronavirus in Europe and the US. There are two small peaks, one sharp increase in numbers on February 12, 2020, when china adjusted coronavirus cases from confirmatory laboratory test and the other peak on April 12, 2020, due to cases around the globe. As of 29 July 2020, the daily number of confirmed coronavirus cases still increasing almost every day and has not reached its highest point yet.
. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted August 26, 2020. . https://doi.org/10.1101/2020.08.24.20180943 doi: medRxiv preprint
The number of reported confirmed COVID-19 cases in Bhutan, Afghanistan, Maldives, Nepal, and Sri Lanka were at a low level compared to other South Asian countries. India, Pakistan, and Bangladesh were the most COVID-19 affected three South Asian countries that overtook China in terms of the number of coronavirus cases. The COVID-19 related searches in India, Pakistan, and Bangladesh researched its initial peak right after the 1st confirmed case reported in the respective country. After the first peak, public interest in COVID-19 related information increased rapidly after the dissemination of confirmed cases in mainland China and Europe.
Public searches about the coronavirus in these countries reached its second major peak right after Table 1 ). Close monitoring and continued evolution of enhanced communication strategies are urgently needed to provide general populations and vulnerable populations with actionable information for self-protection and clear guidance during an outbreak. 24 The application of electronic medium, specifically the internet data in health care research, known as infodemiology, is a promising new field that provides unmatched opportunities for the management of health information generated by the end-users. 10 Using this unique potential, previous researchers were able to correlate the internet searches with traditional surveillance data and can even predict the outbreak of infectious disease several days or weeks earlier. 11, 13 Recent COVID-19 related infodemiology studies modeled daily laboratory-confirmed / suspected cases and associated death with internet search queries in the US, China, Iran and several European countries. [16] [17] [18] [19] 23, 25 Also, the regression/ machine learning model using the Google search queries moderately predicted the incidence of COVID-19 in Iran. Similar attempts were subsequently made to predict the previous coronavirus related outbreaks (e.g., SARS, MERS) and other infectious diseases (e.g., Zika, dengue). 11, 13, 26 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted August 26, 2020. . https://doi.org/10.1101/2020.08.24.20180943 doi: medRxiv preprint Despite the studies above, there is still a lack of research on this theme in South Asia and so fur there is no similar COVID-19 infodemiology study in the countries of this region. According to WHO, South Asia is considered highly vulnerable to any large-scale outbreak of an infectious disease being one of the most populous word region. 27 Therefore, the use of infodemiology particularly internet searches provides unique opportunities to monitor real-time public interest and awareness, particularly in countries with a lack of diagnostic and surveillance capacity, and thereby disseminate evidence-based health information to the people. 28 In South Asia, the first imported coronavirus case was reported in Nepal on 23 January 2020. 6 Starting from the March 2020 number of coronavirus cases started to increase rapidly in South Asian countries except for Bhutan (Supplemental Table 1 which is likely to be related to the number of local cases and lower virulence to COVID-19. As of the 15th March 2020, the number of patients confirmed with COVID-19 in Bangladesh (05 cases) was lower than in India (110 cases), and Pakistan (31 cases). 6 After the peaks within twothree weeks, internet searches continued to decline declined due to massive dissemination of information reported on the local/national news reporting, video news reporting, and health expert reporting in social media. 16,17 These findings suggest that internet searches can potentially help governments to define proper timing of risk communication, improve the public's vigilance, and strengthen the publicity of precautionary measures when facing any public health emergencies like This study has some limitations that should be acknowledged. First, this study used single search engines, Google, to retrieve population interest data form the South Asian Countries. Thus, there might be selection bias since people who use other search engines are not included in this investigation. However, since more than 880 million people in South Asia use the internet and . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted August 26, 2020. . https://doi.org/10.1101/2020.08.24.20180943 doi: medRxiv preprint google as the major search engine (more than 98% market share), google search queries can be a strong tool to estimate public interest. 9, 33 Second, Google trend do not report search query result the form of a relative search value instead of absolute search volumes which might have limited more in-depth and precise investigations. In addition, the Google trend excludes all the search results with any typographical error in the query terms. Third, although the number of studies based on google trend is increasing, Google does not provide the detailed information about the procedures by which they generate search data, and the study population responsible for the searches remain unclear. 13 Finally, search volumes can be influenced by the dissemination of information through the news media and it is still unclear whether changes in online activity translate to changes in health behavior. This requires caution when analyzing results and making interpretations from the analyses.
This work did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted August 26, 2020. . . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted August 26, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted August 26, 2020. . https://doi.org/10.1101/2020.08.24.20180943 doi: medRxiv preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted August 26, 2020. . https://doi.org/10.1101/2020.08.24.20180943 doi: medRxiv preprint CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted August 26, 2020. . https://doi.org/10.1101/2020.08.24.20180943 doi: medRxiv preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted August 26, 2020. . https://doi.org/10.1101/2020.08.24.20180943 doi: medRxiv preprint . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted August 26, 2020. . https://doi.org/10.1101/2020.08.24.20180943 doi: medRxiv preprint
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In December 2019, some unexplained pneumonia cases started to be found in Wuhan, Hubei Province, China. The pathogen was quickly clarified by China researchers as the positive-sense single-stranded RNA coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]), belonging to the same family as of severe acute respiratory syndrome coronavirus (SARS-CoV) and middle east respiratory syndrome coronavirus (MERS-CoV). 1 And homology studies showed that SARS-CoV-2 had nearly 80% homology with SARS-CoV and 50% identity with MERS-CoV, whereas 96.3% identity with a bat's coronavirus. 2, 3 Disease caused by the novel coronavirus was later named as coronavirus disease 2019 (COVID-19) by the World Health Organization (WHO). COVID-19 spread rapidly and has brought about a pandemic with more than 4.0 million laboratory confirmed cases until 11 May 2020 (https: //covid19.who.int).
COVID-19 diagnosis requires to be confirmed by SARS-CoV-2 nucleic acid detection via RT-PCR (Reverse Transcription-Polymerase Chain Reaction) according to WHO COVID-19 guideline. 4 However, nucleic acid detection of SARS-CoV-2 has obvious limitations in practice. 5 Further researches indicated that the COVID-19-infected patients would also produce specific antibodies by immune response, 6, 7 which was similar to those with SARS-CoV infection. Based on it, the detection of IgM/IgG in blood became an optional approach to improve the diagnosis, especially for the COVID-19 patient with negative nucleic acid test result. 8 For this reason, we designed and developed SARS-CoV-2 antibody test reagents. The kit can be performed in the site and took at most 15 minutes to obtain results with only one drop of blood sample, which is more convenient for large population screening and site inspection than nucleic acid test. 9 Although a large number of antibody detection reagent kits were developed, evidence in terms of the clinical application value was still lacking. 10 In order to be more beneficial to improve the diagnosis timeliness and accuracy of COVID-19, we supported following evidence to promote its clinical utility.
We first designed and manufactured all contents of the test cassette of SARS-CoV-2 rapid test kit.
1. The contents of the rapid test kit for blood lgM/IgG antibody were designed to include sample soleplate, reaction soleplate, test line (T), control line (C), suction filter paper, and plastic cassette ( Figure 1A ). Colloidal gold-labeled mouse-antihuman IgM/IgG antibody was on the reaction soleplate, the test line was on the NC membrane and covered by recombinant SARS-CoV-2 antigen, and the control line, used for quality control, was covered by goat-antimouse IgM/IgG antibody. 2. Colloidal gold-labeled mouse-antihuman lgM/lgG antibody was manufactured by SAIYA Hebei Biotechnol- ogy Co., Ltd. To obtain the well-performance antibody, the antibody was selected for functional test including the positive and negative coincidence rates, minimum test threshold, and accelerated stability. First, the positive and negative coincidence rates were tested. The test line and control line were covered by 1 mg/mL recombinant SARS-CoV-2 antigen and 0.5 mg/mL goatantimouse lgM/lgG antibody, respectively. Colloidal gold-labeled mouse-antihuman lgM/lgG antibody from four different batches were spread on the reaction soleplate for testing by positive reference (P1-P3) and negative reference (N1-N6). Colloidal gold-labeled mouseantihuman lgM/lgG antibody evaluated the positive and negative coincidence rates, with samples M1, M3, and M4 showing good coincidence rate in both positive and negative references and selected for further testing (Table S1) . Second, minimum test threshold references with dilution of 1:2, 1:6, and 1:18 were used, and M1/M3 fulfilled the requirement of minimum threshold test (Table S2 ). The test cassettes with M1 and M3 colloidal gold-labeled mouse-antihuman lgM/lgG antibody were further tested for the accelerated stability. The test cassettes were kept under dry and closed condition with 37 • C temperature for 21 days and tested by using threshold references (Table S3) . Finally, the result indicated that M3 fills the requirement. 3. The recombinant SARS-CoV-2 antigen was produced according to the procedure. 8 The recombinant protein was sent to Beijing Jorferin Bio-Technology Co. Ltd. for further process. To obtain the optimized antigen, strict functional selection steps including the positive and negative coincidence rated, minimum test threshold, and accelerated stability test were carried out. The expressed recombined SARS-CoV-2 protein was verified via protein electrophoresis ( Figure 1B ), demonstrating the same molecular weight as that of predicted size around 30 kDa in the reducing condition. And the reactogenicity of the recombinant antigen was further checked by ELISA using biotin-labeled anti-SARS-CoV-2 antibodies. It was observed that the recombined SARS-CoV-2 antigen bound well with both anti-SARS-CoV-2 antibodies in varied concentration, indicating that the quality of the recombined SARS-CoV-2 antigen was viable ( Figure 1C ). Subsequently, to select the high-performance recombinant SARS-CoV-2 antigen, different batches of recombinant SARS-CoV-2 antigen were tested by using positive (P1-P3) and negative (N1-N5) references with a concentration of 1 mg/mL (Table S4) . Two samples (R1 and R2) out of three obtained 100% positive and negative coincidence rates and were brought to the minimum test threshold inspection with the threshold references in the dilution of 1:2, 1:6, and 1:18. Ultimately, R1 sample obtained 100% positive coincidence rate with 1:2 and 1:6 dilution references and was selected as the final recombinant SARS-CoV-2 antigen (Table S5 ).
4. The nitrocellulose membrane control line was covered by goat-antimouse lgM/lgG antibody, manufactured by Beijing Jorferin Bio-Technology Co. Ltd. Colloidal gold-labeled mouse-antihuman lgM/lgG antibody covering the control line was also assessed at different concentrations from 5 to 0 mg/mL in a descending order with the same concentration (0.5 µM) of recombinant SARS-CoV-2 antigen. We found that as the concentration of the solution gradually decreased, the result turned from positive to negative and finally sample G2 demonstrated better performance than G1 (Table S6 ). 5. Specimen diluent contained 2.0% trehalose, 2.0% bovine serum albumin, 0.2% ethylenediaminetetraacetic acid disodium, 0.9% sodium chloride, 0.2% proclin 300, and 1.15% 0.5 M pH 7.2 tris buffer.
Furthermore, RT-PCR assay, 8 colloidal gold immunochromatography assay, 8 . It was observed that there was no cross reaction between SARS-CoV-2 and other common respiratory viruses ( Figure 1E ). In the previous studies, IgM was described as the earliest antibody produced after viral infection, whereas IgG was produced in the recovery phase of viral infection and lasted for several months or years. 11 Positive IgM antibody usually indicated an acute phase of viral infection, whereas positive IgG antibody suggested late or previous infection. Due to only around 50% positive rate of SARS-CoV-2 nucleic acid test 8, 12 under various condition of sample collection and storage, viral infection regions, RNA extraction methods, the quality of nucleic acid detection kit, and so on, 13 detection of IgM/IgG became a powerful approach for the early diagnosis of COVID-19 and could help identify the patients with negative nucleic acid but with obvious clinical symptoms. 8, 14 In addition, detection of IgM/IgG can also provide the time course information of viral infection 12 5 We also reexamined 37 COVID-19 convalescent patients and found that two patients' nucleic acid test was still positive with one of them IgM + /IgG + and the other IgM − /IgG − . In the other published studies, the positive nucleic acid test of COVID-19 convalescent patients was also reported. 22, 23 Therefore, antibody detection could assist to screen COVID-19infected patients accurately, combined with nucleic acid detection. 13 In sum, the SARS-CoV-2 antibody rapid detection kits we demonstrated has high sensitivity and specificity. The reported data suggested that it could be a good prospect for wide application in individual serological qualitative monitoring and might play a valuable role in practical applications for the diagnosis and epidemic control of COVID-19, with the development of the big database of epidemic investigation for SARS-CoV-2 IgM/IgG antibody ( Figure 1F ).
The authors declare no conflict of interest.
HL, ZL, YH, and YQ collected, analyzed, and interpreted the data. HL, XW, and JG conceived and supervised the study. HL and FL wrote the manuscript. All authors read and approved the final manuscript.
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Astroviruses (AstVs) are non-enveloped, positive-sense, single-stranded RNA viruses belonging to the Astroviridae family. Currently, two genera: namely Mamastrovirus and Avastrovirus are distinguished within this family. The genus Mamastrovirus includes astrovirus species isolated from humans and a number of mammals. Isolates originated from avian species, such as turkey, chickens, ducks, and other birds are classified into the genus Avastrovirus 1, 2 . AstVs have been detected in humans and a variety of animal species, including nonhuman primates, other mammals and avian species [3] [4] [5] . Their genomes are 6.8-7.9 kb in length, consisting of a 5′untranslated region (UTR), three open reading frames (ORFs), a 3′-UTR and a poly (A) tail 6 . The high degree of genetic diversity among AstVs and their recombination potential signify their capacity to cause a broad spectrum of diseases in multiple host species 3, 7, 8 . Human classical AstVs are a frequent cause of acute gastroenteritis in young children and the elderly, occasionally with encephalitis 8 .
In poultry, AstV infections have been found to be associated with multiple diseases, such as poult enteritis mortality syndrome, runting-stunting syndrome of broilers, white chick syndrome, kidney and visceral gout in broilers and fatal hepatitis of ducklings, leading to substantial economic losses [9] [10] [11] [12] [13] [14] [15] [16] . Increasing evidence indicates that there is a high degree of cross species transmission of AstVs between domestic birds, and even the potential to infect humans 17 . By comparison, fewer AstV infection cases have been described in domestic goose flocks. Bidin et al. 18 reported the detection of avian nephritis virus infection in Croatian goose flocks and provided evidence that this AstV was associated with stunting and prehatching mortality of goose embryos. Studies to detect AstV genomes from the clinical samples of geese suggested that these viruses might distribute widely among goose flocks, as seen in other poultry flocks 19, 20 . In February 2017, an outbreak of disease was reported in a goose farm in Weifang, Shandong Province, China. Affected flocks (containing 2000-3000 goslings) experienced continuous mortality rates ranging from 20 to 30% during the first 2 weeks of the outbreak despite antibiotic and supportive treatment. We conducted a systematic investigation to identify the causative agent of this disease and report here the isolation and characterization of a genetically distinct avian AstV. The pathogenicity of this virus was evaluated by experimental infection of goslings.
In the field, affected goslings displayed signs of depression and were observed sitting alone (Fig. 1a) . The palpebra tertia of some of the goslings showed an obvious gray-white cloudy appearance (Fig. 1b) . Death occurred from when the goslings were 5-6 days old, and peaked at 12-13 days old; then the mortality rate decreased gradually to the end of the third week. A common feature at postmortem was visceral urate deposition on the serous surfaces of the heart, liver and kidney (Fig. 1c, d) . Distended bile sacs with abundant urate particles were also observed (Fig. 1e) .
Virulent bacteria were not isolated and tissue samples were negative by PCR for goose parvovirus, goose hemorrhagic polyomavirus, reovirus, or Tembusu virus. However, a DNA fragment was amplified from the RNA sample extracted from the pooled spleen, liver and kidney tissues using pan-AstV RT-PCR targeting the AstV RNAdependent RNA polymerase (RdRp) gene 21 . Sequence and phylogenetic analysis of the amplified RdRp gene with other known AstV sequences retrieved in the GenBank database showed that the detected virus could be assigned to the subgroup 1.2 within the avastrovius group 1, with the closest relationship to the astrovirus detected from dropping samples of northern shovelers (Anas clypeata) in Hong Kong (Fig. 2) 22 . However, the nucleotide sequence of the RdRp gene had ≤67.5% similarity to the sequences of other astroviruses within avastrovirus group 1, suggesting that the virus was genetically distinct from known avastroviruses. Therefore, the isolation of AstV was initiated by inoculating tissue samples into goose embryos. For the first inoculation, significant thickening of the embryo's chorioallantoic membrane was noted although no death occurred by 5 days post inoculation (dpi). The subsequent passage of the isolate caused 60-100% mortality of the embryos by 5 dpi. The dead embryos exhibited severe subcutaneous edema and hemorrhages with necrotic foci in the liver (Fig. 3 ). Using the gene specific RT-PCR, the AstV was consistently detected in the allantoic fluids. Quantal assays showed that the infectious virus titers of the embryo allantoic fluid increased from 5 × 10 4 ELD 50 /ml for the fourth passage to 5 × 10 5.5 ELD 50 /ml for the 9 th passage, indicating that the isolates adapted to the goose embryo culture system. Therefore, the isolate was designated AAstV/Goose/ CHN/2017/SD01 (SD01 hereafter) as proposed by Martella et al. 23 .
The complete genome of the SD01 was identified by sequencing of the RT-PCR products and was submitted to the GenBank database under accession number MF772821. The genome was 7175 nucleotides (nt) in length with similar gene organization to other known avastroviruses, consisting of a 5′-UTR of 10 nt, three sequential ORFs (ORF1a, ORF1b and ORF2), a 3′-UTR of 236 nt and a poly (A) tail stretching 30 nt (Fig. 4a) . ORF1a of the isolate was 3255 nt long, encoding a polypeptide of 1084 amino acids (aa) with 27.9-59.5% identity to corresponding regions of other known avian AstVs as determined by BLAST analysis ( Table 1 ). The predicted nonstructural protein contained a trypsin-like peptidase domain as revealed by Pfam analysis with a serine protease motif at position 672 (GNSG), a nuclear localization signal motif at position 773 (KKKGKTK), and four predicted transmembrane domains. As is the case with other known avian AstVs, there was an overlapping region between ORF1a and ORF1b (3247-3265 nt), which contains the highly conserved ribosome frameshift sequence (5′-AAAAAAC-3′) and a downstream hairpin structure (3270-3295 nt) as predicted by RNA folding analysis. ORF1b was 1560 nt long and was predicted to encode a RNA-dependent RNA polymerase. There was an 18 nt spacer between the stop codon of ORF1b and the start codon of ORF2. ORF2 was 2133 nt long encoding a capsid protein of 704 aa. A stem-loop-II-like (s2m) motif consisting of 43 nt was revealed adjacent to 10 nt of ORF2 in the 3′-UTR by Rfam analysis.
To determine the potential genetic mutation(s) that might occur during the goose embryo passage, the initial virus genome was sequenced using the total RNA extracted from the clinical case tissue homogenate. Nucleotide differences between the initial virus genome and that of the fourth embryo-passaged isolate was shown in Table S1 . A single-mutation exhibited in the ORF2 gene of the adapted isolate, leading to the amino acid change from R 225 to Q 225 . The potential effect of the mutation on the virus adaptation need to be further evaluated.
The complete genome sequence of AstV SD01 had the highest similarity to those of turkey AstV 2 (TAstV-2) strains, at the level of 61.6-62.4% (representative TAstV-2 VA/99 in Table 1 ). The next was the duck astrovirus-2 (DAstV-2) SL5, with 60.3% nucleotide identity. Phylogenetic analysis of the full-length sequences showed that the SD01 formed a sister clade neighboring DAstV-2 and TAstV-2 in the avastrovirus genogroup II (Fig. 4b) . Further analysis with the complete amino acid sequence of RdRp (Fig. 4c ) and the capsid protein ( Fig. 4d ) revealed close alignment and closely matched phylogenetic trees.
The pairwise comparison of nucleotide and amino acid identities of the three ORFs among the representative avastrovirus isolates was shown in Table 1 . Based on the available complete sequences of avian AstV strains, the amino acid of ORF1a, ORF1b, and ORF2 of SD01 shared the highest identities of 59.0-59.9%, 68.3-68.7%, and (Table S2 ). According to the species demarcation criteria in the genus avastroviruses (p-dist range between genotypes range between 0.576 and 0.741), the SD01 was grouped within the genotype consisting of TAstV-2, TAstV-3, and DAstV-1 2 . However, the p-dist values between TAstV-2, TAstV-3, and DAstV-1 included in this genotype was much lower, ranging between 0.162 and 0.293 (Table S2 ). These results suggested that SD01 has a higher variability than those previously detected avastroviruses in the genotype.
Seven out of the 13 infected goslings displayed signs of depression from 3 to 8 dpi. One bird died at 4, 5, and 6 dpi, respectively, resulting in a mortality rate of 23% (3/ 13) during the experimental period. At necropsy, slight to moderately swollen kidneys were noted for the deceased birds (Fig. 5a) . Histologic examination revealed degeneration and necrosis of the epithelial cells of the tubules of the kidneys (Fig. 5c ). Neuronophagia and microgliosis was detected in the cortex of the cerebrum and the dying neuron was surrounded by satellite microglia (Fig. 5e) . Following embryo inoculation, the inoculated virus was re-isolated from the liver and kidney tissues and confirmed by RT-PCR.
Infected goslings exhibited signs of depression from 3 dpi and this symptom persisted for 3-4 days. One bird died at 5 dpi and severe urate deposition, similar to that seen in the field cases, was evident on the surface of the heart, liver, and kidney (Fig. 5b) . For the three infected goslings killed at 5 dpi, no evident gross lesion was noted in the visceral organs at postmortem. However, histologic examination revealed the presence of an eosinophilic proteinaceous substance in the renal tubules, and mild interstitial lymphocyte infiltration was noted in sample of two goslings (2/3) (Fig. S1 ). AstV RNA were detected in the collected tissues of three goslings (Fig. S2) , indicating that the isolate has a wide tissue tropism after infection. All tissues from the uninfected birds were normal.
When the samples were tested by RT-PCR for virus shedding evaluation, the AAstV specific RNA was sequentially detected from the cloacal swabs of infected goslings from 2 to 12 dpi (Fig. 6 ). Viral RNA could still be detected in the liver and spleen when the infected birds were killed at 15 dpi. Neither viral shedding nor positivity in the tissue samples was detected in the uninfected control goslings during the experiment. Infected goslings showed decreased body weight gain and the average body weight of infected birds was statistically significantly lower than that in the uninfected group from 6 dpi to the end of the experiment (Fig. 7) . The average body weight in the infected group was 322 ± 73 g versus 370 ± 15 g in the control group at 6 dpi, and 625 ± 180 g versus 878 ± 48 g at 14 dpi, respectively.
Orally inoculation of goslings with the isolate resulted in depression of 4 birds from 5 to 8 dpi. One gosling died at 7 dpi with evident urate deposition on the surfaces of heart and liver at necropsy. Another severely ill bird was killed humanely at 8 dpi for animal welfare reasons. Viral RNA was detected by RT-PCR in the cloacal swabs from 4 dpi (Fig. S3) and growth depression was noticed in this group (Fig. S5) . For the goslings infected by intranasal inoculation, no death occurred in the group, but virus shedding and growth depress was observed (Fig. S4 & S5) . These results indicated that the isolate might infect goslings via oral and nasal routes, further demonstrating the infectivity of the isolate.
Several studies have reported the existence of AstV in goose flocks 18, 19 , but the prevalence and pathogenicity of AstV among domestic geese remains poorly understood due to the lack of efficient in vitro culture techniques and diagnostic assays. In this study, AAstV SD01 was AstV infection occurred within the first days or week of life usually resulted in a worse outcome, as the agedependent pathogenicity of AAstV has been reported 10 . In this study, the mortality of young goslings caused by subcutaneous or oral inoculation indicated that AAstV SD01 was highly pathogenic. The experiment was fairly a represent of the situation in the field, where susceptible goslings are exposed to AstV soon after they are placed in contaminated houses. Apart from mortality, avian AstV infection can decrease feed intake and alter feed conversion efficiency, leading to growth repression. The decrease in body weight of infected goslings is a major concern as a 29% lighter body weight at 14 dpi has a considerable economic impact.
Histologic examination revealed the presence of a proteinaceous substance in the renal tubules, indicating that AAstV SD01 infection caused increased permeability of the kidney epithelia barrier. Degeneration and necrosis of tubular epithelial cells found in the deceased goslings provided further evidence of kidney function damage. These results could explain the development of visceral urate deposition in infected goslings. Increased epithelium permeability due to AstV infection has been reported in both human and avian species 24, 25 . Extra-intestinal infection with nephritis has been reported in birds infected with chicken astrovirus and avian nephritis virus 16, 26 . Viral RNA was found in all of the tissues sampled from the infected goslings killed on 5 dpi, indicating that the goose AstV has a wide tissue tropism and spread systemically after inoculation. Virus shedding was detected by RT-PCR and persisted in the infected goslings for about 12 days, further indicating that the virus replicated efficiently in vivo.
It is interesting that encephalitis lesions were observed in the deceased goslings (data not shown), along with the detection of AAstV SD01 RNA in the brain tissue (Fig. S2) . However, no neurological symptoms were noted in either the field cases or the experimentally infected goslings. The neurologic infection of AAstV SD01 is worthy of further investigation since there are numerous reported cases of AstV-associated encephalitis and meningitis in humans and mammals 9, 27 . Nonetheless, based on the limited number of goslings infected in present study, it is not likely to get accurate evaluation for the virulence of the isolate.
The present work describes the isolation of the astrovirus AAstV/Goose/CHN/2017/SD01 from tissue samples of goslings dying from a disease characterized by visceral urate deposition. The successful reproduction of the disease by experimental infection demonstrates the etiological role of this AAstV. Based on the genetic analysis of the complete capsid region at amino acid level, the isolate should be assigned as a member within the genotype consisting of TAstV-2 and DAstV-1 strains. The high variability of the genomic sequence to other known astroviruses suggest more detailed antigenic investigations should be performed.
For bacteriological diagnosis, liver, and kidney samples from dead goslings were first inoculated onto tryptic soy agar plates (BD Science, MD, USA) containing 2% fetal calf serum, and incubated at 37°C under an atmosphere with 5% CO 2 for 48 h. Then the spleen, liver, and kidney tissue were pooled and tested for the presence of goose parvovirus 28 , goose hemorrhagic polyomavirus 29 , AstV 21 , reovirus 30 , and Tembusu virus 31 , respectively.
To isolate AstV, the kidney, spleen, and liver samples were homogenized with sterile phosphate buffered saline (PBS, pH 7.4) to a 20% suspension (w/v) and centrifuged at 8000×g, at 4°C for 10 min. The supernatant was filtered using a syringe-driven filter unit with a pore size of 0.2 μm and the filtrate was inoculated into five 9-day-old goose embryos (0.2 ml/egg) via the chorioallantoic membrane route. Embryos were incubated at 37°C and candled daily. Embryos that died beyond 24 h and those that survived until 5 day after inoculation were chilled to 4°C overnight. The allantoic fluids were collected for a hemagglutination (HA) activity test performed by a standard method using 1% chicken red blood cells as an indicator, and then were subjected to additional passage in goose embryos.
To determine the infectious titers of the 4 th and 9 th passage, the virus suspension was 10-fold serially diluted with PBS and inoculated into 9-day-old goose embryos via the chorioallantoic membrane route. The embryos were incubated for 7 days at 37°C and the mean embryo lethal dose (ELD 50 ) of infectious virus was calculated using the Reed-Muench method 32 .
To sequence the complete genome of the isolate, total RNA was extracted from the goose embryo allantoic fluids of the fourth passage using a viral RNA kit (Omega, GA, USA) and the cDNA was synthesized using a Reverse Transcription System (Promega, WI, USA) with random primers following the manufacturer's instructions. Viral genomic fragments were amplified by PCR with primer sets designed against conserved regions of the AstV sequences retrieved from the GenBank database (Table 2) . PCR products were purified using Gel Extraction Kit (Omega, GA, USA) and ligated into pEASY-Blunt Simple Cloning Vector (TransGen Biotech, Beijing, China). The recombinant vector was transformed into competent Escherichia coli Trans-T1(TransGen Biotech, Beijing, China) and transformants containing the PCR amplified fragment were selected by PCR following the manufacturer's instruction. At least two representative transformants were subjected to bidirectional DNA sequencing using Applied Biosystems ABI3730 (Shanghai Meiji Biological Medicine Technology Co., Ltd. Shanghai, China). The 5′ and 3′ ends of the viral genome were amplified using the 5′/3′ RACE kit (Clontech, CA, USA) following the guidelines of the manufacturer. The initial complete genome was assembled and manually edited using the Software ContigExpress. Based on the initial genome sequence, additional primer pairs were designed (Table S3) , and PCR amplicons were sequenced to determine the genome.
To evaluate the potential adaptive mutation (s) of the virus that might occur during the process of goose embryo passage, we sequenced the complete genome of initial virus using the total RNA extracted from the clinical case tissue homogenate of kidney, spleen, and liver using the method described above. The genome sequence was compared with that of the isolate of fourth passage.
Nucleotide sequences of the virus genome and the deduced amino acids of the ORFs were compared with known AstV ORF sequences retrieved from the GenBank database. Neighbor-joining trees of the complete genome nucleotide sequences, ORF1b and ORF2 amino acid sequences were constructed using MEGA 7.0 software, with bootstrap values calculated from 1000 replicates. The mean amino acid genetic distance (p-dist) of the viral RdRp and capsid were calculated using MEGA 7.0 with a bootstrap test obtained from 100 replicates.
One-day-old goslings (Anser anser domesticus) were obtained from a local hatchery. Birds were raised in negative pressured isolators with ad libitum access to feed and water. Three experiments were conducted to investigate the pathogenicity of the isolate. Animal infection experiments were approved by the China Agricultural University Animal Ethics Committee. Gosling experiment 1
The aim of this experiment was to evaluate whether the isolate was pathogenic in goslings. Thirteen 2-day-old goslings were infected by subcutaneous inoculation with 0.5 ml of the virus suspension prepared from the infected goose embryos at the fourth passage (containing approximately 2.5 × 10 4 ELD 50 ). Goslings inoculated with sterile PBS (uninfected control) were kept in a separate isolator. Clinical signs and mortality were recorded for 10 days. Dead birds were necropsied immediately, and tissue samples of the heart, liver, spleen, kidney, lung, thymus, bursa, and brain were collected. A portion of these tissues were fixed in 10% neutral buffered formalin, embedded in paraffin, and 4-5μm sections were cut and stained with hematoxylin and eosin (H&E). Pieces of liver and kidney tissue were frozen and subjected to virus isolation.
This experiment was designed to investigate the in vivo replication of the virus and its impact on the growth of infected birds. Fourteen 5-day-old goslings were infected as in experiment 1. Birds inoculated with sterile PBS were used as the uninfected control. The tissue distribution of the virus was analyzed in three infected goslings 5 dpi. Representative tissues samples were collected and subjected to histopathological examination and virus RNA detection. For virus shedding detection, cloacal swabs were collected from both infected and control birds on 2, 4, 6, 8, 10, 12, and 14 dpi. Swabs were immersed in 1 ml of 1 × Dulbecco's modified Eagle's medium (Gibco, NY, USA) and frozen at −75°C. Simultaneously, individual birds were weighed. The difference between the mean body weights of infected and uninfected control birds was tested by Student's t-test. Significant differences were defined by P-values <0.05 (*), <0.01 (**).
To investigate the possible infection route, three groups of 1-day-old goslings were kept at separate isolator. Birds were inoculated orally (n = 6) or intranasally (n = 6) at 5day old with the astrovirus isolate at the dose as experiment 1. Five goslings were kept as uninfected control. Mortality were checked daily. Cloacal swabs were collected for virus shedding detection as described in experiment 2.
Tissue samples were prepared as a 10% suspension (w/ v) in PBS and were homogenized using beads in a highthroughput Tissuelyser (Nibo Scientz Biotechnology Co., Ltd., Zhejiang, China). Then, the homogenate was centrifuged at 8000×g for 5 min at 4°C and 150 μl of the supernatant was used for RNA extraction. Total RNA was extracted and converted to cDNA using the kits described above. PCR amplification was conducted using a set of specific primers (GAstVF7/GAstVR7, Table 2 ), targeting the ORF2 gene of the isolate. For virus shedding detection, swab samples were vortexed and centrifuged. After centrifugation, 150 μl of the supernatant was processed for RT-PCR detection in the same manner.
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. A 73-year-old woman was referred to our emergency department for the evaluation of a 10day history of fever, dry cough, and shortness of breath. Her medical history was unremarkable except for a previous diagnosis of breast cancer. She had no history of lung comorbidities, such as asthma, chronic obstructive pulmonary disease, or interstitial lung disease. On presentation, the patient exhibited significant breathlessness, and arterial blood gas analysis revealed a pH of 7.51, PCO2 of 29 mmHg, PO2 of 43 mmHg, and oxygen saturation of 81%. Based on these data, 15 L/min of oxygen was administered through a non-re-breathing reservoir mask. Chest radiography showed bilateral interstitial and alveolar infiltrates in both lungs, greater on the right side. On the same day, the patient underwent nasopharyngeal swab, which confirmed the clinical suspicion of coronavirus disease . The following day the patient was transferred to an intermediate care unit. During the first few days in the hospital, her oxygen saturation was 90-95% with use of the non-rebreathing oxygen mask. On day five post-hospitalization, the patient experienced a sudden deterioration of lung function. Laboratory parameters also showed a significant increase in D-dimer levels (5250 ng/mL; reference value, less than 232 ng/mL). Based on these data, contrast-enhanced computed tomography (CT) scan was performed. The contrast-enhanced CT images with mediastinal and lung window setting ( Figure 1 ) showed filling defects in some branches of the pulmonary artery (curved arrows) and bilateral ground-glass opacities (arrows) associated with areas of consolidation (asterisks). No evidence of pulmonary fibrosis was found in this initial CT examination.
To monitor parenchymal lung disease, serial chest radiographs with different time intervals were obtained. However, to evaluate the response of pulmonary vascular disease to anticoagulant therapy, a further contrast-enhanced CT scan was performed after one month (day 35 posthospitalization). The follow-up contrast-enhanced CT images with mediastinal and lung window setting ( Figure 2 ) showed significant regression of the pulmonary embolism and lung abnormalities (both consolidations and ground-glass opacities). However, initial signs of lung architectural distortion with some traction bronchiectasis (arrowheads) were observed.
A 73-year-old woman was referred to our emergency department for the evaluation of a 10-day history of fever, dry cough, and shortness of breath. Her medical history was unremarkable except for a previous diagnosis of breast cancer. She had no history of lung comorbidities, such as asthma, chronic obstructive pulmonary disease, or interstitial lung disease. On presentation, the patient exhibited significant breathlessness, and arterial blood gas analysis revealed a pH of 7.51, PCO 2 of 29 mmHg, PO 2 of 43 mmHg, and oxygen saturation of 81%. Based on these data, 15 L/min of oxygen was administered through a non-re-breathing reservoir mask. Chest radiography showed bilateral interstitial and alveolar infiltrates in both lungs, greater on the right side. On the same day, the patient underwent nasopharyngeal swab, which confirmed the clinical suspicion of coronavirus disease (COVID-19). The following day the patient was transferred to an intermediate care unit. During the first few days in the hospital, her oxygen saturation was 90-95% with use of the non-re-breathing oxygen mask. On day five post-hospitalization, the patient experienced a sudden deterioration of lung function. Laboratory parameters also showed a significant increase in D-dimer levels (5250 ng/mL; reference value, less than 232 ng/mL). Based on these data, contrast-enhanced computed tomography (CT) scan was performed. The contrast-enhanced CT images with mediastinal and lung window setting ( Figure 1 ) showed filling defects in some branches of the pulmonary artery (curved arrows) and bilateral ground-glass opacities (arrows) associated with areas of consolidation (asterisks). No evidence of pulmonary fibrosis was found in this initial CT examination.
Diagnostics 2020, 10, x FOR PEER REVIEW 2 of 5 Figure 1 . A 73-year-old woman was referred to our emergency department for the evaluation of a 10day history of fever, dry cough, and shortness of breath. Her medical history was unremarkable except for a previous diagnosis of breast cancer. She had no history of lung comorbidities, such as asthma, chronic obstructive pulmonary disease, or interstitial lung disease. On presentation, the patient exhibited significant breathlessness, and arterial blood gas analysis revealed a pH of 7.51, PCO2 of 29 mmHg, PO2 of 43 mmHg, and oxygen saturation of 81%. Based on these data, 15 L/min of oxygen was administered through a non-re-breathing reservoir mask. Chest radiography showed bilateral interstitial and alveolar infiltrates in both lungs, greater on the right side. On the same day, the patient underwent nasopharyngeal swab, which confirmed the clinical suspicion of coronavirus disease (COVID-19). The following day the patient was transferred to an intermediate care unit.
During the first few days in the hospital, her oxygen saturation was 90-95% with use of the non-rebreathing oxygen mask. On day five post-hospitalization, the patient experienced a sudden deterioration of lung function. Laboratory parameters also showed a significant increase in D-dimer levels (5250 ng/mL; reference value, less than 232 ng/mL). Based on these data, contrast-enhanced computed tomography (CT) scan was performed. The contrast-enhanced CT images with mediastinal and lung window setting ( Figure 1 ) showed filling defects in some branches of the pulmonary artery (curved arrows) and bilateral ground-glass opacities (arrows) associated with areas of consolidation (asterisks). No evidence of pulmonary fibrosis was found in this initial CT examination. The high-resolution CT images with lung window setting ( Figure 3 ) demonstrated the persistence of a diffuse increase in lung density with ground-glass appearance, associated with peripheral irregular reticular opacities (arrows) and several traction bronchiectasis (arrowheads). These findings were consistent with the diagnosis of pulmonary fibrosis. In addition, an unexpected left-sided spontaneous pneumothorax was noted (asterisks).
Subsequent serial chest radiographs showed a progressive reduction in the left-sided pneumothorax. Therefore, considering the reduction in the pneumothorax, chest drainage placement was not indicated by thoracic surgeons.
After 70 days of hospitalization, the patient was discharged and transferred to a rehabilitation center. During hospitalization, the patient was treated with noninvasive ventilation, lopinavir/ritonavir (day 1 to day 10), hydroxychloroquine (day 1 to day 10), empirical antibiotic therapy with azithromycin and ceftriaxone (day 1 to 14), paracetamol, and anticoagulant therapy.
With regard for the noninvasive ventilation, the patient underwent high-flow oxygen therapy with a non-re-breathing reservoir mask (from the day of admission until day 36 post-hospitalization), using a 60% Venturi mask (day 37 to day 63), and then with a nasal cannula (day 64 to discharge).
For the anticoagulant therapy, the patient underwent prophylaxis with low-molecular-weight heparin (from day 1 until day 4 post-hospitalization), therapeutic dose heparin (day 5 to day 47), and then rivaroxaban 20 mg (day 48 to discharge).
At the time of discharge, the patient had no fever but complained of dyspnea on exertion. The left-sided apical pneumothorax became minimal (4 mm thick), and the peripheral oxygen saturation was 95% with a nasal cannula at 2L/min. The blood pressure was 120/65 mmHg. The heart rate and respiratory rate were 99/min and 24/min, respectively.
The most dreaded thoracic complications in patients with COVID-19 pneumonia are acute pulmonary embolism and pulmonary fibrosis. Both the complications are associated with an Figure 3 . The subsequent bedside radiographic follow-up showed a trend toward gradual reduction in pulmonary opacities. On day 61 post-hospitalization, owing to persistent breathlessness and the need for high-flow oxygen therapy, an unenhanced high-resolution chest CT scan was performed. The high-resolution CT images with lung window setting (Figure 3 ) demonstrated the persistence of a diffuse increase in lung density with ground-glass appearance, associated with peripheral irregular reticular opacities (arrows) and several traction bronchiectasis (arrowheads). These findings were consistent with the diagnosis of pulmonary fibrosis. In addition, an unexpected left-sided spontaneous pneumothorax was noted (asterisks). Subsequent serial chest radiographs showed a progressive reduction in the left-sided pneumothorax. Therefore, considering the reduction in the pneumothorax, chest drainage placement was not indicated by thoracic surgeons.
After 70 days of hospitalization, the patient was discharged and transferred to a rehabilitation center. During hospitalization, the patient was treated with noninvasive ventilation, lopinavir/ritonavir (day 1 to day 10), hydroxychloroquine (day 1 to day 10), empirical antibiotic therapy with azithromycin and ceftriaxone (day 1 to 14), paracetamol, and anticoagulant therapy.
With regard for the noninvasive ventilation, the patient underwent high-flow oxygen therapy with a non-re-breathing reservoir mask (from the day of admission until day 36 post-hospitalization), using a 60% Venturi mask (day 37 to day 63), and then with a nasal cannula (day 64 to discharge).
For the anticoagulant therapy, the patient underwent prophylaxis with low-molecular-weight heparin (from day 1 until day 4 post-hospitalization), therapeutic dose heparin (day 5 to day 47), and then rivaroxaban 20 mg (day 48 to discharge).
At the time of discharge, the patient had no fever but complained of dyspnea on exertion. The left-sided apical pneumothorax became minimal (4 mm thick), and the peripheral oxygen saturation was 95% with a nasal cannula at 2L/min. The blood pressure was 120/65 mmHg. The heart rate and respiratory rate were 99/min and 24/min, respectively.
The most dreaded thoracic complications in patients with COVID-19 pneumonia are acute pulmonary embolism and pulmonary fibrosis. Both the complications are associated with an increased risk of morbidity and mortality. While acute pulmonary embolism is not a rare finding in patients with COVID-19 pneumonia [1, 2] , the prevalence of pulmonary fibrosis remains unclear [3] [4] [5] . During previous coronavirus outbreaks, pulmonary fibrosis was reported in up to one-third of patients [3] [4] [5] . Therefore, given the worldwide spread of COVID-19, a considerable number of cases with associated pulmonary fibrosis are expected.
Spontaneous pneumothorax is another possible complication in COVID-19 pneumonia, although its observation is rather uncommon [6] . Spontaneous pneumothorax is the most common type of pneumothorax. It may occur without any clear cause (primary) or due to underlying pulmonary disease (secondary), especially chronic lung disease [7, 8] .
Radiological imaging plays a crucial role in the management of patients with COVID-19 pneumonia. Although less sensitive than CT, chest radiography is an effective technique to quantify the severity and monitor the progression of COVID-19 pneumonia [9] [10] [11] [12] . Therefore, chest CT imaging should only be performed in patients with worsening respiratory symptoms or in selected cases (complex or doubtful cases).
In this paper, we have presented interesting CT images of the first case of COVID-19 pneumonia that initially developed acute pulmonary embolism ( Figure 1 ) and subsequently showed progression toward pulmonary fibrosis (Figures 2 and 3 ) and spontaneous pneumothorax ( Figure 3 ). While several articles have reported the association between COVID-19 pneumonia and acute pulmonary embolism [1, 2, [13] [14] [15] , only a few papers have described cases of pneumothorax secondary to COVID-19 [16] [17] [18] [19] , and none of them have reported its coexistence with pulmonary embolism. In addition, to the best of our knowledge, this report is the first to present unequivocal CT images of progression of COVID-19 pneumonia toward lung fibrosis. COVID-19-associated lung injury and its progression toward pulmonary fibrosis could be the main causative factor for spontaneous pneumothorax in our patient.
This case highlights the importance of considering thoracic complications when the clinical symptoms, respiratory functional parameters, or laboratory tests worsen or do not improve in COVID-19 pneumonia. In such cases, both radiologists and clinicians should be aware of the added value of CT in ruling out complications.
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The host response to a foreign substance is often a well orchestrated series of events designed to protect the individual from harm. Modern techniques help us elucidate the pathways and components of the host response. The immune system and its components are a mainstay of our protection against infections and malignancies. 4, 5 Inflammation is often an unpleasant side effect as the immune system contains and eradicates a microbe or foreign tissue. Specific arms of the immune system can be used as markers in favor or against the presence of an infection. The humoral or antibody response to an invading microbe is an example. Some of the antibodies that are produced have a protective effect with other parts of the immune-inflammatory system and are responsible for eradicating the infection. Other antibodies may not be as effective in this role. However, in their ability to recognize unique and specific structures of a microbe, they serve as beacons that a microbe was recently present or was present in the distant past. Substances such as antibiotics which can rapidly kill a microbe may modify the immune response by removing the infectious driving force for a full-scale response. In clinical medicine and veterinary medicine, measurement of the immune response helps the diagnostician decide what infection was present and how recently. In these situations the intention is to provide treatment. For other pieces of the puzzle, the forensic scientist may exploit parts of the immune response to discover who is likely a victim of an attack and who might be responsible. This chapter will discuss the basics of the host immune response that can have utility in the microbial forensic sense. Examples will provide a sense of what information is achievable and what is not likely to provide clues with a high degree of certainty.
In response to an encounter with a new microbe, the immune system first starts to activate the antibody system. Usually a cell known as a macrophage engulfs some of the microbes. It then presents part of the microbe to a helper T cell (a lymphocyte) which then directs other lymphocytes known as B cells to produce antibodies to that particular microbe and even more specifically to that part which was presented. It usually takes at least 4 days before any microbe-specific antibody can be found. 6 Antibodies are a specific form of the proteins known as immunoglobulins (Igs). IgM, IgG, and IgA are the principal classes of immunoglobulins with relevance to this chapter and will be discussed in more detail. Those individuals unfortunate to have allergies have problems due to IgE against allergens (such as ragweed, peanut, or cat dander). In this case the IgE molecules sit on the surface of cells that can release histamine when the offending allergen bridges 296 MICROBIAL FORENSICS HOST FACTORS two such molecules. In an infection, immunoglobulins usually appear in the order of IgM, IgG, and IgA. B cells first begin to produce IgM, and then some B cells undergo an irreversible switch to those that produce IgG. Later some of this population of cells undergo a switch to become IgA-secreting type B cells. Immunoglobulins persist for varying times; for example, the half-life of particular IgM antibodies is 5 days, while that of IgG can be as long as 21-23 days (Table 14. 1). 4, 6 Similar to a live microbe, vaccines can also provoke an antibody response. The vaccine can be composed of a live or attenuated microbe, a whole nonproliferating microbe, or an antigenic part of the microbe. Regardless, the intent of the vaccine is to produce protection, often by protective antibodies. Although the half-life of an individual IgG molecule is less than a month, a population of antibodies in the IgG isotype form may persist for life. Memory B cells can sustain these antibodies and retain the ability to quickly generate the appropriate antibodies when challenged. When the immune system encounters another infection or is subjected to a revaccination (booster), the result is an accelerated production of the particular antibody and increase in the levels that circulate in the blood. Figure 14 .1 illustrates this.
Perhaps the most discernible pattern of antibody response which has forensic value is the appearance of IgM first, followed by a B-cell switch to the longer lasting IgG. During the early phase of exposure, IgM can be seen first. As time goes on, IgG is seen and predominates, and IgM is no longer found. This is illustrated in Figure 14 .2.
The antibody response to a particular agent may be directed to different antigens at different times, that is, early or later after the initial exposure. That response may involve IgM at the early stage and IgG later. Late in the disease or during recovery, only IgG to particular antigens may be seen. A classic example is the human antibody response to Epstein Barr virus (EBV). 7 EBV is the virus known to cause mononucleosis. During acute early disease, it is common to find high levels of antibody of the IgM isotype to the viral early antigen (EA) and viral capsid antigen (VCA). It is rare to find IgG antibody to the VCA or Epstein Barr Nuclear Acid (EBNA) in anything but low titers. As the patient recovers from their first infection with EBV, it is rare to find anything but low levels of IgM to EA or VCA, but IgG to VCA in higher or increasing levels is common. Antibodies to EBNA are often very low during this stage. Then after clinical recovery, that is, several months later, IgM to EA and VCA stay at low levels whereas IgG to VCA and EBNA remain at high levels, often for years. Table 14 .3 illustrates this pattern by stage of the immune response to EBV and its particular antigens. Figure 14. 3 is a graphic display of this. For the clinician or epidemiologist this provides a framework to determine where in the infectious process a patient may be. Tables 14.2 A controlled experiment or normal clinical event illustrates what happens when the immune system sees the infectious agent or its vaccine representation again. The controlled experiment may be in a laboratory animal or a patient receiving a booster vaccine. The uncontrolled but normal clinical event occurs when the patient is exposed again to the infectious agent for whatever reason. Consider a generic antigen exposure. The first time the immune system sees Antigen X (AgX) it responds as shown in Figures 14.1 and 14. 2. At first any antibody to AgX is barely discernible; then the levels rise and later fall to a plateau. If a mixed infectious exposure were to occur with AgX and a new AgY from another microbe, the immune system would quickly mount a brisk and high level of Ab to AgX, while the course of Ab to AgY would be slow and delayed, just as was the first exposure to AgX. For AgX this is a phenomenon termed immunological memory or an amnestic response. This can be useful when the symptoms and signs of exposure to either X or Y are similar. This is the case with the early flu-like symptoms of pulmonary anthrax and the influenza virus itself.
Another example common to all of us is repetitive exposure to different strains of flu viruses. 4 As illustrated in Table 14 .4, a person infected for the first time with one strain of the influenza virus makes a response to most of its antigens (as a theoretical example, Ag 1, 2, 3, 4, 5, 6). Three years later, the same individual exposed to a partially similar influenza virus responds preferentially to those antigens that were also present on the original influenza virus. The person also makes a smaller initial antibody response to new antigens, that is, those not shared with the first virus. The initial response is minimal in comparison. Ten or 20 years later, during a new flu season and exposure to a third strain of influenza, the most brisk responses would be to antigens previously recognized by the immune system. This is the scientific basis for giving the flu vaccine, which contains a variety of possible antigens common to multiple strains of the flu virus so that a rapid and protective antibody response will occur.
Our knowledge of the humoral response to infection with biothreat microbes is limited compared to our knowledge of the kinetics and time response to common human infections. Nevertheless, in the appropriate context and with sufficient background information, detection of antibodies to a particular microbe and its antigens can have important value for microbial forensics. This information may have critical probative value or it can guide investigative leads. The absence of a specific antibody response may also have equal value in a particular investigation. Certainly its importance is increased in the context of knowledge of what organism may be involved, when the exposure was likely to have occurred, the route of exposure, what symptoms and signs are manifesting in the host, and other hard data points such as detection of antigens themselves, and detection of microbial DNA or RNA. 8 Other information such as how many hosts (people or animals) have had this infection in the geographic region, what is the normal infection rate, and background incidence of antibody titer due to the organism in question or a related organism, is also important. The 2001 anthrax letter attacks raised multiple questions for every person infected, possibly exposed, vaccinated, or treated. Some of these questions included how these persons were infected, if at all; that is, was it by the skin, which could produce cutaneous anthrax; by inhalation of spores, which would produce pulmonary and systemic anthrax infection; did they ingest any spores, which would produce an initial gastrointestinal infection; or, were they among the "worried well?"
Consider the situation where a close associate comes down with symptoms compatible with anthrax infection after receiving a powder-containing letter. Until this is disproved as anthrax, great worry will ensue. We learned that the limited textbook medicine did not apply. Yet there is useful information to be used in the present while designing future studies.
In several cases of documented exposure, there was not enough time for the patient to develop antibody to a specific anthrax antigen, at least as probed for IgG. Serial serum samples obtained on November 16, 17, 18, and 19 of 2001, well after the potential work place exposure during the first week in October 2001, were tested for IgG antibody to the protective antigen (PA) component of the anthrax toxins by enzyme-linked immunosorbent assay (ELISA); all samples were nonreactive. Serial tests for serum IgG antibody to the PA toxin of anthrax were performed on 436 workplace-exposed persons. All but one test was negative. Most specimens were collected on October 10 and 17. 9
It is instructive to look at the positive antibody case in the context and duration of that individual' s symptoms when he developed a positive test. None of the symptoms detailed below were individually unique to raise suspicion of a particular diagnosis. The 73-year-old man (case 2) developed fatigue on September 24. He was the newspaper mailroom clerk who delivered mail to the first patient (case 1). On September 28, he developed a nonproductive cough, intermittent fever, runny nose, and conjunctivitis. These symptoms worsened through October 1 when he was hospitalized. In addition he had shortness of breath with exertion, sweats, mild abdominal pain and vomiting, and episodes of confusion. Temperature was elevated to 38.5°C (101.3°F), heart rate was rapid at 109/min, respiratory rate was slightly fast at 20/min, and blood pressure was 108/61 mm Hg. He had bilateral conjunctival injection and bilateral pulmonary rhonchi. At that time his neurologic exam was normal. No skin lesions were observed. The only laboratory abnormalities were low albumin, elevated liver transaminases, borderline low serum sodium, increased creatinine, and low oxygen content in the blood. Blood cultures were negative on hospital day 2, after antibiotics had been started. The chest X-ray showed a left-sided pneumonia and a small left pleural effusion but no "classical" mediastinal widening. The patient was initially given intravenous azithromycin; cefotaxime and ciprofloxacin were subsequently added. A nasal swab obtained on October 5 grew Bacillus anthracis on culture. Computed tomography (CT) of the chest showed bilateral effusions and multilobar pulmonary consolidation but still no significant mediastinal lymphadenopathy. Pleural fluid aspiration was positive for B. anthracis DNA by PCR. Bacterial cultures of bronchial washings and pleural fluid were negative. A transbronchial biopsy showed B. anthracis capsule and cell-wall antigens by immunohistochemical staining. During hospitalization, the white blood count rose to 26,800/mm, 3 and fluid from a second thoracentesis was positive for B. anthracis DNA by PCR. Both pleural fluid cells and pleural biopsy tissue showed B. anthracis capsule and cell-wall antigens by immunohistochemical staining. Serial serum samples demonstrated a greater than fourfold rise in serum IgG antibody to the PA component of the anthrax toxins by an ELISA assay. The patient was able to leave the hospital on October 23 on oral ciprofloxacin. Table 14 .5 illustrates both the clinical and bioforensic approach and context in which to analyze such a patient. These are likely to be common to most situations where a biocrime is suspected to have affected an individual. The first set of questions revolves around whether the person is sick: does the patient have any indications of not being well and any laboratory evidence suggestive of any infection? The second set of questions addresses whether there is any specific and objective laboratory evidence of a particular infection.
This case points out that direct cultures may be negative at different times from different fluids and tissues. This may be influenced by the early administration of antibiotics. However the remnants of the infection, even dead Utility of Serologic Analysis of People Exposed to Anthrax organisms, can be found by probing for antigens and DNA. This patient manifested a classic principle of infectious disease, a rising antibody titer over time. In this case it was IgG to a particular antigen of the anthrax toxin. This antibody response may have been detected earlier if IgM to this toxin or other antigens of anthrax had been sought. The case also points out the utility of integrating the presence of antibody with that of other indications of an anthrax infection. These take their greatest significance during clinical symptoms and signs of infection in a possibly exposed individual.
Early administration of antibiotics can prevent positive cultures from the organism in question. Of the first 10 pulmonary anthrax cases associated with the 2001 anthrax letter attacks, three patients had no culture growth of B. anthracis from any clinical samples, but culture was attempted after initiation of antibiotic therapy. The diagnosis was made on the basis of history of exposure in conjunction with compatible symptoms and signs of disease, and objective laboratory findings. B. anthracis was identified in pleural fluid, pleural biopsy, or transbronchial biopsy specimens by reactivity with B. anthracisspecific cell wall and capsular antibodies, or DNA by PCR on pleural fluid or blood. 10 It is very important to understand the limitations of the assay used. An IgGbased ELISA against the anthrax toxin' s protective antigen (PA) component illustrates the importance of understanding the limitations of an assay. The ELISA assay was developed at the U.S. Army Medical Research Institute of Infectious Disease (USAMRIID) and put into operation after optimization at the CDC 11 for functional sensitivity and specificity for detecting antibody response to B. anthracis infection. Its major limitation is its restriction to one antigen and to IgG. Therefore a negative result at the time of early exposure may in effect yield a false-negative result. This identifies a gap in our knowledge and application that can be filled by development of an IgM assay, and perhaps one that is enhanced by probing for other B. anthracis antigens or epitopes yet to be discovered.
The assay may be very useful in its present form to screen asymptomatic people with possible exposure. The study by Dewan et al. gives a sense of this, and provides a contemporary background database on a group of individuals who may have been exposed to B. anthracis. 12 They evaluated postal workers. Beginning on October 29, 2001, 1,657 employees and others who had been to the Washington, D.C. postal facility went to the D.C. General Hospital for antibiotics additional to those begun on October 21. Serum samples were obtained from 202 individuals, and all were negative for specific IgG antibody to the PA IgG, including the three participants who reported a remote history of anthrax vaccination. Limitations to this data are the fact that antibiotics were begun before serum testing, and there were no baseline serum samples available for testing. Also, the time period from exposure to sampling was very short. Among 28 individuals with positive nasal swabs in the Capitol exposures who received antibiotics immediately, none had a positive culture from a nasal swab repeated 7 days later, and none had positive serum IgG to PA antigen 42 days after exposure. This again emphasizes the limitation and interpretation of a test in someone who had early antibiotic treatment. It does raise forensic considerations. Even with this easily disseminated strain, an antibody response may be aborted or modified with antibiotics by early eradication. Furthermore, antibiotics taken prior to exposure would likely be effective in preventing laboratory and clinical signs of an infection or exposure. Detection of DNA, antigen, or the organism itself on a person' s body, clothing, or possessions would raise a red flag.
The route of infection is equally important in interpretation of results and the limitations of the assay used. The example of cutaneous anthrax in Paraguay illustrates this, as well as the notion of searching for other antigens as markers of exposure. 13 Analysis of an outbreak of at least 21 cases of cutaneous anthrax developed from touching raw meat of a sick cow was performed. Serum from 12 cases and 16 colony and two noncolony controls 6 weeks after the outbreak were blotted for antibodies to the PA and lethal Utility of Serologic Analysis of People Exposed to Anthrax factor components of anthrax toxin. An ELISA was used to probe for antibodies to poly-D-glutamic acid capsule. Of 12 cases, 11 had a positive PA screen, for a sensitivity of 91.7%; none of the 18 controls was positive for a specificity of 100. Only six of 12 cases had antibody to the lethal factor; all controls were negative. Probing for antibodies to capsule was positive in 11 of 12, but was positive in two of 18 controls. This study demonstrates the need to consider other antigens.
Some of the principles discussed above are highlighted by a recent report on SARS. This coronavirus disease also evoked concern of a possible terrorist origin at the onset. A report in the Morbidity and Mortality Weekly Report (MMWR) 14 on the "Prevalence of IgG Antibody to SARS-Associated Coronavirus in Animal Traders" discussed the need to validate and interpret tests in the appropriate populations-the IgG test, discusses its inability to date the time of the infection, and the possibility of reactivity to a near neighbor that might be unknown. In a Promed bulletin, Dr. Berger looked at the data from a different angle and reported: "This week' s study in MMWR indicates that animal contact may indeed promote infection; however, the most striking finding seems to have eluded the authors: 1.2 percent to 2.9 percent of individuals in a healthy control group of adults were also found to be seropositive! The population of Guangdong Province is 86.42 million (2001), of whom 61.14 million are adults over age 14. If we assume that the seropositivity rates among controls is representative of the province as a whole, 734,000 to 1,773,000 adults in Guangdong have at some time been infected by the SARS virus. These figures are 87-to 211-fold the total number (8,422) of SARS patients reported worldwide to date!" This is a good illustration of the need to question the methodology of acquisition of data before accepting their application in formulas or for analyses.
Yersinia pestis, the cause of plague, is a zoonotic infection which occurs in the U.S. with regularity and has an animal reservoir. This is in contrast to a case of smallpox which would raise an immediate red flag for a bioterrorist event. Cases need to be approached from an epidemiologic standpoint first to determine whether it is an "expected" case or whether the facts point to a deliberate introduction of the organism in a group of people or an individual. Analytic techniques could include genomic analysis of an isolated organism and immunological response of the host. In consideration of animal reservoirs, ELISA assays were compared with other tests for detection of plague antibody 306 MICROBIAL FORENSICS HOST FACTORS and antigen in multimammate mice (Mastomys coucha and M. natalensis). 15 They were experimentally infected and then sacrificed at daily intervals. IgG ELISA was equivalent in sensitivity to passive hemagglutination and more sensitive than the IgM ELISA and complement fixation. Antibody was detectable by day 6 after infection using all four tests. IgM ELISA titers fell to undetectable levels after 8 weeks. Plague fraction 1 antigen was detected in 16 of 34 bacteremic sera from M. coucha and M. natalensis. This shows that the principle of IgM versus IgG to this pathogen works to temporally situate the infection as early versus late or past. It also shows that when the information is combined with antigen detection, it engenders more confidence in the results.
Melioidosis is caused by Burkholderia pseudomallei. 16 It is also an example in which key clinical signs and laboratory features raise the possibility of this infection. Related studies and observations are presented here to illustrate some of the temporal issues of the host response and the need to interpret results of an assay in the appropriate clinical and geographic setting. Whether it is an acute infection, persisting one, or past infection can be determined by looking at several host responses. Often a simple indicator of infection such as erythrocyte sedimentation rate or C-reactive protein (CRP) can create clinical suspicion to begin a probe for a specific infection. In a study of 46 patients with clinical melioidosis, 35 (22 culture-positive and 13 culture-negative) had relatively uneventful disease courses. Initially they had elevated serum CRP that decreased with antibiotic therapy and returned to normal as their disease resolved. In another series of patients, IgM and IgG were measured by ELISA in 95 sera from 66 septicemic cases and 47 sera from 20 cases with localized melioidosis. 17 Sixty-five sera from culture-negative cases seronegative for other endemic infections but suspected of melioidosis were also examined. Other controls included 260 non-melioidosis cases, 169 high-exposure-risk cases, and 48 healthy individuals. The IgG-ELISA was 96% sensitive and 94% specific. All sera from cases with septicemic and localized infections and 61 of 63 sera from clinically suspected melioidosis cases were positive for IgG antibody. The sensitivity and specificity of IgM ELISA were 74% and 99%, respectively. A geometric index for IgM antibody in the sera of the melioidosis cases was significantly higher in melioidosis cases compared to that of the nonmelioidosis disease controls. Another study by some of the same authors using a rapid test also showed IgG and IgM to have clinical utility. 18 Another study with the intent of evaluating the utility of an IgG assay compared to other assays illustrates how the clinical and temporal context must be integrated for interpretation. 19 It also illustrates how there is room for improvement in tests and that the best analysis will result from an understanding of the conditions in the endemic area and utilization of samples and controls from that area. These tests were evaluated in the actual clinical setting in an area endemic for melioidosis. Specificity of specific IgG (82.5%) and specific IgM (81.8%) were
significantly better than that of an indirect hemagglutination test (74.7%). The sensitivity of the specific IgG assay (85.7%) was higher than that of the IHA test (71.0%) and the specific IgM test (63.5%). Specific IgG was found in septicemic cases (87.8%) and localized forms (82.6%). The specific IgG test was also better than the specific IgM test and the IHA test in identifying acute melioidosis cases in the first five days after admission. IgG antibody to a B. pseudomallei antigen remained high for longer than 5 years in recovered disease-free patients. Because this is a disease that may have an incubation of days to years, an acute case may very well be picked up by IgM versus IgG if it were a matter of days from infection. Although endemic for Southeast Asia, if it were used as a biothreat agent in a different environment, its etiology may not be recognized immediately. The importance of understanding endemic area factors as well as the host to the microbe is further illustrated in another zoonotic example. Rift Valley fever virus (RVFV) can be transmitted via aerosols. One study with the intent at looking for improved tests did show the utility of IgM to determine an early exposure to RVFV. 20 Two ELISA IgM tests detected specific IgM antibodies to RVFV during the first 6 weeks after vaccination. Three inactivated vaccine doses were given on days 0, 6 to 8, and 32 to 34. ELISA serum IgM on days 6 to 8 were negative or in the lower range of significance; on days 32 to 34 they were strongly positive; on days 42 to 52 they were waning and later were negative. The plaque reduction neutralization test was negative on days 6 to 8 and became positive in later samples. Similar to the examples shown above, their data suggest that three doses of RVFV vaccine induced a prolonged primary antibody response. The authors of that study concluded that the ELISA IgM could become an important tool for early diagnosis in acute human infection. Good correlation of a neutralization test and ELISA IgG would indicate a later infection.
Taken together these examples illustrate that an ideal test for both clinical and forensics use would incorporate endemic area controls, historical contextual information, knowledge of the route of exposure, background incidence, and kinetics of transmission.
Each of these scenarios must take into account multiple factors and the limitations of any analytic process to be applied. This is often considered by understanding the elements of positive and negative predictive values of an assay within a population being tested. On one extreme is the situation that occurred with the onset of human immune deficiency (HIV) in the U.S. First there were 308 no cases, and therefore a precise highly sensitive and specific test with excellent positive and negative predictive values (such as exists now when a combination of tests are used) would not likely yield a positive result in an area where there was little disease at the onset, Kansas, for example. A positive test by today' s methodologies from a 1970 serum sample from Kansas would be considered a probable false-positive and warrant further investigation. However the same sample tested at the beginning of HIV testing could have been positive if the person had adult T-cell leukemia, which is caused by human T-cell leukemia virus-1 (HTLV-1). This is because the original tests for what became known as acquired immunodeficiency syndrome (AIDS) involved whole viral lysates in which up to 30% of the HTLV-1 sera crossreacted. Suspicion to the contrary would be raised by knowledge of different presentations of the infection. For example, HTLV-1 can actually be used in the laboratory to immortalize cells. In the patient it actually increases the Tcell count, as is the nature with leukemia, instead of decreasing them, as with HIV infections. Other laboratory indicators such as hypercalcemia would now raise leukemia as a consideration.
Interpretation of a positive clinical test must take into account the health status of the person being tested. This is important for the practice of medicine and can have relevance when extended to forensic analysis. The following situations illustrate the concept. Individuals who have syphilis, a bacterial spirochetal infection, can typically have a positive FTA (fluorescent treponemal antibody) test for years. However while infected they would have a positive venereal disease research laboratory (VDRL) test. This reverts to negative with successful antibiotic therapy. There are some notable exceptions related to cross-reactive epitopes or autoimmune diseases. These are readily distinguishable by history and clinical information. Similarly individuals infected with tuberculosis will have a positive skin test (Mantoux), whereas the uninfected healthy person will be negative. In certain instances, a sick person with a cell-mediated immune deficiency will be anergic, that is, he/she will be negative to multiple skin tests including common antigens such as Candida.
The key difference here is that there is a wide difference between the healthy person being tested and a very ill individual being subjected to the same test.
Tests may also discriminate between the time of the infection as acute or chronic, and its limitations may lead to different interpretations unless one is familiar with those limitations. An example of this occurred with the bacterial infection of Borrelia burgdorferi, which causes Lyme disease. Dattwyler' s group showed that antibiotics could abrogate the antibody response because ELISA results were negative in 30% of patients with known disease who were treated early. 21 Another group showed that in early cases reactivity to a unique antigen, OspA, was also negative in serological assays despite a demonstrable T-cell response. 22 Our own group had an opportunity Possible Scenarios of Bioterrorism Attacks to analyze the same sera and found that there was antibody to B. burgdorferi but it was below the threshold of the conventional assays. It was detectable in its bound form, in immune complexes. 23, 24 Anthrax can be used as an example where investigatory leads can be generated by considering a scenario in toto. The elderly lady who died in Connecticut from anthrax clearly had no occupational exposure nor was she known to have had contact with anyone who had anthrax. It was possible that she received contaminated mail. However if this case had occurred as the index case or out of context of the mail attacks, it would have been reasonable to question her travel history, what her work if any was, or if she received or used products from an endemic area for anthrax. Similarly the Vietnamese woman who died in New York City would also have had these questions investigated. It would have been useful to search for direct or indirect evidence of anthrax by physical examinations of her contacts or close neighbors. Inspection and cultures from her workplace, apartment, and apartment complex (especially contiguous neighbors) are important for presence of anthrax. Coworkers, friends, neighbors, and other contacts could have had blood samples analyzed for antibody to anthrax antigens. These samples could have been frozen so that if one were positive it would be available for a comparison study in the future. At a minimum these types of studies could serve as future control data for the geographic region. Although hypothetical, several results could have occurred, and each will be analyzed separately: First example: a close contact is positive for IgM to one of the B. anthracis antigens, e.g. PA. This would suggest that this person had recent exposure and if nothing else should be treated. This individual could conceivably be the one who knowingly or unknowingly passed the spores to the patient. Given the October 26 onset of illness, which is late in the mailing sequence, it would be less likely that this individual was a perpetrator but rather a recent victim too. However if this person were IgG-positive on the assay, then there are several other possibilities. Perhaps this person had past exposure in an endemic region with a subclinical or treated illness (e.g., Haiti, where anthrax is known as "charcoal disease"). Or this person could have been vaccinated for bona fide reasons such as a researcher who received it for occupational protection. Or this person could have obtained the vaccine originally for legitimate or illegal purposes but was nevertheless vaccinated. Animal vaccines may be more obtainable without strict record keeping. This person could have loaded the mail with relative impunity if there were protective antibody generated from the vaccine. These situations require intelligence information regarding access, ability, and motive. However the IgG finding could point investigators towards such an individual, whereas an IgM finding justifies critical therapy. Coming from the other direction, where information points to a particular individual, investigation could be extended to ingestion of antibiotics. Questions would be raised 310 MICROBIAL FORENSICS HOST FACTORS regarding access to antibiotics, recent ingestion of them, half-life of the antibiotic, half-life of the metabolites of the antibiotics, and in which body fluids or tissues the residual can be found. As illustrated from the data in the earlier sections, someone with antibiotics in their system could be protected from exposure to a sensitive microbe. This person would be antibody-negative and likely antigen-and microbial DNA/RNA-negative, since the infection would have been eradicated before the organism could proliferate in any significant quantity.
Similar strategies can be employed to examine suspicious but possible accidental transmission of infections. This is illustrated by a recent series of aviant flu. Tools to determine a person to person spread as the transmission mode included viral cultures, serologic analysis, immunohistochemical assay, reverse-transcriptase-polymerase-chain-reaction (RT-PCR) analysis, and genetic sequencing. 25 It is likely that future understanding of the immune system and evolving technologies such as microarrays will bring new analytic power to the scene, but in the meantime we can make good use of proven principles for forensic purposes.
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Supply chains are victims of a dynamic phenomenon known as the Bullwhip Effect (Lee et al., 1997a (Lee et al., , 1997b . This refers to the amplification of the variability of orders as they pass through the different echelons of a supply chain, which may also have negative implications in terms of the variability of inventories. On the whole, the Bullwhip Effect creates a climate of instability in production and distribution systems that significantly decreases their operational and financial performance (Metters, 1997; Disney and Lambrecht, 2008; Dominguez et al., 2018) . Given its practical importance, the Bullwhip phenomenon has become a fruitful area of research over the last two decades; see e.g. the review of the Bullwhip literature by Wang and Disney (2016) . However, the Bullwhip problem is still far from being solved. A few years ago, a study by Isaksson and Seifert (2016) reported a mean increase of the coefficient of variation (c.v.) of the orders that equalled 90% after analysing a sample of approx. 15,000 buyer-supplier dyad relationships in a wide range of US industries.
As is obvious by its definition, the Bullwhip Effect particularly affects the higher echelons of the supply chain, such as manufacturers. To prevent it from aggressively propagating upstream and thus damaging the operations of all supply chain partners, managers need to understand why it occurs. Disney and Lambrecht (2008) highlighted that this phenomenon emerges through the interaction of behavioural and operational components. The behavioural causes of the Bullwhip problem, studied in detail by Croson and Donohue (2006) , derive from the fact that managerial decisions are not always completely rational; rather, decision makers commonly over-or understanding the effects of price variations by contrasting fixed-price strategies, such as EDLP, versus fluctuating-price strategies, such as HL. As we will discuss in the following subsection, the present paper differs from these previous works in the Bullwhip literature in that we study the relationship between pricing and Bullwhip by assessing the impact of quantity discounts.
A quantity discount is an economic incentive to encourage organisations (or individuals) to purchase goods in large quantities. Basically, the vendor rewards buyers who make big purchases by providing a reduced unit price. These discounts are very common in practice, taking on a variety of formulas; see Weng and Wong (1993) and Rubin and Benton (2003) . Maybe the most common formula is the all-unit discount, based on applying the lower unit price to all the units purchased when a certain threshold is reached (e.g. Chen and Robinson, 2012; Zhang et al., 2019) . For instance, assume the regular price of a product is 1€. The seller may opt to offer a 10% discount that goes into effect if at least 100 units are purchased. That is, buyers who purchase less than 100 units would pay 1€ per unit, while buyers purchasing larger quantities would pay €0.9 per unit.
Quantity discounts not only may help the seller increase the sales revenue and reach economies of scale (Viswanathan and Wang, 2003) , but also have other advantages for businesses that offer them, see Mohammed (2013) . As seems reasonable, the main drawback is that such discounts tend to reduce the profit per unit due to the decrease in the average revenue, unless major economies of scale are achieved (Viswanathan and Wang, 2003) . From the perspective of the buyer, quantity discounts mean an opportunity to reduce purchasing costs; however, buying more than needed at a specific point in time would also tend to increase inventory holding costs. Taking both effects into account, one may (simplistically) argue that quantity discounts are profitable for firms as long as the reduction in purchasing costs outweighs the increase in holding costs. However, the whole picture is more complex, given that pursuing the quantity discount has meaningful implications in the wider supply chain. For example, in line with prior discussions, large order quantities contribute to the distortion of information, thus seriously damaging the higher supply chain echelons through the Bullwhip phenomenon. Under these circumstances, the quantity discount may eventually result in increased production or transportation costs.
Due to their industrial relevance, quantity discounts have been studied in the inventory control literature over the last four decades from different angles, some of which are illustrated below by reviewing a few relevant papers in this area. Monahan (1984) developed an analytical method for establishing the optimal terms of quantity discounts from the perspective of vendors, assuming the buyer uses an EOQ model to order supplies. Weng (1995) also used an EOQ framework, through which the author explored the role of quantity discounts in the coordination of a supplier and several buyers. Li and Liu (2006) showed how quantity discounts can be used to coordinate a supplier-buyer relationship for probabilistic demands, which differs from the previous works that assumed a fixed demand. Along a different line, Meena and Sarmah (2013) used a genetic algorithm to solve the order allocation problem of a manufacturer among multiple suppliers when supply disruptions occur and quantity discounts exist. Recently, Zhao et al. (2020) studied the coordination of a fashion supply chain characterised by demand disruptions through revenue sharing contracts and quantity discounts.
This excerpt of the literature exemplifies that previous works exploring quantity discounts have provided a fair understanding of key effects caused by these pricing strategies that help professionals establish the appropriate discount in practice. However, these papers have not addressed so far the Bullwhip implications of quantity discounts in the supply chain, which play a pivotal role in many real-world industries. That is, these previous works have focused mainly on inventory-related costs, but have not considered the interplays of these costs with Bullwhip-related costs. At the same time, as discussed in the previous subsection, price considerations have been underexposed in Bullwhip studies, which have not examined the implications of quantity discounts despite their practical importance.
From this perspective, our paper attempts to shed more light on the relationship between quantity discounts and operational costs by looking at the propagation of the Bullwhip Effect in supply chains. Specifically, we measure two common metrics in the Bullwhip literature, named as Bullwhip ratio (BW) and Net Stock Amplification ratio (NSAmp), as they are symptomatic of unsteady operation in the supply chain and low efficiency in customer satisfaction, respectively. In this sense, we consider the interactions between five types of supply chain costs: (i) purchase costs; (ii) inventory holding costs; (iii) stock-out costs; (iv) capacity-related overtime costs; and (v) capacity-related opportunity costs. This analysis, which represents the contribution of our paper to the inventory control and Bullwhip literatures, allows us to derive relevant implications for professionals, which help (i) upstream supply chain managers reflect on whether or not they should offer quantity discounts to their downstream partners; and (ii) downstream supply chain managers decide on to what extent they should pursue the offer of a quantity discount made by their upstream partners.
Section 1 has positioned our research work and highlighted our contribution to the advancement of knowledge in the operations management field. To sum up, our paper contributes to the Bullwhip Effect literature by exploring the influence of quantity discounts, a popular pricing instrument that induces dynamics in supply chains that have not been investigated in enough detail so far. Also, our paper brings a new perspective to the area studying the operational implications of quantity discounts, which is based on introducing Bullwhip considerations into the analysis. Bullwhip provokes additional costs, which play a fundamental role in many supply chains, that should not be ignored in the design of quantity discounts.
The remaining of the paper has been structured as follows. Section 2 provides complete detail on the supply chain model under consideration, including the operational and economic performance metrics. Section 3 offers some preliminary analytical insights into the behaviour of the supply chain with quantity discounts. Section 4 presents our numerical analysis in a baseline scenario, carries out sensitivity analyses to explore the impact of the relevant parameters on the performance of the supply chain, and discusses the main findings of our study. Finally, Section 5 concludes, reflects on the managerial implications of our work, and poses insightful avenues for future research.
To understand in detail the operational dynamics induced by quantity discounts in the supply chain and the economic performance of the system, we study a single-product, serial production and distribution system formed by a manufacturer, a retailer, and the consumers. The manufacturer produces the product in response to the purchase orders issued by the retailer, who attends consumers and their product needs directly. In this section, we first present the notation of the supply chain variables and parameters. Next, we detail the sequence of events and the mathematical formulation of the supply chain model, including the underlying assumptions. Finally, we describe the performance metrics that we use for evaluating the behaviour of the supply chain, including both operational and economic indicators.
In this paper, we employ the following notation to refer to the variables that define at each moment, in a generic period t, the operational and financial state of the supply chain (in alphabetical order):
▪ d t : consumer demand of the product, ▪ fd t : forecasted demand of the product, ▪ ns t : net stock, i.e. the on-hand inventory held by the retailer after serving the consumers, ▪ o t : actual order quantity placed by the retailer to the manufacturer, ▪ o d t : product purchased by the retailer to the manufacturer at the discounted price, ▪ o r t : product purchased by the retailer to the manufacturer at the regular price, ▪ pr t : product requirements, i.e. the order quantity that the retailer would go for in the absence of the quantity discount, ▪ r t : receipts, i.e. the products received by the retailer from the manufacturer, ▪ tns t : target net stock, representing a safety stock, ▪ tw t : target work-in-progress, and ▪ w t : work-in-progress, i.e. an on-order inventory of the products ordered by the retailer but not yet received.
In addition, we use the following notation for the supply chain parameters (in alphabetical order):
▪ b: unit backlog cost (an inventory-related cost), ▪ dp: discount offered by the manufacturer to the retailer in percentage terms, ▪ DQ: discount quantity, from which the economic incentive is offered, ▪ h: unit holding cost (an inventory-related cost), ▪ GC: guaranteed capacity that is available each period, ▪ n: per-unit opportunity cost (a Bullwhip-related capacity cost), ▪ p: per-unit overtime cost (a Bullwhip-related capacity cost), ▪ rp: regular price of the product, ▪ Tp: lead time, i.e. the time lag between issuing the order and receiving the product, ▪ δ: safety parameter, i.e. the number of (additional) periods in which the safety stock protects customer service against demand uncertainties, ▪ μ: mean of consumer demand, ▪ σ: standard deviation of consumer demand, and ▪ ψ: discount acceptance parameter, determining the minimum product requirements from which the quantity discount is accepted.
We adopt the following sequence of events 5 for describing the discrete-time operation of the production and distribution system under consideration: at the beginning of a period, the retailer receives the product corresponding to the replenishment orders placed earlier; during the course of the period, the retailer serves the demand of consumers; and at the end of the period, the retailer reviews the inventory (both net stock and work-in-progress), forecasts future demand, and issues the purchase order. At this point in time, the retailer will consider the manufacturer's offer of a quantity discount and will decide on whether or not to order the discount quantity. This sequence of events has been modelled through a set of difference equations that is detailed below, together with the specific assumptions they entail. We will put special emphasis on the modelling of the retailer's decision-making process around the quantity discount offered by the manufacturer, where the novelty of our work lies.
When the period t starts, the retailer receives the product corresponding to the order placed Tp +1 periods ago 6 , as per Eq. (1). Notice that we assume that the manufacturer has always enough capacity and there is always sufficient raw material availability to produce and deliver on time, i.e. after the lead time, the quantity requested by the retailer. Then, demand occurs, which is assumed to be an independent and identically distributed (i.i.d.) random variable following a normal distribution with mean μ and standard deviation σ, see Eq.
(2). This assumption is reasonable when demand stems from a large number of independent consumers as a consequence of the central limit theorem (Lau et al., 2013; Disney et al., 2016) . Note that we also assume that μ ≫ σ, so that the probability of negative demands is small.
After satisfying consumer demand, both the net stock and the work-in-progress are updated. The net stock balance considers the demand (decreasing) and the receipts (increasing), as shown by Eq. (3); while the work-in-progress balance considers the last order issued (increasing) and the receipts (decreasing), as indicated by Eq. (4). Notice that ns t represents the end-of-period position of the onhand inventory, where ns t > 0 indicates excess stock, which can be used to meet next period's demand, while ns t < 0 reveals that stockout has occurred. In this case, |ns t | provides the stock-out size, an unfulfilled demand (backlog) that will need to be satisfied when inventory is again available. On the other hand, it is interesting to note that, due to Eq. (1), Tp = 0 results in w t = 0, while when Tp > 0 the work-in-progress corresponds to the sum of the last Tp orders.
The product requirements are estimated according to an order-up-to (OUT) model. We use this discrete-review replenishment policy because it is very popular in practice (Dejonckheere et al., 2003) , which probably occurs as it is easy to implement and inexpensive to operate (Axsäter, 2003) and it provides good results in terms of inventory performance 7 (Disney and Lambrecht, 2008) . In this sense, the product requirements can be obtained as the demand forecast plus the net stock gap (i.e. target minus actual net stock) plus the work-in-progress gap (target minus actual work-in-progress), see Eq. (5).
We use a static forecasting method, given by Eq. (6). Specifically, we assume the retailer has enough historical data to accurately estimate the mean demand, and uses it to forecast future demand. This is a perfectly rational decision when demand is i.i.d., as it results in a minimum mean squared error (MMSE) technique that also helps to mitigate the Bullwhip propagation in the supply chain . For the target net stock, we employ a safety stock model based on multiplying the demand forecast by the safety parameter δ, as per Eq. (7). This approach is also common in practice, as discussed by Hoberg et al. (2007) . Meanwhile, we use the most popular target work-in-progress model (see Lin et al., 2017) , where the target work-in-progress is obtained as the forecast of consumption over the lead time, see Eq. (8).
Finally, the retailer issues the purchase order, taking into account the quantity discount offered by the manufacturer. We model a 'common-sense' practical setting in which the retailer is only willing to accept the discount offer if the product requirements are higher than or close to the quantity from which the reduced price applies, denoted by DQ. Given that the 'close to' concept may significantly vary among real-world retailers, we model it through the decision parameter ψ, with 0 ≤ ψ ≤ 1, which we label the discount acceptance parameter. This parameter thus represents the willingness of the retailer to pursue the quantity discount offered by the manufacturer.
In this fashion, the retailer will only accept the discount as long as pr t ≥ ψDQ. We can illustrate this with an example. Suppose the manufacturer offers the reduced unit price from 200 units, DQ = 200. Also, assume the retailer sets a discount acceptance parameter of ψ = 0.9. If for a specific period the product requirements are pr t = 175(< ψDQ = 180), the retailer will ignore the discount and order 175 units. By contrast, if the product requirements are pr t = 185(> ψDQ = 180), the retailer will pursue the discount and order 200 units. Of course, if the product requirements are pr t = 205(> DQ = 200), the retailer will order 205 units (that is, this node does not only orders the minimum quantity, but exactly what it needs).
Therefore, the following rationale is assumed to reflect the decision-making process of the retailer about the quantity discount. If pr t 6 Tp +1 applies as orders are issued at the end of each period and the product is received when the period starts. 7 As shown by Karlin (1960) , if the safety stock is appropriately adjusted, the OUT replenishment policy is optimal in terms of the sum of holding and backlog costs when both are proportional to the volume.
is higher (or equal) than DQ, the order equals the requirements -then, the discount will be accepted without any cost. If pr t is lower than DQ but higher (or equal) than ψDQ, the retailer orders the discount quantity -the discount will be accepted at the cost of ordering more than the actual needs. Lastly, if pr t is lower than ψDQ, the discount will be turned down in this period, and the order again meets the exact needs of the retailer. This is described by Eq. (9).
Interestingly, defining the discount acceptance parameter ψ, which plays a key role in Eq. (9), will allow us to explore in detail the behaviour of the supply chain with quantity discounts, which we do in Section 4. Lastly, for evaluation of the economic metrics, it is convenient to define two additional variables. These are the number of products purchased at the regular and the discounted prices, o r t and o d t , given by Eqs. (10) and (11), respectively. It can be easily verified that, of course,
We quantify the operational performance of the supply chain using two common indicators that provide information of different nature but highly interrelated: the Bullwhip ratio (BW) and the Net Stock Amplification ratio (NSAmp). BW measures the variance of orders in relation to the variance of consumer demand, see Eq. (12); NSAmp assesses the variance of the net stock in relation to that of demand, see Eq. (13). As discussed by Disney and Lambrecht (2008) , considering both indicators at the same time provides a rich picture of the dynamic behaviour of a specific replenishment rule; NSAmp reports on the inventory performance of the rule, and BW is indicative of the efficiency of the production and distribution system.
We also measure the economic performance of the system. Specifically, we consider: (i) purchase costs; (ii) inventory-related costs, including holding and stock-out costs; and (iii) Bullwhip-related capacity costs, including overtime and opportunity costs.
Purchase costs (PC) can be easily quantified by considering the products purchased at the regular and the discounted prices, and multiplying them by their prices, as shown in Eq. (14). To quantify the inventory-related costs (IC), we consider the traditional, widely used approach based on a unit holding cost of h and a unit backlog costs of b; see e.g. Disney and Lambrecht (2008) . This model is expressed by Eq. (15), where [x] + = max{x, 0} is the maximum operator. To quantify the Bullwhip-related capacity costs (CC), we assume that a certain guaranteed capacity GC is available in each period to process the orders. If less capacity than GC is needed, an opportunity cost of n per unit is incurred, given that the workforce stands idle for a proportion of the period. If more capacity is required, overtime workers can be hired at a higher cost, where p represents the extra cost per unit. This approach is modelled by Eq. (16). We refer readers to Disney et al. (2012) for further details behind this model.
In line with previous discussions, reducing BW allows for a decrease in CC and reducing NSAmp allows for a decrease in IC. The rationale behind these relationships is explained in Fig. 1 , where it can be seen that reducing the variability of orders (left) and inventory (right) reduces the overtime and opportunity costs (left) and the holding and stock-out costs (right), respectively. Nonetheless, it is important to highlight that to realise the improvements derived from the reduction of variabilities managers need to adjust appropriately the guaranteed capacity GC (for CC) and the safety stock, through the safety parameter δ (for IC). Note, denoting in the graph the safety stock by SS, we obtain SS = δμ in our case, due to Eqs. (6) and (7).
The operational dynamics of the supply chain with quantity discounts is fully characterised by Eqs. (1) to (9). As explained before, Eq. (9) describes the decision making of the retailer around the discount offered by the manufacturer. It is appropriate to note that this equation introduces a nonlinearity in the supply chain model, which has strong implications on the dynamic behaviour of production and distribution systems, as discussed by Nagatani and Helbing (2004) , Wang et al. (2014) , and Disney et al. (2020) . 9) for two different values of the decision parameter ψ, with ψ 1 > ψ 2 , thus providing graphical illustration of the nonlinearity under study. Comparing the ψ 1 and ψ 2 curves, we observe that as ψ decreases (from ψ = 1) -that is, as the willingness of the retailer to pursue the quantity discount offered by the manufacturer increases-, the nonlinear nature of the supply chain is accentuated. Indeed, the nonlinearity does not exist in the specific case that ψ = 1, where the decision making of the retailer is not affected by the quantity discount.
This nonlinearity makes the mathematical analysis considerably more difficult, and often even intractable, unless additional assumptions are considered, such as zero lead times. For this reason, simulation has become the most popular approach to study the dynamics of nonlinear supply chain models; for instance, Chatfield and Pritchard (2013) investigated forbidden returns -a nonnegative condition of orders-and Ponte et al. (2017) considered capacity constraints -an upper limit on the order quantity. In this work, we follow the same methodological approach, based on modelling and simulation techniques, to explore how quantity discounts modify the operations of supply chains and its economic consequences on the supply chain actors.
Having noted that, before the numerical, simulation-based analysis, we now discuss some preliminary analytical insights into the operational behaviour of our supply chain. To this end, Section 3.1 derives analytically the dynamics of the supply chain with ψ = 1, i.
e. the reference linear system, against which we will explore the impact of the quantity discount. Later, Section 3.2 provides an initial understanding of the dynamic effects of the quantity discount by analysing the impulse response of the system when it faces a change in demand that moves the system from the linear to the nonlinear zone. Fig. 2 . The relationship between the product requirements and the actual orders in our supply chain.
3.1. Supply chain dynamics with ψ = 1
As we have just discussed, the interest of the retailer to get a reduced price in the product purchased to the manufacturer, indicated by ψ < 1, adds a nonlinearity to our model. However, for ψ = 1, our model behaves as a linear system, which may be interpreted as the reference system. For this reason, it is convenient to start the analysis by clarifying the dynamics of the linear system where the discount does not exist -or where it exists, but it does not alter the replenishment decisions of the retailer. In this section we use the notation x t to refer to the variables x t in the linear system. To understand the system dynamics, we need to express the order (õ t ) and net stock (ñs t ) as functions of constants and the demand (d t ). When ψ = 1, Eq. (9) simplifies to the following linear equation,
That is, the retailer always orders exactly what it needs. Taking this relationship into consideration, along with Eqs. (5)-(8), we can easily obtain the replenishment rule shown in Eq. (17).
Notice that (1 +δ +Tp)μ defines a time-invariant OUT point. To understand the dynamics of the system, we can use the difference between orders placed in two consecutive periods. Fom Eq. (17), we see that
The inventory equation, Eq. (3), allows us to calculate (ñs t− 1 −ñs t ),
On the other hand, using the work-in-progress balance in Eq. (4),
Using these two relationships, the difference between two consecutive orders can be simplified to
Therefore, we derive the fundamental relationship of our reference linear system shown in Eq. (18).
That is, under these circumstances (in particular, OUT policy with MMSE forecasts and i.i.d. demand), the OUT policy acts as a 'pass-on-orders' rule, in such a way that the replenishment orders are the same as the most recent demand (see e.g. Disney and Lambrecht, 2008) . In this sense, the Bullwhip phenomenon does not occur in the reference linear system, given that, using Eq. (12),
Now we focus on the net stock. Using Eq. (17), the final position of the on-hand inventory can be isolated,
Using the relationship between receipts and past orders in Eq.
(1), we can express the work-in-progress balance in Eq. (4) as follows,
Therefore, we can consider together the sum of the order and the work-in-progress, by
This allows us to present the net stock as a function of the past orders and, via Eq. (18), as a function of the last (Tp + 1) demands. This can be seen in Eq. (20).
Eq. (20) allows us to derive the Net Stock Amplification ratio, defined in Eq. (13), as follows,
Now we aim to understand the nonlinear dynamics induced by the quantity discount in the supply chain. To this end, we make use of the impulse response. Specifically, we compare the impulse response of our nonlinear supply chain with quantity discounts to that of the reference linear system. It is well known that the impulse response provides full characterisation of dynamic systems 8 ; thus, it offers a firm understanding of the dynamic behaviour of supply chains, and hence it has been commonly employed in the literature (e.g. Disney and Towill, 2003; Dominguez et al., 2014; Gaalman et al., 2019) .
Unless unreasonable assumptions are made, our system will often be operating in the linear region of Fig. 2 , due to pr t < ψDQ. At some specific points in time, in particular when pr t ≥ ψDQ (and pr t < DQ), it will enter the nonlinear region of Fig. 2 . When the supply chain is operating as a linear system, pr t =pr t =õ t = d t ; therefore, the arrival of a demand, d t , that verifies ψDQ ≤ d t < DQ is the condition that will make it enter the nonlinear region. To illustrate the short-term dynamics induced by the discount, we then need to generate a demand impulse so that, ∀t ∕ = 0, d t < ψDQ and, for t = 0, ψDQ ≤ d t < DQ. By way of illustration, we use DQ = 140 and ψ = 0.75 (ψDQ = 105) and we consider the impulse function, d t = {100, ∀t ∕ = 0; 110, if t = 0}. Also, we use a lead time of Tp = 4 periods. Fig. 3 shows the impulse response of the linear and nonlinear systems.
Consider that during a short number of consecutive periods, the supply chain is operating in the linear region, given that the last demands were lower than ψDQ, i.e. d t− 1 ,d t− 2 ⋯ < ψDQ. Fig. 3 shows that every time t the supply chain enters into the nonlinear region, due to ψDQ ≤ d t < DQ, the following sequential behaviour emerges, establishing key differences between the linear and nonlinear systems:
i. In t, ψDQ ≤ d t < DQ leads to ψDQ ≤ pr t < DQ, which according to Eq. (9) makes that o t = DQ. This creates a (first) gap between the linear orders, õ t = d t , and the nonlinear orders, o t = DQ, which we denote by Δ t = DQ − d t . In Fig. 3 , Δ t=0 = 140 − 110 = 30. ii. In t + 1, the work-in-progress increases in the nonlinear system by Δ t units due to the last order being larger than the linear one.
That is, as per Eq. (4), w t+1 =w t+1 + Δ t . Using Eq. (5), this provokes a reduction in the product requirements, pr t+1 =pr t+1 − Δ t . Due to Eq. (9), this will make that o t+1 =õ t+1 − Δ t , except if the new demand does not allow for it. iii. From t + 2, the nonlinear system behaves as the linear system would, given that the excess of products ordered in t has been compensated in t + 1. Note that o t+1 =õ t+1 − Δ t makes that w t+2 = (w t+2 + Δ t ) − Δ t =w t+2 . Notice that the difference for the other variables shown in Fig. 3 is also zero. However, this only occurs up to t + Tp, inclusive (t + 4, in Fig. 3 ). iv. In t + Tp + 1, the product associated to the order issued in t is received at the on-hand stock site. That is, via Eq. (1), r t+Tp+1 = r t+Tp+1 + Δ t . Therefore, as per the net stock and work-in-progress balances in Eqs. (3), ns t+Tp+1 =ñs t+Tp+1 + Δ t and w t+Tp+1 = w t+Tp+1 − Δ t . v. In t + Tp + 2, the 'compensation order' of t +1 is received, i.e. r t+Tp+2 =r t+Tp+2 − Δ t , see Eq.
(1). The net stock and work-inprogress then return to their linear states; ns t+Tp+2 = (ñ s t+Tp+2 (Eqs. 3-4) . Thus, the impact of the discount used in t on the system dynamics ends in t + Tp + 2.
Steps (i) to (v) occur repeatedly in our supply chain. When the minimum quantity from which the discount is accepted is sufficiently higher than the mean demand, i.e. ψDQ ≫ μ, the probability of having two consecutive demands that are higher than ψDQ is negligible. For example, for μ = 100, σ = 25, DQ = 180 and, ψ = 75%, we obtain P(d t > ψDQ ⋂ d t− 1 > ψDQ)〈1%. In this case, o t = DQ will (nearly) always be compensated in t + 1, and the effects of the discount do not overlap in time. When the previous condition does not hold, the effects of different discounts will overlap in time.
In any case and for a long time horizon, as in Fig. 3 , a variable in the nonlinear system x t can be expressed as the sum of the linear variable, x t , and the difference between them, denoted by x t , i.e. x t =x t +x t . This decomposition allows us to understand the behaviour of the nonlinear variables. We continue the analysis by focusing on the order (o t ) and net stock (n s t ), which explain the performance metrics of our system.
For the orders, o t =õ t +ô t . As õ t and ô t are not independent, but correlated variables, we obtain that var(o t ) = var(õ t ) + var(ô t ) + 2cov(õ t ,ô t ). We have previously shown that var(õ t ) = σ 2 , see Eq. (19). By the variance definition, var(ô t ) ≥ 0; indeed, considering that , or the probability of entering it is null). In addition, õ t and ô t are correlated variables, see Fig. 3 . Under the normal assumption that DQ > μ, ô t > 0 occurs when õ t = d t takes high values, that is, cov(õ t ,ô t )〉0. Thus, var(o t ) > var(õ t ). In this way, the discount tends to increase the Bullwhip Effect, as also suggested by the increase of order variability in Fig. 3 .
Nonetheless, it is also interesting to note that, if DQ < μ, the nonlinear behaviour generally occurs when õ t = d t is low (for high values of õ t = d t , the system operates again in the linear region, see Fig. 2 ). In this case, cov(õ t ,ô t )〈0. While it may not be reasonable for the manufacturer to offer the discount under such circumstances, this may lead the supply chain to benefit from a reduced BW ratio. We now perform a similar analysis for the net stock. In this case, is ns t =ñs t +ns t , which leads to var(ns t ) = var(ñs t ) + var(ns t ) + 2cov(ñs t ,ns t ). As per Eq. (21), var(ñs t ) = σ 2 (1 + Tp). Again, due to the definition of variance, var (n s t ) > 0, except if the discount does not affect the supply chain operation. Lastly, note that the differences between the nonlinear and linear net stocks, ns t > 0, are provoked by the demand (Tp + 1) periods before, i.e. d t− (Tp+1) . In contrast, ñs t depends on demands from d t− Tp up to d t , in line with Eq. (20). Under these circumstances, the covariance term does not play a meaningful role in the previous relationship, and var(ns t ) > var(ñs t ). Thus, the discount also tends to increase the NSAmp ratio, which is aligned with the analysis of net stocks in Fig. 3 . All in all, we conclude from our preliminary analytical study that BW and NSAmp in the nonlinear supply chain will tend to be higher than that in the linear one due to the impact of the retailer's pursuit of the discount offered by the factory. The impulse response has allowed us to understand why the deterioration of the dynamics occurs in the inventory system. However, this does not necessarily apply in the unusual case that DQ < μ, where the supply chain may benefit from an improved order dynamics.
We now study in depth the operational and economic performance of the production and distribution system with quantity discounts when exposed to the stochastic conditions defined. To analyse the effects of the quantity discount, the discount acceptance parameter, ψ, plays a key role, as it models the retailer's willingness to pursue the quantity discount when making an order. We define a baseline scenario represented by the values of the parameters indicated below, and justified as follows:
▪ We consider a mean consumer demand of μ = 100 (units) and a standard deviation of σ = 25 (units). This implies a c.v. of σ/ μ = 25%, which is within the typical range of variation of the demand time series faced by retailers, [15%,50%], observed by Dejonckheere et al. (2003) . ▪ We assume that there is a lead time of two periods, Tp = 2 (periods), i.e. the product is received by the retailer two periods after it is sent by the manufacturer. This is a typical, frequently used value of the lead time in supply chains studies, such as e.g. Ciancimino et al. (2012) . ▪ We consider that the regular price of the product is rp = 10 (€/unit). Also, we consider that the manufacturer offers a discount of dp = 10% -resulting in a discounted price of rp(1 − dp) = 9 (€/unit)when at least 140 units are ordered, that is, DQ = 140 (units). This percentage (10%) may be interpreted as a reasonable quantity discount found in practice that authors have used in prior literature, e.g. Lightfoot (2019). ▪ We select b = 2 (€/unit) and h = 1 (€/unit), representing a traditional scenario in which backlog is more expensive than holding inventory. This is by far the most common case in practice -otherwise, real-world companies would not need to operate with safety stocks-; for example, b = 2h is generally used in the well-known Beer Game, see Goodwin and Franklin (1994) . ▪ We select p = 2 (€/unit) and n = 1 (€/unit), representing a practical setting in which overtime is more costly than the opportunity cost of being idle. Other studies have also made this assumption, such as Ponte et al. (2017) , who also use p = 2n. In real-world practice, it may also occur that n > p, e.g. if large investments have been made, which will be explored later. ▪ Due to the lack of precise knowledge of the nonlinear system with quantity discounts, we assume that the retailer has optimised the performance of the system in the linear setting by using Eqs. (A.1) and (A.2) in Appendix A to determine the appropriate safety parameter and guaranteed capacity. In this baseline scenario, this results in δ * = 0.1865 and GC * = 110.77 (units).
In Section 4.1, we analyse the long-term behaviour of the system in the baseline scenario. We aim to gain general insights into the dynamic consequences of the manufacturer's offer of a quantity discount, detecting the key cause-effect relationships motivated by the decision parameter ψ. In Section 4.2, we perform several sensitivity studies with the aim of exploring the impact of the other parameters on the performance of the system. This allows us to gain a greater understanding of the operational and economic effects of quantity discounts in different types of real-world supply chains.
Our analysis is based on simulating the long-term response of the stochastic system. This methodological perspective is aligned with many works that claim that simulation techniques can be a very effective and efficient approach to investigate complex, nonlinear logistics systems (e.g. Iannoni and Morabito, 2006; Chatfield and Pritchard, 2013; Matopoulos et al., 2016; Dominguez et al., 2018; Ponte et al., 2018) . To this end, we have implemented the difference equations defining our supply chain model in MATLAB R2019b. We have carried out simulation runs of 400,000 periods to ensure the repetitiveness and consistency of the results. In each case, we have simulated the supply chain for 41 values of ψ in the interval 0 ≤ ψ ≤ 1, i.e. ψ = {0, 0.025, 0.050, ⋯, 1}, to better perceive the impact of this parameter. NSAmp metrics with the discount acceptance parameter, ψ. To interpret the curves, it is important to recall that ψ = 1 defines the behaviour of the linear system -where the dynamics are not affected by the quantity discount. As it is known that the linear system is characterised by BW = 1 and NSAmp = 1 +Tp = 3 (see Section 3.1), we can observe that for ψ = 1 our nonlinear system behaves as expected. The main finding of Fig. 4 is that decreasing ψ provokes a sharp increase of BW and NSAmp, which is in line with the insights derived in Section 3.2 from the impulse response analysis. That is, pursuing the quantity discount significantly increases the volatility in the operation of the retailer, which would also be transmitted upstream in the supply chain.
A more detailed inspection of Fig. 4 reveals that, in this scenario, the increase of variability is more accentuated for orders (BW) than for inventories (NSAmp). For example, for ψ = 0.8, we see that NSAmp has only marginally increased (from NSAmp = 3) to
NSAmp ≈ 3.1, while BW has strongly risen (from BW = 1) up to BW ≈ 1.5. This result points to the more negative impact of the quantity discount on order variability (which has implications in terms of production smoothness and transportation efficiency, among others) in comparison with inventory variability (with implications on the supply chain ability to satisfy consumer demand in a costefficient way). In this way, our analysis confirms that pricing considerations take a key role in the propagation of the Bullwhip Effect in supply chains; in particular, quantity discounts 'force' echelons to unintentionally amplify the variability in the system. Note that the more willingness of the supply chain nodes to pursue the discount, the higher amplification of the variabilities in the system. Thus, the operational analysis suggests that pursuing the quantity discount will tend to increase both the inventory-related costs (because of the increased NSAmp) and, more noticeably, the Bullwhip-related capacity costs (due to the increase in BW). To analyse the economics of the system, Fig. 5 provides information on the impact of ψ on the inventory-related costs (left) and the capacity costs (right).
The Bullwhip-related costs analysis of Fig. 5 is well aligned with the BW curve in Fig. 4 . In general terms, we observe that reducing ψ significantly increases the capacity costs. For instance, when ψ ≈ 0.625, the capacity costs are the double than in to the linear scenario (ψ = 1). This occurs because decreasing ψ increases both the overtime and the opportunity costs in our supply chain; although it can be noted that the increase in overtime costs is more significant in this baseline scenario. This finding can be easily explained: to pursue the quantity discount, the retailer will need to resort frequently to overtime, given that DQ > GC * . All in all, we conclude that the willingness to pursue the discount provokes a dramatic increase of Bullwhip-related costs in the supply chain, unless the discount is only accepted for product requirements that are quite close to the discount quantity, say, ψ > 0.9.
In relation to inventory costs, it is interesting to note that the quantity discount causes a reduction in backlog costs. In other words, pursuing the discount helps the company achieve higher customer service levels. This also seems reasonable; ordering more than the actual needs to achieve the discounted price protects the supply chain against stock-outs in the near future. However, it is relevant to note that this comes at the expense of a stronger increase in holding costs, which makes that the total inventory-related costs increase as ψ reduces despite the improvement in the service level. In line with the BW vs. NSAmp analyses, the impact of ψ on inventory-related costs is lower in relative terms to that on capacity costs. Indeed, as long as ψ > 0.8 inventory costs are not severely affected by the discount.
Overall, the quantity discount increases the inventory-and Bullwhip-related costs of the retailer. Even so, it may be individually Fig. 6 . Purchase and total costs in the baseline system. rational for this node to pursue the discount due to the reduction in purchase costs. Therefore, to have a complete picture of the effects of the discount, we also need to consider purchase costs. These are represented in Fig. 6 . For the sake of completeness, this figure also includes a curve that expresses the total cost assumed by the retailer -which is the sum of Bullwhip-related, inventory-related, and purchase costs-as a function of the discount acceptance parameter, ψ.
First, Fig. 6 shows that decreasing ψ allows for a significant reduction of purchase costs. Note that the slope of the curve is stronger for high ψ; therefore, the retailer may significantly benefit from reducing the value of the decision parameter ψ from the initial ψ = 1. Also, as we discussed before, the increase in Bullwhip-and inventory-related costs is moderately small for high values of ψ; therefore, it may be profitable to pursue the discount, i.e. to use ψ < 1, despite its negative impact on the operation of the supply chain. In contrast, for low ψ, a further decrease of this parameter provokes a relatively small decrease of purchase costs that comes at the expense of a large increase in Bullwhip-and inventory-related costs. Thus, it would not generally be cost-efficient to set ψ close to ψ = 0.
The previous arguments suggest the existence of an optimal discount acceptance parameter, between ψ = 0 and ψ = 1, which we denote by ψ * . This existence is confirmed by the total cost curve in Fig. 6 , which adopts a convex function form. In this sense, professionals can optimise the performance of their production and distribution systems with quantity discounts by appropriately regulating the decision parameter ψ. In the baseline system, Fig. 6 reveals that the optimal value is ψ * ≈ 0.6. In the next subsection, we will investigate the effect of the different parameters on the dynamics of the system with quantity discounts across with their impact on the optimal calibration of ψ.
First, we address the operational parameters: the standard deviation of consumer demand (σ), the lead time (Tp), and the discount quantity (DQ). Once we have clarified the links of BW and NSAmp with the capacity and inventory-related costs, respectively, our analysis focuses on the BW and NSAmp metrics along with the total costs faced by the retailer. . All three curves tend to BW = 1 and NSAmp = 1 +Tp = 3 as ψ approaches ψ = 1, given that these metrics do not depend on σ in the linear system. In this fashion, the curves diverge as ψ decreases; that is, the impact of demand variability is stronger for lower values of the discount acceptance parameter. It is interesting to note that the negative effects of reducing ψ on BW and NSAmp are attenuated as σ grows, which occurs because these metrics are relative to the variability of demand 9 . For this reason, the discount acceptance parameter that minimises the total costs, ψ * , is a decreasing function of σ: for σ = {10, 25, 40}, ψ * ≈ {0.75, 0.60, 0.45}, respectively. That is, when demand variability is low, managers should use higher values of ψ; otherwise, the system will suffer from a deteriorated dynamics. Fig. 8 shows the same information for three lead-time scenarios defined by Tp = {1, 2,4}, where Tp = 2 represents the previously analysed baseline scenario. Looking at the BW and NSAmp curves, we find that the impact of Tp in the nonlinear system is the same as, or at least very similar to that, in the linear system, i.e. the lead-time effects do not depend noticeably on ψ. Note that BW is not affected by Tp, while NSAmp increases by Tp units as a result of the lead-time effects; please recall that BW = 1 and NSAmp = 1 +Tp in the linear system due to use of MMSE forecasts under i.i.d. demand (see Section 3.1). Finally, the total cost curve shows how reducing Tp allows for a decrease in the costs of the retailer. In this regard, detailed inspection of the graph suggests that ψ * decreases as Tp increases (specifically, for Tp = {1,2,4}, ψ * ≈ {0.65,0.60,0.55}, respectively); nonetheless, the impact of the lead time on the optimal selection of the discount acceptance parameter is lower than for the rest of parameters. Fig. 9 considers the implications of the discount quantity. Together with the baseline scenario defined by DQ = 140, we now use DQ = 120 to represent the case in which the discount quantity is relatively close to the mean demand, and DQ = 180 to illustrate the opposite case. Here, the BW and NSAmp curves reveal that reducing ψ has more damaging consequences on the dynamics of the supply chain for high DQ 10 . This occurs because, when DQ is close to μ, the discount can be often accepted at a relatively low operational cost; however, when DQ ≫ μ, pursuing the discount significantly reduces the smoothness of supply chain operation. Under such circumstances, setting the discount acceptance parameter to low values is more costly in the latter case (i.e. when DQ ≫ μ). This explains why, in the total cost curve, the optimal ψ proves to be an increasing function of DQ; notice that, for DQ = 120, ψ * ≈ 0.5; for DQ = 140, ψ * ≈ 0.6; and for DQ = 180, ψ * ≈ 0.7.
It may also be convenient to consider the particular scenario where DQ < μ. Thereby, Fig. 9 also displays the supply chain with DQ = 80. In line with the preliminary insights discussed in Section 3.2, we now observe that BW reduces as ψ decreases; interestingly, in this case the discount offer has a positive impact on the order dynamics. The same positive effect cannot be observed in terms of NSAmp, but it can be noted that the negative impact of the discount on this metric is lower than for DQ > μ. In such cases, the retailer should opt for unusually low values of the discount acceptance parameter. 9 When ψ decreases, the operational variability becomes heavily influenced by the discount, and hence is more insensitive to σ. Thus, for a given σ, the differences in the numerator of the BWand NSAmp metrics decrease when ψ is reduced (as the discount governs the dynamic of the response); while the denominator is not affected (var(d t ) = σ 2 ); see Eqs. (12) and (13). 10 As discussed, the general rule is that, for a given ψ, the increase of DQ(> μ) results in an increased BW and NSAmp. However, it is interesting to note that when ψ > 0.8, the lowest BW and NSAmp is obtained for the highest DQ(> μ). This occurs given that, when ψDQ > μ +2σ (i.e. when Q > μ+2σ ψ ), the product requirements, pr t , are nearly always lower than the minimum quantity to pursue the discount, ψDQ. This implies that the discount is rarely pursued by the retailer, and hence our nonlinear system behaves very close to the linear one. Now we consider the economic parameters; specifically, the discount offered by the manufacturer in percentage terms, dp, and the four unit costs, {b,h,p,n}. As the curves of the operational metrics do not depend on them, our sensitivity analysis will now directly look at the total cost curve.
The impact of the discount, dp, is represented graphically in Fig. 10 , using dp = {5%,10%,20%}. We can see that increasing dp has positive consequences on the economics of the retailer. Also, the figure reveals that the optimal ψ is very sensitive to dp. As discussed, in the baseline scenario (dp = 10%), ψ * ≈ 0.6. For higher discounts, the retailer should react by setting ψ to very low values with the aim of taking frequent advantage of the discount; note that dp = 20% results in ψ * ≈ 0.2. That is, as dp grows, it seems reasonable to increase the willingness to order DQ in an attempt to minimise purchase costs. In contrast, for lower dp, ψ should take higher values; e. g. dp = 5% results in ψ * ≈ 0.85.
At this point, it is convenient to underline that, while the relationship between the operational metrics (BW and NSAmp) and the discount acceptance parameter (ψ) does not directly depend on the percent discount (dp), it can be expected that dp impacts the operational performance of the system. Note that BW and NSAmp depend on ψ, which in turn should be established by taking dp into account. In this regard, as we have just discussed, supply chain managers should opt for a lower ψ as dp grows. Therefore, for high dp, the dynamics of the supply chain will be more deteriorated, as per Fig. 4 .
Lastly, we study the unit costs, {b,h,p,n}, which in the baseline case adopted the values {2,1,2,1}. The top graphs of Fig. 11 modify the unit costs under the same b/h and p/n ratios. The left one considers b and h. When they grow -which refers to scenarios in which inventories are especially costly, both in terms of holding extra stock and stock-out occurrence-, ψ should take higher values. The right graph, showing p and n, reveals similar insights; we can see that as the cost of order variability increases (for example, when capacity is expensive and inflexible), ψ * grows. Notice, when {b, h} increase from {2, 1} to {4,2}, ψ * grows from 0.6 to 0.7 (approx.); if this happens in {p, n}, ψ * becomes 0.85 (approx.). That is, when the unit costs of holding inventory and backlog or (and) opportunity and overtime are particularly expensive, managers should avoid pursuing the quantity discounts from low orders quantities. Under such circumstances, the operational deterioration of the supply chain response caused by the discount results in a significantly reduced economic performance.
The bottom graphs of Fig. 11 Fig. 5 , which showed that reducing ψ contributes to decreasing backlog costs. Finally, we study {p, n}. We observe that as the p/n ratio is reduced, ψ * increases. Therefore, in practical scenarios in which overtime is much more costly than regular working time, managers should show a higher willingness to pursue the quantity discount. For instance, inspection of the graph reveals that p/n = 0.5 leads to ψ * ≈ 0.7, while p/n = 6 results in ψ * ≈ 0.45.
To sum up, Table 1 provides an overview of the effect of the main characteristic parameters of our production and distribution system on the optimal adjustment of the discount acceptance parameter, ψ * . Interpreting the findings of this table in their specific contexts should provide supply chain managers with valuable information on to what extent they should pursue offers of quantity discounts.
Offering quantity discounts is a common pricing strategy in many industries, through which upstream supply chain members entice their downstream partners to purchase in larger quantities. These pricing mechanisms give rise to meaningful interactions between the marketing and the operations functions of organisations that have been considered to certain extent in previous works. However, the implications of quantity discounts on the dynamics of supply chains have remained largely unexplored, mainly due to the complexity of bringing pricing considerations into the operational analysis.
In this paper, we investigate how the manufacturer's offer of a quantity discount and the retailer's willingness to pursue it affect the operational and economic performance of supply chains. Importantly, we provide evidence of how the quantity discount tends to deteriorate the dynamics of these systems by contributing to the Bullwhip Effect propagation. Issuing orders that do not match the actual requirements of the organisation may greatly distort the transmission of information along supply chains, which negatively impacts not only order variability but also inventory performance. In this sense, we reveal that the quantity discount also hinders the satisfaction of customer demand in a cost-efficient manner. As an exception, we observe that discounts may alleviate the Bullwhip phenomenon when the discount quantity is lower than the mean demand. However, offering the discount under these conditions might not be reasonable for the manufacturer even if that improved the dynamics of the system. Although our study also has valuable implications for offerors of quantity discounts (discussed in the next subsection), we adopt the perspective of a retailer that considers to what extent to pursue the discount offered by the supplier. We observe that, even though the discount increases the inventory-and capacity-related costs of the retailer, it may be reasonable for this node to pursue the discount, given that this would decrease the purchase costs. Importantly, our analysis shows the existence of a U-shaped, convex function that relates the total cost with the retailer's willingness to pursue the discount, which we model through the discount acceptance parameter. In this fashion, practitioners can optimise the economic performance of their system by setting appropriately the decision parameter ψ. In addition, we explore the effect of the rest of operational and economic parameters on the retailer's optimal discount acceptance parameter, leading to practical managerial insights on which we elaborate below.
The reported implications of quantity discounts on the Bullwhip Effect should be carefully taken into consideration by sellers that consider the option of offering them to their customers. For instance, this applies to manufacturers. While quantity discounts have the potential to help manufacturers increase sales revenue and achieve economies of scale, under some circumstances they will make production more instable. In the words of the Lean management paradigm, quantity discounts may contribute to the costly wastes of mura and muri, closely related to the Bullwhip phenomenon.
In the light of these findings, our paper highlights the need for considering the interdependencies among the various business functions when making both strategical and tactical decisions. Otherwise, optimising some processes may occur at the expense of creating meaningful inefficiencies from other perspectives, whose actual impact on business performance tends to be underestimated. This is especially relevant in the management of supply chains, due to their complex and dynamic nature. Thus, our paper should encourage upstream supply chain echelons, such as manufacturers, to explore the indirect and non-immediate consequences of their pricing decisions, as they may result in a significant deterioration of the operational dynamics of their supply chains.
All in all, the unintended operational consequences that quantity discounts create in the supply chain may discourage some manufacturers from offering such discounts to their customers. Others, however, may still opt for the offer of a discount for a wide variety of reasons. In such cases, we would strongly recommend manufacturers to promote the implementation of collaborative practices in their supply chains, as this would significantly alleviate the negative dynamics induced by the discount; for example, those practices based on the synchronisation of supply chain operations, see Ciancimino et al. (2012) . When implementing collaborative practices, the integrative framework for supply chain collaboration developed by Simatupang and Sridharan (2005) may be of special interest for professionals. Now we focus on the perspective of buyers that need to consider whether to modify their replenishment decisions due to the discount offer. Our work reveals that it is fundamental to compare the benefits of quantity discounts, mainly in the form of a reduced purchase price, to the additional costs derived from operating with a higher variability than needed, not only in terms of inventoryrelated costs but also in terms of Bullwhip-related costs. Our results highlight that there is a significant economic benefit in determining the approximate form of their convex curves that relate the total cost with the discount acceptance parameter, ψ -or, equivalently, the minimum quantity from which the discount is accepted.
For obvious reasons, our paper is unable to provide practitioners with the exact form of their curves. However, our sensitivity analysis offers valuable clues for managers on how to accurately 'tune' their decision parameter ψ. In this regard, uncertainty in customer demand plays a key role. Interestingly, managers facing highly uncertain demands should calibrate ψ to lower values. Also, while the lead-time effects are less strong, retailers operating in supply chains with long lead times should set ψ to lower values. Taking both into account, it is interesting to note that inventory managers that need to deal with tougher environmental conditions (characterised by high demand uncertainty and long lead times) should show a higher willingness to pursue the quantity discount offered by their suppliers. The discount percentage as well as the ratio of the discount quantity to the mean demand also have significant implications on the optimal discount acceptance parameter, ψ * . Specifically, ψ * decreases as the discount percentage increases and this ratio reduces. In such cases, it is individually rational to alter the operational dynamics of the supply chain with the aim of taking advantage of the reduced price. In addition, when inventory-and/or capacity-related costs are especially costly for the retailer, managers should prevent from being especially keen to pursue the discount quantity. However, when the relative weight of backlog to holding costs is low (e.g. where storage space is especially costly) and the relative weight of overtime to regular time costs is low (e.g. when overtime working is affordable), retailers should not be reluctant to pursue the discount from relatively low product requirements.
The Bullwhip Effect literature should pay particular attention to the effect of price considerations in this upcoming decade. Despite Lee et al. (1997a,b) pointed out that pricing strategies are one of the major causes of Bullwhip, very little has been investigated so far on how they add to the propagation of this harmful phenomenon, as highlighted by modern reviews of the literature (Bhattacharya and Bandyopadhyay, 2011; Wang and Disney, 2016) . It thus becomes necessary to explore in detail how popular pricing strategies impact supply chain dynamics, such as mark-up pricing, skimming, and penetration pricing. In a related way, it would be interesting to study how the psychology of consumption and pricing (Gourville and Soman, 2002) affects the behavioural causes of the Bullwhip Effect.
Also, the Bullwhip discipline in the 2020 decade will need to be populated with more studies delving into the dynamics of closedloop supply chains. As sustainability acquires a critical importance, the supply chain structure is evolving from linear models, such as the one studied in this paper, to closed-loop variants (e.g. Xiao et al., 2020) . It thus becomes necessary to explore the effect of pricing mechanisms on the performance of these new supply chains that incorporate additional sources of complexity (Goltsos et al., 2019) . Note that important interplays emerge here between the pricing of new and remanufactured products (Atasu et al., 2010 ) that need to be investigated from a dynamic perspective.
Finally, we point out to the emerging concept of organisational resilience, which has gained even more importance during the current COVID-19 pandemic (Ivanov, 2020) . Disruptions provoke a Bullwhip-like phenomenon that is labelled as the Ripple Effect of supply chains (Ivanov et al., 2014) . Investigating the interactions between pricing decisions and disruption propagation is also an area of research worth pursuing, which would yield relevant implications for supply chain professionals.
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Health-related quality of life (HRQoL) assessment is increasingly common among children and adolescents and covers diverse clinical areas including haematology [1] , asthma [2] and rheumatic diseases [3] . In measuring HRQoL among children/adolescents, attention should be given to the selection of suitable HRQoL instruments. This is particularly so if the instrument is to be used outside the culture in which it was developed [4] .
Generally, there are three main approaches to the development of HRQoL instruments for children and adolescents. In the first approach, instruments for children and adolescents were adapted from existing instruments for adults. Given that children and adults have different life experiences and priorities and therefore do not necessarily share the same meaning of health and illness, this approach is likely to be of limited value [5] , unless the developers make conscientious effort to ensure that the contents are valid (i.e. meaningful) and the instruments are reliable (i.e. consistent) for assessment of child HRQoL. The third approach, which we shall discuss later, will be particularly useful for assessing content validity. In the second approach, opinions of 'experts' were sought to select items considered important to children and adolescents for constructing the HRQoL instruments. This approach shares the same limitations as the first in that the choice of items by adult 'experts' is likely to be colored by their own values, experiences and expectations [5] . The last and most desirable approach involves children themselves, sometimes together with parents and healthcare professionals. Unfortunately, few developers have taken this approach. In this approach, children and adolescents were asked directly to report or discuss issues that are important to them. For example, the Children's Dermatology Life Quality Index was developed by asking 169 children and adolescents aged 3-16 years to write down, with help from parents when required, how their skin disease affected their lives. However, this study did not allow for group interactions, which are useful for understanding complex behaviors and motivations behind ideas [6] . Three studies that employed the focus group methodology, which allows for group interaction, in design of HRQoL instruments for children and adolescents were identified. Cramer et al. [7] developed the Quality of Life in Epilepsy Inventory for Adolescents (QOLIE -A) through focus group discussion with adolescents [7] . Content validity of QOLIE-A was reported based on the observation that comments derived from focus group discussions did not reveal new content areas that were not already covered in the questionnaire. However, as the contents used in the focus group are largely derived from adult QoL instruments, framing effects may be of concern here [5] . The Canadian Haemophilia Outcomes -Kids Life Assessment Tool was also developed based on items elicited from focus group discussion involving children and their parents [8] . However, the number of subjects in that study was relatively small. The European KIDSCREEN Group is the largest identified study which involved both sick and healthy children in focus group discussions during the development of HRQoL questionnaires [9] .
The focus group methodology is not new and has been extensively employed in the fields of communications studies, marketing, education and political science amongst others [6] . Morgan defined the focus group as a research technique that collects data through group interaction on a topic determined by the researcher [6] . An important feature of the focus group approach is the 'group effect' where interactions between participants give rise to more information than can be obtained from multiple individual interviews. For a detailed discussion of the inherent strength and limitations of the focus group methodology, readers are referred to the work by Morgan [6] . However, the application of focus group as a research tool in the field of HRQoL is still in its infancy. Eiser and Morse [5] commented that current focus group studies that involved children tended to be poorly described with little detail about how the content of discussion is transformed into questionnaire items. Clearly, better designed studies are needed to demonstrate the value of focus group discussion as a useful tool in constructing HRQoL instruments.
To-date, almost all HRQoL instruments for children and adolescents were developed in Western countries [10] . The extent to which these instruments are useful in Asian children and adolescents remains to be determined. It is a fact that Asians and Westerners view health differently. For example, in East Asia, health is viewed as the maintenance of a balance between Yin and Yang in the body and that illness is a result of an imbalance [11, 12] . However, in the west, illness is perceived as a consequence of an external force, such as a virus or bacteria, or a slow degeneration of the functional ability of the body. As a result, the two cultures may conceptualize HRQoL very differently. Hence, the first objective of this study is to evaluate the extent to which instruments developed based on a Western notion of health are useful among children and adolescents in an Asian country. In addition, some instrument developers designed different age versions of the HRQoL instruments to cater to developmental differences [13] [14] [15] [16] . Boys and girls also undergo significant developmental differences. However, we are not aware of any gender-specific HRQoL instruments for children/adolescents, although such instruments are available in the adults. Hence, the second objective of this study is to evaluate the need to develop separate versions of the questionnaire for children/adolescents and boys/girls.
To determine the extent to which HRQoL questionnaires developed based on the Western notion of health is applicable to Asian children and adolescents in a community-based sample in Singapore. 2. To evaluate the need to develop separate versions of HRQoL instruments for children/ adolescents and boys/girls.
In this community-based study, subjects were recruited from a student-care centre (which provides after-school care for children with working parents), one boy school, one girl school and a mosque in Singapore. Approval for participation in the focus group study was sought from the principals, teachers or person-in-charge regarding recruiting participants for focus group discussions. Participants were selected by the principal, teacher or person-in-charge. The principal, teacher or person-in-charge was encouraged to select the participants by using a random number table. Inclusion criteria were ability to understand English and ability to provide logical answers to questions as assessed by the principal, teacher or person-in-charge. Informed consent was obtained from the parents of all participating subjects. Socio-demograhic variables including age, gender, number of brothers and sisters, ethnicity, grade, type of housing, family income and self-reported health status were collected. The participants were then divided according to their age into children (8-12-years-old) and adolescents (13-16-years-old). A total of eight focus groups was planned with each group comprised of four subjects of the same gender and same-age bracket. The advantage of limiting the group composition to same-gender would be the elimination of any confounding effect of gender on communication [17] . The number of groups, the gender mix and the sample size for the study, were based on the focus group protocol used by the European KIDSCREEN group [9] .
Each discussion was moderated by the same moderator, who was an undergraduate in the final year of Pharmacy course using standardised questionnaire to ensure consistency. The structure of the focus group discussion and the questionnaires used were adopted and modified (with written permission from the developers) from the guidelines used by the European KIDSCREEN group [9, 18] . All sessions were conducted in classroom setting and the participants were seated around a square table. At the beginning of each session, the moderator informed the participants about the objectives and approximate duration of the interview. The moderator also informed the participants that he or she may refuse to answer any questions or stop the interview at any time, that interviews would be anonymous and confidential and that he or she had complete freedom of expression. The session begun with a general question, ''In your opinion, what is important for you in your everyday life to make you feel well?'' and respondents were allowed to talk until no new views were expressed. Throughout the discussion, interference from moderator was kept to the minimal and limited to preventing the participants from digression. The sessions were video-and audio-taped to facilitate content analysis. The reason for recording the interview was communicated to the participants. An abridged transcription of the audio tape recording was carried out by the moderator. The exact expressions used by the participants were conserved in the transcripts. The transcript was checked for accuracy against the video recording by an independent postgraduate student (involved in health outcomes research) who was not involved in the focus group discussion. The video tape was also viewed to observe respondents' behaviour during the course of the discussion
Each focus group session was divided into four sections. A list of questions covering major domains of life (Table 1 ) was provided to help the moderator facilitate the discussion. In Section 1, themes that were spontaneously brought up by the subjects were collected. The contents would thus reflect the meaning of general QoL to children and adolescents. The participants were encouraged to be as specific as possible by means of questions such as ''That is to say?'', ''Can you be more specific?'', ''Can you explain that in more detail?'' or ''How is this manifested in your daily life?''. Participants were free to express their views.
During Section 2 which was more directive, the participants were asked to express physical, psychological and social repercussions related to health status. Hence, the meaning of HRQoL to children and adolescents were addressed in this section. Sample questions were listed in Table 1 . Again, participants were prompted to explain and/ or elaborate on their answers. A 10-minute break followed the conclusion of Section 2. During the break, refreshment was served.
In the next section after the break, a paper-andpencil round, we gathered children and adolescents' opinions on themes extracted from existing Quality of Life scales for children/adolescentsthe KINDL Generic Children's Questionnaire (KINDL) and the Generic Children's Quality of Life Measure (GCQ). A total of 12 themes (mobility, energy, self-esteem, cognitive functioning, friends, family, living condition, autonomy, behaviour, emotions, pain/discomfort and selfcare) were extracted from both questionnaires. Asking participants to comment on all 12 themes would impose tremendous respondent burden. Hence, each participant commented on only a subset of four themes.
A small token of appreciation for their time and contribution was presented to each participant at the conclusion of the focus group session.
The data were analysed based on the grounded theory approach [19] , independently by the moderator and a second investigator (the postgraduate student involved in health outcomes research) who did not attend the focus group discussion. First, major themes related to both general and health-related QoL were extracted from the discussions in Sections 1 and 2. Second, sub-themes were identified and classified under the relevant major themes. Lastly, participants' opinions on existing themes of QoL (Section 3) were examined to evaluate the relative importance assigned to these themes. When the analyses were completed, the moderator and the postgraduate student met up to compare the agreement between the two analyses. Areas of discrepancies were highlighted and resolved through discussion. In the event that the moderator and the postgraduate student were not able to reach a consensus, a neutral third-party would be asked to join in the discussion. All discrepancies must be resolved.
Thirty-two children and adolescents (50% female, 72% Chinese, 19% Malay, 3% Indian and 6% other ethnicities) participated in the focus group discussions. The multi-ethnic makeup of the focus group represents the multi-ethnic nature of the Singaporean population.
Each focus group session lasted an average of 90 min. Some groups of participants (usually the adolescents) preferred to finish all four sections without a break. However, the moderator still gave a 5-min break after Section 2 so that participants would maintain their concentration throughout the study. The two sets of data analyses were in high agreement with each other. Data saturation was observed. Results from the discussion on meaning of general and health-related QoL could generally be grouped under three broad themes: (1) physical, (2) psychological and (3) social health. Within each theme, the discussion could be further classified under sub-themes. From the discussion, we were also able to identify items or events that may be used in the construction of quality of life questionnaires (Table 2) .
Physical health A central theme in the discussion was physical health. Two important sub-themes that emerged were: (1) adoption of health-promoting life-style, and (2) having sufficient sleep. During the discussion, the participants brought up the importance of proper meals, regular exercises, the avoidance of certain types of food (such as fast food and food of too high salt and oil content), and the need of abstinence from alcohol and smoking. Although the participants advocated adoption of healthpromoting behaviour (i.e. healthy diet and regular exercise), a few admitted that they do not practise it. For example, a participant commented that it was very troublesome to stay healthy. Participants also said that having sufficient sleep is very important to their physical health. For example, a participant said that he would feel 'groggy', and another said that she has been feeling tired because of insufficient sleep.
The next major theme that emerged was social health. The impact of family and friends were frequently mentioned throughout the discussion. Friends and family were generally cited as source of support and fun although some participants also expressed some negative views such as nagging mother and disturbing younger siblings. Play was also mentioned as an important component of the participants' social health. One participant said the things he liked best about his life are ''riding bicycle and playing computer games because it is fun''. One participant said that he was happy when he played soccer. Another said that she was happy when she played with her brother. A third participant said that he was glad school holiday was approaching as he would have more time to play. Another interesting aspect arising from the discussion was that the school emerged clearly as an important social interacting environment for the participants. Many of the activities that children and adolescents carried out were within school compound.
Three sub-themes related to psychological functioning were identified from the discussion. These were: (1) positive emotions, (2) negative emotions, and (3) self-esteem. The positive emotions expressed by the participants included 'happy', 'glad' and 'satisfied'. Participants were happy when they scored good grades in school. Holidays, good food and recreational activities were also important for them to feel happy and satisfied. Some participants also reported that they felt happy and satisfied when their material needs (e.g. new toys) were met. The negative emotions that participants expressed included 'stressed', 'bored' and 'depressed'. For example, participants were stressed up with examinations. Some said life was boring as it was preoccupied with lessons and schoolwork. Many participants also felt depressed when they did not perform well in their examinations. Several participants described that conflicts with family members and restrictions of freedom made them unhappy. One of the groups lamented about social insecurity brought about by terrorism and the recent severe acute respiratory syndrome (SARS) epidemic. Discussion related to self-esteem included fear of rejection by friends and fear of failing examinations. Some participants were also concerned about their appearance and peoples' opinions of them. Again, school (or more accurately academic performance) featured rather prominently in psychological health.
The meaning of HRQoL to our study participants may similarly be divided into three major themes: physical, psychological and social health ( Table 2) .
When the participants were asked to discuss about the changes that occurred when a child/adolescent fell ill, two important sub-themes emerged: (1) restriction in activities and (2) effects of medications.
The main impact of illness on physical health was restriction of activities. Typically, the response from children and adolescents could be summarised as follows:
''Because have to rest all day, can't play. Cannot do anything, sleep everyday.'' (Child) ''Can't go around doing stuff.'' (Adolescent)
Medications have mixed effects on participants' physical health. In general, the participants considered taking medication as an unpleasant task. Some participants complained that the medications were too sweet (with specific reference to cough syrup) while others complained that the medications were too bitter (with specific reference to traditional Chinese medicine). Interestingly, some participants said they like their medicines because they tasted sweet. Participants also complained that they felt very tired, drowsy, lethargic and have problems concentrating after taking certain medications.
Illness was also perceived to negatively affect social interactions. For example, some participants commented that friends might avoid them because of fear of catching the disease. Others commented that they could not go out to play with friends and they could not communicate well when they fell ill. There was also the fear of missing lessons due to absence from school.
The greatest impact of illness appeared to be on psychological health. Many participants said that they felt 'miserable', 'down', 'frustrated', 'sad' and some even cried when they fell sick. One participant also revealed the fear of death. Generally, the repercussions of falling ill were perceived as increase in homework load due to absence from school and falling behind others in academic performance.
Some differences in contents and intensity of discussion between children and adolescents were observed. First, children and adolescents assigned different level of importance to the three broad domains of health. For instance, when asked ''What is important for you in your everyday life to make you feel well?'', children only talked about physical health. Adolescents, on the other hand, discussed physical, psychological and social health. In another instance, when participants were asked ''When do you feel healthy?'', children again referred only to physical aspect of health (e.g. after exercise, with healthy diet, when not sick, etc). Adolescents, however, referred to both physical and psychological aspects of health (e.g. when not feeling stressed, when not sick, when happy, after exercise, etc).
Second, we observed that children reported positive emotions more frequently than adolescents. For example, in expressing their general QoL, children described more positive emotions, using terms such as 'happy', 'excited' or 'glad'. On the other hand, adolescents expressed more negative emotions, using terms such as 'depressed', 'stressed' and 'tired'. Related to this observation, adolescents discussed the importance of having sufficient sleep a lot more often than children.
Third, adolescents were very mindful of others' opinions. They worried about their physical appearances and body images. On the contrary, none of the children discussed anything related to appearance.
Fourth, we also observed that the social activities of children were limited to family and school while adolescents had a wider range of social activities. For example, adolescent girls talked about going for movies or baking cookies together with friends and adolescent boys talked about going for sports training.
Fifth, children expressed fear for the metaphysical unknown, including darkness, ghosts and being alone. Adolescents, on the other hand, conceptualized fears in terms of failure and rejection rather than the metaphysical unknowns. One group of adolescent boys even claimed that they did not have any fears. In relation, children said they were scared to see doctors or dentists while adolescents said that they had grown out of the fear. A common expression used was ''I used to be scared of doctors but now I'm used to it.'' Lastly, when children were asked to think about their future, they considered both the immediate (e.g. school results) and the distant future (i.e. their ambitions). Some even made considerations on financially supporting their family. The adolescents, in contrast, considered only the distant future (e.g. ambitions, marriage and family planning as well as financial planning). Interestingly, some of the adolescent boys said that ''there is no need to think about the future because nobody knows what is going to happen''.
We observed fewer gender differences in conceptualization of general and health-related QoL. The main differences between the two genders occurred at the item level, that is, the kind of activities that participants described. For example, boys would describe activities such as playing sports (in particular, soccer and swimming) and computer games while girls would describe a different set of activities, e.g. chatting over the telephone, dancing, shopping, baking cookies, going to movies, etc.
From the discussion, the participants demonstrated fairly good health knowledge, despite their age. For example, they knew that exercise would make their hearts pump faster. They also knew that reduction in salt intake was necessary for people with their kidney problems. This demonstrates that we have a well-informed group of participants who are likely to provide reliable information. It was interesting to know that some participants have very negative and not necessarily correct perceptions of healthcare providers. Some comments made during the study included ''(I am) very scared; scared that the doctor say I'd need operation. Very nervous, sad, nervous like anything. My sister always cries, cries, cries. She is a cry baby. Maybe the doctors will take our life away (Laugh). When they do operations, they may kill us. They may cut our kidneys accidentally (Laugh). They will inject us, very painful. The doctor may be a murderer. (Laugh)''
In this study, we attempted to understand the meaning of general and health-related quality of life from the perspectives of children and adolescents in an Asian country and to evaluate similarities and differences in conceptualization of QoL between Asian and Western children/adolescents. Singapore is a very westernized multi-ethnic Asian society and thus serves as an excellent test case for the purpose of this study. The Singapore healthcare system is benchmarked against the British and the U.S. systems and is rated as the sixth most effective healthcare system in the world [20] . At the same time, traditional medicine and Asian philosophy of health is deeply entrenched in the lives of Singaporeans. If the notion of HRQoL in Singaporean children and adolescents were found to be very different from Western children and adolescents, the difference will likely be amplified in other Asian countries. This will then have serious implications for multi-national trials in Asia which incorporates HRQoL as an outcomes measure, not to mention the use of HRQoL in measuring clinical response and disease progression.
The results of this study suggest that there is a 'universal' concept of HRQoL among children and adolescents across the globe. The meaning of general and health-related QoL to Singaporean children and adolescents may be categorised into three broad domains of physical, psychological and social which falls in line with the current widely used definition of HRQoL [21] . The cate-gories and item meanings within each domain ( Table 2) were also strikingly similar to the contents of currently available generic HRQoL instruments for children and adolescents [22] , although minor and important differences exist. Hence, our findings suggest an exciting possibility that existing HRQoL instruments for children and adolescent are potentially useful in the Asian population. A primary concern in the use of HRQoL instruments across different cultures is the issue of conceptual equivalence [23] . The issue of whether the two different cultures conceptualize HRQoL similarly needs to be addressed before meaningful translation or adaptation of the instruments can take place. This study has thus provided empirical support for cross-cultural adaptation of existing HRQoL instruments for children and adolescents in an Asian country, rather than reinventing the wheel to develop new instruments.
However, we did observe that our study participants assigned different weights to the three dimensions of QoL in consideration of the absence or presence of illness. For example, discussion on general QoL tended to focus on physical aspect of health while discussion of HRQoL centred on psychological aspect. The results suggest that falling ill will have greatest impact on psychological well-being of children and adolescents. Therefore, care-givers of children and adolescent with newly-diagnosed chronic medical conditions should pay careful attention to their psychological well-being.
We have also observed developmental differences between children and adolescents in the conceptualization of QoL and these were similar to other published studies [24, 25] . For example, younger children had limited discussion of subjective dimensions of QoL, emphasizing more on the physical aspects of QoL [24] . In addition, certain words carry different connotations for children and adolescents, e.g. fear and future. The immediate social context surrounding children and adolescents were also found to be different, with the latter having a wider social circle. With respect to the observation that children use positive descriptions more often than adolescents, a related finding was made in an earlier study where Singaporean children were found to have better QoL than adolescents [26] . A possible explanation de-rived from the focus group discussions was that academic pressure took a greater toll on adolescents than children. Our findings thus support the current practice of developing HRQoL instruments catered for different age groups [13] [14] [15] . However, further research is needed to understand the influence of developmental changes on HRQoL. For example, in longitudinal studies evaluating effectiveness of programs or interventions to improve health status, expected improvements in HRQoL may not be observed if changes that have occurred in the transition from childhood to adolescents diminished HRQoL. This phenomenon is known as response shift. Sprangers and Schwartz defined response shift as a change in the meaning of one's self-evaluation of a target construct as a result of (a) a change in the respondents' internal standards of measurement, (b) a change in the respondents values or (c) a redefinition of the target construct [27] . Developmental changes may contribute to any of the three components of response shift. Further research is needed to understand the mechanisms by which the process of growing up actually changes an individual's internal standards of measurement, values and conceptualization of QoL.
Compared to developmental differences, gender differences were less important in our study. Boys and girls share highly similar concepts of health and illness. They also engage in many common activities. Hence, different versions of HRQoL instruments for boys and girls are unnecessary, at least in this community-based sample of children and adolescents in an Asian country.
In this study, we have chosen to use the focus group approach to answer our research questions. The focus group methodology has been very useful in providing us with an opportunity to 'hear' the true voice of our target audience. This helped to take out the guess work in developing HRQoL instruments for this demographic subgroup. The merit of this approach lies in its generalizability to the general population since health concepts were directly elicited from the population of interest. In addition, other information that we derived from the focus group, although seemingly unrelated, may be useful in future hypotheses generation.
We recognized the limitations of this study. First, we would have benefited from the expertise of an more experienced moderator. However, as quality of life is a developing research field in this country, people with knowledge in both focus group and QoL are hard to come by. To ensure the highest data quality, our moderator was trained in using an established protocol and mock focus group discussions were performed before the actual study. Second, the sample was selective. We left it to the principals, teachers or persons-incharge to select the participants. This potentially could introduce bias. Nevertheless, we did achieve a good mix in terms of ethnicity and socioeconomic background (based on the type of family dwelling). Third, by including participants of different ethnicities, we are assuming that there are no cultural differences in the conceptualization of HRQoL among these ethnic groups. This assumption needs to be tested in future studies. However, during the course of analysis, we did not observe any blatant differences in the discussion by participants of different ethnicities.
Building on the findings of this study, we would like to propose that future focus group discussion involve younger children (less than 8 years) as there is currently a paucity of QoL instruments suitable for this age group. Younger children are likely to be limited in their ability to express themselves clearly in writing. Hence, the focus group methodology will be very useful in this instance. In addition, it will be useful to involve parents in focus group discussions on QoL so that we can gain a better understanding of the points of departure between parents' and their children's conceptualization of QoL. This would give us a better appreciation of the proxy problem mentioned earlier in the introduction. Furthermore, we would suggest expanding the focus group discussions to children with chronic illnesses. In this study, we have recruited children from the general population, which was necessary because discussions involving only sick children are likely to be biased towards those areas of health that were impaired by their medical conditions. For example, sick children are likely to experience pain and discomfort more than healthy children. In future studies involving sick children, this bias may potentially be reduced by involving groups of sick children representative of the local epidemiology of childhood diseases. Doing so would however incur substantial time and resources, which is not always feasible. Nevertheless, this is certainly worth pursuing in the future.
A remarkably similar conceptualization of HRQoL between our study participants and other Western children was found. This suggests an exciting possibility of a 'universal' concept of HRQoL among Asian and Western children and adolescents. However, this needs to be determined in a larger sample in Singapore as well as in other Asian countries which are less westernised compared to Singapore. In addition, minor but important differences were found in the weights that our study participants assigned to the three broad domains of QoL (physical, psychological and social) in the presence or absence of illness. It will be interesting to study if the same differences would be observed in other Asian study samples. Future focus group discussion could also be extended to younger children and parents with children in childhood or adolescence.
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The severe respiratory disease COVID-19 was first noticed in late December 2019 (1) . It rapidly became epidemic in China, devastating public health and finance. By mid-March, COVID-19 had spread to ~150 countries and infected over 150,000 people (2) . On March 11, 2020 , the World Health Organization (WHO) officially declared it a pandemic.
A complete genome sequence of the etiological agent of COVID-19 (3), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (4), identified it as a new member of the genus Betacoronavirus, which include a diverse reservoir of coronaviruses (CoVs) isolated from bats (5-7). While genetically distinct from the betacoronaviruses that cause SARS and MERS in humans (8, 9) , SARS-CoV-2 shares the highest level of genetic similarity (96.3%) with CoV RaTG13, sampled from a bat in Yunnan in 2013 (8) . Recently, CoV sequences closely related to SARS-CoV-2 were obtained from confiscated Malaya pangolins in two separate studies (10, 11) . Pangolin SARS-like CoVs (Pan_SL-CoV) form two distinct clades corresponding to their collection location. Pan_SL-CoV_GD from Guangdong (GD) province in China and are genetically more similar to SARS-CoV-2 (91.2%) than Pan_SL-CoV_GX from Guangxi (GX) province (85.4%).
Understanding the origin of SARS-CoV-2 may help resolve strategies to deter future crossspecies transmissions and to establish appropriate animal models. Viral sequences nearly identical to SARS and MERS viruses were found in civets and domestic camels, respectively (12, 13) , demonstrating that they originated from zoonotic transmissions with intermediate host species between the bat reservoirs and humans-a common pattern leading to CoV zoonosis (5). Viruses nearly identical to SARS-CoV- 2 have not yet been found. In this paper we demonstrate, through localized genomic analysis, a complex pattern of evolutionary recombination between CoVs from distinct host species and cross-species infections that likely originated SARS-CoV-2.
Phylogenetic analysis of 43 complete genome sequences from three clades (SARS-CoVs and bat_SL-CoVs; SARS-CoV-2, bat_SL-CoVs and pan_SL-CoVs; and two divergent bat_SL-CoVs) within the Sarbecovirus group (9) confirms that RaTG13 is overall the closest sequence to SARS-CoV-2 (fig. S1). It is followed by Pan_SL-CoV_GD viruses next, and then Pan_SL-CoV_GX. Among the bat-CoV sequences in clade 2 ( fig. S1 ), ZXC21 and ZC45, sampled from bats in 2005 in Zhoushan, Zhejiang, China, are the most divergent, with the exception of the beginning of the ORF1a gene (region 1, fig. 1A ). All other Bat_SL-CoV and SARS-CoV sequences form a separate clade 3, while clade 1 comprises BtKY72 and BM48-31, the two most divergent Bat_SL-CoV sequences, in the Sarbecovirus group ( fig. S1 ). Recombination in the first SARS-CoV-2 sequence (Wuhan-Hu-1) with other divergent CoVs has been previously observed (3) . Here, to better understand the role of recombination in the origin of SARS-CoV-2 among these genetically similar CoVs, we compare Wuhan-Hu-1 to six representative Bat_SL-CoVs, one SARS-CoV, and the two Pan_SL-CoV_GD sequences using SimPlot analysis (14) . RaTG13 has the highest similarity across the genome (8), with two notable exceptions where a switch occurs ( fig. 1A ). In phylogenetic reconstructions, SARS-CoV-2 clusters closer to ZXC21 and ZC45 than RaTG13 at the beginning of the ORF1a gene (region 1, fig. 1B) , and, as reported (10, 15) , to a Pan_SL-CoV_GD in region 2 (fig.s 1C and S2), which spans the receptor angiotensinconverting enzyme 2 (ACE2) binding site in the spike (S) glycoprotein gene. Comparing Wuhan-Hu-1 to Pan_SL-CoV_GD and RaTG13, as representative of distinct host-species branches in the evolutionary history of SARS-CoV-2, using the recombination detection tool RIP (16), we find significant recombination breakpoints before and after the ACE2 binding site ( fig. S2A ), suggesting that SARS-CoV-2 carries a history of cross-species recombination between the bat and the pangolin CoVs.
Pan_SL-CoV sequences are generally more similar to SARS-CoV-2 than CoV sequences, other than RaTG13 and ZXC21, but are more divergent from SARS-CoV-2 at two regions in particular: the beginning of the ORF1b gene and the highly divergent N terminus of the S gene (regions 3 and 4, respectively, fig. 1A ). Within-region phylogenetic reconstructions show that Pan_SL-CoV sequences become as divergent as BtKY72 and BM48-31 in region 3 ( fig. 1D ), while less divergent in region 4, where Pan_SL-CoV_GD clusters with ZXC21 and ZC45 (fig . 1E ). Together, these observations suggest ancestral cross-species recombination between pangolin and bat CoVs in the evolution of SARS-CoV-2 at the ORF1a and S genes. Furthermore the discordant phylogenetic clustering at various regions of the genome among clade 2 CoVs also supports extensive recombination among these viruses isolated from bats and pangolins.
The SARS-CoV-2 S glycoprotein mediates viral entry into host cells and therefore represents a prime target for drug and vaccine development (17, 18) . While SARS-CoV-2 sequences share the greatest overall genetic similarity with RaTG13, this is no longer the case in parts of the S gene. Specifically, amino acid sequences of the receptor binding motif (RBM) in the C terminal of the S1 subunit are nearly identical to those in two Pan_SL-CoV_GD viruses, with only one amino acid difference (Q498H)-although the RBM region has not been fully sequenced in one of Guangdong pangolin virus (Pan_SL-CoV_GD/P2S) ( fig. 2A ). Pangolin CoVs from Guangxi are much more divergent. Phylogenetic analysis based on the amino acid sequences of this region shows three distinct clusters of SARS-CoV, SARS-CoV-2 and bat-CoV only viruses, respectively ( fig. 2B ). Interestingly, while SARS-CoV and SARS-CoV-2 viruses use ACE2 for viral entry, all CoVs in the third cluster have a 5-aa deletion and a 13-14-aa deletion in RBM ( fig. 2A)
Although both SARS-CoV and SARS-CoV-2 use the human ACE2 as their receptors (8, 20) they show a high level of genetic divergence (figs. 1 and S1). However, structures of the S1 unit of the S protein from both viruses are highly similar (21) (22) (23) , with the exception of a loop, not proximal to the binding site, that bends differently ( fig. 2C ). This suggests that viral entry through binding of ACE2 is structurally constrained to maintain the correct conformation. Among 17 distinct amino acids between SARS-CoV-2 and RaTG13 ( fig. 2A ), five contact sites are different, likely impacting RaTG13's binding to ACE2 ( fig. 2D and Table S1 ). The single amino acid difference (Q or H at position 498) between SARS-CoV-2 and Pan_SL-CoV_GD is at the edge of the ACE2 contact interface; neither Q or H at this position form hydrogen bonds with ACE2 residues ( fig. 2E ). Thus, a functional RBM nearly identical to the one in SARS-CoV-2 is naturally present in Pan_SL-CoV_GD viruses. The very distinctive RaTG13 RBM suggests that this virus is unlikely to infect human cells, and that the acquisition of a complete functional RBM by a RaTG13-like CoV through a recombination event with a Pan_SL-CoV_GD-like virus enabled it to use ACE2 for human infection.
Three small insertions are identical in SARS-CoV-2 and RaTG13 but not found in other CoVs in the Sarbecovirus group (24) . The RaTG13 sequence was sampled in 2013, years before SARS-CoV-2 was first identified. It is unlikely that both SARS-CoV-2 and RaTG13 independently acquired identical insertions at three different locations in the S gene. Thus, it is plausible that an RaTG13-like virus served as a progenitor to generate SARS-CoV-2 by gaining a complete human ACE2 binding RBM from Pan_SL-CoV_GD-like viruses through recombination. Genetic divergence at the nucleic acid level between Wuhan-Hu-1 and Pan_SL-CoV_GD viruses is significantly reduced from 13.9% ( fig. 1E ) to 1.4% at the amino acid level ( fig. 2B ) in the RBM region, indicating recombination between RaTG13-like CoVs and Pan_SL-CoV_GD-like CoVs. Furthermore, SARS-CoV-2 has a unique furin cleavage site insertion (PRRA) not found in any other CoVs in the Sarbecovirus group (24), although similar motifs are also found in MERS and more divergent bat CoVs (25) (Fig. S3 ). This PRRA motif makes the S1/S2 cleavage in SARS-CoV-2 much more efficiently than in SARS-CoV and may expand its tropism and/or enhance its transmissibility (23) . A recent study of bat CoVs in Yunnan, China, identified a three-amino acid insertion (PAA) at the same site (26) . Although it is not known if this PAA motif can function like the PRRA motif, the presence of a similar insertion at the same site indicates that such insertion may already be present in the wild bat CoVs. The more efficient cleavage of S1 and S2 units of the spike glycoprotein (25) and efficient binding to ACE2 by SARS-CoV-2 (22, 27) may have allowed SARS-CoV-2 to jump to humans, leading to the rapid spread of SARS-CoV-2 in China and the rest of the world.
Recombination from Pan_SL-CoV_GD at the RBM and at the unique furin cleavage site insertion prompted us to examine the SARS-CoV-2 sequences within these regions. Amino acid sequences from SARS-CoV-2, RaTG13, and all Pan_SL-CoV viruses are identical or nearly identical before, between, and after the RBM and the furin cleavage site, while all other CoVs are very distinctive ( fig. 3A and S3) . The average of all pairwise dN/dS ratios (w) among SARS-CoV-2, RaTG13, and Pan_SL-CoV viruses at the 3'-end of the S gene (after the furin cleavage site) is 0.013, compared to w =0.05 in the S region preceding the furin cleavage site, and to w =0.04 after the site for all other CoVs. The much lower w value at the 3'-end of the S gene among the SARS-CoV-2, RaTG13, and Pan_SL-CoV viruses indicates that this region is under strong purifying selection within these sequences ( fig. 3A) . A plot of synonymous and nonsynonymous substitutions relative to Wuhan-Hu-1 highlights the regional differences across the region before and after the RBM and the furin cleavage site ( fig. 3A) : the 3' end of the region is highly conserved among the SARS-CoV-2, RaTG13, and Pan_SL-CoV viruses (Group A), while far more nonsynonymous mutations are observed in the rest of the CoV sequences (Group B). The shift in selective pressure in the 3' -end of the gene among these related viruses versus other CoVs begins near codon 368 ( fig. 3B ), and such a shift was not evident among other compared CoVs ( fig. 3B-D) .
We observe similar patterns of purifying selection pressure in other parts of the genome, including the E and M genes, as well as the partial ORF1a and ORF1b genes ( fig. 4) . Interestingly, the purifying selection pressure varies among different viruses depending on which genes are analyzed. The broadest group includes SARS-CoV-2, RaTG13, all Pan_SL-CoV and the two bat CoVs (ZXC21 and ZC45) for both E and M genes (figs. 4 and S5). The second group includes SARS-CoV-2, RaTG13, and all Pan_SL-CoV only for the 3' end of the S gene. The narrowest selection group only contains SARS-CoV-2, RaTG13, and pangolin CoVs from Guangdong for the partial regions of ORF1a and ORF1b (figs. 4 and S6). Consistently low ω values and strong purifying selection pressure on SARS-CoV-2, RaTG13 and Pan_SL-CoV_GD viruses suggest that these complete and partial genes are under similar functional/structural constraints among the different host species. In two extreme cases, amino acid sequences of the E gene and the 3' end of ORF1a are identical among the compared CoV sequences, although genetic distances are quite large among these viruses at the nucleic acid level. Such evolutionary constraints across viral genomes, especially at functional domains in the S gene, which plays an important role in cross-species transmission (5, 17), coupled with frequent recombination, may facilitate cross-species transmissions between RaTG13-like bat and/or Pan_SL-CoV_GD-like viruses.
Previous studies using more limited sequence sets found that SARS-CoVs originated through multiple recombination events between different bat-CoVs (10, 17, 19, 28, 29) . Our phylogenetic analyses of individual genes show that SARS-CoV sequences tend to cluster with YN2018B, Rs9401, Rs7327, WIV16 and Rs4231 (group A) for some genes and Rf4092, YN2013, Anlong-112 and GX2013 (group B) for others ( fig. S7 ). SimPlot analysis using both groups of bat_SL-CoVs and the closely related bat CoV YNLF-34C (29) shows that SARS-CoV GZ02 shifts in similarity across different bat SL-CoVs at various regions of the genome (fig. 5A ). In particular, phylogenetic reconstruction of the beginning of ORF1a (region 1) confirms that SARS-CoVs cluster with YNLF-34C (29) , and this region is distinctive comparing to all other CoVs ( fig. 5B ). YNLF-34C is more divergent from SARS-CoV than other bat-CoV viruses before and after this region, confirming the previously reported complex recombinant nature of YNLF-34C (29) ( fig. 5A ). At the end of the S gene (region 2), SARS-CoVs cluster with group A CoVs, forming a highly divergent clade ( fig. 5C ). In region 3 (ORF8), SARS-CoVs and group B CoVs, together with YNLF-34C, form a very divergent and distinctive cluster ( fig. 5D ). To further explore the recombinant nature of SARS-CoVs, we compared GZ02 to representative bat CoV sequences using the RIP recombination detection tool (16) . We identified four significant breakpoints (at 99% confidence) between the two parental lineages ( fig. S8A ), further supported by phylogenetic analysis ( fig. S8B-S8D ). In addition, the two aforementioned groups of bat CoVs (shown in light brown and light blue in the trees) show similar cluster changes across the five recombinant regions, suggesting multiple events of historic recombination among bat SL-CoVs. These results demonstrate that SARS-CoV shares a recombinant history with at least three different groups of bat-CoVs and confirms the major role of recombination in the evolution of these viruses.
Of the bat SL-CoVs that contributed to the recombinant origin of SARS-CoV, only group A viruses bind to ACE2. Group B bat SL-CoVs do not infect human cells (5, 19) and have two deletions in the RBM (figs. 1E and 2A). The short deletion between residues 445 and 449, and in particular the loss of Y449, which forms three hydrogen bonds with ACE2, will significantly affect the overall structure of the RBM (figs. 2F and 2E). The region encompassing the large deletion between residues 473 and 486 contains the loop structure that accounts for the major differences between the S protein of SARS-CoV and SARS-CoV-2 ( fig. 2C ). This deletion causes the loss of contact site F486 and affects the conserved residue F498's hydrophobic interaction with residue M82 on ACE2 (fig. 2F ). These two deletions will render RBM in those CoVs incapable to bind human ACE2. Therefore, recombination may play a role in enabling cross-species transmission in SARS-CoVs through the acquisition of an S gene type that can efficiently bind to the human ACE2 receptor.
ORF8 is one of the highly variable genes in coronaviruses (5, 17, 29) and its function has not yet been elucidated (5, 17, 30) . Breakpoints within this region show that recombination occurred at the beginning and the end of ORF8 ( fig. S9) , where nucleic acid sequences are nearly identical among both SARS-CoVs and group B bat CoVs. Moreover, all compared viruses form three highly distinct clusters ( fig. 5D ), suggesting that the ORF8 gene may be biologically constrained and evolves through modular recombination. The third recombination region at the beginning of ORF1a is where SARS-CoV-2 also recombined with other bat CoVs (region 1, fig. 1A ). This region is highly variable (5, 17) and recombination within this part of the genome was also found in many other CoVs, suggesting that it may be a recombination hotspot and may factor into cross-species transmission.
There are three important aspects to betacoronavirus evolution that should be carefully considered in phylogenetic reconstructions among more distant coronaviruses. First, there is extensive recombination among all of these viruses (10, 17, 19, 28, 29) (figs. 1 and 5), making standard phylogenetic reconstructions based on full genomes problematic, as different regions of the genome have distinct ancestral relationships. Second, between more distant sequences, synonymous substitutions are often fully saturated, which can confound analyses of selective pressure and add noise to phylogenetic analysis. Finally, there are different selective pressures at work in different lineages, which is worth consideration interpreting trees.
The currently sampled pangolin CoVs are too divergent from SARS-CoV-2 for them to be SARS-CoV-2 progenitors, but it is noteworthy that these sequences contain an RBM that can most likely bind to human ACE2. While RaTG13 is the most closely related CoV sequence to SARS-CoV-2, it has a distinctive RBM, which is not expected to bind to human ACE2. SARS-CoV-2 has a nearly identical RBM to the one found in the pangolin CoVs from Guangdong. Thus, it is plausible that RaTG13-like bat-CoV viruses may have obtained the RBM sequence binding to human ACE2 through recombination with Pan_SL-CoV_GD-like viruses. We hypothesize that this, and/or other ancestral recombination events between viruses infecting bats and pangolins, may have had a key role in the evolution of the strain that lead to the introduction of SARS-CoV-2 into humans.
All three human CoVs (SARS, MERS and SARS-2) are the result of recombination among CoVs. Recombination in all three viruses involved the S gene, likely a precondition to zoonosis that enabled efficient binding to human receptors (5, 17). Extensive recombination among bat coronaviruses and strong purifying selection pressure among viruses from humans, bats and pangolin may allow such closely related viruses ready jump between species and adapt to the new hosts. Many bat CoVs have been found able to bind to human ACE2 and replication in human cells (10, 19, (31) (32) (33) . Serological evidence has revealed that additional otherwise undetected spillovers have occurred in people in China living in proximity to wild bat populations (34) . Continuous surveillance of coronaviruses in their natural hosts and in humans will be key to rapid control of new coronavirus outbreaks.
So far efforts have failed to find the original pathway of SARS-CoV-2 into humans by identifying a coronavirus that is nearly identical to SARS-CoV-2, as those found for SARS and MERS in civets and domestic camels respectively (12, 13) . However, if the new SARS-CoV-2 strain did not cause widespread infections in its natural or intermediate hosts, such a strain may never be identified. The close proximity of animals of different species in a wet market setting may increase the potential for cross-species spillover infections, by enabling recombination between more distant coronaviruses and the emergence of recombinants with novel phenotypes. While the direct reservoir of SARS-CoV-2 is still being sought, one thing is clear: reducing or eliminating direct human contact with wild animals is critical to preventing new coronavirus zoonosis in the future.
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Coronavirus disease 2019 (COVID- 19) , the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first described in Wuhan, China in December 2019 and rapidly evolved into a worldwide pandemic [1] . Of patients affected with the virus, approximately 5% to 14% will become critically ill [2] [3] [4] . While COVID-19 generally begins as a respiratory tract infection, it can have damaging effects on every organ system. When the virus does spread systemically, the result is often multisystem critical illness associated with a high risk of death. Higher sequential organ failure assessment (SOFA) scores have been associated with increased mortality in critically ill patients with COVID-19 [5] . It is important that clinicians managing these critically ill patients be aware of the multisystem impact of the disease so that care can be focused on the prevention of end-organ injuries to potentially improve clinical outcomes. Here, we review the multisystem complications of COVID-19 and treatment strategies to improve the care of critically ill COVID-19 patients.
The multisystem manifestations of COVID-19 (Figures 1-3) result from a combination of the direct effects of the viral infection and the indirect effects of the body's significant inflammatory response to the virus. Post mortem findings in COVID-19 patients show viral elements within endothelial cells, an accumulation of inflammatory cells, and cellular apoptosis in multiple organs [6] . These widespread effects largely reflect the virus' ability to use the angiotensinconverting enzyme 2 (ACE2) receptors to gain entry into endothelial cells [7] . ACE2 breaks down angiotensin II, a pro-inflammatory factor in the lung, and viral inhibition of this enzyme may also be a contributing factor to the lung injury and multiorgan dysfunction that result from SARS-CoV-2 infection [8] . The indirect effects of the virus result from the host's response to the viral infection, and are associated with a cytokine storm characterized by very high circulating levels of pro-inflammatory cytokines, including tumor necrosis factor (TNF)-α, interleukins, granulocyte-colony stimulating factor, and chemokines [9] . This hyper-inflammatory response combined with hypercoagulability [10] can lead to venous thromboembolism, further increasing the risk of multisystem failure and mortality.
The severity of COVID-19-related respiratory disease varies significantly, from mild symptoms requiring minimal oxygen support with nasal cannula to acute hypoxemic respiratory failure requiring intubation and mechanical ventilation. For about 80% of the patients, the disease will be mild and mostly restricted to the upper airways. The remaining 20% of the patients will develop pulmonary infiltrates as the virus reaches the alveoli, where it preferentially infects the peripheral and subpleural units [4] .
In an earlier phase of the disease, patients often show preserved lung mechanics with normal compliance, despite having severely impaired oxygenation and increased minute ventilation [11] . There have been a number of phenotypes that have been proposed to characterize COVID-19 pneumonia (i.e. 'L' vs 'H' phenotype), however, these phenotypes are controversial [12] . On CT imaging, ground-glass opacities are seen in up to 98% of the patients, which commonly suggests interstitial, rather than alveolar, edema. These characteristics have been categorized as 'type L' and include a low lung elastance, low recruitability, and a poor response to positive end-expiratory pressure (PEEP). In some patients, the disease progresses into a clinical scenario that resembles typical acute respiratory distress syndrome (ARDS), which may be due to the development of ventilator-induced lung injury, worsening of COVID-19 disease, or bacterial superinfection [13] . These patients are found to have high lung elastance, extensive consolidations on CT imaging, and significant response to higher PEEP. These lung findings are categorized as 'type H.' Standard lung-protective ventilation should be used for all stages of the disease, despite the wide spectrum of clinical characteristics.
There has been significant debate regarding the optimal form of respiratory support for non-intubated patients with increasing oxygen requirements and dyspnea. Early intubation has been encouraged to reduce the risk of virus aerosolization and self-induced lung injury. However, early intubation may result in unnecessary intubation of patients who would have otherwise improved with less invasive support [14] . Other strategies that may improve ventilation in these patients include prone positioning and nitric oxide, which is being tested both as an antiviral agent and for its benefits as a pulmonary vasodilator. While prone positioning in awake spontaneously breathing patients is generally well tolerated and has been shown to improve oxygenation and reduce respiratory rate, the effects on clinical outcomes is unclear [15] . The use of noninvasive ventilation and high flow nasal cannula in COVID-19 patients is controversial given the potential risk for aerosolization and exposure to health care workers, and can be minimized when delivered in a negative pressure environment. In-hospital airway management is challenging and we have previously described a practical, stepwise protocol for safe in-hospital airway management in COVID-19 patients [16] .
COVID-19 has profound effects on the hematologic system. Lymphopenia is a characteristic laboratory finding in COVID-19 patients and has prognostic potential in determining severe cases [17] . Throughout the disease course, serial monitoring of lymphocyte count dynamics and inflammatory indices such as lactate dehydrogenase, C-reactive protein, and interleukin-6, may allow identification of patients with poor prognosis and trigger timely intervention. Other biomarkers, including high serum procalcitonin and ferritin, have emerged as poor prognostic factors [5] .
Patients with COVID-19 infection present a complicated clinical paradigm as current research has suggested that they are at risk of both impaired hemostasis as well as thrombotic events. Elevated fibrinogen and D-dimer levels are the most common coagulopathy seen in hospitalized COVID-19 patients. While patients with severe COVID-19 infection commonly meet the clinical criteria for disseminated intravascular coagulopathy (DIC), their thrombocytopenia is generally mild, and microangiopathy is often not present. However, given that some patients can develop fulminant DIC with consumption of coagulation factors, platelet count, PT/aPTT, D-dimer, and fibrinogen should be monitored closely. While abnormal coagulation parameters are common in patients with COVID-19 infection, COVID-19 infection seems to be rarely associated with bleeding. Correction of the coagulopathy should only be pursued in patients with active bleeding or those requiring an invasive procedure.
Patients with COVID-19 are also at an increased risk of venous thromboembolic (VTE) disease. VTE disease is likely due to the combined effects of systemic inflammation, abnormal coagulation, multiorgan dysfunction, and critical illness [18] . Multiple studies have shown the correlation between elevated d-dimer and disease severity [5, 19, 20] . Clinically, d-dimer levels have been followed in patients with COVID-19 infection to determine not only disease severity and clinical progression but also risk of thromboembolic events. While elevated serum d-dimer levels have been associated with increased mortality in COVID-19 patients, there is no current evidence supporting the use of d-dimer levels to guide anticoagulation. Pharmacologic VTE prophylaxis is generally recommended in all hospitalized COVID-19 patients with no specific contraindication. A prospective cohort study that examined the rate of thromboembolic events in 184 ICU patients all receiving standard dosing of VTE prophylaxis and found a 31% incidence of thromboembolic events. Given this finding, the authors suggest increased dosing of prophylaxis medications [21] . The current evidence is limited on the optimal dosing of VTE prophylaxis medication in critically ill patients with COVID-19 and studies to evaluate therapeutic anticoagulation in critically ill patients with COVID-19 are currently ongoing (NCT04359277). Furthermore, post-hospital discharge VTE prophylaxis should be considered in these patients on a case-by-case basis. Assessment for VTE is challenging in these patients, and imaging should only be pursued when clinical examination and condition support the laboratory studies. The decision for treatment with anticoagulation should be made based on imaging findings when possible. A review by Flaczyk et al. compares published guidelines for management of COVID-19 associated coagulopathy in critically ill patients and provides a framework for patient management [22] .
include direct viral damage of nervous tissue, injury resulting from the excessive inflammatory response, unintended host immune response effects after the acute infection (e.g., Guillain-Barré syndrome as reported in a case series of four patients [24] ), and injury resulting from the effects of systemic illness. Most COVID-related neurologic complications in critically ill patients fall into this latter category, and manifest as encephalopathy, delirium, and critical illness myopathy.
A variety of neurological manifestations have been reported, including headache, encephalitis, stroke, seizures, hyposmia, and hypogeusia [25] . The prevalence of hyposmia and hypogeusia suggests direct viral infection of the olfactory nerve [23] and SARS-CoV 2 has been detected in human neuronal cells on postmortem analysis [26, 27] . Several studies have also reported meningoencephalitis manifested by headache, fever, altered mental status, and signs of meningeal irritation as a presenting symptom of COVID-19 that may be secondary to the indirect inflammatory effects of the virus [28] [29] [30] [31] [32] . A case of COVID-associated acute necrotizing hemorrhagic encephalitis within the temporal lobes and thalami has also been reported [30] . SARS-CoV-2 has been detected in the CSF of a patient with encephalitis [29] . There have been several cases of young patients presenting with large-vessel strokes [33] and 5.7% of a hospitalized cohort in Wuhan had an acute stroke (80% ischemic, 20% hemorrhagic) [23] . Given the prevalence of hypercoagulability, neurologic thromboembolic events should be strongly considered in a patient with a fluctuating neurologic examination [34] . Careful clinical assessment in conjunction with imaging and cerebrospinal fluid examination may be essential for diagnosing COVIDrelated neurological disorders.
A significant proportion of patients receive high amounts of sedation to ensure comfort and facilitate ventilator synchrony [35] . Neuromuscular blockade has also been utilized when the effects of sedation are inadequate. Spontaneous awakening trials are vital to alert clinicians to neurologic changes and enable them to take appropriate action. This neurologic assessment is especially important before initiating therapeutic anticoagulation, given the significant morbidity in patients with unidentified intracranial hemorrhage. A growing body of literature is reporting high rates of acute encephalopathy and agitated delirium in critically ill COVID-19 patients [36] [37] [38] [39] . Delirium management strategies should be routinely employed, given the prevalence of the disorder in COVID-19 patients.
Between 5% and 25% of the hospitalized COVID-19 patients will have evidence of myocardial involvement [40, 41] , and preexisting cardiovascular disease has been linked to more severe infections [42] . Cardiovascular complications include infarction, myocarditis, heart failure, and dysrhythmias. There are multiple proposed etiologies for adverse cardiovascular outcomes, including an increased metabolic demand, a hyperinflammatory state, and increased procoagulant activity [42] . There is also evidence that the virus may cause direct damage to the heart via ACE2 receptors located within the cardiac tissue.
Angiotensin II is converted to angiotensin (1-7) by ACE2, and the downregulation of ACE2 among COVID-19 patients has been correlated with increased viral load [43] . Since angiotensin (1-7) has anti-inflammatory and anti-fibrotic effects that counter the pro-inflammatory effects of angiotensin II, there has been concern that patients taking angiotensin-converting enzyme inhibitors or angiotensin receptor blockers might be more susceptible to viral infection and propagation [44, 45] . However, the reduction in angiotensin II activity and upregulation of the anti-inflammatory ACE2 effects from these drugs may be beneficial in COVID-19 infection [46] . Many use the lack of evidence of harm in COVID-19 to support the continuation of such medications [45] , given the risk of heart failure exacerbation with their withdrawal [47] .
Elevated troponins have been found in many patients with COVID-19, which may be secondary to increased cardiac physiologic demand, hypoxia, and/or direct myocardial injury. Myocarditis has also been identified on autopsy of some patients with COVID-19 [48, 49] and presents with variable clinical severity in COVID-19 patients. Fulminant viral myocarditis [48, 50] or diffuse lymphocytic infiltrates characteristic of viral myocarditis [43, 51] are uncommon findings in COVID-19 patients. The patients who have developed COVID-19 myocarditis are typically younger and healthier, often without underlying cardiovascular disease. Myocarditis may result from a cytokine storm in patients who mount a vigorous immune response to the virus.
Differentiating myocarditis from acute coronary syndrome (ACS) can be challenging [52] . Serum troponin values will be elevated in both conditions, and electrocardiogram (ECG) in patients with myocarditis can demonstrate a range of findings, in some cases mimicking ACS. Echocardiographic evaluation is more likely to show global dysfunction with myocarditis, while a focal wall motion abnormality is more suggestive of ACS. ECG and echocardiographic abnormalities are markers of severity in COVID-19 patients, and are correlated with worse outcomes; moreover, troponin elevations in severe COVID-19 patients have been directly associated with an increased risk of mortality. Diagnostic confirmation of COVID-19 myocarditis via biopsy is unlikely to change management and therefore is not generally recommended. Instead, it may be reasonable to empirically treat COVID-19 patients with suspected myocarditis with a course of corticosteroids.
Given the hyperinflammatory and hypercoagulable state, COVID-19 patients may be at increased risk for acute myocardial infarction. Patients should be directed toward appropriate standard of care therapy [53] while also avoiding unnecessary and costly procedures that can both lead to morbidity and increase the risk of infectious exposure to staff.
Approximately a quarter of patients presenting with COVID-19 will develop acute heart failure, with the majority lacking a prior diagnosis of hypertension or cardiovascular disease. It is unclear if heart failure in these patients is a new cardiomyopathy or an exacerbation of an undiagnosed condition. Given the high prevalence of cardiac dysfunction and concern for causing pulmonary edema, fluids should be administered judiciously in COVID-19 patients.
A diagnosis of stress cardiomyopathy should be considered in any critically ill COVID-19 patient with an abrupt decline in cardiac function. Focused echocardiography can be performed at the bedside to allow for rapid evaluation while minimizing exposure to additional staff. Typical echocardiographic findings include impaired systolic function with global hypokinesis or regional wall motion abnormalities that are not limited to a coronary distribution [54] . In stress cardiomyopathy, systolic dysfunction is typically transient, with most patients recovering within days to weeks. However, due to ongoing infection and respiratory compromise, the prognosis for COVID-19 patients who develop stress cardiomyopathy is often poor. Management is mostly supportive, and the use of mechanical circulatory support should be considered for patients in whom myocardial recovery is likely.
A 'pediatric multi-system inflammatory syndrome temporally associated with COVID-19' (PIM-TS) syndrome has been described in children, which shares certain features of toxic shock syndrome and atypical Kawasaki disease and has been linked to a number of deaths and rapid decompensation in children [55] . Common features include rash, fever, gastrointestinal symptoms, and severe cardiac dysfunction from myocarditis and cardiogenic shock. Repeat echocardiography, cardiac catheterization, supportive treatment, steroids, and IVIG may be required.
Gastrointestinal (GI) manifestations of COVID-19 are common and include diarrhea, vomiting, and abdominal pain. The SARS-CoV-2 RNA can be readily detected in stool specimens, even where respiratory tests are negative [56] . SARS-CoV-2 has a tropism for the GI tract, with the viral ACE2 receptor found on gastrointestinal epithelial cells. Critically ill patients with COVID-19 are at high risk of hepatobiliary, hypomotility, and ischemic GI complications [57] , with small vessel thrombosis and viral enteroneuropathy as likely etiologic factors. Consequently, serial abdominal exams with limited sedation are required when there is clinical suspicion of intraabdominal pathology.
Liver injury occurs in 15% to 78% of COVID-19 patients, with the most common finding being abnormal transaminase levels [58, 59] . Most liver injuries are mild and transient, but more severe liver damage can occur and is more likely in patients with severe COVID-19 infection. Mechanisms of liver injury may include direct viral infection of hepatocytes, immune-related injury, and drug hepatotoxicity. In patients with transaminitis, medications with potential hepatotoxicity, including acetaminophen, statins, and hydroxychloroquine, should be adjusted or discontinued.
Acute kidney injury (AKI) is a common complication of COVID-19 infection, occurring in 0.5-15% of hospitalized COVID-19 patients [5] , and up to 23% of critically ill patients [60, 61] . The median onset of AKI from hospitalization ranges from 7 [62] to 15 days [5] , and it has been identified as an independent risk factor for morbidity and mortality [62] . AKI can occur through several proposed mechanisms, including acute tubular necrosis induced by sepsis, fluid restriction, rhabdomyolysis, or hypoxia. Furthermore, intrinsic tissue injury by direct viral invasion of the renal tubular cells, interstitum, or glomeruli has also been proposed. Varying degrees of acute tubular necrosis, lymphocytic infiltration, and viral RNA have been found on postmortem examination of COVID-19 patients, suggesting the direct invasion of kidney tubules [63] .
Management of AKI in COVID-19 patients must account for classical and viral-specific risk factors of renal damage. In a recent study, approximately 30-40% of critically ill patients with AKI required renal replacement therapy (RRT) [34, 61] . The preferred modality is continuous RRT or sustained lowefficiency dialysis, although the American Society of Nephrology notes that whatever is available in these resourcescarce times will suffice. If the AKI is secondary to cytokine storm, some have questioned whether using high-volume hemofiltration would be preferred to clear inflammatory molecules, but current evidence shows no difference in outcome compared to standard volume filtration [18] .
While the effects of COVID-19 on the endocrine system remain largely unknown, given the expression of ACE2 on the majority of endocrine glands, dysfunction of these systems should be considered in critically ill patients.
The ACE2 receptor is expressed throughout the pancreas and dysfunction of both the exocrine and endocrine systems is seen in patients with COVID-19 infection. While pancreatitis is uncommon, elevated lipase or amylase have been seen in up to 17% of the patients with severe disease [64] . Similar to other infections, patients with diabetes mellitus (DM) are more at risk for COVID-19 than the general population and are more likely to have a severe course due to compromised innate immunity and downregulated ACE2 levels [18] . COVID-19 patients with DM have higher serum levels of inflammatory biomarkers and are more susceptible to cytokine storm [18] . Furthermore, infection with SARS-CoV-1 was shown to cause new-onset diabetes in approximately 8% of the patients during hospitalization that may not be classic type 1 or type 2 diabetes but a new type of diabetes [65, 66] . In some patients, hyperglycemia persisted for 3 years after recovery from the virus. While a similar effect has not yet been reported in COVID-19, close monitoring of blood glucose during the acute and convalescent phase of the illness is indicated.
Obesity is associated with severe COVID-19, which may be explained by ACE2 expression in adipose tissue. Furthermore, visceral and subcutaneous adipose tissue produces proinflammatory cytokines that are found in greater abundance in obese patients with COVID-19 as compared to non-obese patients [67] . This may predispose obese patients with COVID 19 to an exaggerated cytokine response in the presence of SARS-CoV-2, manifesting as more severe disease and ARDS [68] .
Hypothalamic and pituitary tissues express ACE2 and given the evidence of viral injury of nervous tissue, it is reasonable to assume that SARS-CoV-2 may affect the hypothalamus-pituitary as well, either directly or via immune-mediated hypophysitis [69] . Accordingly, central hypocortisolism should be suspected in critically ill COVID-19 patients with unexplained hypotension or shock. Diabetes insipidus is common in patients with pituitaryhypothalamic disorders and, in conjunction with insensible water loss from fever and the conservative fluid management strategy employed in critically ill COVID patients, could result in hypovolemia and hypernatremia.
Impairment of the host's cortisol stress response was a primary immunologic strategy utilized by SARS-CoV-1 for facilitating viral spread [70] . The similarities between the two viral strains suggest that SARS-CoV-2 may employ the same strategy. Therefore, patients with severe COVID-19 may be more prone to develop critical illness-related corticosteroid insufficiency. The absence of lymphopenia in patients with COVID-19 could be used as a marker of hypocortisolism (absolute or relative) and clinicians may want to adopt a low threshold for initiating glucocorticoid therapy in the presence of shock.
Data regarding the impact of COVID-19 on thyroid function are limited. A case report suggests that COVID-19 may lead to subacute thyroiditis in some patients, which is suspected to have viral or postviral origin [71] . Recent guidelines advise patients with underlying hypothyroidism or hyperthyroidism to continue prescribed medications since uncontrolled thyroid disease may increase the risk for viral infection and complications [72] .
A variety of cutaneous manifestations such as erythematous rash, generalized urticaria, and chickenpox-like lesions have been associated with COVID-19, and can present even before the onset of symptoms and with an incidence of up to 36% of the patients depending on the cutaneous manifestation [73, 74] . Interestingly, there was no association between cutaneous findings and disease severity [74] . Urticarial eruptions typically preceded additional symptoms of COVID-19 infection, were noted to occur even in the absence of fevers, and tended to be consistent on histology with a viral exanthem [53, 75, 76] . Acrocyanosis and limb ischemia have been described in a cohort of critically ill patients with elevated D-dimer, fibrinogen, and fibrinogen degradation products [77] . In this small cohort, 57% of the patients developed DIC. Livedo reticularis, a cutaneous manifestation commonly associated with DIC, was seen in two patients with only mild-moderate disease [78] . The authors hypothesize that these findings may represent microthrombosis of cutaneous vasculature, as similar pathophysiology has been noted in other organ systems in COVID-19 patients. Chilblains-like lesions, which are erythematous areas on the feet, described colloquially as 'COVID toes,' may represent endothelitis secondary to systemic COVID- 19 . In a small cohort of patients with severe COVID-19 and purpuric skin rash, biopsy demonstrated a thrombogenic vasculopathy of both affected and normal-appearing skin as well as localization of SARS-CoV-2 spike glycoprotein causing complement activation [79] . These findings are consistent with a catastrophic microvascular injury mediated by systemic viral spread and associated with a procoagulant state.
Current evidence does not suggest that dermatologic findings are associated with disease severity, but may reveal microthrombosis, hypercoagulability, and DIC. In the correct clinical setting, these findings may encourage providers to consider therapeutic anticoagulation.
Myalgias are a common presenting symptom of COVID-19 occurring in more than one-third of patients [62, [80] [81] [82] . Elevated creatinine kinase levels are prevalent in hospitalized patients [80] and are more common in patients with severe disease [3, 80] . While myositis and rhabdomyolysis was documented as a manifestation of SARS-CoV-1 infection, RNA from SARS-CoV-2 has not been found within myocytes to date [26] . Critically ill patients in general are at risk of developing myopathy and neuropathy due to prolonged immobility, systemic inflammation, corticosteroids, and the use of neuromuscular blocking agents [83, 84] . Early mobilization and initiation of physical therapy is important in these patients to ensure the best functional outcome.
While COVID-19 generally starts as a local upper respiratory tract infection, it can spread to affect multiple organ systems with significant morbidity and mortality. Clinicians should actively seek evidence of multiorgan system involvement in these patients to guide early management to potentially improve outcomes. The long-term implications of COVID-19 are only beginning to be appreciated, but will likely include cognitive, physical, and psychological impairment.
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Introduction workers (HCWs). Work-related transmission among HCWs constituted a large 23 proportion in previous coronavirus outbreaks. HCWs comprised 37-63% of 24 suspected severe acute respiratory syndrome (SARS) cases in highly affected 25 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted April 11, 2020. In contrast, there is limited discussion on the work-related risks among 6 workers such as taxi drivers, tour guides, cleaners and janitors, and civil 7 servants, who have frequent contact with the public in their daily routines or 8 have workplaces with higher risks of virus exposure [14] . 9 10 In this study, we aimed to identify the occupations at higher risk of Covid-19 11 transmission, and to explore the temporal distribution of work-related cases 12 among local transmission.
Study population selection 16 We extracted and included all locally transmitted Covid-19 confirmed cases 17 from the publicized government investigation reports from six Asian 18 countries/areas, including Hong Kong, Japan, Singapore, Taiwan, Thailand, 19 and Vietnam. These countries/areas were selected since they shared some 20 common temporo-spatial characteristics. First, they are proximal to Mainland 21 China, where the first outbreak of Covid-19 was reported. Second, the first 22 cases of these countries/areas were imported cases from Mainland China in 23 mid-January. Third, the first locally transmitted cases in these countries/areas 24 were identified around late January to early February. We followed each 25 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted April 11, 2020. . https://doi.org/10.1101/2020.04.08.20058297 doi: medRxiv preprint country/area for forty days since the report of the first locally transmitted case 1 and excluded the imported cases. The study population selection process is 2 presented in Fig. 1 to the jobs similarity. 24 All differences between the occupation physicians were reviewed by the third 25 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted April 11, 2020. . https://doi.org/10.1101/2020.04.08.20058297 doi: medRxiv preprint investigator, who is a physician-epidemiologist to reach a consensus. We also conducted sensitivity analysis comparing the results between the six 21 countries/areas and five countries/areas excluding Japan. We excluded Japan 22 due to its different case reporting system from other countries/areas. Unlike 23 other countries/areas that have central reporting systems, Japan had cases 24 reported from each prefecture separately. Differences in reporting 25 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted April 11, 2020. and so on. In terms of occupation grouping, the groups with the most cases 20 were HCWs, drivers and transport workers, services and sales workers, 21 cleaning and domestic workers, and public safety workers. (Table 1) 22 23 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted April 11, 2020. . https://doi.org/10.1101/2020.04.08.20058297 doi: medRxiv preprint . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted April 11, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted April 11, 2020. In further sensitivity analysis excluding Japan because of its different case 21 reporting system, the daily confirmed local transmissions became relatively 22 constant (Fig. 2B) . After excluding Japan, possible work-related cases 23 comprised 44% of the locally transmitted cases in the early period, while only 24 18% in the late period (Chi-squared statistic=18.8, P-value<0.0001).
. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted April 11, 2020. . https://doi.org/10.1101/2020.04.08.20058297 doi: medRxiv preprint 1 HCW comprised 22% of the possible work-related cases. Moreover, we found 2 the occurrence of Covid-19 transmission among the HCW was relatively late 3 compared to the non-HCW population. Fig. 2(A) and Fig. 2(B) CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted April 11, 2020. . https://doi.org/10.1101/2020.04.08.20058297 doi: medRxiv preprint non-HCW comprised the majority of the possible work-related cases and most 1 of the cases were not able to trace back the infection sources. are more likely to be exposed to contaminated surfaces than direct contact 15 with Covid-19 patients [18] . 16 17 In this study, the proportion of HCWs among locally transmitted cases was 18 smaller than non-HCWs in the included countries/areas, 3% versus 12% 19 respectively. The first cases HCWs appeared much later than the first non- CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted April 11, 2020. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted April 11, 2020. . in the non-healthcare workplaces to protect the workers in this pandemic [27] . 1 Early delivery of infection control knowledge and health concepts to workers, 2 as well as providing adequate PPE are crucial in protecting workers and the 3 whole society. should be non-differential as the official reports were not different between 24 whether a case was work-related or not. Third, the criteria of deciding whom 25 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted April 11, 2020. . https://doi.org/10.1101/2020.04.08.20058297 doi: medRxiv preprint to be tested varied between countries/areas, especially during early outbreaks 1 when testing capacities were limited. Therefore, high risk populations, 2 including high risk occupations, might tend to be tested. However, we believe 3 the bias was non-differential, as health authorities should not decide whom to 4 be tested differently based on whether the suspected case was a worker or 5 not. In fact, most of the early cases were tested because of the symptoms or CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted April 11, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted April 11, 2020. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted April 11, 2020. . https://doi.org/10.1101/2020.04.08.20058297 doi: medRxiv preprint Figure 1 . Study population selection process . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted April 11, 2020. . https://doi.org/10.1101/2020.04.08.20058297 doi: medRxiv preprint CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted April 11, 2020. . https://doi.org/10.1101/2020.04.08.20058297 doi: medRxiv preprint
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Dear Editors, It is unclear why some patients with progression to severe COVID-19 pneumonia require admission to an intensive care unit (ICU) for invasive mechanical ventilation while others can be managed with supplementary oxygen on the ward. [1] Several hypotheses have been proposed to explain the differences in clinical course between patients. One hypothesis is that pulmonary embolism results in severe hypoxemia.
Observational studies suggest a high incidence of deep vein thrombosis in COVID-19, up to 25% in ICU patients compared to 6.5% in ward patients [2] , which may progress to pulmonary embolism. Pulmonary edema as a result of dysbalance of the bradykinin-kallikrein system is also suggested to contribute. [3] Another hypothesis is the onset of local thrombosis in the pulmonary microvasculature due to an inflammatory thrombotic microangiopathy. [4] We hypothesized that patients requiring invasive mechanical ventilation for COVID- (Table) .
CT Severity points (max20; mean, SD) 17.7 (2.0) 8.5 pneumonia, [4] although the extent of the perfusion defects is much more evident in this present study.
The strength of our study is that all patients underwent advanced imaging using a high-end dual source CT-scanner dedicated to COVID-19 patients. This limits the chance of measuring artifacts, although even then technical challenges remain. Our J o u r n a l P r e -p r o o f study also has several limitations. First, this is a single center study using a cross sectional design which does not allow to make any causal inferences with regard to the pathophysiology or order of events. Although basis for suspicion of PE was the same, as for the ICU patients evaluation was ordered primarily on clinical grounds and mostly at a later stage, and for the ward patients according to the YEARS-criteria mostly (but not always) at presentation, we cannot exclude confounding differences between the two groups. Second, we used semi-quantitative scores for single pass CT perfusion evaluation. Quantitative measurements for image analysis require a time-consuming procedure, and also are not validated for the investigated questions.
Next, we did not prospectively calculate the dead-space and shunt fractions in the included patients and were unable to link the imaging results with gas-exchange.
Finally, we cannot assess the impact of positive pressure ventilation on the observed perfused blood volumes and perfusion defects. Although the effect of positive pressure ventilation on lung perfusion is well known, little data is available on the changes in regional perfusion defects like we observed.
In
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On December 31, 2019, a novel coronavirus (SARS-CoV-2) was identified in Wuhan, China. Three weeks later, on January 21st, the US Centers for Disease Control and Prevention (CDC) confirmed the first case of COVID-19 in the US. On January 15th, the man returned from a visit to Wuhan, China to Snohomish County in the Seattle Metropolitan Area of Washington state [1] . To mitigate local transmission and prevent global spread, China imposed a lockdown on Wuhan starting January 23rd. In the first months of the pandemic, confirmed case counts vastly unrepresented the rapid expansion of the pandemic as countries raced to ramp up testing and surveillance capabilities [2À5] . By the time of the Wuhan lockdown, only 571 cases of COVID-19 were reported in mainland China [6] , 422 of which were in Wuhan [7] . The Seattle area reported only 245 confirmed COVID-19 cases and 36 COVID-19 deaths by March 9th [8] .
Two studiesÀÀone in Wuhan [9] and the other in Seattle [10] ÀÀ re-examined swabs taken from individuals with symptoms of acute respiratory illness during periods where SARS-CoV-2 may have been spreading undetected. Although some of these specimens were previously tested for influenza viruses, none were tested for SARS-CoV-2. The Wuhan study tested 26 throat swabs taken from adults over age 30 who sought outpatient care at one of two central Wuhan hospitals for influenza-like-illness (ILI) between December 30, 2019 and January 12, 2020 [9] . Although no patients were confirmed COVID-19 cases, four retrospectively tested positive for the virus. In addition to We acknowledge support from NIH grant U01 GM087791 and Tito's Handmade Vodka.
the four COVID-19 positive samples, seven others tested positive for influenza.
The Seattle study performed RT-PCR tests for SARS-CoV2 and influenza on 2353 mid-nasal swabs collected from 299 children under 18 and 2054 adults who reported symptoms of acute respiratory illness (ARI) between January 1, 2020 and March 9, 2020 [10] . Of these, 442 tested positive for influenza, 25 tested positive for COVID-19, and none tested positive for both viruses.
We note that the two studies have overlapping but not identical case definitions. In Seattle [10] , ARI cases had at least two of these symptoms: "feeling feverish, headache, sore throat or itchy/scratchy throat, nausea or vomiting, rhinorrhea, fatigue, myalgia, dyspnea, diarrhea, ear pain or ear discharge, rash, or a new or worsening acute cough alone". In Wuhan [9] , ILI cases included patients reporting fever (with a temperature of at least 100°F/37.8°C) and a cough or a sore throat without a known cause other than influenza [11] .
Our study is premised on the assumption that influenza and SARS-CoV-2 were constrained by similar behavioral and environmental factors in early 2020. The two viruses have overlapping natural histories [12, 13] and modes of transmission [13] . Both are respiratory pathogens with a wide spectrum of illness, from asymptomatic to fatal, with severity that depends on age and underlying conditions. They are similarly transmitted from person-to-person through direct contact, droplets and fomites [13À15] . Thus, we expect that once SARS-CoV-2 got a foothold in a city, spreading across multiple communities, its geographic and demographic patterns might mirror those of influenza. In Hong Kong, for example, COVID-19 interventions concurrently reduced the transmission rates (i.e., the daily reproduction number, Rt) of COVID-19 and influenza in early February 2020 [15] .
Here, we estimate the early prevalence of symptomatic COVID-19 cases in Wuhan and Seattle based on the ratio of SARS-CoV-2 to influenza test positivity (henceforth, the covid-to-influenza ratio) and the local prevalence of influenza in the two cities at the time of the corresponding retrospective study. We derive our estimates of covid-toinfluenza positivity directly from the two studies and our estimates of local influenza prevalence from Chinese and US surveillance data.
To estimate the covid-to-influenza ratio, we used the numbers of COVID-19 positive and influenza positive patients among tested ILI throat swab samples at two hospitals from December 30, 2019 to January 12, 2020 reported by a recent retrospective study [9] . Wuhan has almost 400 hospitals, which collectively have 81,700 beds and 81 million outpatient visits per year [16] . The data we analyzed from ref. [9] were collected from two hospitals that have large and representative catchments: Children's Hospital of Wuhan (the largest pediatric healthcare center in Wuhan that serves both women and children) [17, 18] with 2000 beds and 1.9 million annual outpatient visits and Wuhan No. 1 Hospital [19] , with over 3000 beds and 2 million annual outpatient visits. Both serve as sentinel sites in China's national influenza surveillance system [9] . Together they provide almost 5% of outpatient care in the Wuhan area. The data we analyzed from ref [9] . were collected from two hospitals that have large and representative catchments: Children's Hospital of Wuhan (the largest pediatric healthcare center in Wuhan, serving both children and adults) [17, 18] with 2000 beds and 1.9 million annual outpatient visits and Wuhan No. 1 Hospital [19] , with over 3000 beds and 2 million annual outpatient visits. Both serve as sentinel sites in China's national influenza surveillance system [9] . The SARS-CoV-2 and influenza virus among tested ILI throat swab samples are well kept at À70°C before the SARS-CoV-2 experiments and detected by realtime PCR with reverse transcription [9] .
To estimate the age-stratified numbers of outpatient visits for ILI in Wuhan, we analyzed data from China CDC weekly reports for Wuhan, December 30, 2019-January 12, 2020 [9] . To estimate the age-stratified population sizes of Wuhan's 13 districts, we obtained data from the Sixth National Census of the People's Republic of China in 2010 [20] , and scaled by the growth in overall Wuhan population between 2010 and 2019 reported by Wuhan Statistics Bureau [21] .
Our analysis of Seattle is restricted to the portion of the metropolitan area sampled by the Seattle Flu Study in ref. [10] . Specifically, we analyze King county, which contains the city of Seattle, and Snohomish county, where the first US COVID-19 case was identified. Roughly 77% of the 3.5 million metropolitan population reside in the two counties.
To estimate the covid-to-influenza ratio, we used the numbers of COVID-19 positive and influenza positive patients among tested midnasal swab samples from participants with symptoms of acute respiratory illness (ARI) in the Seattle Flu pandemic surveillance platform from January 1, 2020 to March 9, 2020 [10] . Our analysis combines viral positivity data from cases with ILI and ARI. We assume that the two populations are the sameÀindividuals with ILI and ARI in Seattle during the study periodÀand refer to this population as ILI throughout the text and supplement. The ARI case definition in ref. [10] is at least "two of the following: feeling feverish, headache, sore throat or itchy/scratchy throat, nausea or vomiting, rhinorrhea, fatigue, myalgia, dyspnea, diarrhea, ear pain or ear discharge, rash, or a new or worsening acute cough alone". The CDC's case definition for ILI is "fever (temperature of 100°F [37.8°C] or greater) and a cough and/or
The early pace and extent of the COVID-19 pandemic remains unclear. Given that many countries are still scrambling to provide wide access to coronavirus tests, confirmed case counts underestimate the true prevalence of the virus. Recent studies suggest that SARS-COV-2 may have spread extensively in both Wuhan (China) and Seattle, Washington (US) before the first community-acquired cases were reported in each city.
We introduce a new method for indirectly gaging the early spread of COVID-19 based on two pieces of informationÀÀthe concurrent prevalence of influenza and the ratio of SARS-CoV-2 positive to influenza positive tests among patients with clinical respiratory illness. We apply the method to estimate the dates of emergence and prevalence of COVID-19 in Wuhan prior to the January 23, 2020 lockdown and in Seattle prior to March 9, 2020.
Given the epidemiological similarities between influenza and COVID-19, influenza surveillance data can provide a retrospective window into the emergence of COVID-19 in cities around the globe. In both the Wuhan and Seattle metropolitan areas, there were likely thousands of undetected cases of COVID-19 during the first months of transmission. The large discrepancy between confirmed cases and true prevalence of the virus highlights the difficulty of determining infection fatality rates from readily available COVID-19 data. a sore throat without a known cause other than influenza" [11] . Thus, the case definitions overlap considerably, but are not identical. The tested mid-nasal swab samples were kept at 4°C before the influenza and SARS-CoV-2 tests by TaqMan PT-PCR, with an average time from nasal swab collection to receipt at the study laboratory of 2.8 days [10] . We analyzed the age-stratified numbers of outpatient visits for ILI in HHS region 10 between January 1, 2020 and March 9, 2020 available on the CDC's FluView interactive website [22] and the age-stratified population sizes of the 22 Public Use Microdata Areas (PUMA's) in King and Snohomish counties [10, 20] . Details are provided in Table 1 .
Our methods for estimating the prevalence of symptomatic COVID-19 in Wuhan and Seattle are similar, but not identical. We describe our method for Wuhan in this section and our method for Seattle in the Appendix. The key methodological difference is that the retrospective study in Wuhan [9] but not Seattle [10] reported the date of symptom onset for each positive influenza test. For Seattle, we took the extra step of estimating these dates based on the total number of positives and the daily influenza positivity reported by the CDC for HHS Region 10 (Supplementary Figure S1 , Tables S1 and S2).
For Wuhan, we assume that the age-specific risks of COVID-19 and influenza infection are identical in all 13 central districts of the city. Therefore, the ratio of COVID-19 to influenza adult outpatients (r) estimated from the subset of outpatients sampled in ref. [9] can be used to estimate the number of COVID-19 infections across all of central Wuhan (Fig. 3 ).
To estimate the number of COVID-19 infections we use a binomial distribution, denoted B(N, p), where N is the total population in each district and p is an estimate of the age specific prevalence of symptomatic COVID-19 in the population adjusted by the proportion of individuals in that age group. We chose a binomial distribution as it is the most commonly used distribution to statistically model case counts when the population size and probability are known. We denote by H d, a, t the number of COVID-19 infections in district d and age range a (over 30 years) during the focal fourteen-day period t, and model it as:
where N d is the number of people of all ages in district d; Q a t is the number of ILI outpatients in age group a over a period of time t; V t is the number of all cause outpatients of all ages in Wuhan over a period of time t; F t is the percent of influenza tests that are positive in the South Provinces of China during time period t; the r is the ratio of COVID-19 outpatients to influenza outpatients over age 30 . Given the small sample size, we could not reliably estimate COVID-19 prevalence by sex or narrow age brackets. We take a Bayesian approach using Markov Chain Monte Carlo, where at each iteration we take a draw from the distributions of r and V r , and then use these to draw H d, a, t according to the specified binomial distribution. Since the other parameters are assumed to be known constants, we do not take draws of these parameters; the values of these parameters can be found in Table 1 . H d, a, t is then specified by the set of draws, defining a predictive distribution that we use to calculate the mean and credible intervals for the number of COVID-19 infections. We chose a Bayesian approach to allow an intuitive structuring of the model and avoid making assumptions that are not appropriate for our small sample sizes.
To estimate the distribution of r and V r , we first derive r as the following posterior distribution. Let N denote the total number of adults in the sample, and x c and x f denote the observed number of adults who tested positive for COVID-19 and influenza, respectively. As before we assume a binomial distribution where
If we assume uninformative priors on p c and p f [23] ,
then the posterior distributions are known in closed form [23] :
We use Markov Chain Monte Carlo to draw from p c and p f at each iteration and calculate r ¼ p c =p f . We combine these draws to obtain the distribution for r. Using this method we estimate that the ratio of COVID-19 to influenza adult hospitalizations across central Wuhan during December 30, 2019 to January 12, 2020 was 0.61 [95% CrI: 0.20À1.64]. We use 10,000 draws and report the medians and 95%
To project the number of adult infections in Wuhan prior to the closing on January 23, 2020 (H cum ), we assume
where T d is the epidemic doubling time, t 0 is the day of the first adult infection in Wuhan, and L corresponds to January 22, 2020 (the day before the Wuhan lockdown). We use our age-and district-stratified estimates for adult COVID-19 infections for December 30, 2019 to January 12, 2020 to estimate this quantity, under the assumption that the values reflect cumulative incident infections during that fourteen-day period (Fig. 4) .
We use Monte Carlo sampling to incorporate the uncertainty in both the epidemic doubling rate in Wuhan during this period [2] and adult infections from December 30, 2019 to January 12, 2020 (H d, a, t ). We take draws from the distribution of H d, a, t and T d (summarized in Table 1 ) to estimate the time since the first adult infection by
That is, the estimated date of the first COVID-19 infection in Wuhan (t 0 ) is d days prior to December 30, 2019. We then estimate H cum according to the equation above to project the cumulative COVID-19 adult infections preceding the Wuhan lockdown.
This research was made possible, in part, by NIH grant U01 GM087791 and funding from Tito's Handmade Vodka in support of the UT COVID-19 Modeling Consortium. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Based on the numbers of confirmed SARS-CoV-2 and influenza cases in ref. [9] , we estimate that the ratio of symptomatic COVID-19 to influenza infections in Wuhan (Fig. 4) . We note that the Wuhan study [9] also tested swabs taken from 54 ILI patients under age 30. Of these, 30 tested positive for influenza and none tested positive for COVID-19. Given that there were likely symptomatic pediatric COVID-19 cases in Wuhan during the study period [27] , we do not believe that the true prevalence in this age group was zero. Because estimates close to zero require greater amounts of data to estimate with any certainty, we lack the statistical power to reasonably estimate the COVID-19 to influenza ratio based on the reported zero out of 54 without making additional assumptions. Thus, to avoid potentially problematic assumptions or invalid generalizations, we restricted our analysis to the over 30 age group.
For the Seattle area, we similarly estimate that the ratio of symptomatic COVID-19 to influenza infections in children under 18 50% of infections are asymptomatic [26] , then we project there may have been over 15,000 undetected COVID-19 cases at the time. We further estimate that the Seattle epidemic originated with cases that arrived infected around January 6, 2020 [95% CrI: December 25, 2019 -January 15, 2020] (Fig. 4) .
In cities across the Northern Hemisphere, the emergence of the COVID-19 pandemic coincided with the 2019À2020 influenza season [9, 10] . Mild COVID-19 and influenza infections have overlapping constellations of symptoms that often fall within the criteria for influenza-like-illness (ILI) and acute respiratory infections (ARI) [28] . Prior to widely available SARS-CoV-2 tests, symptomatic COVID-19 cases who sought care were likely to have been tested for influenza. A few studies have retrieved and retrospectively tested swabs taken from such patients for SARS-CoV-2 and thereby identified early undetected cases of COVID-19 [3, 5, 9, 10] . Given the spatiotemporal overlap and epidemiological similarities between influenza and SARS-CoV-2, we hypothesized that the observed prevalence of influenza might shed light on the unseen early spread of COVID-19. To extrapolate COVID-19 prevalence from influenza surveillance data, we assume that the [9] . We then estimate the number of symptomatic COVID-19 infections among adults across Wuhan during this time period based on the proportion of influenza positive outpatients and the ratio of COVID-19 to influenza positive outpatients, using Monte Carlo sampling to incorporate uncertainty in our estimates of both quantities (upper right). Finally, we estimate the age-specific COVID-19 adult infections for the 13 central districts in Wuhan based on the district level population sizes for each age group. Given that the four detected COVID-19 cases lived in central Wuhan in ref. [9] , we assumed that risk was uniform across all 13 districts during the 14-day time period. . [3] and that the numbers of COVID-19 infections estimated across the 22 PUMA's are equal to the sum of the daily number of incident infections from February 24th to March 9th, 2020. Using an exponential model of epidemic growth we estimate the initial pandemic wave in Seattle originated with a single infected case who developed symptoms on January 6, 2020 [95% CrI: December 25, 2019 -January 15, 2020] and then project the daily COVID-19 infections until March 9, 2020. In both graphs, lines and bars indicate the median and 95% CrI estimates, respectively. Gray shading indicates the time period of our initial estimates. ratio of COVID-19 positive to influenza positive cases detected retrospectively in small samples generally holds for the surrounding metropolitan area.
We analyzed data provided by two studies À one in Wuhan [9] and the other in Seattle [10] À that re-tested swabs taken from ILI and ARI cases in early 2020. The identification of overlooked COVID-19 cases in both cities was not surprising, given the large numbers of cases, hospitalizations and deaths that were detected shortly after these retrospective periods. Nonetheless, the ratios of SARS-CoV-2 to influenza positive swabs were surprisingly high. In Wuhan, there were roughly two symptomatic cases of COVID-19 for every three cases of influenza; in Seattle, there was one pediatric case of symptomatic COVID-19 per every 9 influenza cases, and one per every seven in adults. Given that influenza was circulating widely at the time of these infections, these ratios led us to conclude that there may have been over 5000 undetected cases of symptomatic COVID-19 both in Wuhan prior to January 12th and in Seattle prior to March 9th.
Our results do not imply that health authorities were aware of these undocumented infections, rather that they went unseen during the early and uncertain stages of COVID-19 emergence in the two cities. In Wuhan, other data have suggested similar levels of unseen COVID-19 prior to the January 23, 2020 lockdown of the city. For example, we previously estimated that there were 12,400 (95% CrI 3112-58,465) total cases based on extrapolation from the timing and location of the first 19 COVID-19 cases imported from Wuhan to other countries [2] . These numbers are further corroborated by a similarly-derived estimate from Imperial College of 4000 (1000À9700) cases as of January 18, 2020 [29] . Our estimate that the epidemic in Wuhan started in mid to late November of 2019 is consistent with the first known case reporting symptoms starting December 1, 2019 [30] .
In Seattle, we estimate that sustained community transmission of SARS-CoV-2 began in early January (Fig. 4) , around the time of the first confirmed case [1] . Two recent phylogenetic studies using SARS-CoV-2 genomic data provide conflicting backcasts. The first suggests that a locally-infected case detected on February 24th could be traced back to the initial imported case detected on January 15th [3] ; the second calls this claim into question and suggests that the current epidemic originated roughly four weeks later, in early February [5] .
Our estimates are based on sparse data and multiple assumptions that have resulted in wide credible intervals and potential biases. For one, we do not explicitly consider the accuracy of the viral tests. For example, the Wuhan study tested oropharyngeal (OP) swabs rather than (NP) nasopharyngeal swabs, which have lower sensitivity [31] . The SARS-CoV-2 RT-PCR tests used have a reported false negative rate of 29% [32] and false positive rate of 0.8% [33] . For influenza, both error rates are under 10% [34] . Under the maximum reported error rates for both viruses, we would expect that ref. [9] may have missed approximately 1.4 SARS-CoV-2 cases and over-diagnosed influenza by 1.5 cases. This would imply an even larger ratio of COVID-19 positive to influenza positive cases and a 41% higher overall prevalence of COVID-19 among adults over 30 in Wuhan during this period than we estimated. Larger samples using NP rather than OP swabs for the SARS-Cov-2 test would allow more precise estimation of the early prevalence of SARS-CoV-2 in cities worldwide.
Both studies leveraged data from existing surveillance systems that are designed to provide reliable and representative data on respiratory virus prevalence. Thus, we made two key assumptions. First, influenza and COVID-19 were widespread and exhibited similar epidemiological patterns throughout the 13 central Wuhan districts and throughout the 19 PUMA's of Seattle, during the study periods. Second, the studies provide representative data for these cities. In Wuhan, if SARS-CoV-2 was only spreading in the 6 districts where it was detected, then our estimate for the prevalence of SARS-CoV-2 would decrease by 51%. Nonetheless, we believe that our methodology and qualitative insights are robust, given that the two Wuhan hospitals serve as sentinels for the Chinese Influenza Surveillance System [9] and the high inter-district mobility within Wuhan [35] . Likewise, the Seattle Flu Study was designed to broadly sample the metropolitan area [36] .
Finally, the validity of our estimates hinges on our assumption that influenza and COVID-19 spread similarly during the periods of the two retrospective studies. Both studies tested specimens taken during the heart of the influenza season, when transmission was rampant. The simultaneous global expansion of the COVID-19 pandemic suggests that conditions were equally favorable for the spread of SARS-CoV-2. Moreover, the two studies analyzed specimens collected through surveillance systems in China and the US that were specifically designed to provide reliable estimates of the prevalence of influenza and other similarly-spreading respiratory viruses. That said, influenza is highly seasonal and SARS-CoV-2 may exhibit very different seasonal or non-seasonal transmission dynamics. While we conjecture that our approach was robust for the short period when both viruses were circulating in the focal communities, it may not provide reliable estimates for samples taken over longer periods of time or during the influenza off-season.
With these caveats in mind, we conclude that our method provides a way to roughly triangulate the unseen emergence of the COVID-19 pandemic in cities around the world during the early months of 2020. Retrospective testing of swabs from ILI and ARI patients stored in laboratories can indicate the local ratio of symptomatic SARS-CoV-2 infections to symptomatic influenza infections. If we know the prevalence of influenza when and where the swabs were taken, then we can extrapolate the concurrent prevalence of COVID-19. This approach can elucidate the past as well as provide sentinel surveillance for novel respiratory viruses that co-circulate with influenza, prior to widely available testing.
The COVID-19 epidemics in Wuhan and Seattle were far more extensive than initially reported and had likely been spreading for several weeks before they became apparent. The large discrepancy between confirmed cases and true prevalence highlights the difficulty of determining infection fatality rates from readily available COVID-19 data.
We declare no competing interests.
Zhanwei Du, Ciara Nugent and Lauren Ancel Meyers: conceived the study, designed statistical methods, conducted analyses, interpreted results, wrote and revised the manuscript. Benjamin J. Cowling: conceived the study, interpreted results, and revised the manuscript. Emily Javan: collected the demographic and epidemiological data of Census Block Groups and Public Use Microdata Areas in the Seattle area and revised the manuscript.
Supplementary material associated with this article can be found in the online version at doi:10.1016/j.eclinm.2020.100479.
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O, let us hence; I stand on sudden haste. Wisely and slow; they stumble that run fast.
-William Shakespeare, Romeo and Juliet, Act II, scene 3
The first confirmed case of COVID-19 in the United States was a travel-associated case in Snohomish County, Washington screened on January 19 th , 2020 (1) . As of June 6 th , the United States has recorded 1,917,080 cases and 109,702 deaths (2) . On February 29 th , Governor Jay Inslee declared a state of emergency in Washington, soon after which companies began urging employees to work from home if possible (3) . On March 13 th , President Trump declared a national emergency (4). On March 23 rd , eight states had statewide stay-at-home orders in place, and by April 7 th that had increased to 42 states (5) . Stay-at-home-orders began to expire as early as April for a few states, with most lasting in to May and a few in to June (5) . All 50 states have begun reopening, though approaches to doing so vary (5) .
While shutdown measures have been necessary to control the spread of COVID-19, they also take a toll on the economy: unemployment in the U.S. is over 13%, with the highest rate in Nevada, at more than 24% (6) . However, heedlessly reopening the economy could lead not only to drastic increases in COVID-19 cases, but also to even greater economic downturn due to added health burden and consumer risk (7) . Part of planning to reopen the economy will be carefully considering which businesses to reopen and when to do so.
The economic impacts of the shutdown have not been uniform across industries; therefore, reopening will have differential impacts for different industries. Unemployment has centered on industries that rely on in-person interactions, specifically those that cannot be done with remote work such as restaurants and in-person retail. Ideally, leaders will target reopening industries that have experienced large unemployment or overall economic distress due to COVID-19, however, it is also important to consider the transmission risks in each industry. Workplaces that require significant close contact with large numbers of people or utilize work that cannot be done remotely have a higher likelihood of increased transmission than others. Here, we define reopening of an industry to indicate that should stay-at-home orders be lifted, employees able to work from home would continue to do so, and safety interventions such as hand-washing and mask wearing would continue. In this analysis we aim to quantify the tradeoffs between economic impact and health risks for economic reopening by industry for each state in the US.
We aimed to evaluate (1) the economic impact of the shutdown and (2) the relative transmission risk of reopening industries in each state. Industries were categorized by the North American Industry Classification System (NAICS) (8) . There are many sub-industries and business types within the NAICS industry groupings with economic impacts and transmission risks that may not be accurately reflected in industry-level data. The fact that this report reflects only industry-level data is a limitation. For all data sources referred to below, see Appendix 1 for details. We chose to compare Washington and California in the examples below, due to the first reported case occurring in Washington state and the relevant comparison of California due to proximity and large economy.
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To estimate total economic impact by industry ( ), we summed income loss due to unemployment ( ) and profit loss ( ) as follows:
where Econ is the total economic impact in industry I in state S. All costs were converted to 2019 USD.
To estimate income loss due to unemployment by industry and state, , , we used continued unemployment claims from April 2020 ( , ) to calculate the industry distribution of unemployment due to COVID-19. Continued unemployment claims are reported for each state by industry once a month, representing continued claims the week of the 19 th , or people who were unemployed the week of the 12 th of each month (9) . We then applied the industry unemployment proportions to the total unemployment due to COVID-19 in each state. Total unemployment due to COVID-19 in each state was calculated as the difference between weekly unemployment percent, , the week of May 23 rd and the average weekly unemployment percent for all of 2019 (6) . This rate was applied to the total civilian employed population age 16 and older in the state, (10), and finally average weekly wage in that industry , (11). To estimate profit loss, , , we first found the percent decrease in sales likely attributed to Covid-19. Using SafeGraph weekly mobility data (12), we calculated the percent decrease in customer interactions, , in each industry from the week of March 30 th , 2020 (the lowest point of mobility) to the equivalent week in 2019. SafeGraph is a data company that aggregates anonymized location data from numerous applications in order to provide insights about physical places. To enhance privacy, SafeGraph excludes census block group information if fewer than five devices visited an establishment in a month (two devices in a week) from a given census block group. Customer interactions include any interaction lasting less than four hours (12). We assumed that any job that can be done from home ( ) would not be subject to profit loss (13) . For jobs that cannot be done from home (1 − ), we calculated profit as the weekly revenue, , (14), multiplied by the expected profit margin, . (15). . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted June 12, 2020. . https://doi.org/10.1101/2020.06.11.20128918 doi: medRxiv preprint and where , , , is the number of human interactions in industry , state , during week of year .
This risk index is intended to quantify potential transmission risk differences between industries. It cannot be used to directly predict cases or disease burden.
We hypothesized that a workplace building with more employees would be more likely to facilitate higher levels of transmission. For this factor, we found the mean number of employees per establishment in each industry in each state and normalized the result from zero to one (16). This data source does not include the physical size of each workplace (e.g., warehouse workers may have less frequent physical contact than those in office buildings), which is a limitation of this approach.
In addition to potential interactions between employees, we aimed to quantify a factor for total human interactions in each industry that have been eliminated due to social distancing and shutdown policies. These interactions would be expected to restart if the industry were reopened. We used SafeGraph weekly mobility data to calculate the difference in total interactions , , , between the week of March 30 th , 2020, which was the lowest point of mobility, to the equivalent week in 2019 for each industry, and we assigned interaction scores on a scale from zero to one, with zero representing the fewest interactions and one representing the most (12).
Additionally, we included a factor for the percent of jobs that cannot be done from home for each industry and included a factor for the size of the industry, measured by total number of employees in each state, normalized from zero to one (10,13). The transmission risk index assumes that if the industry was reopened, those who can do their job from home would continue to do so.
In California, for example, the top three industries for economic impact due to COVID-19 shutdowns were (1) manufacturing, (2) healthcare and social assistance, and (3) . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted June 12, 2020. . https://doi.org/10.1101/2020.06.11.20128918 doi: medRxiv preprint After summing the four factors of workplace size, human interactions, inability to work from home, and industry size, in both California and Washington, the industries with the highest transmission risk index were (1) accommodation and food services, (2) retail trade, and (3) healthcare and social assistance ( Figure 2 ). For results for all states see Appendix 2 and https://idmodresearch.shinyapps.io/industry_state/.
In examining economic impact and transmission risk simultaneously for reopening purposes, we should target industries for reopening that have a high economic impact and low transmission risk. In terms of tradeoffs of economic losses from the shutdown versus the health risk of reopening, industries toward the top left of the Figure 3 would have the most economic gain for minimum health risk. The industry with the highest economic impact per unit of transmission risk was wholesale trade in California and manufacturing in Washington (Figure 3 ).
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The copyright holder for this preprint this version posted June 12, 2020. . https://doi.org/10.1101/2020.06.11.20128918 doi: medRxiv preprint We found that the industry with the highest estimated economic impact due to COVID-19 was manufacturing in 40 states; accommodation and food services in six states (AZ, CO, FL, HI, NV, and NY); healthcare and social assistance in three states (AK, MD, and RI); and wholesale trade and other services (which includes repair and maintenance; personal and laundry services; religious, grantmaking, civic, professional, and similar organizations; and private households) in one state each (NJ and DC, respectively) (Figure 4 , top left). We found that the industry with . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted June 12, 2020. . https://doi.org/10.1101/2020.06.11.20128918 doi: medRxiv preprint the largest transmission risk index was accommodation and food services in 41 states; retail trade in five states (CT, ME, NH, NJ, and UT); healthcare and social assistance in three states (ND, SD, and VT); and manufacturing and educational services each in one state (IN and IA, respectively) (Figure 4, top right) . Finally, we found that the industry with the highest economic impact per unit of transmission risk was manufacturing in 37 states; wholesale trade in ten states (AZ, CA, CO, CT, FL, MA, MD, NJ, NY, and RI); accommodation and food services in two states (HI and NV); and construction and other services each in one state (AK and DC, respectively) (Figure 4, bottom left) . These can be interpreted to have the highest value of reopening.
While reopening states and returning individual livelihoods to the millions of unemployed Americans is of key importance, it must be done in balance to limit further spread of COVID-19, which has claimed over 100,000 American lives, sickened nearly 2 million, and ravaged healthcare systems across the US. In estimating the economic impact due to COVID-19 alongside the relative transmission risk in each industry by state, we find that the manufacturing industry would be a good target for early reopening in the majority of states. This is driven by the high economic impact of reopening this industry with . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted June 12, 2020. . https://doi.org/10.1101/2020.06.11.20128918 doi: medRxiv preprint relatively lower COVID-19 transmission risk. However, it is important to note that high reopening value does not necessarily imply low transmission risk. Indeed, in Nevada, Hawaii, and Indiana, the industry with the highest value for reopening also has the highest transmission risk index. For this reason, each state must weigh priorities carefully in establishing reopening strategies.
Use of transmission mitigation strategies will be essential to ensure a safe reopening of the economy and determine industry reopening readiness. Due to the nature of the industry, accommodation and food services, for example, presents the highest transmission risk in most states. This risk, however, may be mitigated though strategies such as capping seating capacity and robust personal hygiene, in which case restaurants would be a key target for early reopening. Furthermore, the mitigation tactics -and the ease to which they are implemented and enforced -will need to be thoughtfully considered, as they will vary significantly between-and within-industries. For instance, within the arts, entertainment, and recreation industry, social distancing may be appropriate for both movie theaters and indoor concert venues but it might only be enforceable in the movie theater setting. This may indicate that movie theaters are a target for early reopening but that concert venues remain closed for the time being. Similarly, transmission risk is likely lower in large manufacturing facilities where employees have little interaction with each other or those that take place outdoors compared to smaller or indoor operations.
The healthcare industry has high economic impact and high transmission risk in several states and should be given careful consideration for several reasons. First, the industry is essential, so it has not been fully closed. Instead, we consider reopening of the health care industry to mean restarting nonemergent and elective care. We must consider transmission risk more carefully in this population: On one hand, healthcare settings may have increased transmission risk due to likelihood of interactions with infected people; on the other, they are best equipped to prevent the spread of infections (both in training and in personal protective equipment) and have frequent testing and symptom screening of healthcare employees.
Similarly, we must give careful thought to the education industry. First, for most settings within education, economic gain may not be the primary goal. This analysis does not incorporate the future effects of limited or lower quality education due to shelter-in-place policies. Additionally, our analysis is based on data assuming that teachers can work from home, which may not be the case for effective education, particularly for young children. We also do not consider the disproportionate effects of closing schools on marginalized and vulnerable populations independently, or the effects on other industries of parents having limited childcare options during work hours, which is a limitation of this approach (17-19). For these reasons, we recommend that education not be directly compared to other industries, and instead be given special consideration for reopening purposes. Routine COVID-19 testing (weekly, or even semiweekly) and frequent symptom screening may help schools reopen safely; but cheaper PCR tests or pooling of specimens may have to be implemented in the face of limited resources in schools.
This work is meant to inform initial discussions regarding the reopening of industries. While it illuminates high-level industry economic impacts and transmission risks, there are a host of other considerations vital to the policymaking processes. Questions remain regarding the social, cultural, and mental health impacts of industry closures that may outweigh risks of reopening. Data is newly surfacing on how the shutdown has disproportionately affected communities of varying socio-economic status. We need to understand this better and ensure that burden relief reaches the most affected. These, . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted June 12, 2020. . https://doi.org/10.1101/2020.06.11.20128918 doi: medRxiv preprint among many other, questions and considerations need to be a part of the process with which policymakers develop policy and redefine the road back to an open economy. Our work emphasizes that the reopening of states should not be done in haste, nor should it be motivated by political agenda. We can and should use data-driven approaches to control this unprecedented public health risk. Lives are at stake, both due to COVID-19 disease itself and dire economic consequences for millions of Americans. Researchers and decision makers must work together to consider both health and economics when making tough decisions.
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Isolation of paused 80S-mRNA complexes. Messenger RNAs (~190 nt) were derived from plasmid pEMC-PK or -SL and contained the minimal IBV pseudoknot 23 or related stem-loop structure 23 respectively. In vitro translations were carried out using nuclease-treated rabbit reticulocyte lysates (RRL; Promega). The relevant mRNA transcript (300pmole) was annealed to a chimeric biotinylated DNA/2' O-allyl modified RNA oligonucleotide (5' TbTbTbCAGAUCUAUUAAGAGCGGUCGGTbTbTb 3'; 800pmol) in a 10µl reaction containing 20mM Tris pH 7.5, 4mM MgCl2 and 100mM KCl for 5 min at 68°C, 4 min at 37°C and 10 min on ice. The mRNA/oligonucleotide complex was added to 2.4ml of RRL and translation allowed to proceed for 15 min at 27°C prior to addition of cycloheximide (to 1mM). The translation reaction was diluted to 4 ml with HMCK buffer (25mM Hepes-KOH pH 7.8, 5mM MgOAc, 1mM cycloheximide, 150mM KOAc), loaded onto a cushion of sucrose (10ml 34% sucrose in HMCK), centrifuged at 440,000g for 1 hour at 4°C and the pellet resuspended gently in 900µl HMCK. A 1ml (settled bed volume) aliquot of avidin resin (SoftLink, Promega) was preadsorbed with biotin (10mM) and tRNA (100µg).
Subsequently, the resin was preadsorbed with unprogrammed RRL (1ml) and BSA (1mg) before addition of the sucrose-purified ribosomes. After 30 min, the resin was washed (four times with 1 ml HMCK), removed from the column, collected by centrifugation (13,000g, 1 min) and resuspended in 250µl HMCK containing 1nmole of a DNA oligonucleotide (5'ATTCTTGTTGAATCATTCAG 3') complementary to mRNA sequences 3' of the pseudoknot/stem-loop. After incubation, mRNA/ribosome complexes were released from the SoftLink resin by addition of 30U RNaseH (Promega). The resin was pelleted (13,000g, 1 min), the supernatant retained and respun to remove all traces of resin. Ribosomes, final concentration 5 OD260/ml, were aliquoted and frozen at -70°C prior to cryo-EM.
Cryo-electron microscopy and image processing. Samples were blotted onto holey carboncoated copper mesh microscope grids and vitrified by plunging into liquid ethane. Images were captured using a 200 kV Phillips CM200 FEG electron microscope under low dose conditions and at a range of defocus values. The micrographs were scanned using a UMAX PowerLook 3000 scanner on an 8.322 µm raster and then interpolated to 16.64 micron, providing a pixel size at the specimen of 3.33A. Particles were excised and CTF-corrected using EMAN 31 . 80S Apo particles were subjected to ab initio structure determination using angular reconstitution in IMAGIC 24 . Once initial maps were obtained, they were refined iteratively in SPIDER 25 by projection matching. The 80S Apo was used as the alignment template for the stalled ribosome images, again by projection matching in SPIDER. Once initial reconstructions of the stalled ribosomes were generated, several rounds of iterative refinement followed. Alignments in SPIDER were initially on a 15º grid, iteratively refined to 5º. Reconstructions were improved during this process by using a cross-correlation function between each particle image and the corresponding reconstruction to select the best 50% of each set, and by three-way alignment with ranking by correlation coefficient. Next, local alignment procedures 32 were employed down to an angular spacing of 1º and maps were produced by weighting the contribution of individual particle images by the correlation coefficient calculated for them to the alignment model within a mask defined by the common presence of a P-site tRNA in both stalled reconstructions. Finally, pairwise alignment of each image of the 80S PK and 80S SL samples was carried out, each being aligned to the current-best model for that sample and to the 80S Apo reconstruction. Images of 80S PK or 80S SL complexes were judged to be fully occupied if their correlation coefficient within a mask defined either by the P-site tRNA, eEF2 and pseudoknot (for 80S PK ) or by the P-site tRNA (for 80S SL ) was greater when correlated to the current-best complex map than to the 80S Apo map; 12,161 out of 17,672 images of 80S PK and 9,805 out of 14,887 images of 80S SL were in this manner selected. Use of these selected images subsequently produced reconstructions in which tRNAs, eEF2 and pseudoknot displayed full and equal occupancy. The 80S Apo map incorporated 10,296 images. The final data were divided into halves and compared using Fourier shell correlation (FSC) to give resolutions of 14.0 Å (80S Apo ), 15.7 Å (80S SL ) and 16.2 Å (80S PK ) at the FSC 0.5 cutoff. Maps were scaled in reciprocal space to evenly-spaced scattering centres computed within the unscaled maps, as previously described (programmes
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The cyclic oligosaccharides α-, β-, and γ-cyclodextrin consist of 6, 7, and 8 glucose units, respectively, linked by α-1, 4-glycosidic bonds. Cyclodextrins form inclusion complexes with many different small, hydrophobic guest molecules, improving their solubility and stability in aqueous environments. This property makes it have many applications in scientific, medical and industrial fields (Roy et al. 2017) . The industrial use of α-cyclodextrin is in its infancy, yet is still expanding because of its small internal cavity, high water solubility, and resistance to enzymatic hydrolysis. Previous reports have shown that α-cyclodextrin can be used as a carrier of active ingredients, a solubilizer of lipids, a stabilizer of oils, a modifier of flavors or aromas, and a natural soluble dietary fiber (Aytac and Uyar 2016; Li et al. 2010b Li et al. , 2014a .
With the expanding use of cyclodextrins on an industrial scale, the cyclodextrin glucosyltransferases (CGTases, EC 2.4.1.19) , which catalyze the formation of cyclodextrins, have received increased scientific interest. Although CGTases can be obtained from a wide range of bacteria, the characteristics of the CGTases from Bacillus strains are among the closest to industrial requirements (Tonkova 1998) . Early work focused on CGTase production in Bacillus strains (Gawande et al. 1998; Rosso et al. 2002) , and efforts were made to improve CGTase yield by manipulating environmental factors (Arce-Vazquez et al. 2016; Es et al. 2016) . Unfortunately, the strict regulatory mechanisms present in wild-type strains have limited productivity enhancements, resulting in high costs and low yields.
A substantial improvement in CGTase expression was observed when the overexpression was performed in recombinant Escherichia coli (Mana et al. 2015; Open Access *Correspondence: [email protected] 2 School of Food Science and Technology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, Jiangsu, People's Republic of China Full list of author information is available at the end of the article Sonnendecker et al. 2017) . Unfortunately, previous reports have demonstrated that the CGTases expressed in E. coli usually accumulated in the cytosol as biologically inactive inclusion bodies (Makrides 1996; Choi and Lee 2004) , and the refolding processes have been proved to be inconvenient (Li et al. 2005) . Although secretion into the periplasm is helpful for the rapid isolation of recombinant proteins, current methods for the selective release of periplasmic proteins are not suitable for largescale production (Yang et al. 1998; Jeang et al. 2005) . Therefore, the limitations of cytosolic and periplasmic expression of CGTase make the extracellular secretion of CGTases highly needed.
In our previous study, the α-CGTase gene from Paenibacillus macerans JFB05-01 was cloned into the plasmid vector pET-20b(+). This plasmid was then inserted into E. coli BL21(DE3) to form a strain used for the extracellular expression of α-CGTase by E. coli (Li et al. 2010a, b) . The greatest amount of extracellular recombinant α-CGTase was produced when expression was induced at a constant temperature of 25 °C (Li et al. 2010a, b) . Extracellular α-CGTase secretion was inhibited when expression was induced at temperatures >30 °C, and very little recombinant enzyme was obtained at 37 °C (Li et al. 2010a, b) . Additional studies were devoted to improving the yields of these recombinant α-CGTase by optimizing the composition of the culture medium (Ding et al. 2010; Li et al. 2013a, b) . When a one-stage temperature control strategy was used, the membrane permeability was generally at a low level. This low degree of membrane permeability did not favor the secretion of mature α-CGTase into the culture medium. Using a variable temperature control strategy, the membrane permeability may be increased. Therefore, in this study, a novel two-stage temperature control strategy was developed to further improve extracellular expression of P. macerans α-CGTase by E. coli. The underlying mechanisms for the enhanced enzyme secretion are discussed.
Construction of the recombinant plasmid cgt/pET-20b(+), which directs expression of the wild-type α-CGTase from P. macerans strain JFB05-01 (CCTCC M203062) fused to the pelB signal peptide, has been described in a previous report (Li et al. 2009 ). Peptone and yeast extract powder were obtained from Oxoid (Basingstoke, Hampshire, United Kingdom). Isopropyl β-d-1-thiogalactopyranoside (IPTG), O-nitrophenyl-β-d-galactopyranoside (ONPG) and N-phenyl-α-naphthylamine (NPN) were purchased from Beyotime Institute of Biotechnology (Nantong, China). Glycerin and methyl orange were purchased from Shanghai Chemical Reagent Ltd. (Shanghai, China). All inorganic compounds were of reagent grade or higher quality.
A single colony of E. coli BL21 (DE3) harboring plasmid cgt/pET-20b(+) was used to inoculate 50 mL of Luria-Bertani (LB) medium supplemented with 100 mg/ mL ampicillin (inoculum size, approximately 0.1%). This starter culture was incubated on a rotary shaker (200 rpm) at 37 °C until the optical density at 600 nm (OD 600 ) reached 0.6 (about 8 h). The resulting culture was diluted (1:25) into 100 mL of terrific broth medium in a 500-mL flask, and IPTG was added to a final concentration of 0.01 mM to induce protein expression. The induction was allowed to proceed on a rotary shaker (200 rpm) at the specified temperature for 90 h. Samples of the culture were taken at intervals and analyzed for cell concentration and enzyme activity.
Cell fractionation was performed as previously described, with minor modifications (Li et al. 2010a, b) . A 1-mL sample of the culture solution was centrifuged at 10,000 rpm for 10 min and the supernatant was collected. To separate the periplasmic fraction, the bacterial pellet from the 1-mL sample was washed twice with pure water and then completely resuspended in pure water containing 25% (w/v) sucrose and 1 mM EDTA. This suspension was adjusted to a final volume of 1 L, incubated on ice for 2 h, and then centrifuged at 10,000 rpm for 5 min. The supernatant was collected as the periplasmic fraction. The pellet was resuspended in l mL of 10 mM sodium phosphate buffer (pH 6.2) containing 0.5 mM calcium chloride and disrupted by ultrasonication with a sonifier (Branson, USA) for 5 min. After centrifugation at 10,000 rpm for 10 min, the residual cell fragments were mixed with 100 μL of 1% (w/v) SDS-PAGE loading buffer and heated for 10 min in a boiling water bath. After a final centrifugation, the α-CGTase inclusion bodies were in the upper buffer.
α-CGTase activity was determined using the methyl orange method (Li et al. 2013a, b) . The culture supernatant (0.1 mL) was mixed with 0.9 mL of 5% (w/v) soluble starch in 50 mM phosphate buffer (pH 6.0) and incubated at 40 °C for 10 min. After terminating the reaction by the addition of 1.0 mL HCl (1.0 M), 1.0 mL of 0.1 mM methyl orange in 50 mM phosphate buffer (pH 6.0) was added. After the mixture had reacted at 16 °C for 20 min, the amount of α-cyclodextrin in the mixture was determined by measuring the absorbance at 505 nm. One unit of α-cyclodextrin-forming activity was defined as the amount of enzyme able to produce 1 µmol of cyclodextrin per min.
Samples were removed from the fermentation specified times after induction and centrifuged at 10,000 rpm for 10 min. The cell pellets were washed twice with 10 mM sodium phosphate buffer (pH 7.4) and diluted with the same buffer until the OD 600 reached 0.5. Samples (1 mL) of these cell suspensions were used to assess the permeability of their inner and outer membranes as described below.
A previously described absorbance assay was used to evaluate the permeability of the inner membrane (Liao et al. 2004 ). Briefly, cell samples described above were mixed with ONPG (100 μg/mL) to assess permeability of the inner membrane. Cleavage of the ONPG that entered the cell, which is catalyzed by cytosolic β-galactosidase, was determined by measuring the absorption of light at 420 nm using a spectrophotometer. Measurements were taken every 5 or 10 min for 2 h.
Completeness of the outer membrane was assessed using a previously described NPN fluorescence assay (Eriksson et al. 2002) . The fluorescence of NPN is weaker in aqueous solution than it is in hydrophobic environments. When NPN is applied to intact cells, it is excluded from the cells' interior by the lipopolysaccharide layer of the cells' outer membranes. Once the outer membrane is compromised, NPN gains access to the lipid bilayer and its fluorescence becomes strong in this hydrophobic environment. Cell suspensions (1 mL, prepared as described in the previous paragraph) were treated with NPN at a final concentration of 10 mM. Fluorescence was measured every 5 or 10 min for 2 h using excitation and emission wavelengths of 350 and 428 nm, respectively, and slit widths of 1 nm. Elevated NPN fluorescence was considered evidence of compromised cell membranes.
All measurements were performed in triplicate. The mean and standard deviations of the data collected were calculated using SPSS 17.0 software (SPSS Incorporated, Chicago, Illinois, USA).
In an effort to enhance extracellular α-CGTase expression, a novel two-stage temperature control strategy, incubating the expression strain at 25 °C for 24 h and then raising the temperature directly to 30, 34, or 37 °C was investigated. The two-stage temperature control strategy had substantial effects on extracellular α-CGTase production (Fig. 1) . A control culture maintained at 25 °C showed a slow rise in extracellular α-CGTase activity until about 50 h of cultivation, a rapid rise between 50 and 80 h of cultivation, then a leveling off between 80 and 90 h of cultivation. Shifting the temperature to 30 °C at 24 h accelerated the increase in extracellular α-CGTase activity between 24 and 80 h of cultivation, compared with the control. At 90 h of cultivation, the enzyme activity reached approximately 27 U/mL, which was 1.2 times that of the control. Shifting the temperature to 34 °C at 24 h further accelerated the increase in extracellular α-CGTase activity when comparing with the increase seen at 30 °C, but in this culture, the plateau was reached earlier (approximately 70 h of cultivation) and the activity at 90 h was not a significant improvement over the level seen in the control culture. Shifting the temperature to 37 °C at 24 h gave the greatest initial rise in extracellular α-CGTase activity; however, the activity peaked at a low activity level at 65 h, and then decreased.
Encouraged by the modest increase in extracellular α-CGTase activity observed when the temperature shift occurred at 24 h of cultivation, the temperature shift from 25 to 30 °C was conducted at 14, 24, 28, 32, or 36 h of cultivation (Fig. 2) . Shifting the temperature during mid-log growth (14 h) gave the poorest extracellular α-CGTase activity at 90 h of cultivation. Results improved as the timing of the temperature was delayed until a maximum was reached when the temperature was shifted at 32 h of cultivation (late logarithmic growth). Shifting the temperature at the onset of stationary phase (36 h of cultivation) gave substantially poorer extracellular α-CGTase activity at 90 h of cultivation. When the temperature was changed from 25 to 30 °C at 32 h and fermentation was allowed to continue for a total of 90 h, the enzyme activity reached 32.5 U/mL, which was 1.45 times that of the control.
To investigate the mechanisms enhancing extracellular expression, the permeability of the E. coli outer membrane was assessed using the fluorescent probe NPN (Fig. 3a) . At the same time, the permeability of the inner membrane was assessed using the colorimetric probe ONPG (Fig. 3b) . The permeabilities of both membranes increased with induction time (Fig. 3) . Furthermore, the induction temperature shift from 25 to 30 °C resulted in the obvious increase in the permeabilities of both membranes (Fig. 3) .
To further investigate the mechanisms enhancing extracellular expression, the SDS-PAGE was used to show the amount of α-CGTase protein in the medium, the periplasmic space, the cytoplasm (as a soluble protein) and the insoluble inclusion bodies. The results using the control strategy (induction at 25 °C for 90 h) and the one using the two-phase induction strategy (induction at 25 °C for 32 h, then induction at 30 °C for an additional 58 h) were compared in Fig. 4 To investigate the time course of α-CGTase movement, the activity of the α-CGTase in the periplasm was determined as a function of time (Fig. 5) . Periplasmic α-CGTase activity increased dramatically during the first 15 h of induction at 25 °C, and then had a slow decline. When maintained at 25 °C, the decline continued until 45 h, and then there was a slow increase followed by a slow decline. This produced a peak of periplasmic activity at approximately 65 h of induction. Shifting the induction temperature to 30 °C after 32 h of induction at 25 °C increased the periplasmic α-CGTase activity substantially until it peaked at approximately 55 h. Thereafter, the activity dropped dramatically until, at 90 h, the activity was much lower than that observed when the induction temperature was maintained at 25 °C. These data are consistent with the SDS-PAGE study, suggesting that the two-phase induction strategy increased the flux of α-CGTase through the periplasmic space.
Extracellular α-CGTase production occurs in a series of steps. The pre-α-CGTase produced on the ribosome contains an N-terminal pelB signal peptide sequence. This N-terminal signal peptide directs translocation of the pre-α-CGTase across the inner membrane to the periplasmic space via the SecB pathway (Su et al. 2012) . During this process, the signal peptide is removed. Once α-CGTase enters the periplasm, it has two potential fates: it can pass through the outer membrane and enter into the culture medium, or it can aggregate and form inclusion bodies in the periplasmic space (Li et al. 2014a, b) .
A previous study showed that the greatest amount of extracellular α-CGTase was produced when the induction was conducted at a constant temperature of 25 °C (Li et al. 2010a, b) . Extracellular α-CGTase production was inhibited when the induction temperatures was >30 °C, and very little recombinant enzyme could be obtained at 37 °C. The reason of this phenomenon was probably that the pre-α-CGTase formed inclusion bodies at the inner membrane at temperature above 30 °C, which could block the pre-protein translocation channels and suppress the entrance of newly synthesized pre-CGTase into the periplasm (Chen et al. 2014) . At 25 °C, pre-α-CGTase synthesis proceeded at a desirable rate and most of the pre-CGTase passed smoothly through the inner membrane into the periplasm, and then folded correctly (Mergulhao et al. 2005; Fang et al. 2010) . The rate of protein synthesis at 25 °C may have prevented the target protein from saturating the secretion machinery and have facilitated the translocation of α-CGTase across both E. coli membranes (Yamabhai et al. 2008; Fang et al. 2010) .
Having previously established that an initial induction temperature of 25 °C was optimal (Li et al. 2010a, b) , we considered changes that would increase α-CGTase flux across both the inner and outer membranes without also increasing the rate of α-CGTase aggregation in the cytoplasm or periplasmic space. Increasing the temperature is a reasonable strategy to increase the α-CGTase movement across the membranes since it can increase the membrane permeability. However, prolonged induction periods at elevated temperature, especially at 37 °C, may cause cell lysis, which would decrease productivity and secretion capacity (Mana et al. 2015) . Therefore, the second-stage temperatures between 30 and 37 °C were investigated during the total induction period of 90 h. The timing of the temperature shift had to be selected to minimize formation of inclusion bodies through accelerating translation. In the first experiment, 24 h was chosen because the inspection of the growth curve (Fig. 3) revealed that 24 h was well past the mid-point. The results showed that increasing the temperature increased the initial rate of α-CGTase production, but temperatures >30 °C gave poorer overall yields at 90 h of induction. This phenomenon was perhaps due to the premature cell lysis (Mana et al. 2015) .
After selecting 30 °C as the optimal second-stage temperature, we decided to further investigate the timing of the temperature shift. The time course of α-CGTase activity in the periplasmic space during induction at 25 °C was clearly biphasic, with an early peak at 14 h of induction and a late peak at approximately 64 h (Fig. 5) . 1, 3, 5, 7) We decided to investigate the temperature shift times beginning with the early peak (14 h, Fig. 5 ) and extending through late-log phase (36 h, Fig. 3 ). The optimal yield of the extracellular α-CGTase was finally obtained with a temperature shift time of 32 h (Fig. 5) .
The mechanistic data presented in Figs. 3, 4 and 5 strongly suggest that the two-stage induction strategy increased membrane permeability, which caused increased extracellular α-CGTase production. The increased inner membrane permeability in the ONPG study (Fig. 3 ) and the decreased amount of cytosolic protein and inclusion bodies in the SDS-PAGE study (Fig. 4) suggest that the two-stage induction strategy increased E. coli inner membrane permeability and then accelerated the transit of the α-CGTase across the inner membrane. This is confirmed by the increased α-CGTase activity that observed in the periplasmic space between 32 and 60 h of induction (Fig. 5 ). This accumulation of the α-CGTase activity in the periplasmic space further suggests that outer membrane permeability plays a significant role in the extracellular expression. The low degree of the outer membrane permeability was the main reason why only a small portion of the mature α-CGTase was secreted into the culture medium during the early stage of induction. The increased permeability of the outer membrane in the NPN study (Fig. 3 ) and the decreased amount of periplasmic α-CGTase in the SDS-PAGE study (Fig. 4) suggest that the two-stage induction strategy increased the E. coli outer membrane permeability, and then accelerated the transport of the α-CGTase across the outer membrane. This is confirmed by both the rapid decrease in the periplasmic α-CGTase activity during 60-90 h of induction and the simultaneous increase in the extracellular α-CGTase activity (Fig. 2) . In summary, this study showed that when the α-CGTase from P. macerans strain JFB05-01 was expressed in E. coli as a recombinant fusion protein carrying a pelB leader sequence, a two-stage induction temperature control strategy can help to obtain the optimal extracellular α-CGTase production. In this two-stage induction temperature control strategy, induction was conducted at 25 °C for 32 h, and then the temperature was shifted to 30 °C and the induction was continued for an additional 58 h. Using this two-stage induction control strategy, the extracellular α-CGTase activity was increased by 45% compared with the induction at a constant temperature of 25 °C. The primary mechanism responsible for the increase of the α-CGTase production was due to the increase of the membrane permeability. This is the first report describing a two-stage temperature control strategy used for increasing the extracellular α-CGTase production in E. coli. Abbreviations α-CGTase: α-cyclodextrin glucosyltransferase; E. coli: Escherichia coli; IPTG: isopropyl β-d-1-thiogalactopyranoside; ONPG: O-nitrophenyl-β-dgalactopyranoside; NPN: N-phenyl-α-naphthylamine; LB: Luria-Bertani; OD: optical density; EDTA: ethylenediaminetetraacetic acid; SDS-PAGE: sodium dodecyl sulfate polyacrylamide gel electrophoresis.
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Cardiovascular disease continues to be a leading cause of death and reduced quality of life. The renin-angiotensin system (RAS) and its effector molecule, angiotensin (Ang) II, are known to affect a wide variety of functions in the cardiovascular and renal systems, playing an important role in the pathophysiology of cardiovascular disease. Therefore, there has been considerable interest over the years in understanding exactly how the RAS functions and is regulated. The RAS was once thought to be a fairly simple linear cascade operating systemically, but over the past few decades it has become increasingly clear that the RAS is actually a complex system that includes multiple alternate pathways and feedback mechanisms. The fact that the RAS functions locally as well as systemically, and that this local function may be differently regulated and involve different components than the systemic RAS, is of particular importance in understanding the impact of current or potential therapies designed to inhibit the pathophysiological effects of Ang II. In addition, the discovery of additional Ang peptides, including Ang-(1-5), Ang-(1-7), Ang-(1-9), Ang-(2-8), Ang-(3-8), and Ang-(1-12) [1-3], has made it clear that Ang II can no longer be viewed as acting in isolation.
Nevertheless, Ang II is generally still considered to be the primary effector molecule of the RAS, and its impact on the heart, both directly and as a result of renal and vascular effects, is significant. With roles in vasoconstriction, mitochondrial function [4], thrombosis, fibrosis, hypertrophy [5] , apoptosis [6] , and autophagy [7••], Ang II is intimately involved in cardiac function and remodeling. Heart failure is associated with RAS upregulation, and acute myocardial ischemia-reperfusion significantly increases expression of several of the major cardiac RAS components, including Ang II [8] . This review will focus on the regulation of Ang II in the heart, in the context of current and emerging modes of intervention.
In the classic RAS, angiotensinogen produced in the liver enters the bloodstream, where it is cleaved by kidneyderived renin to form the decapeptide, Ang I. Endothelial cell-bound angiotensin-converting enzyme (ACE) then further cleaves Ang I to produce the biologically active octapeptide, Ang II. The ubiquitously expressed ACE exists in both membrane-bound and soluble forms, and has two independent catalytic sites with distinct substrate and inhibitor specificities. ACE is also capable of hydrolyzing a variety of other substrates, including the cardioprotective agents bradykinin, N-acetyl-seryl-aspartyl-lysyl-proline tetrapeptide, and Ang-(1-7) [2, 3, 9] . Furthermore, ACE inhibitors enhance kinin B1 and B2 receptor signaling [10]. Thus, ACE has both Ang II-dependent and Ang IIindependent effects on cardiovascular function and is a logical target for RAS regulation.
Indeed, ACE inhibition reduces blood pressure, left ventricular hypertrophy, and cardiac inflammation, possibly through inactivation of NFκB, in spontaneously hypertensive rats [11, 12] . Clinical studies have shown various ACE inhibitors to be effective in treating congestive heart failure, acute myocardial infarction, and coronary artery disease, as well as hypertension [13•]. Several different ACE inhibitors are commercially available, and current guidelines include the use of ACE inhibitors as first-line therapy for patients with heart failure or at risk for heart failure [14] . However, use of ACE inhibitors is associated with a relatively high incidence of adverse effects, presumably owing to their effect on the kallikrein/kinin system.
Although acute ACE inhibition decreases plasma Ang II, chronic treatment results in an escape phenomenon in which Ang II returns to pretreatment levels. The mechanisms involved in this rebound are not well understood, but there is some evidence that ACE may be involved in cellular signaling, in addition to its enzymatic role [15] . Protein kinase CK2 binds and phosphorylates Ser 1270 in the ACE cytoplasmic tail, an interaction that is enhanced in endothelial cells in the presence of bradykinin or an ACE inhibitor. The phosphorylated ACE activates JNK, leading to nuclear accumulation of c-Jun and an increase in ACE expression. Although Kohlstedt et al. [15] suggest that this ACE inhibitor-induced increase in ACE expression may somehow contribute to the beneficial effects of ACE inhibition, this "ACE signaling" may act as a negative feedback mechanism by which ACE inhibition becomes self-limiting. On the other hand, it is also possible that long-term ACE inhibition eventually shifts the balance toward the alternative, chymase-dependent, Ang II synthesis pathway.
Although ACE is the main enzyme responsible for systemic Ang II synthesis, chymase is also a major Ang II-forming enzyme in the human heart. Chymase is found mainly in the secretory granules of mast cells, where it remains inactive until its release into surrounding interstitial tissues. It is also strongly inhibited by endogenous serine protease inhibitors when not complexed with heparin proteoglycan. This fact, together with the existence of significant species variability in both the number and types of chymase, has contributed to some controversy about the physiological role of chymase, but there is accumulating evidence that chymase plays an important role in cardiac tissue formation of Ang II, particularly under pathophysiological conditions [16] [17] [18] . Recently, Wei and colleagues [19••] demonstrated that, although chymase activity in the interstitial fluid of conscious mice was negligible under basal conditions, chronic ACE inhibition markedly increased transcription and activity of an Ang II-forming chymase via a kinin B2 receptor/mast cell-dependent mechanism, while Ang II levels remained unchanged. Addition of a chymase inhibitor significantly lowered Ang II levels, demonstrating that chymase was, in fact, responsible for the maintained Ang II levels. Dual treatment with both ACE and chymase inhibitors dramatically improved left ventricular function, remodeling, and survival following myocardial infarction in hamsters. Furthermore, recent evidence suggests that Ang-(1-12), a recently discovered biologically active Ang peptide, can act as an alternative precursor for Ang II [20••] , and that chymase is responsible for this process in cardiac tissue [21] .
In addition to cleaving Ang peptides, chymase also appears to play a role in tissue remodeling and organ damage during heart failure. Chymase activates transforming growth factor-β (TGF-β), which increases fibroblast proliferation and collagen deposition, and matrix metalloprotease-9 (MMP-9), which is involved in extracellular matrix turnover. Thus, as with ACE inhibition, chymase inhibition potentially could provide benefits in patients with cardiovascular disease that are both dependent and independent of Ang II [22] .
Clearly, the existence of alternate pathways for conversion of Ang I to Ang II makes complete inhibition of the RAS problematic at this point. As mentioned above, renin functions further upstream in Ang II formation, converting angiotensinogen to Ang I. Circulating renin originates primarily in the kidneys, where it is synthesized by cleavage of its precursor, prorenin. The source of renin involved in local Ang II synthesis is less clear, as renin expression levels in cardiac tissue are generally very low under basal conditions. However, cardiac renin expression has been detected under certain pathological conditions, such as diabetes [23] , and a nonsecreted, truncated active form of renin is induced by myocardial infarction [24] . In addition, circulating prorenin and renin can bind to mannose-6-phosphate and (pro)renin receptors, allowing them to contribute to local Ang II synthesis. Whether cardiac mast cells are a significant source of renin remains controversial and may depend on context, species, or both [25] [26] [27] .
A number of direct renin inhibitors exist [28• ], but the most extensively studied inhibitor is aliskiren. In spontaneously hypertensive rats, aliskiren was equivalent to other RAS inhibitors in improving coronary endothelial function and cardiac hypertrophy, but it provided superior long-term suppression of cardiac angiotensin [29] . Similarly, diabetesinduced intracellular Ang II synthesis in adult rat cardiomyocytes, and the associated oxidative stress and fibrosis, were inhibited more effectively by aliskiren than by other RAS inhibitors [23] . Though approved for antihypertensive use, the relative effectiveness of aliskiren in reducing hypertension is still a matter of debate. Though some studies have shown aliskiren to be superior to other RAS inhibitors, others have shown comparable but not superior effectiveness [28•, 30, 31] . Although direct renin inhibition should more completely inhibit downstream RAS function, and aliskiren has a longer half-life than other RAS inhibitors, the absence of negative feedback from Ang II signaling leads to an increase in plasma renin/prorenin levels. This increase in renin/prorenin concentration may enhance (pro)renin receptor signaling, which has been shown to activate extracellular signal-regulated kinase (ERK) in an Ang II-independent manner even in the presence of aliskiren [32••] , although the physiological relevance of this pathway in vivo remains to be determined. Alternatively, Ang-(1-12) may serve as an alternate substrate for Ang II formation in the absence of renin activity [33] , thereby limiting Ang II suppression. On the other hand, there is evidence that aliskiren may have cardioprotective effects in patients with left ventricular hypertrophy or heart failure [28•, 30, 31] , and ongoing studies should provide additional data on its clinical usefulness against conditions associated with high plasma renin activity.
Angiotensin II Type 1 Receptor Blockers Ang II can bind to either of two seven-transmembrane G protein-coupled receptors, the Ang II type 1 receptor (AT1R) or the Ang II type 2 receptor (AT2R). Although it has been suggested that intracellular Ang II may have intracrine functions independent of the AT1R [17] , most of the known functions of Ang II involve binding to this receptor, and the AT1R exerts its effects through both G protein signaling and heterodimerization with or transactivation of other receptors [3]. AT1R is found on the cell surface, where it binds extracellular Ang II and is rapidly internalized, as well as on mitochondria [4] and nuclei [34] . AT2R, on the other hand, has very limited expression in adult organisms but is upregulated during certain pathophysiological conditions. Its functions generally oppose those of the AT1R [5, 35] .
AT1R blockers (ARBs) are designed to specifically inhibit Ang II-induced AT1R signaling, and, therefore, theoretically should provide more complete RAS blockade than interventions that block only one of the alternative Ang II formation pathways. Moreover, AT2R signaling induced by the resulting accumulated Ang II may further potentiate the protective effects of ARBs. Clinical trials have shown ARBs to be effective in reducing hypertension [36] , but reports on the effectiveness of ARBs in treating other cardiovascular disease outcomes have been mixed [37•] . These results may be due in part to the absence of rigorous dosage optimization, as suggested by the differential effects of high and low doses of losartan seen in the HEAAL study [38] . In addition, small differences in the structure of different ARBs have proven to have a significant impact on their functionality, including both AT1R-dependent and AT1Rindependent effects [39, 40] . Therefore, the effectiveness of any given ARB may depend on the specific disease condition. Current guidelines recommend the use of ARBs in patients at risk for heart failure and as an alternative treatment for selected heart failure patients who are intolerant of ACE inhibitors [14] . However, a recent meta-analysis found that ARBs may be associated with an increased risk of cancer [41•] , suggesting that further investigation of these drugs is warranted.
AT1R-associated protein (ATRAP) is an 18-kDa protein which, upon Ang II stimulation, binds to the carboxylterminal cytoplasmic tail of AT1R in cardiovascular cells and promotes receptor internalization, acting as an endogenous AT1R inhibitor [42] . Although the physiological importance of this protein needs further clarification, it appears that the AT1R:ATRAP ratio is important in determining the effect of Ang II on the heart. Ang IIinduced cardiac hypertrophy was accompanied by a significant decrease in ATRAP expression in wild-type mice and was completely abolished in transgenic mice with cardiomyocyte-specific overexpression of ATRAP, independent of any effect on blood pressure [43••] . Thus, increasing ATRAP expression could be a novel therapeutic option for inhibiting AT1R signaling.
Cell-penetrating peptides are typically short cationic peptide sequences, which can be used to deliver proteins into intact cells. A cell-penetrating peptide consisting of the second intracellular loop of the AT1R linked to the HIV-transactivating regulatory protein domain effectively inhibited AT1R functions mediated by the second intracellular loop, but not those previously shown to be unaffected by mutations in this region [44] . Although this approach requires further development and a more complete understanding of the mechanisms involved in AT1R signaling, this study suggests that cell-penetrating peptides potentially may be used to take advantage of the biased agonism observed in AT1R signaling, serving as a powerful tool for selectively regulating Ang II receptor function.
As mentioned above, Ang II-AT2R signaling generally opposes that of the AT1R, and AT2R signaling triggered by accumulated Ang II may be partially responsible for the antihypertensive effect of ARBs through its induction of bradykinin/nitric oxide-mediated vasodilation [45] . In addition, the AT2R may have ligand-independent protective effects, inhibiting AT1R signaling directly through heterodimerization of the two receptors [3] and constitutively inhibiting cardiomyocyte autophagy [7••]. However, AT2R signaling has also been linked to cardiac hypertrophy and apoptosis [5] , and a recent study suggests that AT2R function can change from relaxant to constrictor upon Ang II binding under hypertensive conditions [46••] . Nevertheless, direct AT2R stimulation with a novel nonpeptide AT2R agonist, compound 21, inhibited myocardial infarction-induced apoptosis, inflammation, scar formation, and systolic and diastolic left ventricular dysfunction [47] , suggesting that direct AT2R stimulation could be an effective way to prevent cardiac remodeling.
Like its homolog, ACE, ACE2 is a zinc-metallopeptidase that can exist in both membrane-bound and soluble forms. Whereas ACE synthesizes Ang II from Ang I, however, ACE2 serves the opposite function, degrading Ang II to Ang-(1-7). In addition, ACE2 can cleave Ang I to Ang-(1-9), which can then be further cleaved by ACE to give Ang-(1-7). Although its importance in baseline cardiac function is somewhat controversial [48] , several studies in mice and rats have shown ACE2 to be protective against pathologic cardiac remodeling and dysfunction, owing to either the resultant decrease in Ang II levels or the increase in the biologically active Ang-(1-7) [49] [50] [51] [52] .
Degradation of Ang II is an obviously important part of ACE2 function, but synthesis of biologically active cleavage products also appears to play an important role in mediating its cardioprotective effects. The degradation product of Ang II, Ang-(1-7) , binds to the Mas receptor, thereby exerting effects that oppose those of Ang II, including inhibiting cardiac hypertrophy and fibrosis [53, 54••, 55] . Ang-(1-7) has also been shown to bind to ACE, inhibiting bradykinin degradation, as well as to AT1R and AT2R, inhibiting the former and stimulating the latter [2]. Ang-(1-9) is formed by cleavage of Ang I by either ACE2 or carboxypeptidase A. Though Ang-(1-9) was once thought to be simply a stable intermediary in Ang-(1-7) production, it has now been shown to be biologically active in its own right. Administration of Ang-(1-9) following myocardial infarction in rats decreased plasma Ang II, inhibited ACE activity, and prevented cardiomyocyte hypertrophy [56••] . Furthermore, treatment of myocardial infarcted rats with either an ACE inhibitor or ARB led to an increase in circulating Ang-(1-9) but not Ang-(1-7), suggesting that Ang-(1-9) may be an important cardioprotective factor. ACE2 expression is inhibited by Ang II and is upregulated by treatment with ACE inhibitors and ARBs, suggesting that it may contribute to the effectiveness of these drugs and may itself be a good candidate for therapeutic intervention. Possible approaches for increasing ACE2 activity include using a small-molecule activator, such as XNT ([1{(2-[dimethylamino]ethyl) amino}-4-[hydroxymethyl]-7-[{(4-methylphenyl)sulfo-nyl}oxy]-9 H-xanthen-9-one]), and gene transfer therapy [53] . Further investigation is warranted, however, as longterm extreme overexpression of ACE2 resulted in severe cardiac fibrosis in stroke-prone spontaneously hypertensive rats [57] , and ACE2 has recently been identified as the receptor for the severe acute respiratory syndrome (SARS) virus [58] . As with ACE2, Ang-(1-7) levels are increased by ACE inhibitor and ARB treatment, suggesting that it too plays a role in the beneficial effects of these drugs. However, Ang-(1-7) has a short half-life, making it unsuitable for direct therapeutic use. Alternative Mas agonists, such as AVE0991, as well as approaches to increasing the stability of Ang-(1-7), are currently under investigation [53] .
Because patient adherence to a daily medication regimen can be problematic, a vaccine administered only several times a year may be a more effective mode of treatment. Although early attempts to develop vaccines against renin and Ang I were not successful, recent work on an Ang II vaccine, CYT006-AngQb, appears to be more promising. In initial testing, a 300-μg dose significantly reduced blood pressure and appeared to be well tolerated [59] . Further study is required, however, to determine the long-term efficacy and safety of such a vaccine. In a somewhat different approach, injection of antibodies against the C-terminal fragment of the AT1R (kardos) also appears to have an antihypertensive effect and is currently under investigation [60] .
Ongoing advances in modern medicine have led to the development of many effective treatment options for hypertension and cardiovascular disease. Nevertheless, morbidity and mortality related to cardiovascular disease remain high. The RAS plays an important role in determining cardiovascular function, and several currently used therapeutic approaches specifically target critical points in the RAS signaling pathway. However, because of the existence of alternative synthesis and signaling pathways and tight regulation via positive and negative feedback loops, the goal of complete inhibition of the effects of Ang II remains elusive. The extent to which Ang II exerts its effects via pathways dependent on blood pressure or independent of it remains a matter of debate, prompting some to argue that the main focus of any treatment regimen should be blood pressure control, rather than specifically targeting the RAS. On the other hand, drugs chosen for effective control of hypertension may not be optimal for preventing organ damage and may require further optimization for treatment of heart failure. Combinations of multiple RAS inhibitors are also being heavily investigated as a means to more completely inhibit RAS function, but these remain controversial. As our understanding of the mechanisms involved in RAS function and its inhibition grows, however, it should become possible to further improve patient outcomes. The ongoing discovery of new functions of current drugs, as well as new potential therapeutic targets, is an indication that there is still much to be learned and great potential for more effective cardiovascular treatment.
Disclosure No potential conflicts of interest relevant to this article were reported. This study describes a previously unknown function of the RAS, providing the first evidence that Ang II and its receptors are involved in regulating autophagy in the heart.
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Since Dec 2019, novel coronavirus (Covid-19) involved 207 countries and territories, infected 976249 people with a mortality rate of 50489 (5.17%). 1 The Covid-19 created health, economic, political, and social challenges worldwide.
The Covid-19 pandemic revolutionized the threat dimensions. The policy makers and strategists had been debating traditional and non-traditional security threats, especially in the last five decades, wherein the wideners have over taken the traditionalists. 2 Traditional security threats revolved around violation of human rights through the act of terrorism, nuclear war, civil war, inter or intra-state wars, struggle for power maximization and other state-centric threats. However, the non-traditional security threats encompassed poverty, hunger, epidemics, food security, climate change impacts and other assorted challenges which go beyond the serious consideration of the international community including leading global institutions like the United Nations and others.
On the contrary, the greatest threat for the maintenance of global peace and security for human survival has emerged from this pandemic of corona virus, for which neither individuals nor nations were prepared. The causes and effects of this real threat have surpassed the heralds of nuclear war, war on terror and even the climate change.
China was the first to thwart and contain, whereas Italy and Iran were later in the run; they had prior warnings but failed to restrict the virus. The basic reason other than the evident medical facilities and economic resources were the conceptual policy making and implementation. China being a strict state implemented measures aggressively and effectively. The military worked under the government directives and results were obtained. In Iran, the disconnection between military and government officials was evident. In Iran the advice of military to restrict movement went unheeded and later on it was a disjointed and half-hearted effort. 2 Italy on the other hand was a liberal democracy, which when tried to implement the isolation formula was defeated due to civic rights usurping slogans and a care free attitude, until it was too less and too late.
Lessons were derived from Word War I (1914-18) and World War II , but what were the lessons from the threat which affected quarter of the world's population and death of about 50 million in 1919. Unfortunately, not much was derived from the Spanish flu, rather it was forgotten in the annals of history. Now, what are lessons a miniscule, emerging pathogen has taught to 7.8 billion humans at the start of new decade after all? Threats to humanity are not confined, and limited by borders and financial situations. This crisis motivates us to see through the fog of fake individualism at national and international level. Role of institutions have been rearranged the United Nations Security Council (UNSC) has been replaced by World Health Organization (WHO), and medical fraternity has gained ancillary importance in collaboration with military. Medical and pramedical workers are the new frontline soldiers. Netizens are the mouths and ears, which with medical authentication can become credible and effective. In dealing with any threat, we direly need to have singleness of conception, incorporating medical experts and harmonious execution. The fear-provoking pathogens such as Covid-19 can be seen as a revelation, as some time crisis turning the challenges into opportunities.
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T he new coronavirus outbreak, following the rapid spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus worldwide, has imposed a reshaping of the health system. In Italy, the onset of infection in February 2020 was followed by a rapidly escalating cluster of infections.
Physicians and healthcare professionals are at the forefront of the pandemic response and are certainly the ones most dangerously at risk of infectious disease. The Department of Oral and Maxillofacial Surgery is particularly vulnerable to coronavirus disease 2019 infection due to the close exposure to the oral and nasal areas of patients in routine clinical practice.
During the SARS-CoV-2 pandemic, it is mandatory to organize the treatment of patients in such a way that the transmission of infection is minimized. [1] [2] [3] [4] [5] [6] The aim of this work is to draw up new guidelines for infection prevention in clinical control, treatment processes, clinical management, protection, and disinfection of healthcare professionals. The resultant guidelines may be used by all maxillofacial surgeons during the pandemic, supporting decision making that is likely to be different from current practice. Especially for the next phases of the pandemic where will be crucial the correct approach to the patient to avoid the same errors made at the beginning of the pandemic.
For certain time intervals, healthcare may need to focus on COVID-19 patients in critical patients. In addition to infectivologists, anesthesiologists, and pneumologists, oral and maxillofacial surgeons must be aware of the new challenges in the risks of viral transmission between patients and medical staff. To reduce the pressure on the health system, it may be necessary to request the postponement of elective surgeries. The departments of maxillofacial surgery should focus their activity on oncologic patients, deep head-neck infections, and facial-skull traumatology.
Given the high number of asymptomatic patients that are SARS-CoV-2-positive, all patients should be considered infectious. 7, 8
All patients should undergo a telephone triage for any signs or symptoms that may suggest COVID-19 infection and/or pending problems, such as severe dysphagia or airway impairment. Patients who are believed to be at risk for significant negative results if they are not evaluated should be offered a visit to the clinic in person. Those with symptoms that suggest possible COVID-19 infection should be directed to specialized departments. 9, 10 Outpatient Activities, First Visits, and Checks
During the peak of the COVID-19 pandemic, any potential outpatient visits should be carefully considered and kept to a minimum. At the current stage of infection, patients with re-infection for insufficient acquired immunity cannot be ruled out; every patient should be treated as potentially positive. Medical masks must be provided to the patients in the waiting room while maintaining the necessary safe distances. Patients with respiratory symptoms should be separated if other patients are present; if the reason for the visit proves to be low priority, they should be reprogrammed.
Before accessing the hospital, all patients should disinfect their hands and monitor their body temperature. The examination of the head and neck, which will include the mucous membranes, should be performed while maintaining the suggested level of precaution.
Given the frequent exposure to saliva and sputum, which are related to a high risk of viral transmission, the clinical examination of a patient must be practiced in a separate room away from other patients with only the necessary staff authorized to be present. The examination must be carried out by the most experienced medical staff for a more targeted assessment. When performing clinical examination, use of safety devices such as a mask, glasses, gloves, headdress, and disposable gown is recommended. The patient should practice washing the mouth with an antiseptic solution to reduce any potential viral load (eg, with 50% solutions of chlorhexidine, hydrogen peroxide, povidone iodine). In addition, the nose and nasopharynx have been referred to as reservoirs for high concentrations of the SARS-CoV-2 virus, so for endoscopic examinations of the nasal cavities it is vital to take the same precautions. [11] [12] [13]
During the COVID-19 pandemic, all patients admitted to a hospital unit shall have to undergo a SARS-CoV-2 test on a routine basis. Patient admitted to a department of maxillofacial surgery, waiting for surgery, or in immediate postoperative, should undergo monitoring of their oxygen levels and temperature every 6 hours.
Patients should be placed in single rooms whenever possible, or alternating beds (as it is obvious that infected and uninfected patients must be separated); rooms must be aired every 2 hours, and visits by family members must be suspended to limit the infectious risk. Visitors who must enter by absolute necessity should be screened for acute respiratory illnesses before entering the health facilities. Each patient must be provided with a new protective mask on a daily basis.
Patients should be instructed to limit their movements within the hospital; if instrumental examinations are scheduled outside the department, this must be carried out following the established COVID-19 guidelines by providing the patient and medical staff with personal protective equipment. 11, 12 During the dressing of postoperative patients, the same precautions should be taken as for an outpatient examination: each patient should be considered as infected. Before taking a patient to the operating room, a SARS-CoV-2 test must be performed. An emergency patient who does not have sufficient time for testing should be treated the same way as an infected patient.
Patients who need surgery should practice mouth washing and hand disinfection before leaving their room; they must wear an FFP2 or N95 respirator mask without a valve and a disposable gown when they are taken to the operating room. The nursing staff responsible for the transfer must wear an FFP2 or N95 respirator with valve, as well as the proper dress and gloves. The operating room must have negative air pressure to reduce the spread of the virus. Before entering the operating room, all staff members must wear personal protective equipment: a disposable coat, gloves, mask, and face shield. The surgical team must come in to the operating room only after the patient has been intubated. Operating room staff must be reduced to the necessary minimum, and the surgical team must be equipped with the aforementioned protective equipment complemented by a watertight sterile dress.
During surgery, aerosol formation should be reduced as much as possible; thus, it is necessary to limit the use of rotating and piezoelectric instruments in favor of osteotomes where possible. 1 The electrocauterization should be avoided or used at the least possible power if strictly necessary. The operating field should be strictly limited to the area of surgical interest, and an extraoral approach should be preferred to the intraoral one whenever possible. The surgical team must leave the operating room before the patient is extubated. After the patient has left the operating room, at least 15 minutes must pass before the operating room disinfection procedures begin; waste management must follow well-defined rules. [11] [12] [13] [14] [15] Treatment Algorithm Based on Urgency and Severity of Pathology During the SARS-CoV-2 pandemic, the treatment of the patient must be organized in such a way that the transmission of the infection is minimized. Concepts need to be developed that account for the possible need to assess patients based on the degree of treatment urgency. 16 All patients who need elective procedures, such as for cleft lip and palate, dentofacial deformities, chronic respiratory deficits, and benign nondebilitating pathologies, are recommended to postpone surgery. Patients with clinical priority, such as malignant tumors and chronic infections, are not deferrable; they must be admitted to hospitalization and administered a full assessment with blood tests, electrocardiogram, chest radiography, and anesthesiologic evaluation. Lung computed tomography and laboratory tests for SARS-CoV-2 should be carried out according to the anesthesiologist's instructions. Patients in critical conditions, or surgical emergencies due to life-threatening conditions such as bleeding and upper respiratory obstructions, should be treated in accordance with all protocols for infection prevention and control in addition to the routine universal precautions.
Subacute patients with stable vital parameters, which includes patients with stable closed fractures where there is no risk of infection or death, should be thoroughly screened for COVID-19 and receive accurate anamnestic and preoperative assessment to avoid possible exposure to COVID-19. Subacute patients with stable vital parameters that may be subject to rapid clinical deterioration (including patients with exposed fractures, fractures with bone stump mobility, functional deficits, risk of nerve vascular injury, or soft-tissue substance loss) should be treated in accordance with all protocols.
Availability of blood products during the COVID-19 emergency may be limited, so requests for strictly necessary patients is recommended; surgical and treatment plans that are as simple as possible are recommended. Patient stay times should be limited to that which is strictly necessary, within the limits of patient safety, to avoid unnecessary exposure to COVID-19 (Fig. 1) .
Both medical and nursing health staff must be reduced to the necessary minimum as well as residents, researchers, and students. Separate teams should be created such that the eventually infected team can be isolated while safeguarding the remaining teams. It is necessary to limit aggregation during meals and meetings while always maintaining interpersonal distances. Meetings and teaching must be done using video conferencing. 9 The time spent by medical and nursing staff in the ward and in the operating room must be limited to the minimum necessary. 12, 13 Protective Devices Personal protection devices must be properly selected and used appropriately. Staff training on the use, elimination, and disposal of equipment may currently be required, as there are conflicting practices regarding the use of masks and tight-fitting glasses or the use of powered air-control respirators in the published literature. Healthcare personnel have to be provided with the proper amount of protective masks, disposable gowns, headdresses, overshoes, double gloves, and protective glasses or facial shields. The hospital
The Journal of Craniofacial Surgery Volume 00, Number 00, Month 2020 could provide for the in house production of protective devices, such as masks and shields, with 3-dimensional printers. [17] [18] [19] DISCUSSION Despite the pandemic emergency, the protocols we have implemented have allowed us to respond to COVID-19 infection while ensuring the efficiency and safety of the health service. These guidelines will help all maxillofacial department as well as all head and neck departments that are located in, or unfortunately will soon find themselves in, our situation.
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The Coronavirus disease 2019 (COVID-19) pandemic has led to unprecedented levels of movement restriction, job losses, and economic uncertainty in the United States and around the world. 1 Concerns regarding illness, death, and the death of loved ones may be compounded by financial uncertainty, as reports of mass unemployment with variable international governmental responses circulate. 2 Mental health outcomes have been associated with pandemics in the past. [3] [4] [5] While there has been a rapid response to the COVID-19 pandemic in terms of nonpharmaceutical interventions, vaccine development, and medical support, little comprehensive planning has been performed to predict and respond to the possible mental health crisis that could emerge from the pandemic, and the only data available on general public responses to the pandemic are in Chinese populations. 6, 7 These data are echoed by recent research that has suggested that healthcare workers have a significant burden of mental health challenges in the face of COVID-19. 8 Moreover, pandemics and other natural disasters may disproportionately affect those with underlying mental illness. 9 We therefore sought to investigate the prevalence of anxiety and depression in the general US population in the context of the early COVID-19 pandemic, and explore associations of these mental health outcomes with loneliness (of particular concern given enhanced social distancing and isolation), health status, socioeconomic status, residence size, time spent outdoors, and other baseline demographic characteristics. A better understanding of the prevalence of these mental health outcomes and their putative risk factors may help guide public policy in establishing improved guidelines for those required to stay at home.
This study is a cross-sectional, internet-based survey performed via age, sex, and race stratification, conducted between March 29, 2020 and March 31, 2020. Responses to all survey questions were recorded (Supplemental file). This study was deemed exempt by the Ascension Health institutional review board.
We developed an online survey using the Qualtrics platform (Qualtrics Corp, Provo, Utah) after iterative online pilot testing. The survey was distributed to a representative sample of the US population using Prolific Academic (Oxford, United Kingdom), an established platform for academic survey research. 10 Respondents were rewarded with a small payment (<US$1). Participants provided consent and were permitted to terminate the survey at any time. All surveys were anonymous and confidential, with linkages between data performed using a 24character alphanumeric code. The investigators had no access to identifying information at any time.
This internet-based survey was stratified by age, sex, and race to reflect the makeup of the general US population. Sample size calculations were conducted for the primary endpoint of detecting a 10% difference in the Generalized Anxiety Disorder-7 scale (GAD-7) between those that were and were not under a stay at home order at the time of survey completion. 682 subjects (341 per group) would be adequate to detect a 10% change in GAD-7 with 80% power and with an alpha of 0.05, assuming a baseline GAD-7 mean of 11.6 with a standard deviation of 5.4 and assuming equal group sizes. 11 We inflated our sample size to 1,000 given that approximately 2/3 of the US was under stay at home orders at the time of survey initiation and given uncertainty regarding changes in those orders over the duration of the survey, as well as to permit subgroup analyses.
Demographic information was self-reported by respondents. Responses to a battery of questions regarding attitudes to the COVID-19 pandemic, were collected using Likert scales.
For our main outcome measures, anxiety and depression, validated scales were used. Anxiety was assessed using the GAD-7, a validated self-report scale for anxiety, with scores ranging from 0 (no anxiety) to 21 (extreme anxiety). Prior psychometric research suggested cutoffs as 0-4 (no anxiety); 5-9 (mild anxiety); 10-14 (moderate anxiety); and 15-21 (severe anxiety). 8, 11 Depression was assessed with the Patient Health Questionnaire-9 (PHQ-9), a validated measure for clinical depression. 12 Scores range from 0 (no depression) to 27 (severe depression). Prior psychometric research has suggested cutoffs as 0-4 (no depression); 5-9 (mild depression); 10-14 (moderate depression); and 15-27 (severe depression). 8, 13 Loneliness was quantified with the UCLA short-form loneliness scale (ULS-8), a validated measure of loneliness. 14 Scores range from 8 (no loneliness) to 32 (extreme loneliness); no clinically meaningful cutoffs have been established psychometrically.
Normally distributed baseline demographic data are presented as mean values with 95% confidence intervals (CI). Outcomes that were not normally distributed are presented as medians with interquartile ranges (IQR). T-tests and chi-squared tests were used as appropriate for baseline continuous and categorical variables. Subgroup comparisons of non-normally distributed data were performed using the Kruskal Wallis test. Unadjusted and multivariable (adjusting for age and sex, which are not modifiable confounders) logistic regression odds ratios of association were assessed between the dependent variables of anxiety or depression, presented as dichotomous outcomes using the established cutoffs of 10 for both the GAD-7 and PHQ-9, and putative risk factors.
All statistical analyses were performed using Stata 13 for Mac (Stata Corporation, College Station, Texas).
. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted May 28, 2020. . https://doi.org/10.1101/2020.05.26.20114140 doi: medRxiv preprint
Of the 1,020 subjects who were recruited, 1,005 finished the survey, yielding a completion rate of 98.5%. The mean (SD) age of respondents was 45 (16), and 494 (48.8%) of the respondents were male; baseline respondent characteristics are outlined in Table 1 . Baseline demographic data were similar between those that were (n=663, 66.2%) and were not (n=339, 33.8%) under a shelter in place or stay at home order, with the exception of sex and geographic location (urban versus rural status). The median (IQR) ULS-8 score for loneliness was 16 (8), similar to baseline estimates from previous studies. [14] [15] [16] Anxiety The median (IQR) GAD-7 score was 5 (9), and 513 subjects (52.1%) of subjects had at least mild anxiety. Overall, 264 subjects (26.8%) met criteria for an anxiety disorder based on a GAD-7 cutoff of 10 ( Table 2 ). Adopting a more liberal GAD-7 cutoff of 7, as used in a recent study on healthcare worker anxiety in the COVID-19 context, 8 would yield 416 subjects (41.4%) meeting clinical criteria for anxiety. Women (p=0.002) and those living in rural areas (p=0.041), reported more severe anxiety than men and those in urban areas, respectively.
Unadjusted logistic regression analysis demonstrated that men were less likely to meet criteria for anxiety ( (Table 3) .
The median (IQR) PHQ-9 score was 4 (8), and 465 (47.3%) of subjects reported at least mild depression by screening ( Table 2) . A total of 232 subjects (23.6%) met criteria for clinical depression. Women (p=0.008) and unmarried subjects (p<0.0001) reported more severe depression than men and those who are married, respectively.
Unadjusted logistic regression analysis demonstrated that men were less likely to meet criteria for depression ( CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted May 28, 2020. (Table 3) .
In this first study of general US population mental health during the COVID-19 pandemic, we found high baseline levels of both anxiety and depression, independent of living under a shelter in place or stay at home order. More than half (52.1%) of respondents had at least mild anxiety, and 47.3% of subjects had at least mild depressive symptoms. Adopting the cutoff of 7 on the GAD-7 score for anxiety, as used in a recent study on COVID-19, would yield 416 subjects (41.4%) meeting clinical criteria for anxiety. This high burden of mental health concerns in the general population in the pandemic context suggests the need for further study and consideration for intervention.
Living in a larger home was associated with a reduced risk of both anxiety and depression; this effect was seen despite the lack of any association between anxiety or depression and household income and persisted when including income and number of household members into a multivariable model. Similarly, we found that increased time spent outdoors correlated with a reduction in depression (but not anxiety) risk, and those that spent more than an hour a day outdoors had approximately half the risk of depression as those that spent no time outdoors. This association of depression with time outdoors echoes prior research on access to green space access and its impact on mental health. 17 Our finding that both larger living space and increased time spent outdoors correlate with a reduction in mental health burden may have actionable implications for public health initiatives and decisions regarding access to outdoor recreation areas during stay at home or shelter in place orders.
History of hospitalization, a rough measure of overall health status, was associated with an increased risk of both anxiety and depression. This effect persisted even when controlling for age and history of anxiety and depression, respectively, suggesting that those with a poorer health status may be at increased risk of adverse mental health outcomes in the context of the COVID-19 pandemic.
Media consumption, measured by the number of hours spent watching or reading about the pandemic, was not associated with the presence of anxiety or depression. Similarly, we did not detect significant associations between likelihood of meeting criteria for anxiety or depression and household income or religiosity on adjusted multivariable analyses.
Notably, we found that less than half of respondents had no anxiety; that is, more than half of subjects reported a level of anxiety that would at least be classified as mild. Conversely, 13.4% of subjects demonstrated severe anxiety, a higher proportion than has been reported even in healthcare workers responding to pandemic COVID-19. 8 Loneliness is an established risk factor for both anxiety and depression, 15 ,18 and we found an approximately 5-to 10-fold increase in odds of anxiety and depression, respectively, with being in the highest loneliness quartile. As with those living in smaller homes with minimal access to . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted May 28, 2020. . https://doi.org/10.1101/2020.05.26.20114140 doi: medRxiv preprint the outdoors, loneliness can be seen as an independent risk factor for anxiety or depression in the context of the COVID-19 pandemic.
This study has several limitations. First, as with any survey-based research, its generalizability may be limited. We used Prolific Academic for survey distribution in order to maximize our generalizability to the general US population by using an age-, sex-, and race-stratified survey panel design. As with any survey data, however, the sample willing to participate may not fully reflect the population of interest. Second, our study took place during the early phase of the COVID-19 pandemic, when shelter in place and stay at home orders were only just beginning. If anything, however, this underestimates the prevalence of anxiety and depression as these outcomes would only be expected to increase as restrictions persist, and highlights that even the anticipation of such restrictions may present a stressor. Third, as with any survey study, response bias and social desirability bias may play a role, though the anonymous survey design may help mitigate these concerns. Fourth, while our study relied on validated scales wherever possible, some survey questions were the product of pilot testing alone, and therefore their methodology-while consistent with the survey development literature-has not been fully vetted. Finally, and importantly, this cross-sectional study that lacks a comparator group cannot establish causation; therefore, we do not know whether the associations we describe are truly clinical risk factors.
In this first study of mental health outcomes in the US population during the COVID-19 pandemic, we found high rates of depression and anxiety, with the most profound mental health effects in women, those with a history of hospitalization over the past two years, those who were most lonely, and those living in smaller homes and (for depression) those spending the least time outdoors.
. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted May 28, 2020. . https://doi.org/10.1101/2020.05.26.20114140 doi: medRxiv preprint . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted May 28, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted May 28, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted May 28, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted May 28, 2020. Table 3 . Risk factors for anxiety and depression in unadjusted and multivariable analyses.
. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted May 28, 2020. . https://doi.org/10.1101/2020.05.26.20114140 doi: medRxiv preprint
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Introduction R.W. is a 30-year-old man presenting to his family nurse practitioner (NP) with (1) worsening abdominal pain, (2) low-grade fever, (3) jaundice, and (4) generalized pruritus.
The patient developed right upper quadrant abdominal pain and pruritus 2 days before his clinical visit. He reports taking one dosage of bismuth subsalicylate for the abdominal pain with minimal relief. The subsequent day he noticed the sclera of his eyes had turned yellow. His mother encouraged him to schedule a visit with his family NP for evaluation. The patient denies any recent changes in medications or health. He denies exposure to sick contacts and denies recent travel.
The patient's past medical history is notable for a diagnosis of ulcerative colitis at age 19. The patient was admitted to a local hospital with a chief complaint of hematochezia on first presentation. After evaluation and continued management, the patient's condition has been stable. He is prescribed mesalamine (800 mg, 3 times per day). The patient's last colonoscopy was 4 months prior with no significant changes or acute findings. He is seen by his gastroenterologist every 6 months and as needed. He has been immunized against measles, mumps and rubella, tetanus, and hepatitis A and B. The patient has no known drug allergies.
R.W. works full time as a law clerk at a law firm in an urban city. He exercises regularly and participates in a local baseball league on the weekends. He denies any alcohol, tobacco, or illicit drug use. The patient's grandparents are deceased. His mother is alive and well, age 55. His father is alive and well, age 60 with a diagnosis of hyperlipidemia. He has a brother, alive and well, age 23.
General: The patient reports a low-grade fever ranging from 99 -101 F, generalized pruritus, and fatigue. He denies recent weight loss or gain.
Eyes: The patient reports "yellowing of my eyes." He denies blurred vision.
Gastrointestinal: The patient reports nausea and early satiety. He reports worsening abdominal pain in the right upper quadrant. He reports acholic stools. He denies vomiting, constipation, diarrhea, hemoptysis, melena, and hematochezia.
Genitourinary: The patient reports dark amber-colored urine.
Integumentary, cardiovascular, respiratory, neurologic, musculoskeletal, and psychiatric examinations are unremarkable.
The patient is a young-adult white man and appears stated age. Mild jaundice noted. The patient appears ill.
Vital signs: Body mass index, 19 kg/m 2 ; blood pressure, 118/64 mm Hg; pulse, 99 beats/min; temperature, 100 F; respirations, 18 breaths/min; oxygen saturation on room air, 100%.
Scleral icterus. Mild hepatomegaly on examination. Abdominal pain on deep palpation that is worse in the right upper quadrant.
The Journal for Nurse Practitioners j o u r n a l h o m e p a g e : w w w . n p j o u r n a l . o r g Regular rate and rhythm of the heart, no murmurs. Lungs clear to auscultation. Genitourinary: deferred.
After completing a detailed history and physical assessment, the family NP advised the patient to seek emergency treatment for further evaluation at the nearby local hospital. The NP contacted the patient's gastroenterologist, and R.W. was admitted to the medicine unit.
Notable laboratory studies The patient's most likely diagnosis is acute cholangitis, or an infection of the bile ducts with inflammation caused by an obstruction of the biliary tree. 1 The patient's serologic workup is consistent with a cholestasis, a condition where bile does not flow properly from the liver into the small intestine. 1 The NP appropriately referred RW for urgent evaluation to assess for obstruction of the biliary tract.
2. What further testing should be ordered with ultrasound findings of biliary ductal dilatation?
The patient should undergo diagnostic cholangiography testing for evaluation of intrahepatic and extrahepatic biliary ductal dilatation (Figure) . 2,3 A magnetic resonance cholangiography (MRCP) enables the provider to assess the biliary tree. Endoscopic retrograde cholangiopancreatography and endoscopic intervention should be used to relieve biliary obstruction and directed for patients with evidence of cholangitis or biliary stricture. 2, 3 3. What are various contributing causes for patients with biliary ductal dilatation and a cholestatic laboratory workup?
The NP should consider all potential causes for a patient with cholangitis, including but not limited to medications, secondary sclerosing cholangitis, immunoglobulin G4 disease, choledocholithiasis, biliary tumors, primary biliary cholangitis, and primary sclerosing cholangitis. 1, 2, 4 Abdominal ultrasound imaging is necessary to exclude biliary obstruction and assess the hepatic vasculature. 1
During R.W.'s admission, an MRCP with and without IV contrast was ordered by the clinical team. The study found abnormal biliary duct dilatation alternating with strictures. There was heterogeneous peribiliary enhancement of the liver, which likely represents cholangitis. No gallstones or intrahepatic biliary calculi were identified.
These imaging findings are consistent with primary sclerosing cholangitis, a progressive autoimmune cholestatic liver disease that leads to inflammation, strictures, and hepatic fibrosis (scarring). 5 Presentation for patients with this disease can range from asymptomatic with abnormal liver tests to patients experiencing symptoms of acute cholangitis. 2 The majority of patients with PSC over time will develop advanced fibrosis, cirrhosis, and complications of liver disease such as portal hypertension and hepatic decompensation. 2 PSC patients with decompensated cirrhosis should be evaluated for liver transplantation. The patient's history of ulcerative colitis is also notable in this case. Data has shown as high as 80% of patients with primary sclerosing cholangitis have inflammatory bowel disease, including ulcerative colitis in 70% to 80%, Crohns disease in 10% to 15%, and unspecified inflammatory bowel disease in 5% to 10%. 5 Research suggests a link between the microbiome and liver disease in this unique patient population. There are 23 genomewide risk loci that are thought to contribute to the pathogenesis of primary sclerosing cholangitis. 4 In addition, associations with chromosome 6 and inflammatory bowel disease development has been shown, which may also play a role in primary sclerosing cholangitis development. 4 There is ongoing research investigating this gut-microbiome link. In summary, for best clinical outcomes NPs should assess and screen patients with inflammatory bowel disease for liver disease during annual screenings and as needed depending on the patient's symptoms and clinical presentation. 6
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J o u r n a l P r e -p r o o f 3 Amidst the COVID-19 crisis, it is crucial to understand how people think about risk and how this determines their risk-reduction behaviors [1] . As in other public health problems, outcomes hinge on people's choices: whether to practice social distancing to prevent the spread of COVID-19, safer sex to prevent HIV-AIDS, or vaccination to prevent seasonal flu. However, there is a fundamental mismatch between how most people think about risk and the assumptions experts make about actual and ideal human thinking. That is, most people think about risk in terms of qualitative meaning, called gist, as opposed to the precise details of risk information [2] . This mismatch produces predictable pitfalls in risk communication that are avoidable.
The mismatch between gist and precise representations of risk goes beyond merely rounding off numbers, lumping rather than splitting, or innumeracy--the numerical equivalent of illiteracy [3] . To be sure, numeracy is a good thing. Popular numeracy tests ask respondents about probabilities and risks, such as questions about how to convert frequencies into probabilities, order different probabilities, and discriminate lower from higher risks. Other tests ask people to estimate the values displayed in a bar graph [4] . It is important to be able to read a graph and to know that a .10 probability of contracting COVID-19 is higher than a .01 probability. Every day during the pandemic, graphs and numbers hurl past the public.
But numeracy is not sufficient to understand risk. In fact, numbers are ambiguous in the way that words are ambiguous, perhaps more so [5, 6] . Suppose that a person hears that the number of deaths in the U.S. has surpassed 80,000, that the risk of transmission of COVID-19 is two to three times greater than that of the seasonal flu, and that the mortality rate is about 3% of J o u r n a l P r e -p r o o f reported cases (Box 1). Decisions to act depend on the meaningful essence of this information. A simple linear transformation of numbers to categories does not capture the essence of risk. A nonlinear transformation of numbers does not suffice either. For example, a probability of 3% of rain would be very low, but a probability of death of 3% from COVID-19 is very high.
Context matters for meaning.
Much research in the decision sciences has been devoted to demonstrating that context biases risky decisions, even making people who are risk-avoiding become risk-seeking just by changing how the same underlying facts are described [7] . These biases illustrate the human tendency to focus on changes relative to a reference point [8] . For example, a woman consulting the Breast Cancer Risk Assessment tool online (https://bcrisktool.cancer.gov/) is likely to be relieved to discover that her risk of cancer is below average because it is less than that of the population rate of about 13%. But how should she interpret these numbers? The numbers do not tell her the most important thing, namely, whether her risk is low or high. Her actions, whether to be screened more often than the average woman, and emotions, whether to feel calm or anxious, hinge on her interpretation of the gist of the risk: What does this information mean in context?
Meaning in context does not mirror literal reality. Typically, people do not think using what are called "verbatim representations" of information. They think in fuzzy imprecise ways that interpret reality. For example, during a recent meeting I attended, public-health experts pointed out that those who test negative for a genetic mutation that increases breast-cancer risk technically do not have the same probability of developing breast cancer as members of the general population. But what is the gist of their risk? Testing negative does not mean that they J o u r n a l P r e -p r o o f 5 have zero risk. Rather, their risk is less than the population average but remains in the same ballpark-the bottom line is that they could still develop cancer and need to take measures to reduce their risk (e.g., screening). For those who test negative, the numbers change (and risk relative to before the test was given declines) but the gist of absolute risk stays about the same.
Having a sense of relative and absolute risk can be important in different ways for different decisions [cf. 9].
Unfortunately, people cannot look up their individualized risk for COVID-19 using an online tool. As the average person looks around, he or she is likely to perceive little risk from COVID-19. After all, few people have died out of a vast number of people in the state where he or she lives. This ratio competence-the ability to understand that probabilities depend on the frequency of target events relative to a reference class of target and nontarget frequencies-is present early in life and in nonliterate cultures [10] . Thus, the perception of low personal risk is understandable and is likely to evoke resistance to risk-reduction measures such as social distancing, especially when they involve extreme limitations on economic activity and human interaction.
Although the risks of COVID-19 flu might seem low, background knowledge provides more than facts. It provides the context for interpreting the meaning of numbers such as 3% risk of mortality. For example, experts realize that seasonal flu often kills less than .1% who are infected, making COVID-19 more than 10 times more lethal than the seasonal flu, which kills 30,000 to more than 60,000 annually in the U.S. alone. Furthermore, COVID-19's greater J o u r n a l P r e -p r o o f 6 lethality and transmissibility (relative to seasonal flu) combine to produce an exponential explosion in serious cases. When only 1% of a population is infected, the threshold at which an epidemic can be contained has already been crossed. A risk threshold is not an arbitrary cutpoint; it is the point at which risk changes qualitatively not just quantitatively. The significance of "flattening the curve" is that, without social distancing, the number of serious cases will hit a categorical boundary: exceeding the capacity of the healthcare system and causing many preventable deaths. Therefore, despite what seem like tiny numbers to laypeople initially, public-health experts perceive the risk of COVID-19 to be high.
Note that background knowledge, and scientific literacy broadly, allows members of the public to recognize what is plausible-what is likely to be true-as opposed to necessarily providing memorized truths that directly contradict incoming misinformation [11] . For example, one might accurately argue that the link between vaccines and autism has only been studied for a limited number of childhood vaccines. This argument was made by a vaccination opponent; it is perfectly logical and even true. However, the question is whether such a link is plausible given current scientific knowledge.
Misinformation takes root in ignorance, when the world does not make sense [12] . For example, the causes of autism, multiple sclerosis, and narcolepsy are unknown. Susceptibility is fostered by mistrust and suspicion of those perceived as powerful elites (the government, the rich, researchers working in secret labs) and "the other" (e.g., the "Wuhan virus"). Bias can occur regardless of political persuasion [13] . Most important, misinformation is effective when it makes sense of the world and troubling events in it, when it offers a qualitative meaning that draws together pieces of reality and interprets them. This meaning might be woefully J o u r n a l P r e -p r o o f 7 incomplete, but it is unlikely to be challenged if people do not seek out dis-confirmatory tests and if they limit their contacts to likeminded others [14] . Reality is not infinitely reinterpretable, however, which creates opportunities to reach the public by communicating more than the facts, that is, conveying what the facts mean. captured-yet-in artificial intelligence. To a machine, "human beings" can be defined as "featherless bipeds" without irony or bemusement. Humans chuckle. This definition is accurate in that it picks out the correct referents, but it omits the essence of what it means to be a human being.
So, what can we do to better communicate risk? Begin with the end in mind: Give people what they need to understand the qualitative, contextualized meaning of risk information. Figure 1 presents examples of how to combine pretest probabilities with COVID-19 testing to yield qualitative meanings. This approach has been applied to patients deciding among medications with serious side effects, teenagers making decisions about unprotected sex, and healthy people trying to figure out their genetic risk for cancer.
J o u r n a l P r e -p r o o f
The facts and figures described in this article are illustrative and not intended to provide medical advice. They were drawn from such sources as the Center for Disease Control and the World Health Organization (e.g., https://www.cdc.gov/coronavirus/2019-ncov/casesupdates/cases-in-us.html; https://www.who.int/emergencies/diseases/novel-coronavirus-2019/question-and-answers-hub/q-a-detail/q-a-similarities-and-differences-covid-19-and-influenza#:~:text=Mortality%20for%20COVID%2D19,quality%20of%20health%20care.; both retrieved May 7, 2020). Moreover, uncertainty surrounds these numbers, especially probability at the individual level, which is not the same thing as a case rate: Case rate relies on the number of confirmed cases, but many cases are not confirmed. Case rate relies, too, on the number of attributable deaths. Deaths at home may not be attributed accurately to COVID-19. Conversely, those with mild to moderate symptoms may be undercounted as cases. Therefore, despite enormous quantities of data at people's fingertips, it is extremely difficult to make accurate estimates of the true risk of death for an individual. Yet, it is crucial to have some sense of this number for individuals to make decisions about risk. Fortunately, the human brain seems well adapted to accommodating "fuzzy" numbers. Health officials need to give people enough of the right kind of information so that they can get the gist of whether their risk--or society's risk--is "low" or "high."
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Understanding transmission dynamics in the early stages of an infectious disease outbreak is essential for informing effective control policy. Valuable insights can be gained by the reconstruction of the transmission tree, which describes the history of infectious events at the resolution of individual cases [1] [2] [3] [4] . Recent years have seen significant progress in the development of statistical and computational tools for inferring such trees [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] , with a major emphasis placed on the analysis of whole genome sequence (WGS) data, now routinely collected in many outbreak scenarios [16] .
Two approaches to the inference of transmission trees from WGS have emerged. One begins with an underlying transmission model, attaching to this a model of sequence evolution that relates observed genetic relationships between pathogens to unobserved epidemiological relationships (i.e. transmission pairs) between infected individuals. A simple implementation involves ruling out direct transmission events between individuals separated by more than a fixed threshold of substitutions [17] [18] [19] . More sophisticated methods have specified models of sequence evolution as components in a joint likelihood, formalising expected genetic relationships in a probabilistic manner [5] [6] [7] [8] [9] 20 ]. The other approach considers outbreak reconstruction from a phylogenetic perspective, inferring unobserved historical relationships between pathogen samples to capture more complex evolutionary dynamics. WGS data is used to reconstruct phylogenetic trees which are either treated as data upon which transmission histories are overlaid [10] [11] [12] , or jointly inferred alongside the transmission tree itself [13] [14] [15] . Given the unprecedented level of detail of WGS data and the epidemiological insights it has provided in real-life scenarios [21-23], genetic analysis is clearly an indispensable tool for outbreak reconstruction.
However, a fundamental and so far largely unaddressed limitation of WGS data in informing outbreak reconstruction is the requirement for genetic diversity to accumulate on epidemiological timescales. The scope of outbreak scenarios for which such requirements are met has, to our knowledge, never been described. Specifically, at least one mutation must accumulate in the time between sampling of two individuals in a given transmission pair (i.e., an infector and a secondary case) in order for their position within the transmission tree to be distinguishable by genetic means. This represents a limit in the resolution of the data itself, independent of the methodology considered. Though groups of genetically identical pathogens may be identified as a cluster of infections, finer reconstruction of the transmission events would be impossible based on genetic data alone. Such limitations may be even more problematic in methods relying on accurately estimated phylogenetic trees for inferring transmission events [11, 14] .
The impact of limited genetic diversity on the reconstruction of disease outbreaks remains to be investigated. While this impact undoubtedly varies across different methods, the intrinsic informativeness of genetic data with respect to the underlying transmission tree can be evaluated. The genetic diversity accumulating along transmission chains depends on various genomic and epidemiological factors. To quantify this diversity, we introduce the concept of 'transmission divergence', which we define as the number of mutations accumulating between pathogen WGS sampled from transmission pairs. Transmission divergence can be estimated empirically from a transmission tree by determining the number of mutations separating pathogen samples of known transmission pairs. However, accurately reconstructed transmission trees with corresponding genetic sequence data are generally not available for most pathogens. We present here a simulation based approach for estimating the transmission divergence of different pathogens using parameters available in the literature, namely the length of the pathogen genome (L), its overall mutation rate (M), its generation time distribution (W) (i.e. the distribution of delays between primary and secondary infections [24] ) and its basic reproduction number R 0 (i.e. the average number of secondary infections caused by an index case in a fully susceptible population [25]). Specifically, we model transmission trees alongside sequence evolution and extract the number of mutations separating individual transmission pairs. Intuitively, greater transmission divergence should enable better reconstruction of these transmission trees, although the nature of this relationship remains to be described.
To explore this issue, we compare the transmission divergence of ten major outbreak-causing pathogens, namely Zaire ebolavirus (EBOV), SARS coronavirus (SARS-CoV), MERS coronavirus (MERS-CoV), pandemic influenza A (H1N1), Methicillin-Resistant Staphylococcus aureus (MRSA), Klebsiella pneumoniae (K. pneumoniae), Streptococcus pneumoniae (S. pneumoniae), Shigella sonnei (S. sonnei), Mycobacterium tuberculosis (M. tuberculosis), and Clostridium difficile (C. difficile). We first conduct a literature review to obtain estimates of W, M, L and R 0 for each pathogen and then estimate transmission divergence using simulations. To compare estimates of transmission divergence under different models, we use two approaches described in the literature, namely the outbreaker model by Jombart et al. [5] and the phybreak model by Klinkenberg et al. [26] These differ significantly in their model of sequence evolution, with the prior considering a single dominant pathogen strain within each host and the latter modelling the additional complexities of multiples lineages coexisting and coalescing within host. Finally, we illustrate the impact of transmission divergence on our ability to infer transmission trees, using the outbreaker and phybreak inference algorithms for the R software [27] .
We conducted a literature review to obtain, for each pathogen, estimates of W (S1 Table) , M (S2 Table) , L (S3 Table) and R 0 (S4 Table) , and used these to simulate outbreaks under the outbreaker and phybreak models (Table 1) . Simulated outbreaks varied in size from 30 to 99 infected individuals, with a median size of 63 and 62 cases for outbreaker and phybreak simulations, respectively. To describe the distribution of transmission divergence values for each pathogen, we calculated the number of mutations separating individual transmission pairs ( Fig 1A, S5 Table) . As expected from the mutational models of outbreaker and phybreak, transmission divergence appears to follow a mixed Poisson distribution, with the mixing distribution of the Poisson rate determined by variation in the generation-, sampling-and coalescent times.
Transmission divergence simulated under the two models differed significantly, with phybreak consistently estimating higher values than outbreaker (S5 Table) . This discrepancy ranged from 1.56 times higher on average for S. pneumoniae to 1.84 times higher for M. tuberculosis, with significantly longer tailed distributions especially for K. pneumoniae and SARS-CoV. On the other hand, outbreaker and phybreak agreed on the relative amount of transmission divergence between pathogens, both assigning larger mean transmission divergence to viral pathogens than bacterial pathogens, with the exception of K. pneumoniae.
Notable across both models was the fact that transmission divergence was generally low. Pathogens such as S. sonnei, S. pneumoniae and C. difficile were essentially never separated by more than one mutation even when accounting for within-host diversity, suggesting that little to no genetic diversity is to be expected over the course of such outbreaks. Even rapidly mutating viral pathogens such as EBOV and MERS were generally separated by no more than five mutations under both models, and in the absence of significant within-host diversity the most common number of mutations separating such transmission pairs was indeed zero. In fact, outbreaker estimated a mean value below one for eight of the ten pathogens considered. In contrast, two pathogens that demonstrated significantly higher transmission divergence were K. pneumoniae and SARS-CoV, which accumulated as many as 15 mutations between individual transmission pairs and were rarely separated by fewer than two.
We also quantified genetic diversity by the number unique of sequences as a proportion of total sequences (Fig 1B, S5 Table) . This value is closely related to the zero term in the transmission divergence distribution, however notable observations include that over 90% of sequences in S. sonnei and S. pneumoniae outbreaks were identical under both models of sequence evolution, and on average 30% to 50% of sequences in MERS-CoV and EBOV outbreaks were identical depending on the model of within-host diversity. Few genetically identical cases were observed in SARS-CoV and K. pneumoniae outbreaks.
As the proportion of unique sequences in an outbreak can be determined without knowledge of the transmission tree, we used this metric to compare our predictions with empirical estimates from studies collecting WGS in an outbreak setting (Fig 1B, S6 Table) . The proportion of unique sequences observed in M. tuberculosis, Influenza A, MERS-CoV and SARS-CoV outbreaks were well predicted by one or both evolutionary models. The phybreak model better predicted the observed genetic diversity for both M. tuberculosis outbreaks and the SARS-CoV outbreak, the latter of which fell outside the prediction interval of the outbreaker model, whereas the diversity observed in the Influenza A and MERS-CoV outbreaks was similarly supported by both models. Outbreaks were simulated using both the outbreaker and phybreak models. B) For each simulated outbreak, we calculated the proportion of sequences that were unique. Black circles represent empirical observations of the proportion of unique sequences for a given outbreak (S6 Table) , scaled by the size of the outbreak. The grey circle in the EBOV column represents the weighted mean across the four outbreaks. The violin plots with the dotted outlines in the K. pneumoniae column were generated using the empirical serial interval of 25.8 days observed over the course of the outbreak described by Snitkin et al. [106] , which differs significantly from the value of 62.7 days in our literature review.
The mean proportion of unique sequences observed across four EBOV outbreaks was also in good agreement with our simulations, with slightly greater support by the outbreaker model. However, diversity between these outbreaks was more variable than expected, ranging from 0.40 to 0.92, with one value falling outside both prediction intervals and two values only expected under either the phybreak or outbreaker model. Furthermore, though the genetic diversity observed across 333 cases of C. difficile infection in Oxfordshire, UK [17] fell just within the prediction interval of our simulations, this result was unlikely under both evolutionary models, especially given the large sample size of the study.
The greatest disagreement with our predictions was observed for a K. pneumoniae outbreak described by Snitkin et al. [106] , for which 7 out of 18 WGS were identical, while our simulations predicted nearly all cases to be genetically distinguishable. However, the average serial interval over this outbreak was only 25.8 days (S6 Table) , which was unusually short compared to the average value of 62.7 days from our literature review. When repeating our simulations using the realised serial interval, the observed genetic diversity was well predicted by the phybreak model (Fig 2B) .
To quantify how these results affect the inference of transmission trees, we analysed the simulated outbreaks using the outbreaker and phybreak inference algorithms, applying the same models used for outbreak simulation in their reconstruction. We reconstructed each outbreak with and without WGS data, and quantified the accuracy in outbreak reconstruction, as well as the statistical confidence in ancestry assignments using the posterior entropy (S1 Fig, S2 Fig) .
To describe the informativeness of the genetic data alone, and minimise confounding epidemiological differences between pathogens (e.g. temporal data will be more informative with lower R 0 , as there exist longer chains with a greater temporal signal), we calculated the absolute change in accuracy of outbreak reconstruction upon incorporating WGS data and related this to the mean transmission divergence of the outbreak. As the accuracy of reconstruction in the absence of WGS data was very low (S1 Fig) , there was similar, considerable scope for improvements in accuracy for all pathogens.
Unsurprisingly, higher average transmission divergence across an outbreak led to greater improvements in the accuracy of outbreak reconstruction of both outbreaker and phybreak simulations (Fig 2A) . However, the nature of this relationship differed between the two models. Using outbreaker, a sharp contrast was observed between outbreaks with low mean transmission divergence (C. difficile, S. pneumoniae), for which WGS provided essentially no additional information, and outbreaks exhibiting the largest mean transmission divergence (K. pneumoniae, SARS-CoV), for which WGS improved nearly every incorrect ancestry assignment. The effect of mean transmission divergence on the accuracy of outbreak reconstruction was strongly nonlinear, with the greatest improvement in accuracy obtained between 0 and 1 mutations on average between transmission pairs. Under the phybreak model this relationship was less pronounced, with increases in mean transmission divergence resulting in markedly lower improvements in accuracy (Fig 2A) . This was most evident in SARS-CoV and K. pneumoniae outbreaks, for which improvements in accuracy were lower than in the outbreaker simulations even though the average transmission divergence was nearly two times higher, with a significant number of ancestries remaining incorrectly assigned (S1 Fig). At high values, mean transmission divergence was also poorly predictive of increases in accuracy, which were identical between SARS-CoV and K. pneumoniae in spite of significantly different average transmission divergence (4.83 and 3.40, respectively).
A similar trend was observed when considering the statistical confidence in ancestry assignments ( Fig 2B) . Under the outbreaker model, higher average transmission divergence strongly reduced posterior entropy, resulting in essentially complete support for a single transmission We also related the informativeness of WGS data to the proportion of sequences that were unique in an outbreak, and found a nearly linear relationship for both outbreaker and phybreak reconstructions (Fig 3A) . Once again, the slope of this relationship was significantly steeper in the outbreaker model, to the extent that the proportion of unique sequences was a near perfect predictor of the informativeness of WGS data, and outbreaks essentially perfectly reconstructed if all sequences were genetically distinct. This was not the case with the phybreak reconstructions, which assigned incorrect ancestries even when all sequences were unique. However, the proportion of unique cases was still a good predictor of the increase in accuracy of outbreak reconstruction, and successfully identified K. pneumoniae and SARS-CoV as having similarly informative WGS, where mean transmission divergence as a metric had placed them far apart.
The change in posterior entropy was also linearly correlated with the proportion of unique ancestries (Fig 3B) , with an outbreak of genetically distinct cases sufficient for outbreaker to converge on a single posterior transmission tree. In contrast, there remained considerable uncertainty around phybreak reconstructions even in a fully genetically resolved outbreak.
This paper has introduced the concept of 'transmission divergence' as a measure of the informativeness of WGS data for reconstructing transmission chains during an infectious disease outbreak. We estimated transmission divergence for ten major outbreak causing pathogens with a simulated based approach, using two distinct models of sequence evolution for comparison. We then demonstrated how the mean transmission divergence across an outbreak affects our ability to infer transmission histories.
Though average transmission divergence varied significantly amongst the diseases studied, it was generally very low, with a modal value of zero for most pathogens under both evolutionary models. Our results suggest that a large fraction or even a majority of cases will be genetically indistinguishable in many epidemic scenarios, including outbreaks of rapidly evolving RNA viruses such as EBOV and MERS.
These results were generally well supported by empirical observations of genetic diversity. Our simulations accurately predicted C. difficile, Influenza A and M. tuberculosis cases to be genetically identical a majority of the time, EBOV and MERS-CoV cases to display greater diversity yet still be frequently identical, and SARS-CoV cases to be largely genetically distinct. Though the proportion of unique sequences observed across 333 C. difficile cases was unexpectedly high, this metric assumes that each case is related to another case by a direct transmission event. This appears unrealistic when considering that 120 patients (36%) had no recorded epidemiological contact with their genetically related case [17] . A number of these pairs were probably separated by unobserved transmission events, for example by asymptomatic carriers, increasing the observed genetic diversity between supposed transmission pairs. The true proportion of unique sequences likely agrees better with our model predictions. Furthermore, though our original estimates for K. pneumoniae disagreed with empirical observations, this discrepancy was largely due to an unusually short serial interval compared to previously reported values in the literature. Once accounted for, the reported diversity agreed with our predictions.
Therefore, even though predicting the specific number of unique sequences observed in an outbreak is challenging due to confounding factors such as unobserved cases and stochastic variations in epidemiological context, our predictions using two fairly simple models of sequence evolution largely agreed with the data. This suggests that our results represent broadly useful predictors of the extent to which cases in a transmission cluster are genetically resolvable. The wider conclusion that a significant proportion of cases are expected to be genetically identical for a number of different pathogens is certainly well supported. When are pathogen genome sequences informative of transmission events?
It is tempting to suggest that the data from M. tuberculosis and SARS-CoV outbreaks lend greater support to the phybreak model, thereby indicating significant levels of within-host genetic diversity among these pathogens. While this explanation is feasible, the significant variation in unique sequences across four EBOV outbreaks demonstrates the sensitivity of such individual observations to stochastic effects. In the absence of greater amounts of empirical data, any such conclusions are only weakly supported.
The limited genetic diversity as predicted by our simulations had a considerable impact on our ability to reconstruct outbreaks, and clearly identified transmission divergence as a limiting factor in the utility of WGS data for many pathogens in an outbreak setting. These informational limitations were further compounded by within-host genetic diversity, which significantly reduced our ability to reconstruct outbreaks even when mean transmission divergence was high, in agreement with previous studies [11, 107] . Combined, these results demonstrate that WGS data will often be insufficient to fully resolve transmission chains, and reveal the need to incorporate other sources of information into transmission inference frameworks. Promising avenues include an analysis of deep sequencing data as an alternative to WGS, which may reveal additional within-host variation informative of likely transmission events, as well as a methodological approach to inferring transmission routes from contact data.
Our results do not imply that WGS is of no use for inferring transmission routes as a whole. For example, Didelot et al. used C. difficile WGS to identify distinct transmission chains caused by separate introductions to the same ward, vastly reducing the number of plausible transmission links given only epidemiological data [23] . However, samples within the transmission chains were genetically identical and remained unresolved in the absence of additional data. Low transmission divergence therefore represents a hard limit to the resolution of various reconstruction methods using WGS as primary source of information, regardless of the underlying genetic model. This may especially impact approaches relying on previously constructed phylogenetic trees [12, 14] , which are known to skew infection time estimates in the presence of multiple genetically identical sequences, as described by Hall et al. [15] We also showed that greater transmission divergence generally improved the inference of transmission histories, however only to an extent. Beyond the first discriminatory mutation, diversity between transmission pairs seemed to provide limited additional information, as demonstrated by the fact that the proportion of genetically unique sequences, rather than the average transmission divergence, best predicted the informativeness of WGS data. Though this relationship was weaker in the phybreak model, as within-host diversity increases the number of plausible transmission trees even when all cases are genetically distinct, this linear relationship held across both models.
It is important to note that other epidemiological factors beyond genetic diversity will impact the accuracy of outbreak reconstruction, such as R 0 , heterogeneities in infectiousness, the generation time distribution and the sampling time distribution. To account for these effects, our study focused on the improvement in the accuracy of reconstructed transmission chains, compared to a baseline without WGS data while keeping these other factors constant. Importantly, in spite of considerable variation in R 0 and generation time distributions (Table 1) , the robustness of the correlations presented in Figs 2 and 3 suggests that our measures of genetic diversity have captured a central determinant of the utility of WGS data in reconstructing outbreaks.
This study made several assumptions which might be relaxed in further work. Firstly, we assumed that the sampling time distribution is equivalent to the generation time distribution. While this assumption was largely driven by the lack of available data on sampling delay distributions, this could result in biases. For instance, our approach would underestimate transmission divergence in the presence of systematic and substantial lags between transmission times and sampling (S3 Fig). It is worth noting, however, that additional mutations accumulating in a lineage after onward transmission has ceased would increase the overall genetic distance from this lineage to all other isolates equally, without providing additional information about the underlying epidemiological relationships between hosts. Therefore, it is unclear how this additional diversity would translate in terms of improving outbreak reconstruction, and we believe the approach used in this study should capture the diversity informative of the transmission network.
Secondly, outbreaks were simulated and reconstructed under idealised scenarios, in that all cases were observed, WGS were available for all cases, and the same parameter values used for simulation and inference. Most importantly, we assumed error-free sequencing. In reality, when considering that transmission divergence is generally on the order of single mutations, individual sequencing errors can heavily bias the topology of the inferred transmission tree. Our estimates of the informativeness of WGS in inferring individual transmission links are therefore likely to be optimistic.
Finally, both the outbreaker and the phybreak model assumed a complete bottleneck at transmission, with a single strain being transmitted. Allowing for an incomplete bottleneck greatly increase the complexity of the problem, as two strains in a given host may have diverged several infectious generations ago and passed through multiple bottleneck together. This issue also opens up a number of questions about optimal sampling and sequencing strategies, the exact magnitude of the genetic diversity bottleneck at transmission, and the more fundamental mechanisms permitting the coexistence of multiple strains within a host. Further work should be dedicated to investigating the impact of these issues on the use of WGS for outbreak reconstruction [107, 108] .
The advent of WGS data has initiated a revolution in modern infectious disease epidemiology, shedding new light into disease dynamics and evolution at a variety of scales [109, 110] . At a local scale, these data have opened up exciting perspectives for improving our understanding of the person-to-person transmission process [5, 6, 13, 20] . This work suggests that, while useful, the analysis of WGS alone will struggle to reconstruct transmission trees accurately for a large number of pathogens, in particular bacterial ones. Integrating other types of outbreak data, such as locations of patients, community structure, or contact tracing data, therefore represents a promising alternative strategy for outbreak reconstruction.
We conducted a literature review using OvidEmbase to attain values for the generation time distribution, basic reproduction number, mutation rate and genome length of the pathogens under consideration. The searches were performed between 1st June 2015 and 3rd March 2017 and limited to publications in English. Common name variants for each pathogen were included in the searches as follows:
For the generation time distribution, we used the search terms 'generation time OR serial interval OR generation interval'. Estimates of the serial interval were used as a proxy for the generation time. We summarised the mean and standard deviation of these distributions by calculating the arithmetic mean weighted by the sample size of the study. We then generated discretized gamma distributions of the generation time distribution, using the function DiscrSI from the R package EpiEstim [111] .
Studies describing the mutation rate were identified using the search terms 'mutation rate OR substitution rate OR spontaneous mutation'. The arithmetic mean was calculated to summarise findings (Table 1) . A discrepancy of two orders of magnitude between mutation rate estimates for Clostridium difficile was resolved by choosing the short-term molecular clock estimate, derived from serial pairs of isolates in a hospital outbreak [23], over a long-term estimate using historical phylogenetic analysis [112] . Mutation rates were converted to units of mutations per site per day.
Core genome length estimates were retrieved from complete genome assemblies in the GenBank repository [113] , and the rounded arithmetic mean used as a summary value.
Studies estimating R 0 were identified using the search terms: 'basic reproduction number OR basic reproductive number'. Only studies explicitly inferring the basic reproduction number, defined as the expected number of secondary infections caused by an index case in a wholly susceptible population, were selected. The arithmetic mean was used as a summary value.
We define the transmission divergence K as the number of mutations separating pathogen WGS sampled from transmission pairs. We estimated the distribution of values for K by simulating transmission events alongside sequence evolution under two different models. The first is the outbreaker model, described in full by Jombart et al. [5] Briefly, the infectiousness of a case at a given time since infection is described by the generation time distribution W scaled by the basic reproduction number R 0 . The time of sampling is drawn from the sampling time distribution S. Mutations accumulate in the time between infection of a primary and secondary case, at a daily rate given by the product of the genome length L and the mutation rate M. Within-host pathogen diversity is considered negligible, such that the same strain is both onwardly transmitted and sampled, and the bottleneck at transmission is assumed complete.
The phybreak model is described by Klinkenberg et al. [26] , and differs from the outbreaker model primarily in its model of sequence evolution. Instead of modelling mutations as independent events between individual transmission pairs, phybreak accounts for patterns of shared evolution and within-host diversity by simulating phylogenetic 'mini-trees' within each case, which are combined according to the transmission tree. The coalescent events withinhost are simulated under a linearly growing pathogen population size, assuming a complete bottleneck at transmission. Mutations accumulate along the branches as a Poisson process with a mean value of the mutation rate M. As with outbreaker, infection times and sampling times are drawn from the generation time distribution W and sampling time distribution S, respectively. The number of contacts is Poisson distributed with a mean of R 0 , resulting in transmission if these occurred with previously uninfected cases.
For both outbreaker and phybreak, we simulated outbreaks with 100 susceptible hosts and a single initial infection using parameter values for M, W, L and R 0 obtained by literature review. The sampling time distribution was assumed to be the equivalent to the generation time distribution, and external imports of infection were not considered. Within-host evolution was modelled in phybreak with an effective pathogen population size increasing at a daily rate of 1. Simulations were run for 500 days or until no more infectious individuals remained, except M. tuberculosis simulations which were run for 500 weeks due to the longer generation time. For each pathogen, we generated 100 outbreaker simulations and 100 phybreak simulations with a minimum size of 30 infected individuals. The distributions of transmission divergence values were extracted by determining the number of mutations separating each transmission pair.
We reconstructed outbreaker and phybreak simulations using the transmission tree inference algorithms in the outbreaker2 and phybreak packages, respectively, which implement the same models used for simulation described above. The generation time and sampling time distributions used for simulations were also used for inference, and the assumed rate of within-host population growth in phybreak fixed at the simulated value. outbreaker MCMC chains were run for 100,000 iterations with a thinning frequency of 1/200, and phybreak MCMC chains for 10,000 iterations with a thinning frequency of 1/20. The burn-in period for both analyses was 1,000 iterations. To assess the improvement in transmission tree reconstruction due to genetic data alone, two types of analyses were performed for each simulated dataset, the first one using only sampling times, and the second one using both sampling times and WGS data. As the phybreak algorithm requires WGS data to be provided, all cases were assigned identical genomes to imitate the absence of genetic information.
For each simulation, we quantified the accuracy of outbreak reconstruction as the proportion of correctly inferred ancestries in the consensus transmission tree, defined as the tree with the modal posterior infector for each sampled case. Cycles were resolved using Edmond's algorithm [114] . The change in accuracy was defined as the absolute difference in accuracy upon inclusion of WGS data.
To quantify the statistical confidence in ancestry assignments contained in the posterior distribution, we calculated the entropy of posterior ancestries for each case [115] . Given K ancestors of frequency f K (k = 1, . . .,K), the entropy is defined as:
An entropy value of 0 therefore indicates complete posterior support for a given ancestry, with higher values indicating a larger number of plausible transmission scenarios. Infection and sampling times are indicated by circles and diamonds, respectively. The generation time W i,j is defined as the intervals between infection of i and the secondary case j, and is drawn from the distribution W. S i denotes the time to sampling of individual i, and is drawn from the distribution S. The time for discriminatory mutations to occur between pathogen genomes sampled from i and j is denoted O i,j , and is represented by red lines. A. If sampling of i occurs after onwards infection:
If the difference between the expected generation time and expected time to sampling is negligible:
If sampling of i occurs before onwards infection:
The time for mutations to occur is well approximated by the generation time if the delay between sampling and onwards infection is small. If sampling consistently occurs long after onwards infection, the time for mutations to occur will be underestimated. (TIF) S1
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Background: The coronavirus disease 2019 (COVID-19) pandemic originated in China in late 2019 and continues to spread globally (1) . At the time of writing, there were nearly 2 million COVID-19 cases causing approximately 110 000 deaths across more than 200 affected countries and territories (2) . As some health care systems approach collapse, a pressing need exists for tools modeling the capacity of acute and critical care systems during the COVID-19 pandemic.
Objective: To develop an online tool to estimate the maximum number of COVID-19 cases that could be managed per day within the catchment area served by a health care system, given acute and critical care resource availability.
Methods: We modeled steady-state patient-flow dynamics constrained by the number of acute care beds, critical care beds, and mechanical ventilators available for COVID-19 -infected patients seeking health care during the pandemic. Parameters for patient-flow dynamics were extracted from evolving data on COVID-19 and assumptions based on expert guidance. We used the package shiny within R, version 3.5.3 (R Foundation for Statistical Computing), to create the interactive tool.
The tool determines the maximum number of COVID-19 cases that could be managed per day within the catchment area served by a health care system, where the rate of patients with COVID-19 who are being admitted or transferred to acute care or critical care or requiring mechanical ventilation ("patients in") equals the maximum daily turnover of each of those resources available for patients with COVID-19 ("patients out"). These estimates represent the maximum steadystate constraints imposed by these limited resources being managed by a health care system or hospital. Resources available for patients with COVID-19 should account for the proportion of existing staffed resources that could be made maximally available to support patients with COVID-19 plus any additional staffed surge capacity.
The tool first calculates the maximum daily turnover of acute care beds, critical care beds, and mechanical ventilators available for patients with COVID-19 by taking the maximally available number of each of those resources for these patients and dividing it by the expected duration of their use for patients with COVID-19. On the basis of published data, the average length of stay in acute care and critical care was set at 11 and 9 days, respectively, whereas the average length of time for mechanical ventilation was set at 9 days (1, 3, 4) . The tool then calculates the population-weighted age-stratified probabilities of COVID-19 cases requiring acute care hospitalization and critical care, and in the base case assumes that 70% of critical care patients will be mechanically ventilated (3) (4) (5) . Finally, the maximum number of new COVID-19 cases per day that a health care system could manage is calculated by dividing the daily turnover of maximally available acute care beds, critical care beds, or mechanical ventilators by the probability of each resource being used among COVID-19 cases. The tool outputs maximum numbers of manageable cases per day separately for acute care beds, critical care beds, and mechanical ventilators (Figure 1 ), so that health systems can determine the limiting resource at steady state ( Figure 2 ) and consider system adjustments, such as allocating more acute and critical care resources to COVID-19.
All inputs and parameters of the tool (namely total resource capacity, percentage of resources available for COVID-19 and potential additional surge capacity, age distribution, age-stratified probability of resource use, and proportion of critical care patients requiring ventilation) can be tailored for use in any region of the world and applied to either a large health care system (such as a national or state-level system) or to an individual hospital. Although the default parameters for age-based case distribution and severity reflect data from the United States and acute and critical care resource availability inputs reflect provincial data from Canada's most populous province of Ontario (5), users can modify these parameters to match their local data.
Findings: The COVID-19 Acute and Intensive Care Resource Tool (CAIC-RT) is open access and available at https: //caic-rt.shinyapps.io/CAIC-RT. As a demonstration, the maximum number of new COVID-19 cases per day that could be managed by the Ontario health care system (default output of the tool) is detailed in Figures 1 and 2 .
Discussion: By using an online tool, health care systems can estimate the maximum number of COVID-19 cases per day that could be managed on the basis of age-based case distribution and severity and the number of maximally available acute and critical care resources. Unlike forecasting in-This article was published at Annals.org on 16 April 2020. struments, our tool determines a sustainable threshold for resource use during the pandemic rather than forecasting when resources might become depleted on the basis of assumptions about reporting, epidemic growth, and reproduction numbers.
Outputs from the tool allow planners to examine how increases in acute and critical resources available for patients with COVID-19 can affect health care system sustainability. Finally, the tool allows customization of age-based case distribution and severity, which is essential for countries with differing population demographics and health care systems.
Limitations of this tool include the steady-state assumption; assumptions that patients with COVID-19 are hospitalized instantaneously and that all beds and ventilators can be adequately staffed; and the application of Canadian, Chinese, Italian, and U.S. data for default parameters, which may not be generalizable to all health care systems. Further, if the tool is applied to a single hospital in a region with several hospitals receiving patients with COVID-19, the proportion of cases directed to that hospital must be considered.
Although we intentionally left the tool modifiable, we will update the default values as new data emerge to account for the ramp-up of diagnostic testing in such countries as the United States, with the understanding that most persons tested will not be hospitalized. The figure shows the COVID-19 patient-flow dynamics in the Ontario health system when each resource (acute care beds, critical care beds, and mechanical ventilators) available to patients with COVID-19 is in full use and at steady state. In this example, 2847 COVID-19 cases per day would result in 761 of those cases being admitted or transferred to acute care ("patients in"), assuming that 26.7% of all COVID-19 cases require acute care. Assuming that 8378 acute care beds are available for patients with COVID-19, with an average stay of 11 days in acute care, we can expect 761 patients with COVID-19 to leave acute care per day ("patients out") when at capacity (either by transfer, discharge, or death). If the province of Ontario reaches 2847 new COVID-19 cases per day, the acute care system would be at capacity and steady state, because the number of patients with COVID-19 entering and exiting the acute care system would be equal at 761 (patients in = patients out). Also shown are the same steady-state scenarios for critical care beds and mechanical ventilators for Ontario. The calculation can be broken down into 3 steps to estimate the maximum number of manageable COVID-19 cases per day that can occur for each resource (acute care beds, critical care beds, and mechanical ventilators). First, calculate the daily turnover of a resource when in maximal use: TO res = N res /LOU res , where TO res is the number of resource units that become available per day (turnover) for patients with COVID-19, N res is the total number of units of that resource available for patients with COVID-19, and LOU res is the mean length of use of that resource for patients with COVID-19. Second, calculate the proportion of COVID-19 cases that require a resource: P res ϭ i ϭ 1 N P i ϫ P i,res where P res is the proportion of COVID-19 cases that require that resource, P i is the proportion of COVID-19 cases that are within age group i of N age groups, and P i,res is the proportion of COVID-19 cases within age group i that require that resource. Third, calculate the maximum number of new COVID-19 cases per day that can occur such that the daily number of COVID-19 cases requiring a resource is equal to the daily turnover of that resource: C max,res = TO res /P res , where C max,res is the maximum daily number of COVID-19 cases that can occur for that resource and TO res and P res have been defined previously. * Number of existing acute or critical care resources for patients with COVID-19.
The tool, available at https://caic-rt.shinyapps.io/CAIC -RT, was developed by the authors for this article by using a third-party application, which may have limited access and functionality. Neither Annals of Internal Medicine nor the American College of Physicians is responsible for the content and functionality of this online application. Questions regarding the use of the application should be addressed to Dr. Stall (e-mail, [email protected]).
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Remarkable advances in the life sciences hold the promise of solutions to the world's growing health, food, and energy challenges, as well as the benefits of a new bio-economy. But the developments are also sparking a range of ethical, social and legal concerns, including that the knowledge, tools, and techniques resulting from these discoveries could be used to produce new bioweapons or enable bioterrorism. In the security realm, the scope and pace of the advances potentially pose fundamental challenges to the national and international institutions and policies that have been developed to prevent the misuse of the life sciences to cause deliberate harm.
The present international security landscape combines a strong norm against the misuse of the life sciences to cause deliberate harm with a weak institutional regime to prevent such actions. The cornerstone of the international regime, the 1972 Biological and Toxin Weapons Convention (BWC), has no agreed mechanisms to verify compliance with its prohibitions or to act against violations of its terms. The BWC's 8th review conference in November 2016 failed to agree on new, positive measures or even the continuation of its annual meetings of experts, highlighting concerns about the future of international efforts at biological nonproliferation and disarmament (Mackby, 2017; BWC, 2017) . Although salvaged with agreement on a new set of experts meetings in December 2017, the concerns remain.
As the formal political process around the BWC unfolds over the next several years, filling any gaps and promoting constructive action will likely continue to rest on achieving a "web of prevention" as an active strategy. 2 The argument for the web concept is that multiple organizations and arrangements at the national, regional, and international level are relevant to the task of fostering and sustaining biosecurity. Beyond governments, a wide and varied array of nongovernmental stakeholders are essential elements of a successful prevention strategy, including industry, the public health community, the law enforcement and security communities, and so on. The web's effectiveness, however, depends on engaging the active support of stakeholders for policies and actions where their contributions are most relevant. This paper focuses on the efforts to engage the scientific community, both individual scientists and scientific organizations, in preventing and mitigating the particular risks associated with the potential misuse of research.
Mobilizing the scientific community in support of biological nonproliferation and disarmament faces a number of challenges. One is the scope of research about which policy makers should be concerned. In 2003, a report from the U.S. National Academy of Sciences coined the phrase "dual use dilemma" to describe the risk that research intended for benign purposes could also be misused to develop biological weapons or for bioterrorism (NRC, 2004) . 3 The members of the committee that produced the Fink report, named for the committee's chair, Gerald Fink of MIT, could not have anticipated that "dual use research" would become the standard term for a set of the security issues raised by modern biotechnology. But although in common use, it remains controversial. Critics argue in particular that the concept is too broad to be useful and could lead to policies that unnecessarily hamper important research. In 2007, when the U.S. National Science Advisory Board for Biosecurity (NSABB) proposed a framework for oversight of dual use research, the Board argued that Because arguably most life sciences research has some potential for dual use, the NSABB strove to delineate a threshold that would identify that subset of life sciences research with the highest potential for yielding knowledge, products, or technology that could be misapplied to threaten public health or other aspects of national security. This subset of research is referred to herein as "dual use research of concern" (NSABB, 2007: 16).
U.S. policy has primarily focused on this narrower category of dual use research of concern or DURC for the last decade. 4 The Fink report also illustrated dual use risks with the example of seven classes of experiments that the authoring committee considered plausible potential microbial threats. The committee argued that the potential risks extended well beyond advances in microbiology, 5 but policy in the United States and overseas has continued to concentrate on this field of life sciences research. 6 This reflects the history of past biological weapons programmes that weaponized human, plants, and animal disease causing agents, and the international norm embodied by the BWC is thus traditionally described as preventing "the use of disease as a weapon." 7 ; But it also affects how ongoing policy debates and efforts to engage scientists are framed.
"Framing" refers to a set of sometimes overlapping concepts and theoretical perspectives, developed in a number of social science fields, which provide insights into how individuals, groups, and societies perceive, organize, and communicate about reality. "Framing effects refer to behavioral or attitudinal outcomes that are not due to differences in what is being communicated, but rather to variations in how a given piece of information is being presented (or framed) in public discourse" (Scheufele and Iyengar, 2014: 1) . "Competing interests frame issues in ways that strategically advantage their political positions, emphasizing certain aspects of an issue over other considerations, influencing estimations of the causes, consequences, and solutions to a policy problem" (Nisbet and Lewenstein, 2002: 5) . Efforts to create a compelling frame that defines an issue in policy debates over emerging technologies are thus often a key feature of the strategies used by different groups. One can think of examples such as "Frankenfoods" in the battles over genetically modified organisms in agriculture or the current competing frames of "autonomous weapons systems" versus "killer robots." Studies of communication provide insights into how to design and convey information and messages to enhance the chances of understanding and acceptance by the recipients, including for emerging technologies (Nisbet & Lewenstein, 2002; Scheufele & Lewenstein, 2005) . The understanding and application of insights about framing is central to the emerging "science of science communication" (Jameison, Kahan, & Scheufele, 2017) . The next section offers an example of how what I call "competing catastrophes" came to frame the controversy over research with pathogens with pandemic potential. This is followed by an example of how some international scientific organizations have framed scientists' engagement in biosecurity issues as part of the "responsible conduct of research" or the larger "social responsibility of science." 3 This is different from the traditional concept of "dual use" in security, which refers largely to technology and products that, although intended for commercial purposes, may have military applications. There are traditional dual use commercial items in biotechnology, such fermenters, that may be subject to controls, and the ready availability of these items via the internet is a subject of proliferation concern (see, for example, Zilinskas, 2015) . Controls may also extend to "intangible technology," which comes closest to the Fink Committee's concept of "dual use." According to the U.S. State Department, this "includes, but is not limited to, instructions (written or recorded), working knowledge, design drawings, models, operational manuals, skills training, and parts catalogues" (https://www.state.gov/ strategictrade/practices/c43180.htm). 4 The current U.S. government definition of DURC is "life sciences research that, based on current understanding, can be reasonably anticipated to provide knowledge, information, products, or technologies that could be directly misapplied to pose a significant threat with broad potential consequences to public health and safety, agricultural crops and other plants, animals, the environment, materiel, or national security" (U.S. Government, 2012: 1-2). 5 "The seven areas of concern listed here only address potential microbial threats. Of course, modern biological research is much broader, encompassing all of the health sciences, agriculture, and veterinary science. It also includes diverse industries such as those that manufacture pharmaceuticals, cosmetics (e.g., Botox), and soft drinks (e.g., citric acid production). Moreover, all of these areas are changing rapidly. The great diversity as well as the pace of change makes it imprudent to project the potential both for good and ill too broadly and too far into the future. Therefore, the Committee has initially limited its concerns to cover those possibilities that represent a plausible danger and has tried to avoid improbable scenarios. Over time, however, the Committee believes that it will be necessary not only to expand the experiments of concern to cover a significantly wider range of potential threats to humans, animals or crops but also to include oversight of work conducted for or performed within the private sector as well as non-NIH [National Institutes of Health] government facilities and sponsored activities that are not already voluntarily complying with the Guidelines [recommended in the report]" (NRC, 2004: 114) . 6 The seven types of experiments covered by the 2012 U.S. policy for DURC, are essentially the same as those in the Fink report. 7 For a history of past weapons programmes, see Wheelis et al. (2006) . More recently advances in fields such as neuroscience, in genome editing tools such as gene drives, and the growth of a global "bioeconomy" that relies on biotechnology-based production methods are expanding the range of security concerns (see, for example, Dando (2015) , National Academies of Sciences, Engineering, & Medicine (2016a), and Royal Society (2015)). These new issues are not yet widely reflected in policy.
2. Competing catastrophes and research with pathogens with pandemic potential Fig. 1 illustrates a widely cited portrayal of the spectrum of sources of biological risks, from the specter of naturally occurring pandemics at one extreme to biological warfare by states or terrorists at the other. Both ends represent low probability, but high consequence events. The original purpose of the graphic was to convey a range of risks, and it is often used to encourage an audience to think about how policies to address one set of risks could help ameliorate others. The current emphasis on "health security," in which increasing global capacity to prevent and combat infectious disease outbreaks provides important capabilities that could be deployed in the event of a deliberately caused disease outbreak is a good example. The Global Health Security Agenda, launched in 2014, acknowledges the essential need for a multilateral and multi-sectoral approach to strengthen both global and national capacity to prevent, detect, and respond to infectious disease threats whether naturally occurring, deliberate, or accidental. Once established, the capacity would mitigate the devastating effects of Ebola, MERS, other highly pathogenic infectious diseases, and bioterrorism events." 8 The figure can also be used to present a more zero-sum view of the risks, however. Could efforts to prevent one catastrophe increase the risks of another? For example, could policies to limit some areas of dual use research out of security concerns hamper vital efforts to prevent or respond to potential pandemics? "Nature is the best bioterrorist" is a common riposte to anyone arguing for the need to pay attention to risks from dual use research or sometimes even biological weapons or bioterrorism. Millions of casualties each year from naturally occurring infectious diseases offer a graphic contrast to the lack of any bioterrorist incidents since the anthrax letter attacks of 2001, which are sometimes presented as a "biocrime." And it should be noted that the continuing lack of consensus within the security community about the nature, likelihood, and severity of the risks from state and non-state actors compounds the problem of crafting and presenting a compelling alternative frame. 9 An example of this zero-sum competing catastrophes argument is illustrated by the ongoing controversy over research with pathogens with the potential to cause pandemics.
What became known as the "gain-of-function" (GOF) controversy emerged in late 2011. 10 It began when influenza researchers in the United States and the Netherlands funded by the U.S. National Institutes of Health (NIH) submitted manuscripts with the results of experiments with highly pathogenic H5N1 avian influenza to Nature and Science. Influenza is widely considered to pose the greatest threat of a devastating global outbreak and the H5N1 strain is one of the flu strains considered to have pandemic potential. So the researchers set out to explore the conditions under which the virus might become transmissible among mammals.
Using well-known techniques, the groups had selected for influenza strains highly transmissible between ferrets [the human model for influenza research], identified and sequenced the strains' genetic mutations, inserted the mutated genes into a new virus, and, by observing the behavior of the newly constructed viruses, demonstrated a causal link between the mutated genes and degree of transmissibility between mammals (NRC, 2013: 1).
However, reviewers flagged the manuscripts as raising biosecurity concerns because the experiments could also provide knowledge to those who would use the results to cause deliberate harm. The journals sought the advice of the NSABB, which had been consulted about several potentially problematic publications since its creation in 2004. 11 When the NSABB initially recommended against publication unless certain details were omitted from the methods section in December 2011, a storm of controversy erupted. One of the key features of the debate over the merits of the research was that there were vocal scientists on both sides of the argument; this was not simply the science community aligned against the government as was more typical of such publication controversies in the past. 12 The initial phases of the controversy played out over the next few months. In January 2012, a group of influenza researchers announced a 2-month moratorium on H5N1 research that could produce new highly pathogenic, highly transmissible strains to allow time for an international debate on the issues (Enserink, 2012) . In February the World Health Organization (WHO) brought together a small group of public health and influenza experts. WHO was a natural international convener because it oversees a global network of collaborating research centers on influenza as well as the international process to identify the candidates for annual flu vaccines. In addition, national limits on influenza research in the name of security could disrupt the painstakingly negotiated Pandemic Influenza Preparedness Framework (PIP) adopted by the World Health Assembly in May 2011. 13 But critics of the research argued that this also gave WHO a major stake in the outcome of the controversy, which raised questions about its capacity to be a neutral forum. The group's recommendation to publish the manuscripts in full once concerns about biosecurity and appropriate communication of the results were addressed confirmed the expectations of both advocates and critics. Editorials in major newspapers such as one in the New York Times headlined "An Engineered Doomsday" reflected the intensity of the public controversy (New York Times, 2012). The NSABB met again in late March and, based on further discussion, the presentation of additional information by the authors and other experts, and the statement by NIH that it did not have a legal basis to demand redaction, the Board voted (unanimously for one paper and by a majority vote for the other) to recommend publication in full of revised versions of the manuscripts. Both papers were published soon thereafter. In addition, on March 29 the U.S. government released a new Policy for Oversight of Life Sciences Dual Use Research of Concern. The policy set out an agreement among all 15 federal agencies supporting life sciences research to establish regular reviews of their portfolios for work involving 15 specific agents and toxins and 7 categories of experiments. As part of the review, the agency would "Assess the risks and benefits of such projects, including how research methodologies may generate risks and/or whether open access to the knowledge, information, products, or technologies generates risk [and] based on the risk assessment, in collaboration with the institution or researcher, develop a risk mitigation plan to apply any necessary and appropriate risk mitigation measures" (U.S. Government, 2012: 3) . A subsequent policy, to provide guidelines for the responsibilities of researchperforming institutions receiving federal funds for DURC research, took effect in September 2014 (U.S. Government, 2014) .
In addition to the engagement of the WHO, the controversy had other international dimensions. Because one of the researchers, Ron Fouchier, was based in the Netherlands, the Dutch government also became involved. It decided that, under European Union regulations aimed at preventing the proliferation of weapons of mass destruction (WMD), submitting the paper to Science constituted an "export" and Professor Fouchier should have applied for a license in advance. Under protest, Fouchier applied for a license, which was approved, but he also appealed the ruling. A Dutch court upheld the ruling in 2013, and the Dutch government continues to view exports controls, along with an extensive programme of outreach to the research community, as the appropriate method for addressing concerns about publication of dual use research (Enserink, 2013) . 14 After the United States government issued its DURC policy and the two research papers were published, the controversy continued to simmer at a lower level as new research with highly pathogenic avian influenza periodically raised concerns. In Europe, for example, the Fouchier case raised serious questions at the national and regional level about whether the European Union might decide that its measures against weapons of mass destruction (WMD) should apply to all member states and become engaged in more active oversight. The European scientific community expressed widely different views to the European Commission in the second half of 2013 about the relative risks and benefits of such research. The European Society for Virology wrote to the head of the European Commission (EC) in October to raise concerns about the damage to important research that would result if it became subject to export controls. In December, another group of scientists wrote an opposing letter through the Foundation for Vaccine Research to highlight what it saw as the safety and security risks associated with the research (NASEM, 2016b: 54-55). (Although the controversy began over security concerns, the potential biosafety risks of an accidental release from a laboratory soon became equally important in the debates.) The divisions within the scientific community led the EC and its chief scientific advisor to request a study from the European Academies Scientific Advisory Council (EASAC) in 2014 in search of common ground (EASAC, 2015) . Leaders of both camps were represented on the committee for the consensus study, giving its recommendations particular weight.
In addition, the German government asked the German Ethics Council to review whether the current legal framework as well as existing codes of conduct in the academic and private sectors were adequate to support decisions about funding for such research. The Council's Opinion made a series of recommendations, ranging from proposals for individual researchers and the scientific community to proposals for funding bodies, legislators, and international initiatives (German Ethics Council, 2014: 179) . At present, a series of voluntary measures are being implemented under the leadership of the German National Academy of Sciences Leopoldina and the German Research Foundation, but the potential for future legislative action remains as an incentive for the German scientific community to take the issues seriously. 15 The debates continued into 2014 and a series of significant biosafety lapses at U.S. government laboratories spurred different groups of scientists to organize to provide a collective expression of their views about the implications for what had now become 13 The PIP's goals are to maintain "a dynamic, equitable balance between sharing influenza viruses that have pandemic potential, and distributing the benefits that result" (http://www.who.int/influenza/pip/WHO_PIP_brochure.pdf?ua=1). Further information may be found at http://www.who.int/influenza/pip/en/; accessed January 27, 2018. 14 The Dutch government also asked the Royal Netherlands Academy of Arts and Sciences (KNAW) to review and update the code of conduct for biosecurity it had known as "gain-of-function" (GOF) research. 16 One group, called the Cambridge Working Group after its founding meeting at Harvard University, issued a consensus statement in July focused solely on biosafety concerns that recommended For any experiment, the expected net benefits should outweigh the risks. Experiments involving the creation of potential pandemic pathogens should be curtailed until there has been a quantitative, objective and credible assessment of the risks, potential benefits, and opportunities for risk mitigation, as well as comparison against safer experimental approaches. A modern version of the Asilomar process, which engaged scientists in proposing rules to manage research on recombinant DNA, could be a starting point to identify the best approaches to achieve the global public health goals of defeating pandemic disease and assuring the highest level of safety. Whenever possible, safer approaches should be pursued in preference to any approach that risks an accidental pandemic (Cambridge Working Group, 2014).
This statement was soon followed by a competing statement from another new group, Scientists for Science, which argued
Scientists for Science are confident that biomedical research on potentially dangerous pathogens can be performed safely and is essential for a comprehensive understanding of microbial disease pathogenesis, prevention and treatment. The results of such research are often unanticipated and accrue over time; therefore, risk-benefit analyses are difficult to assess accurately.
If we expect to continue to improve our understanding of how microorganisms cause disease we cannot avoid working with potentially dangerous pathogens. In recognition of this need, significant resources have been invested globally to build and operate BSL-3 and BSL-4 facilities, and to mitigate risk in a variety of ways, involving regulatory requirements, facility engineering and training. Ensuring that these facilities operate safely and are staffed effectively so that risk is minimized is our most important line of defence, as opposed to limiting the types of experiments that are done (Scientists for Science, 2014).
The groups gathered signatures and sought press coverage for their views. Individual scientists also spoke out, and although a number of scientists signed both statements, the signs of polarization within the community grew.
On October 16, 2014, the United States again became the center of attention in the controversy. The White House announced the launch of a "deliberative process" to assess the risks and benefits of some GOF experiments. To the surprise of those beyond the interagency decision-makers, the scope of the process was extended beyond highly pathogenic H5N1 avian influenza to include Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). This was the first time these viruses had figured in the discussions. The most controversial part of the deliberative process, which the White House expected to last less than one year, was the decision to institute a federal funding "pause" in parallel to the other elements.
New USG funding will not be released for gain-of-function research projects that may be reasonably anticipated to confer attributes to influenza, MERS, or SARS viruses such that the virus would have enhanced pathogenicity and/or transmissibility in mammals via the respiratory route. The research funding pause would not apply to characterization or testing of naturally occurring influenza, MERS, and SARS viruses, unless the tests are reasonably anticipated to increase transmissibility and/or pathogenicity (White House, 2014a: 2). 17
The deliberations would have a number of components. The NSABB was charged to "(1) advise on the design, development, and conduct of risk and benefit assessment studies" and "(2) provide recommendations to the USG [sic] on a conceptual approach to the evaluation of proposed GOF studies" (NRC, 2015: 2-3). The National Institutes of Health, which funded almost all the research subject to the process and oversaw the NSABB, would commission the formal assessment of the potential risks and benefits; the assessment would be carried out by private contractors. The NSABB also commissioned an analysis of the ethical issues associated with GOF research from bioethicist Michael Selgelid. The National Academies of Sciences, Engineering, and Medicine (NASEM) were requested to "provide a forum for broad public debate, which will inform the NSABB's deliberations and the development of USG [sic] policy on GOF research" (NRC, 2015: 3). The forum would consist of two public conferences with international participation. "The first conference would offer the opportunity for input from a wide range of stakeholders about both general principles that should guide the assessments of benefits and risks and what specific issues should be considered, while the second would provide an opportunity for comments on the NSABB's draft policy recommendations once the assessments were completed (NRC, 2015: 3).
The first public symposium by the National Academies was held in December 2014, but after that the process slowed down (NRC, 2015) . The NSABB produced its framework to guide the formal risk and benefit assessments in May 2015 (NSABB, 2015a), which was carried out by Gryphon Scientific. The draft risk and benefit assessments (Gryphon Scientific, 2015) , 18 along with the Selgelid paper 16 As the NSABB noted, "Recently, the phrase "gain-of-function research" has become synonymous with certain studies that enhance the ability of pathogens to cause disease. However, gain-of-function studies, as well as loss-of-function studies, are common in molecular microbiology and are essential to understanding molecular pathogenesis of infectious diseases. Changes to the genome of an organism, whether naturally occurring or directed through experimental manipulations in the laboratory, can result in altered phenotypes, as biological functions are lost or gained. Investigators routinely conduct loss-and gain-of-function experiments to understand the complex nature of host-pathogen interactions that underlie transmission, infection, and pathogenesis" (NSABB, 2016: 5) . Employing the more general term also had the effect of engaging a wider swath of the virology community who now became concerned that proposals to limit research would expand beyond the narrow focus on highly pathogenic avian influenza. 17 The pause applied only to certain experiments within a broader grant or contract, and an appeals process allowed that "an exception from the funding pause may be granted by the head of the federal funding department or agency if that official determines in writing that the research is urgently necessary to protect public health or national security" (White House, 2014b: 5). NIH initially identified 18 experiments as likely to be subject to the pause; the number eventually rose to 21, of which 10 received exemptions. 18 The Gryphon Scientific draft and final reports, along with substantial additional material, are available at http://www.gryphonscientific.com/gain-of-function/ (Selgelid, 2015) and the NSABB's draft recommendations (NSABB, 2015b), were released in December 2015 and discussed at an NSABB meeting in January 2016. 19 The second Academies symposium was held in March (NASEM, 2016b) and the final NSABB recommendations were produced in May 2016 and provided to the interagency process (NSABB, 2016) . The NSABB recommended a process that put substantial emphasis on reviews and decisions early in the life cycle of research, and, like the broader U.S. policy for DURC, allowed for monitoring and adjustments to any risk mitigation plans if unexpected results emerged. One of the NSABB's findings was "There are life sciences research studies, including possibly some GOF research of concern, that should not be conducted because the potential risks associated with the study are not justified by the potential benefits" (NSABB, 2016: 2) . By this point, the deliberative process had stretched toward two years. Once the interagency process began, there were no further public discussions by the government. On January 17, 2017, the White House Office of Science and Technology Policy released its Recommended Policy Guidance for Departmental Development of Review Mechanisms for Potential Pandemic Pathogen Care and Oversight. "The Guidance recommends consistent and appropriate Federal agency review and reporting processes for the oversight of Federally funded research that is anticipated to create, transfer, or use enhanced potential pandemic pathogens (PPP)" (White House, 2017: 1). Federal agencies that adopted a review mechanism consistent with the recommendations in the Guidance would fulfill the necessary conditions to end the funding pause. On December 19, 2017, more than three years after the deliberative process began, the Department of Health and Human Services announced its review mechanism and later that day NIH announced that the funding pause was lifted (NIH, 2017) . A few of the headlines that followed the announcement -"NIH lifts 3-year ban on funding risky virus studies" in Science (Kaiser, 2017) or "NIH Lifts Ban On Research That Could Make Deadly Viruses Even Worse" on National Public Radio (Greenfieldboyce, 2017 )suggest the controversy over this and other forms of dual use research is far from over.
Against this backdrop of controversy and division among parts of the life sciences community, this paper argues that what is needed is a way to frame biological risks that can address the controversies, or at least make them more manageable. The irony is that this controversy among some scientists is accompanied by a widespread lack of awareness among most life sciences researchers. Even a longrunning dispute like the gain-of-function debates, or the imposition of polices such as the U.S. review procedures for DURC has not led to a significant increase in awareness in the United States (NASEM, 2017a) and the situation seems to be true in other parts of the world. 20 For those interested in making security issues an accepted feature of discussions about the implications of developments in life sciences research, a successful framing of the problem would have a number of characteristics. It would facilitate engaging many stakeholders and fit within the mandates of governments and relevant international organizations. In particular, it would enable reaching the broadest possible array of scientists in settings ranging from academia to industry to public health and beyond. At the same time, it would be compatible with engaging specialized groups of scientists working on more security-relevant activities such as research in high containment laboratories. Finally, such a framing would complement existing legal and regulatory structures and provide a basis for discussing potential changes in research practices or additional security measures.
As discussed further below, a number of organizations and actors argue for framing security issues related to the life science within a broader context of "Responsible Science" and utilize it in their outreach efforts. Potential risks of dual use research are framed as one part of the general social responsibility of science, along with other ethical issues. Note that this puts the initial emphasis on responsibilities rather than legal obligations, which is the more natural focus of the security community.
There are a number of arguments to support a Responsible Science framing. This approach provides the opportunity to build on the existing culture of responsibility in the life sciences (and science more generally). The current culture is certainly imperfect, but the international scientific community is giving increasing attention to improving and expanding it. This presents a moment of opportunity for including issues related to dual use research. The current attention reflects the increasingly global nature of life sciences research and capacity, which is increasing the need to build common standards and practices to facilitate growing international collaboration (IAC-IAP, 2012). It also reflects the need to respond to conspicuous cases of ethical lapses (NASEM, 2017b). The effort is also genuinely international, which offers significant advantages in the world of international policy.
The current culture includes broad norms of science in service to humanity, including the public that supports continued funding for research. Discussions of responsible conduct of research are part of the larger question of the social responsibilities of science, which puts an emphasis on what scientists "should" do, rather than what they "must." Increasingly, scientists are considered to be responsible for more than simply doing the very best science. This view was a major theme in a 2012 report from the IAC-IAP, Responsible Conduct in the Global Research Enterprise:
Because of the increasing importance of research in the broader society, scientists and other scholars bear a responsibility for how research is conducted and how the results of research are used. They cannot assume that they work in a domain isolated from the needs and concerns of the broader world (IAC-IAP, 2012: x).
Over the last decade there have been a number of important statements from international scientific organizations reflecting the recognition that scientific freedom is not absolute and that researchers also bear important responsibilities. Names do matter as part of framing and a striking example comes from the International Council for Science (ICSU), for decades one of the staunchest 19 The draft papers, along with archived webcasts of the discussions at the NSABB meeting, may be found at https://osp.od.nih.gov/biotechnology/nsabb-meetings/. 20 The first and most systematic attempt to document the level of awareness internationally was the series of seminars conducted by Malcolm Dando and Brian Rappert. For further information, see Rappert and MacLeish (2014).
advocates for the principles of unfettered scientific freedom.
To address and promote both aspects [freedom and responsibility], ICSU established the Committee on Freedom and Responsibility in the conduct of Science (CFRS) in 2006. This Committee differs significantly from its predecessors that, since 1963, had focused on scientific freedom, in that it is explicitly charged with also emphasizing scientific responsibilities (ICSU, 2014: 3).
A list of international statements and reports that make some form of this argument for a broader conception of scientific responsibilities, including some already cited, may be found in Box 1.
There are also significant traditions of self-governance in the life sciences, sometimes as independent initiatives such as some of the continuing efforts related to dual use issues, and also in conjunction with government guidelines or other "soft law" measures. It is important to note, as a 2015 report from the European Academies Scientific Advisory Council recognized, that "self-regulation means that there are checks and balances on research agreed within the scientific community and does not mean that each researcher is free to decide for themselves what procedures to follow" (EASAC, 2015: 17) .
Within a number of life sciences fields of particular interest for biosecurity, biosafety norms and practices are central components of a culture of responsibility. 21 More generally, various types of codes set out basic standards of responsible behavior.
• Codes of ethics: Aspirational codes that aim to set realistic or idealistic standards as well as alert individuals to certain issues; • Codes of conduct: Educational or advisory codes that aim to provide guidelines for action, raise awareness of issues, and foster moral agency;
• Codes of practice: Enforceable codes that prescribe or proscribe certain behavior (Rappert, 2004: 2) .
A second argument in favor of the Responsible Science framing is that it makes scientists part of the solution, not part of the problem. This is particularly important for dual use issues. If researchers have undertaken their work for the benefit of humankind, what is the relevance for them of security or the national and international measures to promote it? Rejection or resentment is a plausible response to the suggestion that their research could pose security risks, particularly if it means additional administrative costs or requirements for a problem they may not recognize or accept as a legitimate concern.
Scientists and scientific organizations hold important keys to building and sustaining the prevailing scientific culture (NASEM, 2017b), and some are already contributing to an extension of the existing culture to include biosecurity. One example is the In-terAcademy Partnership (IAP), a network of 130 academies of science and medicine. 22 According to the IAP website Just as each academy has the potential to represent an authoritative voice nationally, this unified voice of academies aims to have 22 Founded in 1993 and expanded and re-launched in 2016, the InterAcademy Partnership (IAP) is a global partnership of more than 130 merit-based national and regional academies of science, engineering, and health, which aims to maximize the contributions of science toward understanding and solving the world's most challenging problems. Through this structure, IAP and its members are active in countries that constitute 95 percent of the world's population. Building on the extensive track record of independent, evidence-based advice delivered by its member organizations over the past two decades, IAP projects include statements, reports and convening activities, with the aim of providing knowledge and sound advice to governments and international organizations. Further informaiton is available at http://www.interacademies.org/ great impact at the international level. IAP provides a collective mechanism and voice for science academies to further strengthen their crucial roles as providers of evidence-based policy and advice at both national and international levels (IAP, 2017) .
When the IAP, then known as the InterAcademy Panel on International Issues, became engaged in biosecurity issues in 2004, it provided an opportunity to add the voice of the science community at a time when most of the voices arguing that biosecurity and dual use research should be treated as a significant policy issue were coming from governments and international security organizations. IAP mobilized its member academies to establish a Biosecurity Working Group. The Working Group's original membership has grown to include the national academies of Australia, China, Cuba, Egypt, India, Nigeria, Pakistan, Poland, Russia, the United Kingdom and the United States. Over the years the Working Group has engaged with international organizations, in particular the BWC, to highlight the implications of trends in science and technology for the Convention and international security more broadly, and to support outreach and education projects to promote attention to biosecurity. Other national academies have also carried out important work. All of the IAP activities employ the Responsible Science framing.
A few examples will illustrate the range of IAP's work and its application of Responsible Science, beginning with its 2005 Statement on Biosecurity that provided principles to guide science bodies while preparing codes of conduct. A major motivation for the Statement was the opportunity presented by the decision to devote the 2005 BWC intersessional agenda to "the content, promulgation, and adoption of codes of conduct for scientists" (IAP, 2005) . That year's meetings of Experts and States Parties provided an important opportunity to engage scientific organizations in the work of the BWC, and a number of national academies have since been involved in developing their own codes, sometimes with the encouragement of their national governments. Another statement, this one on Realising Global Potential in Synthetic Biology: Scientific Opportunities and Good Governance in 2014 concluded that "Maintaining biosecurity brings challenges beyond those of biosafety: for biosecurity the core defence rests on the responsibility of the scientific community" (IAP, 2014).
As mentioned above, the IAP's most ambitious efforts to date are its 2012 report Responsible Conduct in the Global Research Enterprise and a companion educational handbook, Doing Global Science, released in 2016. The report explicitly frames scientists' responsibilities to address the risks of misuse as part of broader responsible conduct of science Science and other forms of scholarship have been incredibly productive by seeking knowledge unfettered by tradition, ideology, and external pressure. At the same time, research can have a profound influence on the environment, human health and wellbeing, economic development, national security, and many other facets of human life. Many areas of science and technology can be used for destructive as well as constructive purposes, and researchers have a special responsibility to understand and address issues of "dual use." Research on biological pathogens, for example, poses both risks and benefits for human health (IAC-IAP, 2012:15).
The report concluded that "Researchers should bear in mind the possible consequences of their work, including harmful consequences, in planning research projects," and included a discussion of biosecurity as a key example of scientists' responsibility to help prevent the misuse of their research (IAC-IAP, 2012: 16) .
Doing Global Science is intended to help a range of audiences explore the dimensions of responsible conduct, including the "values that should inform the responsible conduct of scientific research in today's global setting" (IAP, 2016) . Like the parent report, the handbook addresses biosecurity and offers a variety of resources for those who wish to delve further into the issues.
Increasing the inclusion of biosecurity as part of a broader recognition of the social responsibility of science within the scientific community and its leading organizations is only one part of the effort. Policy makers and the security community also need to accept Responsible Science as a legitimate framing for their activities. As mentioned above, this is not the immediately obvious choice. Not surprisingly, members of the security community and diplomats who inhabit the world of international treaties are more inclined to frame their engagement strategies on the legal requirements with which individuals and institutions must comply. The final report of the 6th BWC Review Conference in 2006, for example, urged …the inclusion in medical, scientific and military educational materials and programmes of information on the Convention and the 1925 Geneva Protocol. The Conference urges States Parties to promote the development of training and education programmes for those granted access to biological agents and toxins relevant to the Convention and for those with the knowledge or capacity to modify such agents and toxins, in order to raise awareness of the risks, as well as of the obligations of States Parties under the Convention (BWC, 2006: 11) .
The Weapons of Mass Destruction Directorate of the U.S. Federal Bureau of Investigation has framed its outreach to the life sciences community as "Security Protecting Science," in this case from insider threats and others with nefarious intent.
Over the past decade, however, there have been growing signs of acceptance for a Responsible Science framing, particularly as a way to conduct initial engagement that can reach a wide audience and then lead to more security-focused efforts as appropriate depending on the nature of a scientist's or an institution's research. In the BWC, the report of 2013 BWC Meeting of States Parties included the conclusion that "In order to further efforts on education and awareness-raising about risks and benefits of life sciences and biotechnology, States Parties agreed on the value of using science responsibly as an overarching theme to enable parallel outreach efforts across interrelated scientific disciplines…" (BWC, 2013: 8) The final report of the 8th BWC review conference included the statement that as part of their national implementation measures, States Parties should "encourage the promotion of a culture of responsibility amongst relevant national professionals and the voluntary development, adoption and promulgation of codes of conduct" (BWC, 2016: 12) .
Responsible Science is also finding footholds beyond the BWC. One of the five deliverables for the Biological Security sub-Working Group of the Global Partnership for the Prevention of Weapons of Mass Destruction, a coalition of some 30 countries that seeks to fund and coordinate projects and activities in the areas of chemical, biological, nuclear and radiological security, is "Reduce proliferation risks through the advancement and promotion of safe and responsible conduct in the biological sciences" (U.S. Department of State, 2012). In October 2013 the UK government chose "Responsible Science" as the theme for one of the Global Partnership meeting under its presidency, and added a public session on the topic held at the Royal Society (UK Foreign & Commonwealth Office, 2013) . And although those outside government using the Responsible Science framing prefer to talk about "enhancing" or "building on" an existing culture, the 2013 Nobel Peace Prize Lecture by Ambassador Ahmet Üzümcü, Director-General of the Organization for the Prohibition of Chemical Weapons also deserves mention Our aim is to contribute to efforts towards fostering a culture of responsible science. This will ensure that current and future generations of scientists understandand respectthe impact that their work can have on security (OPCW, 2013) The signs of acceptance from both the scientific and policy side suggest that taking a less traditional approach to framing dual use issues to engage a key sector in biological nonproliferation and disarmament can gain traction among both scientists and the policy community.
The change reflects a growing recognition that compliance with legal obligations is a necessary but not sufficient condition to fully address the potential risks of dual use research in the life sciences. This is part of a wider effort to move beyond a "check-theboxes" mentality of adherence to regulations to active engagement in addressing risks. 23 The remarks by Ambassador Üzümcü about "promoting a culture of responsibility" () and the recommendations of the Federal Experts Security Advisory Panel in the United States (FESAP, 2015) are examples. Responsible Science offers a constructive alternative to the zero-sum competing catastrophes frame that supports this broader approach.
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What is the highest education level of the main earner?
1. 1 Without a diploma or primary education 2. 2 General lower secondary education (first 3 years completed) 3. 3 Technical, artistic or professional lower secondary education (first 3 years completed) 4. 4 General upper secondary education (6 years completed) 5. 5 Technical or artistic upper secondary education (6 years) 6. 6 Professional upper secondary (6 years) 7. 7 Higher education: graduat, candidature, bachelor 8. 8 University education: bachelor's degree, post-graduate, master's degree 9. 9 Complementary master 10. 10 Doctorate
What is the occupation of the main earner?
What is the profession that the main earner last exercised?
What is your occupation?
What is the occupation of the person with the highest income?
1. Fever or high temperature 2. A cough that has lasted for at least several hours 3. Shortness of breath 4. Aches and pains, e.g. in back, neck, shoulders or joints 5. Blocked nose 6. Sore throat 7. Feeling unusually tired 8. None of these 9 Don't know 10. Prefer not to answer Q30. Have you, or anyone else in your household, done any of the following for these symptoms? ROWS: 0. Yourself 1. Name 1 2. Name 2 etc.
1. Phoned NHS 111 or used NHS 111 online service 2. Phoned a GP practice/GP out of hours service 3. Visited a GP practice/GP out of hours service 4. Visited a walk-in centre, urgent care centre, urgent treatment centre or minor injuries unit 5. Visited Accident & Emergency (A&E) 6. Visited a testing location somewhere different to these services 7. Been admitted to hospital 8. Don't know 9. None of these 10
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Periodontal diseases are a group of chronic inflammatory diseases, including gingivitis and periodontitis (1) (2) (3) . These diseases are driven by several microbial agents that cause inflammation and destruction of tooth-supporting tissues (4) . According to Organization Health World (WHO), PD affect 10% of the global population (5) . Poor oral hygiene, tobacco smoking, diabetes, medication, age, hereditary, and obesity have related to increasing the risk of PD [6] [7] [8] . Similarly, other studies suggest the association between PD and other diseases such as diabetes, hypertension, asthma, liver diseases, among others (9) (10) (11) .
COVID-19 is a disease caused by novel coronavirus named SARS-CoV-2 that triggers damage to the lungs and other organs (12) . Most COVID-19 patients present mild symptoms; however, a few could develop severe illness having pneumonia, pulmonary edema, acute respiratory distress syndrome (ARDS), multiple organ dysfunction syndrome, or even die (13) . There are other diseases like severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS) by other coronaviruses that cause respiratory problems (12, 14) . COVID-19 was declared a pandemic by the World Health Organization (WHO) on March 11th. At present, in May 2020, there are more than 3,000,000 infected people around the world. Of all infected, only a small percentage induces critical state, considering the presence of any comorbidity or condition, which can be diabetes, hypertension, obesity, asthma, pregnancy, lung diseases, liver diseases, oral dysbiosis, aging, and gender (12, 15, 16) .
This work proposes to evaluate if PD could be a risk factor for developing severe of COVID -19 illness because of shared risk factors.
PD could be associated with severe COVID-19 illness. Oral medical history of PD could be a characteristic to identify a risk group to severe COVID-19. The suggested relationship between PD and severe COVID-19 illness could be connected to closely shared risk factors among these affections. Most comorbidities and risk factors reported in patients with severe COVID-19, also aggravate the development of PD. Until now, information on oral health history including periodontal status in patients with severe COVID-19 illness has not been reported.
Aging Aging is considered a process that causes degenerative changes at the cellular level and sometimes leads to various diseases that can be autoimmune, infectious, or inflammatory, including PD (17, 18) . According to the WHO, PD affects elderly adults, who are among the main target groups, because it is common that they have the following additional risk factors: poor oral hygiene habits, presence of chronic diseases, use of medications, smoking or lack of timely dental treatment, which can alter gingival microbiota and allow the development of PD and even respiratory infections (19) (20) (21) .
People over 65 years are the highest risk group by severe COVID-19 illness, mainly for the multimorbidity which is a common factor in this group that allows the rapid attack of the virus and increase mortality (22). Another critical factor for the disease to be severe is the immune response, which is not as strong compared to young people (18) .
Therefore, it is clear that aging is a determining risk factor in linking PD and severe COVID-19 since they share the associated risk factors that can lead to complications, thus allows to identify risk groups to severe COVID-19.
Different studies have suggested that men are more prone to severe forms of PD than women (23-26). It was proposed that differences in immune function could be involved; moreover, probably behavioral and environmental factors could have an important role to explain differences in gender, however this has not been well determined (26).
In similar way, it was suggested that men are more prone to become seriously ill by COVID-19 than women (27-29). Recently, it was proposed that differences of immune response to SARS-CoV-2 between men and women could explain this variance (28). Thus, PD could show the risk of COVID-19 illness, considering its association with gender and possible immunologic factors.
Diabetes mellitus (DM) is a chronic disease determined by loss of control of glucose homeostasis that can affect the organs of the body (WHO). This disease is associated in a bilateral way with PD. That is, the PD can be a complication of diabetes by out of control the level of glycemia, and having diabetes increases the possibility of developing PD (30-32). The proposed mechanisms to understanding this association include alterations in vascular, cellular, and host repair processes (33).
Increasing evidence supports an association between severe COVID-19 and DM, this is supported by chest tomography and other clinical parameters that state alterations in patients with diabetes (34, 35). Several studies show patients with severe COVID-19 may have affected expression of the angiotensin-converting enzyme 2 (ACE-2) in the lungs. This receptor is greater in diabetic than in no diabetic patients due to treatment with ACE inhibitors and angiotensin II type I receptor blockers (ARBs) (36, 37). In both periodontal disease and COVID-19 the response immune is affected by host factors, external and internal (37, 38).
Diabetes is a significant predictor of severe COVID-19 and periodontal disease, so that the latter could be useful to identify risk groups of COVID-19.
Hypertension and cardiovascular disease.
Hypertension is a health disorder that affects a large part of the population worldwide. High blood pressure (BP) is considered the main risk factor for cardiovascular disease (CVD) (39). Epidemiological studies have shown an association between hypertension, CVD and PD (40). The latter is currently considered a risk factor in hypertension and CVD (41-43).
In PD, the accumulation of various bacterial species in the subgingival biofilm induces a chronic inflammatory response by inducing the production of cytokines (IL-1, IL-6, IL-8 and TNF-a) (44), which regulate and increase levels of C-reactive protein (CRP). Detection of high-density CRP has been considered a marker in CVD and hypertension. In PD, presence of CRP is the link between these diseases (41, 45, 46) .
Hypertension is among the main comorbidities in COVID-19 infection (47) . Treatment of hypertension with ARBs increases expression of ACE-2 (48) . Another study in EP showed that the activity of ACE and ACE-2 was increased in this disease (49) . Hao Xu analyzed seqRNA profile data and demonstrated that ACE-2 could be expressed in oral mucosal epithelial cells (50) . Therefore, the expression of ACE-2 in hypertension and periodontitis may represent a major risk factor for severe COVID-19.
In industrialized countries, about 50% of the population is overweight or obese, with prevalence increasing annually. After smoking, obesity is the highest risk factor to develop PD, and its relationship has been studied since 1977 by Perslein and Bissada studying obese rats (51, 52) . Different mechanisms linking PD and obesity have been suggested. Obesity can alter the periodontal microbial composition and is associated with an increase in periodontal pathogens (53) . The main consequence of obesity is a systemic inflammation state (51) . Adipose tissue typically secretes low levels of proinflammatory cytokines (IL-6, IL-8, TNF-ɑ), adipokines like leptin and adiponectin (54) . These cytokines may contribute to the development of PD altering the response to bacteria in gingival tissue (53) . Additionally, the production of reactive oxygen species that generate oxidative stress is increased in obesity (55); this is important, since oxidative stress is increased in PD and it could contribute to its progression (56). If PD is established in individuals with obesity, there is an induction of an increased inflammatory systemic state triggered by the dissemination of bacterial products and proinflammatory cytokines (53) .
Obesity and their complications increase the risk to develop severe COVID-19 illness (57) (58) (59) . Factors implicated in this association could be decreased expiratory reserve volume, functional capacity, and respiratory system compliance. Additionally, augmented inflammatory factors reported in obesity could contribute to amplify the response of the patient and develop severe COVID-19 (58, 59) .
PD could contribute to the amplification of a systemic inflammatory response by dissemination of bacterial products and as a source of inflammatory cytokines in patients with COVID-19, therefore aggravating the disease. Moreover, it is possible that individuals with obesity and PD have an increased risk of developing severe COVID-19.
Pregnancy allows various physiological changes, (60) and suppresses the mother's immune system to allow gestational development. Over the last few years, some epidemiological studies have suggested the vulnerability of pregnant women to PD due to an affected inflammatory response (61, 62) Furthermore, it has been established that increased progesterone levels trigger the gingival response causing dysbiosis. In this way, high periodontopathogens growth occurs, (63, 64) causing clinical manifestations in the supporting and protective tissues of the teeth. Although, the link between PD and pregnancy is controversial, some risk has been suggested among pregnant women and PD as they may have complications during pregnancy, (65) or premature delivery.
As long as the novel coronavirus SARS-CoV-2 is spreading worldwide, some cases of COVID-19 have confirmed in pregnant women. Although, immunosuppression, high progesterone and estrogen levels, and the physiological adaptive changes predispose pregnant women to respiratory infections diseases, (66, 67) less than 10% developed severe COVID-19 disease (68) (69) (70) . However, this infection could complicate perinatal events such as preeclampsia, premature rupture of the membrane, low birth weight even death (67, 71) . Vertical transmission cases of COVID-19 are not fully confirmed (66, 67) .
Despite the fact, that the association between pregnancy and PD is not clear. Coinfection of SARS-CoV-2 in pregnant women with PD and other comorbidities could complicate pregnancies.
Chronic obstructive pulmonary disease (COPD) COPD is a chronic inflammatory lung disease caused by important exposure to noxious particles or gases, being smoking a main risk factor in developed countries (72) . Different studies have associated COPD and PD (73) (74) (75) , however, this link could be confounding by different factors like age or smoking. Recently, it was suggested that the severity of PD increases the risk for COPD mortality in older patients (75); though, causality or involved molecular mechanisms have not been reported.
It was suggested that patients with COVID-19 have an increased risk of aggravation when they present COPD (76) and patients with pre-existing COPD have a 4-fold increased risk to develop severe COVID-19 illness (77) . It was proposed that the increased risk could partly be because COPD patients present increased expression of ACE-2 in airways (78) . Thus, the association of PD with COPD could be helpful to identify risk groups to develop severe COVID-19, since COPD increased importantly the risk of this affection.
Smoking is a major risk factor to develop PD, and it affects the progression, severity and response to treatments of this condition. Different molecular mechanisms have been suggested to explain the contribution of smoking to progression of PD; smoking promotes dysbiosis in periodontal tissue, improving the virulence factors of key periodontal pathogens, favors the microenvironment to these pathogens and impairs the immune response of the host (79) .
On the other hand, smoking is a risk factor of COVID-19 progression, being 1.4 times more probable to have severe COVID-19 symptoms (80). Additionally, as COPD, smoking could increase the expression of ACE-2 (78) . It was proposed that smoking cessation could decrease the risk of developing severe COVID 19 complications (81) However, relationship between smoking and severity of COVID-19 illness is not completely clear, since a meta-analysis suggested not association of active smoking to severity of COVID-19 (82) . It is possible that discrepancies could be due to absence of information (as smoking duration or current and ex-smokers) in all the analyzed reports (77) . Thus, more deep studies are necessary to determinate the real risk of smokers and progression of COVID-19.
Since it is well established that smoking history is association to PD and it could be associated to severe COVID-19 (77) , probably, PD in smokers and comorbidities like COPD could identify a risk group to severe COVID-19.
Asthma is characterized by chronic inflammation of airways and diverse studies have positively associated asthma and PD (83) (84) (85) (86) . It was suggested that asthma could be a risk indicator for periodontal disease in adults. Even though, it not has been established causal relation or a molecular mechanism to explain this association, it was proposed that inflammatory factors and genetics (86) or dysbiosis could be involved. Moreover, it is possible that this association is related to a comorbidity or result of medication used for treatment (84).
It was proposed that asthma could be a risk factor for severe COVID-19 illness (87); however, asthma had lower prevalence than that expected in COVID 19 patients (88). Moreover, decreased expression of ACE-2, the cellular entry receptor used by SARS-CoV-2, was reported in patients with asthma (89) . It was speculated that lower prevalence might be due to underdiagnosis or lack of recognition of asthma in patients with COVID-19 (87, 88) . Furthermore, asthma patients with DM presented increased expression of ACE-2 and TMPRSS2 (Transmembrane protease, serine 2), and in addition to ACE-2 receptor used by SARS-CoV-2, the entry to cells is dependent on the priming of the spike (S) protein of this virus by proteases of host as TMPRSS2. Thus, increased expression of ACE-2 and TMPRSS2 in these patients could indicate increased susceptibility for SARS-CoV-2 infection and COVID-19 morbidity (90) . Together these observations could suggest that PD could indicate a potential risk of developing severe COVID-19, since it has been closely associated with comorbidities like diabetes and asthma.
Patients with HIV or a compromised immune function, represent a group at higher risk of systemic and oral manifestations (91, 92) . PD associated with HIV has been studied by several researchers (93) (94) (95) , this possible association has been considered since PD is a source of chronic inflammation (96) . Some authors suggest that HIV is a contributing factor in the prevalence of PD. However, results have been inconclusive, and the issue is currently controversial (96) (97) (98) .
On the other hand, HIV has been considered a risk factor for COVID-19 infection (99) . Early reports suggest that HIV patients are no more at risk than a non-HIV patient (100). There are not enough studies yet, but it is believed that the degree of immunosuppression may contribute to a higher susceptibility to SARS-CoV-2 infection (101).
Cancer is a malignant neoplasms disease driven by mutations that cause changes in the genome of normal cells. These mutations are consequence by exposition to chemical, physical, or environmental agents (102) (103) (104) . In recent years, PD has been identified as a risk factor that increases the development of cancer (105) . This fact has provided valuable information in researches on head and neck cancer (106), prostate cancer (107), breast cancer (108, 109), lung cancer [110, 111] and hematological cancer (112) .
There is no enough evidence about specific mechanisms of interaction among cancer and PD. In this respect, several studies have already shown how dysbiosis induces inflammation, systemic translocation of periodontal pathogens through the weakened periodontal epithelium, systemic immune dysregulation, and the increase in circulating cytokines and chemokines (113) (114) (115) (116) . According to several studies, inflammation can be promoted by microorganisms that increase the risk of developing cancer (117, 118) .
Patients with cancer are more susceptible to developing severe COVID-19 illness in large part owing to the presence of another comorbidity or risk factor (119) (120) (121) .Therefore, their immune response is suppressed by treatments and nutritional deterioration, which in turn induces dysbiosis breakdown and increases the possibility of respiratory infections (122) . Patients with lung cancer are more likely to develop complicating COVID-19 (123) . Thus, identifying cancer patients with PD could represent a group at risk for severe COVID-19.
Oral dysbiosis is the loss of the homeostatic balance of the oral microbial communities with the host, and it has associated with oral diseases like as PD (21,30,38) . The main pathogens associated with PD are Porphyromonas gingivalis, Tanerella forsythia, and Treponema denticola (red-complex), but there more pathogenic bacteria including species of the genera Prevotella, Desulfobulbus, and Selenomona as well as Aggregatibacter and others (30, 38, 124) . Host factors such as diet and immune system are determinant by the emergence and persistence of dysbiosis that allows the growth of pathobionts and their virulence factors in PD (38). Microbial communities execute a mechanism named "polymicrobial synergy and dysbiosis" that allows interaction between bacteria to become a dysbiotic community, where pathobionts grow and stimulate inflammation and tissue damage. Successfully, these pathobionts escape from epithelial barriers and an immune over-response of the host through mechanisms such as manipulation of neutrophils, inhibition of macrophage response, or subversion of complement (19) .
On the other hand, in severe COVID-19 illness was reported that hospitalized patients with intubation or some life-saving invasive mechanism impaired their oral health. Also, there are other risk factors like the use of drugs routinely or experimentally to attack the SARS-CoV-2 virus, lack of oral hygiene, and other comorbidities that can produce dysbiosis of the oral microbiota that could trigger oral diseases like periodontal disease (15, 20, 125) . Within a metagenomic analysis of patients with severe COVID-19 illness has reported the emergence of genre Prevotella, Fusobacterium, Veillonella, which are associated with periodontal disease (20) . Additionally, some researches suggesting that the virus recognizes the ACE-2 receptor, which is localized in the nasopharynx but in oral mucosa too (50) . Therefore, the entry of the virus can subvert the immune system, and oral microbiota of host triggering a dysbiosis that allows a superinfection, understanding of the association of the PD with severe COVID-19.
Association has been found between PD and liver diseases (LD). As they are, liver cirrhosis (LC), hepatocellular carcinoma (HCC), and Non-alcoholic Fatty Liver Disease (NAFLD) with a prevalence of 20-30% around the world. Even liver transplantation (LT) is associated with PD, since to avoid sepsis by periodontopathogens the patient has to be examined by an oral professional before LT (126) (127) (128) (129) . Structural components and products of subgingival microbiome stimulate inflammation of periodontal tissues generating cytokines (IL-1β, IL-6, IL-10, IL-12, and TNF-α and INF-γ) (130) that are involved in the progression of liver diseases. Also, the lipopolysaccharide from Porphyromonas gingivalis induces liver inflammation (131) .
Liver injury by SARS-CoV-2 is associated at the time of infection occurs and post treatment (132) . Although, it is considered that pre-existing LD patients would be more vulnerable to severe COVID-19 because the novel coronavirus bins hepatocytes and cholangiocytes using the ACE-2 receptor (133) . Thus, patients with liver diseases and PD could help to identify a group at risk for severe COVID-19.
According to WHO, rheumatoid arthritis (RA) is a chronic inflammation and disabling disease that affects the joints and connective tissues among other tissues. The prevalence ranges from 0.3-1%. Several studies reveal that relation between RA and PD exists (134, 135) . Meta-analysis studies show that people with RA get worse when they have PD (136) . The molecular mechanism is not entirely clear. However, a member of the red complex Porphyromonas gingivalis is known to produce an enzyme that causes citrullination (135) , and periodontal bacteria have been isolated from synovial fluid (134, 137) .
Nowadays, the main concern of rheumatologists in front of COVID-19 pandemic is the vulnerability (138) to SARS-CoV-2 of their patients with RA (which is an inflammatory disease) because it has been reported that patients with RA have twice the risk of infectious diseases and it also increases mortality when there is bronchopulmonary infection (139) . On the other hand, they are calm and have had experience in the management of certain medications such as chloroquine and hydroxychloroquine that they are using as a potential treatment for COVID-19 (140, 141) . Closely association between PD and RA and possible inflammatory and bacterial underlying mechanisms could affect the outcome in patients with COVID-19.
There is enough evidence to propose that PD acts as a risk factor for COVID-19. PD has been widely associated with several disorders such as diabetes, HTA, obesity, among others. Thus, PD could be indicative of systemic health. Furthermore, these comorbidities and additional factors are common risk factors in patients with severe COVID-19 illness. Since periodontal health status has not been assessed in patients with COVID-19 illness, it is difficult to determine this association. However, it is possible that inflammatory, microbial and environmental factors could be implicated. It has been suggested that inflammatory factors could play important roles in the association of PD with comorbidities. In this sense, dysregulated inflammatory response also has been observed in severe COVID-19 illness contributing to its progression.
Alterations in oral microbial communities can affect the microenvironment with increases in pathogens and over-stimulation of the immune system (38). Coinfection of pathobionts and the SARS-Cov-2 virus with established risk factors and comorbidities may play a role in increased inflammatory response and cytokine storm (142) . On the other hand, researchers suggest that exists a close relationship between lung microbiota and admission to intensive care. Patients have required ventilators for complications associated with bacteria belonging to gut microbiota not commonly found in the lung ecological niche. Therefore, there is a proposal to identify patients with initial gastrointestinal symptoms, since that could help predict patient outcomes and help to improve decision making relating preventive measurements and appropriate treatment. Consequently, it would be useful to characterize the microbiome in PD patients with COVID-19.
Even though some of the reported risk factors have not been strongly associated with PD or their causal relationships are not completely established, it is convincing to propose an association between PD and COVID-19, where the latter could be affected by the intervention of periodontopathogenic bacteria outside its ecological niche and cause chronic inflammation. Additionally, it is possible that the association between PD and severe COVID-19 illness could be non-causal, suggesting that prevention or treatment of PD does not prevent a worse progression and outcome of COVID-19. Future studies on the periodontal status of patients with COVID-19, including from mild to severe forms, could allow the opportune identification of people in risk of severe illness, and generation of relevant recommendations.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Acute respiratory infection (ARI) is among the major causes of death in young children worldwide. 1 In Australia, ARI is the main cause for short-term illness in children aged 0-14 years. 2 The number of newly identified viruses in respiratory tract specimens, including the recently discovered polyomaviruses WUV and KIV, 3, 4
Influenza causes a substantial health burden with direct and indirect costs, including hospitalisations and loss of productivity. [5] [6] [7] [8] Inactivated and live-attenuated influenza vaccines offer both direct and herd benefits to vaccinated children, their contacts and the broader community. [9] [10] [11] Several studies have shown that children attending child care centres (CCCs) are at greater risk of ARI including influenza. [12] [13] [14] [15] In 2008, formal child care was undertaken by 9% of Australian children aged <1 year, 35% aged 1 year and 47% aged 2-3 years. 16 In order to determine the health, social and economic effects of influenza vaccination in young children, we planned a randomised controlled trial (RCT) of an unadjuvanted trivalent influenza vaccine in children aged 6-35 months who attended a CCC in metropolitan Sydney during 2010. However, because of the 2009 pandemic, the Australian government recommended and funded universal use of inactivated pandemic influenza A(H1N1)pdm09 vaccination for those aged >6 months in 2010. Hence, a RCT design became unethical. The study was restructured to a prospective cohort design addressing the epidemiology of ILIs among young children.
Children were recruited through 90 CCCs and one general practitioner with a special interest in paediatrics. Informed consent was obtained from a parent or legal guardian. To meet inclusion criteria, children needed to be aged ≥6-35 months on 1 March 2010. Exclusions were for known allergy to any component of the influenza vaccine, a history of Guillain-Barre syndrome, a bleeding disorder, an unstable chronic illness or enrolment in another trial. Parents reported influenza vaccinations their children had received and, where possible, the influenza vaccination status was validated from vaccination records. The children were divided into three cohorts: fully vaccinated (usually two doses in 2010), partially vaccinated (usually one dose in 2010) and unvaccinated according to their receipt of vaccines that contained influenza A (H1N1)pdm09full definitions are in the footnotes to Table 1 .
We planned to commence ILI case reporting as soon as an upswing in influenza cases in Sydney was recognised through laboratory surveillance. During the ILI follow-up period, parents were asked to report to us whenever a subject child developed an ILI, defined as fever ≥37Á8°C or feeling feverishness according to the carer's assessment, plus at least one of the following symptoms: cough, rhinorrhoea/nasal congestion, sore throat. During the ILI-reporting period, each family received a weekly e-mail, text message or telephone call to remind them to contact the study team immediately if a child developed an ILI. Before the ILIreporting period, e-mail addresses and mobile telephone numbers of all parents/guardians were confirmed with parents/guardians to ensure that they received messages. In addition, during the 1 week of the ILI-reporting period, all parents/guardians were contacted/recontacted until they indicated that they had received the message that the ILIreporting period had commenced. Parents/guardians were provided with plastic shaft rayon-budded swabs and plastic transport tubes with a foam pad reservoir soaked in viral transport medium (Virocult MW950; Medical Wire & Equipment, Wiltshire, UK). They were given verbal and written instructions on how to collect a nose swab and a throat swab from the subject whenever an ILI occurred. We asked for a nose swab to be done first and did not insist on a throat swab if the parents felt uncomfortable to collect one. Parents mailed swabs to the Queensland Paediatric Infectious Diseases Laboratory (QPID), where they were stored at À80°C until tested. Swabs were tested for 19 respiratory viruses by qualitative real-time PCR, 17-19 including influenza viruses A and B (Flu A, Flu B), adenovirus (AV), human rhinovirus (HRV), polyomaviruses (JCV, BKV, WUV, KIV), parainfluenza viruses 1, 2, 3 (PIV1, PIV2, PIV3) , coronaviruses (HCoV-OC43, HCoV-NL63, HCoV-229E, HCoV-HKU1), human metapneumovirus (HMPV), bocavirus (BV) and human respiratory syncytial viruses A and B (hRSV A, hRSV B). All RNA virus assays used Qiagen One-Step RT-PCR, Qiagen (Melbourne, Victoria, Australia), and all DNA virus assays used Qiagen Quantitect Probe PCR Mix, Qiagen, Australia. In order to assess extraction quality, specimens were spiked with equine herpes virus-1 (EHV-1) and tested for EHV-1 using a duplex real-time PCR assay. Any samples that failed the EHV-1 quality control were re-extracted. In order to monitor quality of specimen collection, specimens were tested for human endogenous retrovirus 3 (ERV3) using a duplex realtime PCR assay. In addition, the positive controls included in each PCR run were monitored for any shift in cycle threshold values to detect problems within individual runs.
In order to determine health impacts of the ILI event upon the child and the household, study staff interviewed the child's parent/guardian by telephone 2 weeks after the onset of each ILI in subject children, and if, at that time, the subject child still had ILI symptoms other than a dry cough, another telephone interview was arranged and conducted 2 weeks later. Data collected included the nature and duration of symptoms, severity of illness, intrahousehold spread, visits to healthcare providers and medication usage. Severe ILIs were defined as having at least one of the following features: fever ≥5 days, any symptom other than dry cough persisting more than 14 days, otitis media, suspected bacterial respiratory infection or admission to hospital.
During ILI outcome assessment interviews, parents were asked to report ILIs in household members in the week before and the week after the onset of an ILI in the subject children. ILI attack rates in household members were calculated for the week following ILI onset in subject children.
Statistical tests used were one-way ANOVA for continuous variables, chi-square tests for categorical data (SPSS 19, Chicago, IL, USA) and t-tests for normally distributed data to compare means.
Poisson regression (STATA/SE 12Á0, StataCorp LP, TX, USA) was used to compare incidence rates. We used There were eight subjects vaccinated late, and for the incidence rate calculations, their person-time contributions to the partially and fully vaccinated cohorts have been determined using the date of receipt of the second dose of vaccine as the time-point at which they changed between the cohorts. person-year in the calculation. For children who became (fully) vaccinated in the few days after the formal start date of follow-up (30 July 2010), we deducted the number of days until the children became (fully) vaccinated from the surveillance time.
Meta-Analyst 3Á13 (Tufts Medical Centre, Boston, MA, USA) was used to calculate the probability of a virus being the sole agent identified from nose/throat swabs during an ILI episode (binary analysis with model type Random (D/L) and random method Der-Simonian Laird).
The study was approved by the Human Research Ethics Committee at The Children's Hospital at Westmead and was registered with the Australian New Zealand Clinical Trials Registry (ANZCTR, ACTRN12610000319077).
Between March and August 2010, we enrolled 399 children, of which 95Á6% completed follow-up (exclusions: 9 were of incorrect age and nine others withdrew without contributing to the ILI-reporting period); therefore, 381 children (208 males) from 358 households participated. The ILI-reporting period was 30 July to 31 October 2010. There were just four subjects who were enrolled slightly late during the first week of the ILI-reporting periodtheir person-year contribution to the ILI follow-up period was adjusted to be from the time of joining the cohorts (one was fully vaccinated, one partially vaccinated and two unvaccinated). The majority (89%) of enrolled children attended CCCs. On commencement of ILI surveillance, the mean age of enrolled children was 2Á3 years (0Á9-3Á4 years). At that time, 83 (22%) children fulfilled the criteria for 'fully vaccinated' against influenza A/California/7/ 2009 (H1N1) (A(H1N1)pdm09); 60 (16%) were 'partially vaccinated', and 238 (62%) were unvaccinated (see Table 1 ). The great majority given influenza vaccine (94Á4%) completed vaccination by the beginning of the formal ILI followup period; eight subjects received their second dose of influenza vaccine after follow-up began (between 1 August and 3 September). These subjects were primarily assigned to the fully vaccinated cohort, and for incidence rate calculations, their person-time contributions to the partially and fully vaccinated cohorts were determined using 1 week after the date of receipt of the second dose of vaccine as the timepoint at which they changed status.
All vaccines given were licensed unadjuvanted inactivated split virion vaccines. There were no demographic differences between the vaccinated children, partially vaccinated children and unvaccinated children (Table 1) .
During the 13 weeks 30 July to 31 October 2010, parents/ guardians reported a total of 124 ILI episodes in 105 children (13 had two ILIs, three had three). Symptomatic ILIs were reported significantly more commonly in recipients of influenza vaccination (Table 1) . Non-influenza ILIs were more common among fully vaccinated subjects (33 non-influenza ILIs, 1Á59/person-year of observation) and partially vaccinated subjects (20 non-influenza ILIs, 1Á54/ person-year) than among unvaccinated subjects (59 noninfluenza ILIs, 0Á99/person-year, P = 0Á001, rate ratio 1Á6, vaccinated versus unvaccinated, Table 1 ). Excluding ILIs from which no virus was identified made no significant difference to this finding. No particular respiratory virus, with the exception of AV, was found less frequently in ILI episodes among unvaccinated subjects compared to fully or partially vaccinated subjects (P = 0Á04, data not shown). The vaccination status of subjects was not correlated with the mean number of doctor (GP, emergency department or specialist) visits made in response to non-influenza ILIs (P = 0Á45, data not shown). Nor were there significant differences in the mean duration of ILIs (P = 0Á95) or use of antibiotics (P = 0Á92) for non-influenza ILIs between fully or partially vaccinated subjects and unvaccinated subjects (data not shown). However, before enrolment in the study, there was evidence for an increased use of healthcare services in both the partially and fully vaccinated groups with significantly higher rates of prior hospitalisation, hearing tests and grommet insertion, whereas the incidence of past otitis media was not significantly different between the groups ( added to a multivariate model to predict non-influenza ILI in study subjects (data not shown).
The apparent greater risk of non-influenza ILI in influenza-vaccinated subjects did not vary significantly over time, compared with non-vaccinated participants. For example, the rates of non-influenza ILI between the two groups (vaccinated versus non-vaccinated) were 1Á88/person-year and 1Á09/person-year, respectively (rate ratio = 1Á72, P < 0Á001) in the first half of follow-up period, while the rates in the second half were 1Á40/person-year and 0Á97/ person-year, respectively (rate ratio = 1Á45, P = 0Á02).
Telephone follow-up 2 weeks after ILI onset was conducted for all 124 ILIs. Symptoms other than dry cough persisted in 29 ILIs at that time. At the 4-week telephone interview, symptoms other than dry cough still persisted in eight ILIs. Data on ILI duration were not available for five ILIs. The most commonly reported symptoms (data available for 121 of the 124 episodes) were rhinorrhoea 92% (111), cough 63% (76), decreased activity 27% (33), gastrointestinal symptoms 22% (abdominal pain, diarrhoea, vomiting; 27) and sore throat 20% (24) . Fever was documented in 84 ILIs (68%). The mean temperature was 38Á7°C. The frequency of documented fevers was similar in each of the three cohorts see Table 1 . Managing the ILIs required 134 GP visits (for 70 ILIs, 35 of which required more than one GP visit), 106 pharmacy visits (64 ILIs), five emergency department visits and three specialist visitsevenly distributed between the cohorts (data not shown). No hospitalisations were reported. Antibiotics were used for 52 ILIs and 73 were treated with analgesic/antipyreticsevenly distributed between the cohorts (data not shown). The median duration of ILIs was 8 days, but 16 (13%) lasted more than 28 days.
Forty-four ILI episodes (35%) met our definition of 'severe ILI': 15 had otitis media, 31 had symptoms other than post-ILI dry cough persisting >14 days, and 9 had fever persisting ≥5 days (some overlap).
Swab samples were available for 117 (94%) of the 124 ILI episodes, both nose and throat (69 ILIs) or nose only (48 ILIs).
The quality of samples was high in terms of extraction and cell collection; only one sample failed EHV testing and ERV3 was detected in all but one specimen, and this specimen was negative of all other viruses. A total of 175 viruses were identified from 103 ILIs (see Figure 1 ). Multiple viruses were detected in 52 (44%) of the swabbed ILIs -38 ILIs yielded two viruses each, nine yielded three viruses, four yielded four, and one yielded five. The probability of a virus being the sole agent identified from nose/throat swabs during an ILI episode is shown in Figure 2 . Influenza A(H1N1)pdm09, which was the sole virus causing 5 ILIs, was the only virus consistently identified as the sole agent from all ILIs with which it was associated. Although coronavirus NL63 (3 of 5 ILIs in which they were identified) and rhinovirus (15 of 39 ILIs in which they were identified) were frequently identified as sole agents of ILIs, that tendency was not statistically different to the probabilities of the other non-influenza viruses being solely identified.
No particular virus or virus combination or multiplicity of virus infection was associated with any particular symptom or combination of symptoms or with greater frequency of antibiotic or analgesic/antipyretic use, GP visits or other healthcare service usage. One or more of the polyomaviruses WUV and KIV were more commonly identified in children aged <2 years (P = 0Á05), and adenoviruses were more common in females (P = 0Á03)data not shown. Rhinovirus alone or in combination with other viruses was associated with longer duration of ILI than other viruses (P = 0Á02). None of these values were corrected for multiple testing.
Of the five children who had influenza A(H1N1)pdm09 infection, one was fully vaccinated, one was partially vaccinated (1 dose of Panvax, CSL, in October 2009), and three were not vaccinated against influenza. The management of the A(H1N1)pdm09 infections required GP visits for four of the children; three received antipyretic/analgesic medications, and two received antibiotics.
Nose swabs were collected from 117 swabbed ILIs, while throat swabs were collected from 69. The use of neither nose nor throat swabs was not significantly differently distributed across the three cohorts. Furthermore, there was no statistical difference in the number of throat swabs collected from the three study groups (P = 0Á20). Swabs were not combined prior to testing. One or more viruses were detected in 88% of swabbed ILIs. Nose swabs more often yielded viruses -102/117 (87%)than did throat swabs -45/69 (65%), P < 0Á001. Nose swabs yielded more viruses per swab than did throat swabs (161 virus identities from 117 nose swabs = 1Á38 viruses/swab compared to 59 virus identities from 69 throat swabs = 0Á86 viruses/swab, P < 0Á001). Limiting the comparison of virus yields from nose versus throat swabs to ILIs from which both nose and throat swabs were taken (n = 69) gave the same rates of virus identification (1Á37 viruses per swab for nose swabs, 0Á86 viruses per swab for throat swabs, P = 0Á001) with 61 (88%) of 69 nose swabs yielding a virus and 45 (65%) of 69 throat swabs yielding a virus, P = 0Á002.
In the week before onset of their ILIs, only nine subjects were exposed to one or more household members with ILIs (three other children and eight adults). In the week after onset of the subject's ILI, eight other children (154 exposed, 5% attack rate) and 38 adults (244 exposed, 16% attack rate) in the ill subjects' household reported ILIs. Adult household members more often developed an ILI in the week after ILI onset in subject children than did child members of the households, P = 0Á001 (asymptomatic carriage and transmission were not taken into account as it could not be identified). No virus was more likely than any other to be transmitted from the ill subject to members of the household.
In the 2010 Southern Hemisphere influenza season in Sydney, Australia, we found that young children suffered relatively often from ILIs, but less than in previous studies. 20 The ILIs were caused by many different viruses, most commonly rhinoviruses and adenoviruses. Adenovirus was more commonly found in females, an association which has not been reported previously 21, 22 and may be due to chance as no correction for multiple testing was performed. In contrast to others, we detected few RSV infections 14, 20, 23, 24 probably because RSV infections peaked in Sydney during June and July 2010 and had declined significantly in frequency by the time we commenced observations for ILIs in the study participants (from 30 July 2010).
We found only 5 ILIs caused by influenza virusesall A (H1N1)pdm09. Their illnesses were little different to the ILIs experienced by the children from whom other viruses were identified (data not shown). However, the small number of influenza infections is consistent with the low degree of influenza activity during 2010, 25 limiting the power of this study to detect differences in influenza infection rates.
We did, however, unexpectedly find that non-influenza ILI occurred about 1Á6 times more commonly in children vaccinated with one or two doses of the influenza vaccine than in unvaccinated children. These results support the findings of a recent RCT reported by Cowling et al. 26 Cowling's study in Hong Kong concluded that non-influenza ARI may be detected at a higher rate in children for a short period after they received influenza vaccine. The noninfluenza virus incident rate ratio (IRR) was higher in the Hong Kong study (4Á4 versus 1Á6), but there are some key differences to our study, including age of subjects, follow-up period, proportion of illnesses swabbed and proportion of swabs yielding viruses. As with all observational studies, bias must be considered. Vaccinated and unvaccinated cohorts in Sydney were demographically similar (Table 1) ; however, lack of blinding by vaccination status makes it difficult to rule out selection or measurement bias. We could find no evidence of different parental responses to ILIs in vaccinated and unvaccinated children: parents of vaccinated children were no more likely to seek medical care during an ILI. However, we did find that health-seeking behaviours, recorded on enrolment (before the ILI observation period), such as hospitalisation (any cause), hearing tests and grommet insertion were significantly more common in the vaccinated groups, suggesting that families that vaccinate children have a prior preference for greater healthcare service usage. This may be a partial explanation for the observed difference in ILI frequency between the groups; however, prior access to any of these healthcare services did not predict the frequency of reported ILI.
Cowling et al. proposed possible explanations ranging from an unknown biological mechanism by which vaccineinduced immunity to influenza was accompanied by decreased immunity to other respiratory virus to a temporary non-specific immunity (interferon-and/or cell-mediated related) to other respiratory viruses after wild influenza infection. A formal biological explanation is lacking. A recent US observational (case-control) study has not found an association between influenza vaccination and detection of non-influenza respiratory viruses 27 . Re-analysis of observational studies or preferably new RCTs with high parentcollected specimen availability is required to further examine this phenomenon. It should be a priority to determine whether a causal association exists, whether it is consistent across vaccines and populations and whether any observed increase in the rate of non-influenza respiratory virus identification outweighs the benefit of seasonal TIVs in children.
In nearly half (44%) of the nose/throat swabs, multiple viruses were detected. Other studies in different settings, using a variety of definitions for ILI, have reported diverse virus aetiologies for ILIs, but, in general, with lower frequencies of virus co-infection than we report. 14, 20, 23, 24, 28 Our finding may be explained by the large number of viruses for which we tested and also by our high rate of swabbed ILIs being positive (88%).
While we found no increased severity or number of symptoms with multiple virus compared with single virus infection, this study lacked power to tease apart the relative significance of each virus, virus combinations and multiplicity of infection. A simultaneously sampled asymptomatic control group would have been useful to explore further the meaning of multiple virus identification. Interestingly, influenza A(H1N1)pdm09 was the only virus constantly identified as the sole virus from ILIs. However, there were too few cases (five only) to permit a firm conclusion about this.
We found that nose swabs were more effective than throat swabs for detecting respiratory viruses in young children with ILIs. Also, parents more frequently collected nose swabs than throat swabs from their children, suggesting that they may be more acceptable.
In our study, we detected the polyomaviruses WUV and KIV at higher frequencies (mainly as co-infections) than other investigators. [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] Children aged <2 years were more often infected than older children, but this barely reached a statistical significance. To date, the pathogenicity and clinical significance of WUV and KIV (discovered in 2007) 3,4 remain unclear and studies, conducted in a variety of settings and with a variety of respiratory disease definitions, have yielded inconsistent results.
Key strengths of our study include the high rate of specimen collection (94% of ILIs were swabbed) and the high rate of virus detection in swabbed ILIs (88% of all cases swabbed yielded at least one virus). We believe that parentcollected specimens combined with mail return of the specimens to the laboratory can be considered a reliable means of virus detection for studies such as ours, partly because children are sampled earlier when viral loads may be higher.
The participant characteristics are somewhat different to the general Australian population. Participating households had a higher income (83% of the studies households compared to 30% of Australians had income of $ 2000/week or more), 39 the mothers were slightly older (33Á1 years compared to 30Á1 years in the general population) 40 and were more likely to live with a partner (married or de facto 97% compared to 88%) 41 and, because we recruited in CCCs, 89% of the study population were in formal child care compared to 35% of Australian children aged 0-4 years. 42 At the start of the ILI follow-up period, we established that all parents/guardians were receiving reminder messages, and during the course of the ILI follow-up period, we spoke to parents/guardians of 52% of the enrolled children (evenly distributed across the cohortsdata not shown). However, we did not contact all parents/guardians after the ILI follow-up period in order to determine whether they had not reported ILIs. We did record at enrolment data on prior healthcare service usage (e.g. hospitalisation) and this was higher in vaccinated children; all this might have biased the research to show a higher frequency of ILI in influenza vaccinees. The open-label cohort design is also open to unmeasured confounding.
Influenza-like illness is common in children, and the burden on their families may be considerable. Many different respiratory viruses are responsible for ILIs in children. In this study, conducted after the RSV season, adeno-and rhinoviruses were the most commonly detected viruses. Symptom profiles were similar among the different viruses, and the rate of virus co-infection was high. Recipients of influenza vaccines had about 1Á6 times more ILI episodes than did unvaccinated children, and although this may be at least partly explained a healthcare service-seeking bias, further investigations are warranted into whether influenza vaccine increases the risk of non-influenza ILI, as healthcareseeking behaviour did not predict ILI in a regression model.
Nose swabs collected by parents had a high yield of respiratory viruses when using multiplex PCR methods and had significantly more viruses compared to throat swabs. In addition, parents appeared to feel more comfortable in performing nose than throat swabs. This is of relevance to future studies requiring parent-collected samples for PCR analysis.
Dr. Alexa Dierig contributed substantially to the design of the study, helped with analysis and interpretation of data and wrote and revised the intellectual content. She was also the study co-ordinator. Dr. Leon Heron contributed substantially to the concept and design of the study, helped with analysis and interpretation of data and wrote and revised the intellectual content. A/Prof Stephen Lambert contributed substantially to the concept and design of the study, helped with analysis and interpretation of data and wrote and revised the intellectual content. Dr. Jiehui Kevin Yin analysed the data, helped with their interpretation and revised the intellectual content. A/Prof Julie Leask contributed substantially to concept and design of the study and revised the intellectual content. Maria Yui Kwan Chow helped with analysis of data and revised the intellectual content. Prof Theo Sloots contributed substantially to the concept and design of the study and helped with the analysis of data. Prof. Michael Nissen contributed substantially to the concept and design of the study and helped with the analysis of the data. Dr Iman Ridda helped with the interpretation of data and wrote and revised the clinical content. Prof Robert Booy contributed substantially to concept and design of the study, helped with analysis and interpretation of data and also with writing and revising of the intellectual content. He was the supervisor of the whole project. All authors approved the final version.
This work was supported by a grant from the Australian Research Council and Sanofi Pasteur (industry partner) with kind assistance from KU Children's Services.
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The latest statistics indicate that there has been an exponential increase in the number of publications since the discovery of the Covid-19 pandemic; the results provide a comprehensive view of interdisciplinary research in medicine, biology, finance and other fields.
The number of publications in international databases aims to disseminate and share the contributions and advances of academic research from different groups of researchers from different universities and countries in the thematic of Covid-19.
Bibliometrics [1] is a tool for mapping the state of the art in a field related to given scientific knowledge. So the use of bibliometric analysis [2] to identify and analyze the scientific performance of authors, articles, journals, institutions, countries through the analysis of keywords and the number of citations constitutes an essential element which provides researchers with the means to identify avenues and new directions in relation to a theme of scientific research.
Scientometrics [3] is considered as the science of measurement and the analysis of science which is based on an input set and an output set which uses bibliometrics in the field of study of publications. The latter is a meta-science which takes science as its object of study based on three elements of scientific activity: its inputs, its outputs and its impacts. Thus, it makes it possible to map and broaden knowledge on a research field, by clarifying the links between the authors, the publications, the institutions, and other characteristics of the studied field.
Scientific publications [4] represent all publications in newspapers or conferences, either chapters in scientific books or scientific patents. All these types of publications represent the work of a researcher who publishes these works with the aim of circulating these results in databases which have broad international visibility and scientific credibility such as Web of Science, Scopus… and renowned publishing houses such as Elsevier, Springer, Wiley, etc.; but with all the efforts made, the benefits that can be drawn remain limited if we cannot manage this large mass of publication which is added every day to the thousands or millions of existing scientific papers.
Bibliometric data is used for:
• Measure and compare the scientific output of the researcher, research groups, institutions, regions or countries using indicators based on: -The number of publications.
-The quotes received.
-The collaborations.
• Identify the most important or influential journals in a given field.
• Monitor the evolution over time of a discipline or research subject.
These data represent the main part of the data provided for each paper by the databases which allow bibliometrics to carry out statistical processing, and bibliometric analysis.
According to statistics provided by Johns Hopkins University [5] until May 23, 2020, the death of more than 339,949 people worldwide, was the infection of 5,267,452, considerable efforts were made in the various disciplines relating to the treatment of this pandemic either from near or far.
Since the beginning of the year, Covid-19 represents an increasing interest for researchers from all over the world, in response to this crisis, a lot of research was carried out in many fields of research (medical, biology, financial, ...) by several Institutions and organizations, either public or private worldwide, each with their own means available.
By reviewing most of the scientific databases, the search to identify the scientific output related to the subject of Covid-19 [6] was carried out using a set of terms as search criteria, the language of the documents is the English because it is the universal language of research, all disciplines are authorized in order to provide a global view of Covid-19 research in the various disciplines, research is limited to the period from early 2020 (Beginning of the pandemic a been listed) so far.
Using the Scopus search engine to search for the word "covid-19" and "coronavirus" from 01/01/2020 until 23/05/2020, we find 10,228 documents: -According to the authors: Using the search engine of Web of Science to search for the word "covid-19" and "coronavirus" from 01/01/2020 until 23/05/2020 results in 5,161 documents: -According to the authors: -According to the country:
Scopus: Africa:
The exploitation of the bibliometric parameters available on the scientific data base on multiple field and discipline makes it possible to release relevant information which can meet the expectations of researchers, research teams and research institutes. The bibliometric analysis reveals to the researcher exact information for the construction of new research as in the case of our study on Covid-19.
This study was carried out on the basis of specific research using the three databases (Scopus, Web of Science, Pubmed) from the beginning of 2020 until 23/05/2020. The sample consists of 5,161 academic publications (Web of Science), 10,228 academic publications (Scopus) and 7,991 academic publications (Pubmed). The use of bibliometrics will contribute to the exploration and description of the existing scientific literature on the theme of Covid-19.
The steps taken to achieve the desired results are manifested as: The use of bibliometric tools plays an important role in guiding a particular field of study by collecting scientific data and synthesizing the results obtained.
Statistics from different bibliographic databases which differ either in terms of data volume or coverage constitutes a reliable source for bibliometric indicators [9] .
Choosing the right database, the right keywords and applying the filters that reflect the research objectives is a crucial step to have reliable results.
Among the credible scientific database which brings together most of the publishing houses known as Elsevier, Taylor & Francis, Springer…, we find Scopus, web of Science and for the medical field Pubmed [10] equipped with different filters to refine the search and limit the results found.
Some researches try to analyze data coming from the various scientific databases, but there are structural differences between the platforms. Thus the differences in the classification of information adopted by each of them builds an obstacle for an exploitation of the common data.
For a good bibliometric analysis, we choose the following bibliometric data:
-Article title.
-Authors.
-Keywords.
-Number of citations.
-Year of publication.
-Journals.
-Type of documents.
-Institution.
-Country.
-Field of research.
Regarding the indicators used by Scopus we find:
-H-index [11] : is based on the highest number of articles with at least the same number of citations.
-CiteScore: measures the average number of citations received per document published in the serial publication.
-SJR: measures the weighted citations received by the periodical, the weighting of the citations depends on the domain and the prestige of the citing series.
-SNIP: the standardized paper impact of the source which measures the actual citations received compared to the expected citations for the field of serial publication.
Regarding the indicators used by Web of Science we find:
-H-Index: the most used research indicator that measures both the productivity and the impact of an author's scientific production.
-The impact factor: measures the importance of a review according to the number of citations received in a year.
-Journal Citation Reports: Web of science product and an authoritative resource for impact factor data.
In the present case study, the keywords employed are "Covid-19" / "Coronavirus" from the beginning of 2020 (date of the start of the pandemic). The search should focus mainly on the titles, keywords and abstracts of articles in each of the databases. Then the results found for each of the three databases (Scopus, Web of science, Pubmed) builds our separate database on which our bibliometric analysis will be applied. We export the data from Scopus in format (.csv), Web of science, Pubmed in format (.txt).
Next, we use the VOSviewer software [12] which represents a high-performance solution with numerous viewing options with co-quotation, co-word, co-author network analysis.
Through bibliometric analyzes we try to get the trends of scientific research in the theme of Covid-19.
In order to observe and evaluate the trends in publications in the thematic of Covid-19, the VOSviewer software was used to analyze the academic literature and examine the evolution of published articles, co-authorship, geographic area (country) of authors, co-citation, co-occurrence.
The analysis of the authors belonging to the database allows to have a global view on the authors active in the thematic by offering the possibility to follow the work of these researchers by opening the door to achieve cooperation and partnerships.
Thus, the analyzes of research institutions and countries constitute an effective asset for finding the pillar institutions in each field, with the aim of seeking possible cooperation at the level of research institutions.
The software used for viewing and mapping the structure of a research are including Bibexcel, Histcite, Citespace, Gephi, and VOSviewer. For this work, we chose to work with VOSviewer because it allows us to easily display and interpret the display of large bibliometric maps.
In order to carry out the various analyzes previously cited and to examine the evolution of the articles published, we have for: We have 1 cluster which contains 12 items.
We deduce that most institutions collaborate with each other on an international scale and not at the regional or continental level.
-For countries: Figure 18 : Country organizations network in the "Network visualization" display mode.
We have 9 clusters distributed as follows:
Cluster 1-2-3: 5 items; Cluster 4-5-6: 4 items; Cluster 7-8-9: 3 items.
As we see in Figure 21 , the map indicates a large node representing China which means the great involvement of the Chinese giant through these researchers in the various research fields related to Covid-19. Bibliometric studies are used to identify networks of researchers or to map the structure of researchers in a given research area. Figure 19 : Author co-authorship network in the "Network visualization" display mode.
We have 9 clusters distributed as follows:
Cluster 1:46 items; Cluster2: 46 items; Cluster3: 20 items; Cluster 4:16 items;
Cluster 5:15 items; Cluster 6:11 items; Cluster 7: 11 items; Cluster 8: 10 items; Cluster 9: 10 items.
The results clearly show that there are 9 groups of researchers who collaborate. Two groups have a significant number of researchers despite an exponential increase in the number of publications since the start of the pandemic, international collaboration between the authors remains low. From the results found, it can be deduced that geographic proximity between institutions tends to strengthen the collaborative relationships of institutions. Thus, it warns of the need to expand cooperation in other regions, countries or continents.
-For countries:
The analysis of the network of countries is an important form of analysis which makes it possible to visualize the most influential countries in a given field of research, thus it exposes the degree of scientific cooperation between the countries. We have 11 clusters distributed as follows:
Cluster 1: 7 items; Cluster 2-3: 6 items; Cluster 4: 5 items; Cluster 5: 4 items;
Cluster 6-7-8: 3 items; Cluster 9-10-11: 2 items.
As we can see in Figure 18 , the map shows a large node representing the countries and regions with the highest number of publications: China, United States, Italy, England, France and Spain.
Pubmed: -For authors: Figure 22 : Author co-authorship network in the "Network visualization" display mode.
We have 6 clusters distributed as follows:
Cluster 1:27 items; Cluster 2-3-4: 15 items; Cluster 5: 7 items; Cluster 6: 4 items.
The results clearly show that there are 6 groups of researchers who collaborate with each other, a group has a large number of researchers, followed by a group that is distinguished by the number of researchers who compose them.
-For institutions: Figure 23 : Author organizations network in the "Network visualization" display mode.
In 1 cluster with 13 items, we notice that there is a significant presence of Italian medical institutions, the analysis of data from Pubmed by VOSviewer does not offer the possibility of analyzing the network of countries.
VOSviewer: Figure 24 : Author keywords network in the "Network visualization" display mode.
We have 3 clusters distributed as follows:
Cluster 1: 6 items; cluster 2-3: 4 items.
The results found build a map dividing the keywords into three groups with the minimum number of occurrences of a keyword fixed at 6 elements for the first group and 4 elements for the second and third group. The keyword "Coronavirus" has the highest occurrence and total binding strength, other keywords with a high occurrence include "Sars-cov-2", "Covid-19".
Among the existing display means, there is the word cloud which is a practical tool allowing to have a dimensional visualization of the keywords most used in the database. For our case, we use wordle which is an analysis tool which makes it possible to display a word cloud which gives greater importance to the words which appear more frequently in the source text, for the three scientific databases already mentioned, we find: -Scopus: From the figures (24-25-26-27) provided by VOSviewer and Wordle, a set of words related to the pandemic such as (Covid-19, Coronavirus, Sars-cov-2, 2019-ncon) as synonyms used in scientific literature, so the appearance of terms (China, Wuhan, USA) refers to the place of appearance of the pandemic and the countries that are conducting research to find the vaccine, too (Medical, Health, Hospital, virology) refers to the most concerned research area, (Zhang, Wang) for the most productive researchers in the topic of Covid-19 in scientific databases.
Since the onset of the pandemic, considerable effort has been invested by researchers worldwide depending on the fields and resources available, an exponential increase in scientific production has been recorded in the various databases around the Covid-19.
In this work, we opted for a statistical study for the data from the bibliographic databases Scopus, Web of Science for the theme of Covid-19. The scientific contribution of researchers from the USA and China shows a total involvement of institutions from these two countries, so for the African continent researchers from "South Africa and Egypt are the exception, while for the Arab region Saudi Arabia and Egypt are leading the efforts of the Arab countries for this pandemic.
Afterwards, a bibliometric analysis method was adopted in order to map the state of the art on the theme of Covid-19, so the three scientific databases (Scopus, Web of Science, Pubmed) were used. Thus, the search must be precise and planned by combining the precision of the terms to be used and adequate filters to refine the results found, in order to conduct a relevant bibliometric analysis by analyzing the contributions of the authors, institutions, countries and the wordskeys.
Finally, it is well known that the method presented remains applicable for other scientific themes and not only for the Covid-19 theme, it should be noted that the results obtained with the application of the proposed method may vary depending on the basis of scientific data chosen and the appropriate filters in order to present the evolution of published articles, co-authors, geographic area of the authors, co-citation, co-occurrence analysis and keywords.
We wish to draw the attention of the Editor to the following facts which may be considered as potential conflicts of interest and to significant financial contributions to this work.
[OR] We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome. We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us. We confirm that we have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. In so doing we confirm that we have followed the regulations of our institutions concerning intellectual property.
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Our understanding of the epidemiology of the severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) infection and associated COVID-19 illness continues to evolve. Statistics from early in the pandemic indicate that ~1 in 5 infected individuals are hospitalized, and 1 in 10 may be admitted to an intensive care unit (ICU), with most of these critically ill patients experiencing acute respiratory distress syndrome (ARDS) and requiring mechanical ventilation 1 . Although most individuals infected with SARS-CoV-2 seem to be asymptomatic or experience mild symptoms (such as persistent cough, with chest pain and chest tightness), the pandemic has resulted in an unprecedented spike in the incidence of ARDS and critical illness. The success of critical care medicine in reducing mortality will result in a large number of survivors of COVID-19. Up to 80% of patients surviving acute respiratory failure after receiving mechanical ventilation in the ICU experience new or worsened physical, cognitive and/or mental health impairments that persist beyond hospital discharge, collectively known as the post-intensive care syndrome 2 . Although old age, pre-existing physical frailty, psychological symptoms (for example, anxiety and depression) and cognitive impairment (for example, dementia) are risk factors, even those without such risk factors are at risk for long-lasting sequelae. Optimizing the COVID-19 survivorship experience, based on this knowledge, demands careful implementation of evidence-based critical care interventions combined with robust rehabilitation programmes that begin in the ICU and continue after discharge.
Critical illness and its treatments have important, sometimes under-recognized, effects on the neuromuscular system. Physical impairments after critical illness can last for months or years and commonly include joint contractures and substantial muscle wasting and weakness, with associated limitations in physical functioning 3 . Severe respiratory failure occurring with COVID-19 may require long durations of mechanical ventilation, deep sedation, neuromuscular blockade and the associated immobility, which increase the risk of physical impairments. In the setting of COVID-19, virus-related or medication-related (for example, hydroxychloroquine) myopathy can occur, along with other critical illness-associated polyneuropathy or myopathy. Additionally, patients may be repeatedly moved between supine and prone positions with potential shoulder subluxation and brachial plexus injury, leading to upper extremity sequelae. Moreover, prolonged mechanical ventilation may result in diaphragm dysfunction, along with laryngeal injury, dysphagia and dysphonia from prolonged endotracheal tube intubation that may be under-recognized without systematic screening and assessment 4 .
New or worsening cognitive impairment commonly occurs and persists in survivors of ICU stay. For instance, at 1 year after hospitalization, one-third of survivors of acute respiratory failure or shock experience cognitive impairment, with neuropsychological test scores consistent with moderate traumatic brain injury 5 . Such cognitive sequelae usually manifest as impairments in memory, attention and executive function, with survivors reporting inability to manage medications and finances and difficulty with reading comprehension and following conversations with friends and family. Patients with COVID-19 and severe respiratory failure with deep sedation often have prolonged delirium; the duration of delirium in the ICU is an important risk factor for cognitive impairment 5 . Moreover, owing to infection control precautions, family are frequently prohibited from visiting the hospital and health-care staff may reduce their time spent in direct contact with patients. This reduction in human interactions causes a 'domino effect' of reduced cognitive stimulation, reorientation and reassurance to patients. In some hospitals, such infection control precautions may also reduce access to essential rehabilitation services and spiritual care. These effects of the COVID-19 pandemic exacerbate patients' delirium and are expected to increase the risk for long-term cognitive impairment.
Survivors of ICU stay commonly experience long-lasting mental health impairments. Clinically significant symptoms of anxiety, depression and post-traumatic stress disorder (PTSD) may occur in one-quarter to one-third of survivors and persist for up to 5 years, with half of survivors reporting prolonged symptoms in at least one of these categories 6 . Although pre-existing psychological symptoms are associated with new or worsened post-ICU mental health morbidity, the severity of the critical illness is generally not associated with psychological outcomes. These findings suggest a need to screen all survivors for mental health impairments. COVID-19-related changes in the hospital environment may pose an increased risk of negative psychological symptoms. For instance, reduced access to family members, pleasurable activities and rehabilitation may result in anxiety and demoralization in patients. Contact isolation has been associated with increased symptoms of depression and anxiety, as well as fear and hostility towards medical providers. Literature from prior outbreaks (for example, influenza A subtype H1N1 virus and Ebola virus) may provide insights for the current pandemic. Notably, survivors from the 2002-2003 SARS epidemic 7 reported stressors that are also relevant to the COVID-19 pandemic, including constant media coverage emphasizing high death rates, stigma due to community or family members blaming survivors for the spread of illness, the fear of infecting loved ones, death of close family members and survivor's guilt. Such stressors may have important implications for psychological outcomes in survivors of COVID-19.
The interplay of physical, cognitive and mental health impairments can lead to important functional problems, such as persistent fatigue, chronic pain and sleep dysfunction, and reduced health-related quality of life 8 . Moreover, globally, at 1-year follow-up, one-third of previously employed survivors of ICU stay are jobless 9 . The financial burden of job loss is worsened by direct or indirect health-care costs and lost income of patients' caregivers. Furthermore, patients' loved ones are at risk of new and persistent mental health impairments, a phenomenon known as post-intensive care syndrome-family 2 . Many of these sequelae may be modifiable with adequate access to rehabilitation that promotes both engagement with health-care teams and self-management of symptoms.
To optimize both survival and survivorship of critically ill patients with COVID-19, meticulous attention to delivering evidence-based critical care interventions is required, as well as early and sustained comprehensive rehabilitation that targets physical and neuropsychological recovery along with adequate social support. Optimal critical care interventions include evidence-based management of ARDS (for example, lung-protective mechanical ventilation and prone positioning) and consistent implementation of guideline-recommended strategies for assessing and managing pain, sedation, delirium, immobility and sleep. Although current literature about early rehabilitation is not definitive, we believe it is important in patients' recovery (see the Society of Critical Care Medicine PADIS guidelines). A comprehensive approach to rehabilitation begins early during critical illness. As soon as patients have achieved cardiopulmonary stability and meet established safety criteria, physical rehabilitation interventions can begin, even while patients are receiving mechanical ventilation and other life-support therapies. Comprehensive rehabilitation services include physical and occupational therapists, speech language pathologists, psychologists and physiatrists. Benefits of early and intensive rehabilitation include reduced muscle weakness and duration of mechanical ventilation, with potential for reduced delirium and improved cognitive function. Moreover, participation in rehabilitation may enhance patients' mental health by providing a sense of normalcy and control over their recovery. Rehabilitation initiated in the ICU should continue throughout hospitalization and after discharge, via multi-disciplinary out-patient care, home health services and peer support groups 10 . During COVID-19, telehealth is an important adaptation for delivering these post-discharge assessments and interventions.
COVID-19 as a catalyst for collaboration Multi-disciplinary critical care can prevent imminent death while also setting vital foundations for improving patients' overall long-term survivorship experience. Awareness of the post-intensive care syndrome is important for patients treated in the ICU and their families, as well as for all members of the health-care team. With an unprecedented incidence of severe critical illness during the COVID-19 pandemic, we must apply knowledge gained from over two decades of critical care survivorship research to improve implementation of evidence-based practices for in-ICU care, and provide access to comprehensive rehabilitation across the care continuum to help survivors of COVID-19 attain full and meaningful lives.
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Introduction Q5 The ease of transmission of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), the virus which causes COVID-19, has been a key factor driving the current pandemic. With a reproductive rate between 2 and 3 [1] , low case numbers can exponentially rise without proper infection prevention and public health interventions in place. In parallel to public health responses, health services have had to swiftly implement internal strategies to maintain their workforce. One of these key strategies is rapid and effective contact tracing within the healthcare workplace. The World Health Organisation (WHO) defines contact tracing as "the process of identifying, assessing, and managing people who have been exposed to a disease to prevent onward transmission" [2] . In the context of COVID-19, this involves identifying index cases, establishing close contacts of the confirmed case and isolating them, with or without initial testing as appropriate. Predictive modelling has shown that contact tracing and case isolation is an effective way to contain COVID-19 outbreaks and prevent transmission [3, 4] . As a vaccine is at least months away from being widely available, reducing the spread of COVID-19 is our only option to prevent mass hospitalisations and unnecessary deaths.
In Australia, contact tracing is the responsibility of the relevant state or territory public health department which, in the state of Victoria, is the Department of Health and Human Services (DHHS). However, the DHHS has outlined the expectation that local health services initiate their own contact tracing should they have a confirmed case involving a patient or healthcare worker (HCW) within their health service [5] . In the 2003 SARS CoV-1 epidemic, a significant proportion of cases were amongst HCWs, demonstrating that this group, and therefore hospitals, are susceptible to outbreaks [6e8]. Similarly, early evidence suggests that HCWs are at an increased risk of becoming infected with COVID-19 [9] . Given that HCWs can come into contact with hundreds of vulnerable patients each day, it is vital that contact tracing is completed in a timely manner to prevent the possibility of 'super-spreading' events. Despite this need, clear policies for large hospitals to enact in order to achieve this goal are lacking.
Here we describe the approach taken by Monash Health for contact tracing during the COVID-19 pandemic, in order that other centres may contrast their approach and outcomes.
Monash Health is the largest healthcare provider in the Australian state of Victoria, with more than 40 sites and 16,000 employees. It provides care to the south-eastern suburbs of Melbourne, a city of five million, with more than 250,000 admissions annually. In response to the COVID-19 pandemic, Monash Health implemented a strategy to establish rapid contact tracing for confirmed cases within the service.
This strategy consists of four steps completed within defined timeframes as outlined in Fig. 1 . The intended benefit of this approach was to allow for rapid escalation and implementation of contact tracing once a positive COVID-19 case was identified. This approach was developed and led by the Hospital Incident Command Team (HICT) overseeing the COVID-19 response within Monash Health.
Step One: notify 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 infectious and the likelihood of transmission in the workplace, and briefs the executive team comprising the Chief Executive (CE) and Chief Operating Officer (COO).
Step One is completed within one hour of the confirmed COVID-19 case. This rapid notification is intended to ensure that the issue is escalated to the highest level so that a co-ordinated contact tracing process can commence.
Step two: build the team To implement and monitor the contact tracing process, an Outbreak Management Team (OMT) is created, with clearly defined roles as outlined in Table 1 . Once notification has been received, the CE and COO activate the OMT and an Infection Prevention Consultant (IPC) is allocated to drive the contact tracing process. Having this team structure ensures that there are no delays to commencing contact tracing and isolating individuals. It also reduces any lack of role clarity regarding individual responsibilities during the process.
During the contract tracing, the OMT meets numerous times via video conference to monitor and support the contact tracing process. Other relevant staff members are invited as necessary. Each OMT meeting covers a specific agenda, as outlined in Table 2 . The use of a consistent agenda provides a formal structure to each meeting, ensuring that all implications of a positive COVID-19 case are managed, limiting unintended consequences such as HCW shortages. Frequent meetings over a short time period also provide an easy way to track the progress of contact tracing and provide any additional support as required.
Step Three: trace Predictive modelling has shown that any delays in contact tracing can significantly reduce its effectiveness [10] . In recognition of this, Step Three commences simultaneously with Step One. This process is led by Infection Prevention, a multidisciplinary unit tasked with preventing nosocomial infections. First, a comprehensive phone interview is conducted with the index case to determine where and how the virus was acquired, time of symptom onset, and identify any potential close contacts. A contact tracing team (CTT) is then formed, with the assistance of the Operational Lead (see Table 1 ), to notify relevant managers and compile a list of potential contacts through employee and patient lists. The CTT proceeds to call each potential contact to determine exposure risk, based on amount of contact, the environment in which the potential exposure occurred, PPE use, and whether the employee works at multiple sites or across different wards. Using this 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 information, contacts can be stratified using a risk matrix (Table 3) to determine the need for 14-day quarantine and/ or testing. This risk matrix is able to be adjusted for an individual situation and ensures consistent guidance for the CTT. To update the HCW team impacted upon by the case and provide support, a forum for team members via video conference is also organised. As contacts are identified and placed in isolation or quarantine, the Operational Lead assesses how this will impact on service delivery. If a large number of employees need to be furloughed, a Contingency Workforce Plan is activated to ensure services can be provided as close to normal levels as possible. While Step 3 is underway, it is vital that Infection Prevention and the Operational Leads meet regularly to ensure that it is progressing at an appropriate speed. This can be achieved through regular team 'huddles' via video or phone conference. It is critical that this step is completed within three to 24 h of the confirmed COVID-19 case so that employees can be furloughed before onward transmission.
Step four: communicate transparently Once close contacts are identified and in isolation, it is imperative that they are followed-up daily to monitor for any symptoms of COVID-19 infection as well as their general health and wellbeing. This responsibility is initially given to Infection Prevention to communicate the need for isolation. Thereafter this is handed over to the People and Culture (Human Resources) team who provide daily welfare checks, help with accommodation needs, and provide reminders for testing on day 11. If a large number of staff have been furloughed, the Operational Lead will implement the Contingency Workforce Plan to ensure continuity of health service delivery. The DHHS and HICT are also updated.
During this step, it is important that communication with employees is open and transparent. This is achieved through a series of strategies. Organisation-wide emails, and regular 'huddles' lead by managers, take place daily or on alternate days. Weekly staff fora are held that allow frank and open communication between those directly affected by the contact tracing process and leadership including the CE and COO. Additional communications strategies include a dedicated COVID-19 website allowing around the clock access to the latest information such as PPE tier requirements, and regular updates from the CE. When an outbreak occurs, the CE uses these updates to inform all employees of data including the number of positive COVID-19 patients, HCW cases, and employees on furlough. This transparency is intended to build trust, allow for questions to be answered to reduce knowledge asymmetry, and maintain a sense of belonging.
A review of every HCW infection is also undertaken. This is aimed to establish processes that need refining and lessons learnt are then communicated to both the OMT and 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 wider health service community, so that an ongoing infection prevention strategy is maintained.
This report covers the period between June and September 2020, during the second wave of the pandemic in Melbourne, Victoria. At this time case numbers escalated to a peak of over 600 cases a day, compulsory mask wearing was in place and community lockdown was at stage 4 for a prolonged period. In this time, forty-one OMTs occurred, involving 23 HCW and 18 patient index cases. The total furloughed HCWs arising from these contact traces was 383, with individual contact traces furloughing a mean (range) of 10 (0e80) HCWs. Importantly, 15 furloughed HCWs subsequently became COVID positive during their 14-day isolation period, showing the importance of the contact tracing process and the ability to remove workers from the workplace before they become infectious. No ongoing transmission has been identified from any outbreak once an OMT has been put in place.
Since implementing the contact tracing process outlined here in June 2020, we have been able to evaluate risk and follow the identify, trace and isolate algorithm in a timely, open and transparent manner in every case. The development of an OMT with dedicated roles and structured meeting agenda items ensures any impacts of COVID-19 positive cases are consistently managed. This response framework may be of use to other health services and help reduce the transmission of COVID-19 in the workplace.
Ethics approval not required.
Rhonda Stuart contributed to the concept, analysis, methodology, supervision, writing, reviewing and editing. Wendy Zhu contributed to the methodology writing, reviewing and editing.
Eric Morand contributed to the supervision, reviewing and editing.
Andrew Stripp contributed to the concept, methodology, supervision, reviewing and editing. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61
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The theory of five circuits and six qi (FCSQ; five circuits refers to wood, fire, earth, metal, and water; six qi indicate wind, cold, summer heat, dampness, dryness, fire) is an essential part of traditional Chinese medicine (TCM). The theory represents a holistic view held by early doctors based on the correspondence between heaven and humankind. It is a doctrine for understanding the laws of nature and climate change, as well as their impact on human diseases. FCSQ theory, which is based on the theory of yin and yang and uses symbols such as "heaven" and "earth" as deductive tools, has been passed down from the era of Yellow Emperor's Canon of Medicine. Using current meteorological data and data on the incidence of diseases, scholars have conducted a series of studies to evaluate the correlations between FCSQ and climate change, occurrence of diseases, and TCM patterns. 1À4 These studies have found varying levels of correlation between the complete meteorological data, based on continuous modern meteorological observations, and the climate mode deduced from FCSQ. Furthermore, a relationship between FCSQ and common diseases has been found in some internal medicine and TCM patterns. All of this previous work has objectively proven that FCSQ exerts an influence on human life activities and provided a basis for using FCSQ theory to treat diseases in TCM clinical practice. Unique effects were observed for TCM treatments guided by FCSQ theory for epidemic cerebrospinal meningitis in North China in the 1950s and severe acute respiratory syndrome in China in 2003. 5 In recent years, a number of studies on FCSQ have been published.
Nevertheless, the clinical value of FCSQ theory is very controversial in the field of TCM, and doubts have existed since the theory's emergence. Some medical doctors have explicitly opposed FCSQ theory. For example, in the Ming Dynasty, Xiyong Miu wrote a chapter entitled "On the falseness of FCSQ" in his book, Commentary on Shen Nong's Classic of the Materia Medica. He believed that what was called FCSQ theory by later generations was not beneficial for treatment, because there was no mention of FCSQ recorded in the books written by Zhongjing Zhang, Tuo Hua, Shuhe Wang, and others. Xiyong Miu therefore denied the significance of FCSQ theory in TCM. During the Republic of China era (1911e1949), two important controversies regarding FCSQ occurred in the field of TCM, and stances denying or proposing the abolishment of FCSQ theory were predominant. Yuanlei Lu, one of the representatives of this view, published an article entitled "Overthrowing FCSQ fundamentally" in 1934 to express the idea that there is no reason for FCSQ theory to exist. 6 Currently, the body of work on FCSQ is increasing, but applications of the theory have not been given much importance in mainstream TCM clinical practice. Is FCSQ theory beneficial for improving the effectiveness of treatments? To answer this question, it is insufficient to rely on traditional literature reviews, theoretical derivations, or medical reports. Therefore, to provide evidence-based medical evidence on this controversial issue in the field of TCM, we systematically collected and evaluated randomized controlled trials (RCTs) that examined FCSQ theory in the treatment of diseases.
The databases searched included China Network Knowledge Infrastructure (CNKI), Chinese Scientific Journals Database, Wanfang Data, SinoMed, Cochrane Library, PubMed, and Embase, which were queried from their inception to June 12, 2018. The search terms were "yunqi" (circuit and qi), "wuyun" (five circuits), "liuqi" (six qi), "keqi" (guest qi), "zhuqi" (dominant qi), "sitian" (celestial control), "zaiquan" (terrestrial effect), "suiyun" (circuit of year, that's the characteristics of one circuit in the whole year), "suiji" (random), and "zhongyi" (TCM). These terms were selected as MeSH terms, free words, or keywords in combinations for comprehensive retrieval based on different characteristics of the selected databases. For example, in CNKI, a Chineselanguage database, we retrieved records with "yunqi," "wuyun," "liuqi," "zhuqi," "keqi," "sitian," "zaiquan," or "suiyun" in the title field in addition to "suiji" and "zhongyi" in the full text. In the PubMed database, the search string was "(( (((((five yun and
The inclusion criteria were as follows: (i) study design type: randomized controlled trials aimed at evaluating the clinical effectiveness of FCSQ; (ii) study subject: any disease type; (iii) intervention: experimental group receiving TCM treatments guided by FCSQ theory, including traditional Chinese herbal medicine, acupuncture and moxibustion, and tuina massage and control group receiving conventional TCM treatments without FCSQ, biomedicine, or placebo; and (iv) outcomes: because of the varying disease types covered, we selected primary outcomes such as effectiveness rate for evaluating the improvement of symptoms, signs, and laboratory tests, as well as mentions of adverse reactions.
Exclusion criteria included the following aspects: (i) duplicate publications (only the original publication was included); (ii) publications including only "yunqi" (circuit and qi) in intervention measures (e.g., the Wenzhen Yunqi Formula), without including or reflecting on FCSQ thought; and (iii) publications of abstracts only that did not provide the details of the research design or access to the full-text report of the study.
For the methodological quality evaluation, we adopted the Cochrane Collaboration's tool for assessing risk of bias. 7 The items included random sequence generation, allocation concealment, blinding of participants and personnel, and blinding of outcome assessment, as well as incomplete outcome data, selective reporting, and other biases. The possible evaluations for each item were applicable, nonapplicable, and unclear, corresponding to low, high, and unclear risks of bias, respectively. Two investigators (YH and JS) assessed the quality of each study independently and cross-checked their assessments. In case of disagreement, the evaluation was determined through discussion or submission to a third researcher (JH).
After discussion, we designed the data extraction form. The data were extracted independently by two authors. The extracted contents included titles, characteristics of the research methods, basic information on the subjects, interventions applied in the treatment and control groups, courses of treatment, consideration of FCSQ in the intervention for the treatment group, outcomes, and adverse events.
The data analysis included an analysis of the consideration of FCSQ in the treatment and a statistical analysis of outcomes. For the analysis of FCSQ being considered in the treatment, descriptive methods were used. For the statistical analysis of outcomes, RevMan 5.3.5 analysis software, provided by the Cochrane Collaboration, was adopted to quantify the primary outcomes. For measurement data, weighted mean differences are expressed. For enumeration data, relative risks and their 95% confidence intervals are presented. When two or more studies had good clinical homogeneity in terms of researched diseases, intervention measures, and outcomes, we planned to conduct a pooled meta-analysis, applying the corresponding model based on the results of the heterogeneity test. Where possible, subgroup analyses were performed according to the different modes of FCSQ application and the type of control measures. If not, only the effect sizes (expressed as relative risks or mean differences with 95% confidence intervals) of the individual studies are described.
After searching the above-mentioned databases, 143 articles were obtained. Of these articles, 130 were removed because of duplication, irrelevance, or failure to meet the inclusion criteria. The remaining articles included 13 RCTs, which were included for further analysis. All studies were conducted in China and published in Chinese (Fig. 1) .
A total of 13 RCTs 8À20 involving 4695 patients were included in the analysis. In these studies, 12 categories of diseases/ patterns were mentioned, including cough, 8 rheumatoid arthritis, 9 post-menstruation deficiency, 10 psoriasis, 11, 12 peptic ulcer, 13 hypertension, 14 hand-foot-and-mouth disease, 15 menopausal insomnia, 16 dizziness, 17 externally contracted cough, 18 insomnia after stroke, 19 and chronic fatigue syndrome. 20 The average sample size in these studies was 361, with a maximum of 3666 and a minimum of 60 subjects. The longest course of treatment was 1 year, and the shortest was 5 days. Outcomes reported in these studies included symptom scores, laboratory test indicators, morbidity, and recurrence rate. Symptom scores were the primary outcome of 11 studies. Seven articles reported the occurrence of adverse reactions. 8,9,12,14,16À18 With regard to interventions in the treatment group, 10 studies used oral administration of traditional Chinese herbal medicine 8À12,14À18 (combined with the regular biomedicine or external treatment in four for these studies), and the other three studies used acupuncture therapy, 19 tuina massage, 20 or acupoint application therapy. 13 The interventions using FCSQ theory can be divided into three categories: TCM prescriptions or external therapy devised by the researchers based on the theory of FCSQ, 8À13,19,20 the use of an FCSQ formula taken directly from the work of early medical doctors, 14, 15 and formulas conforming to the "heavenly stems and earthly branches" from Sanyin Sitian Fang, an FCSQ monograph written by Wuze Chen in the Northern Song Dynasty (960e1127 AD). 16À18 As for the control group, in six studies, control subjects were treated with conventional biomedicine, 9, 10, 12, 14, 16, 18 and three studies 13 Figure 1 Selection of randomized controlled trial studies on the five circuits and six qi. Effectiveness evaluation of five circuits and six qi external treatments to compare the effectiveness between external treatments under the guidance of FCSQ with external treatments that were not guided by FCSQ. Chinese patent medicine, 8 prescription based on conventional pattern identification and treatment, 11 and diet therapy 15 were each applied as the control treatment in one study, and an external treatment combined with Chinese patent medicine was the control treatment in one study. 17 The basic characteristics of each study are shown in Table 1 .
The FCSQ thought included and the basis for FCSQ as an intervention in the treatment group are displayed in Table 2 . reported the study dropout rate, but they did not analyze these subjects' data. We cannot judge whether there was selective reporting bias because there was no clinical protocol registration in the examined studies. With regard to other research biases, seven studies 9,13,15À17,19,20 reported receiving funding for related projects. All of the included studies reported consistent baseline data for the treatment and control groups. None of the studies reported the method of sample size calculation. The methodological quality of the included RCTs is displayed in Fig. 2 .
Of the 13 included studies, the disease types, intervention measures, and outcomes of 10 varied. Although the disease type (i.e., insomnia) was the same in two RCTs, the interventions were different, and there was significant heterogeneity. Pooling the studies into a meta-analysis was therefore not possible, and only estimates of effects from single study are described. Our results showed that all of the included studies reported that the effectiveness of the FCSQ treatment was superior to the control treatment (Table 3 ).
Four RCTs 8, 9, 12, 16 reported specific adverse reactions. Loose stools occurred among children receiving an FCSQ-formula treatment for cough 8 ; nausea and loss of appetite occurred among those treated with methotrexate for rheumatoid arthritis 9 ; and skin or mucous dryness, desquamation, and itching occurred among those treated with traditional Chinese herbal medicine for psoriasis vulgaris. 12 Mild diarrhea occurred in the menopausal insomnia treatment group, whereas drowsiness, dizziness, headache, and diarrhea occurred in the control group. 16 Three RCTs reported that there were no adverse reactions, 14, 17, 18 and the remaining six RCTs 10, 11, 13, 15, 19, 20 did not report on adverse events.
In this study, 13 RCTs evaluating the safety and effectiveness of applying FCSQ theory to treat diseases were systematically reviewed. The effectiveness of TCM treatments in the FCSQ treatment groups was higher, compared with the effectiveness of either conventional TCM treatments without guidance from FCSQ theory or Western medicine treatments, and these differences were significant. However, because of the low methodological quality of the included studies and inability to rule out publication bias, we cannot definitively conclude that FCSQ theory improves the effectiveness of TCM. The results in our study are similar to those of a 2014 narrative review by Liu et al, 21 which evaluated four RCTs and two case reports that used FCSQ theory. This previous review pointed out that there have been few evaluations of the effectiveness of applications of FCSQ theory in clinical trials, that the research quality has been low, that there has been obvious publication bias in case reports, and that the demonstration of causal relationships has been weak; therefore, a precise conclusion on FCSQ treatment could not be drawn. In contrast to this previous article, we adopted the Cochrane Collaboration's tool for assessing risk of bias and included all published RCTs on the evaluation of the clinical effectiveness of FCSQ, thus avoiding selection bias in our literature search. Additionally, we summarized the ways in which FCSQ theory has been applied in existing clinical research. We found that the methodological quality of relevant studies published in recent years had not significantly improved, compared with earlier work. Two types of methodological problems were common in the included RCTs. The first type includes common problems in TCM clinical research. 22e24 For example, the examined studies do not design, perform, or report on research in accordance with international standards on clinical research; the details of the random allocation are inappropriately concealed (or may even not be reported at all); there is a lack of information on the sample size calculation; the studies do not report on study dropouts or provide intention-to-treat analyses of their data; evaluations of subjective outcomes are performed without blinding; and there is no clinical trial registration, resulting in an inability to judge publication bias, selective reporting bias, and other biases. The other type of problem is specific to the formulation of control treatments and FCSQinformed interventions. First, the main FCSQ-specific problem is the unreasonable design of control treatments. Western medicine alone has been used in the control group in many studies, without including a group receiving conventional TCM treatment without FCSQ as a control. In this case, even if the effectiveness of the FCSQ treatment is higher than that of the treatment in the control group, we can only reach the conclusion that the effectiveness of TCM is better than that of Western medicine; with this study design, it is impossible to prove whether or not the observed effectiveness is the result of guidance by FCSQ theory. Second, no reliable evidence is provided on the formulation of interventions for FCSQ treatment groups, leading to problematic performance and poor repeatability. In most studies, the FCSQ treatment interventions were based on the researchers' own experience or prescriptions devised by the researchers with consideration of the features of FCSQ. These studies have usually not reported the rules applied for herbal prescription or even defined whether their interventions were related to FCSQ theory. For instance, in a clinical trial for treating hypertension based on FCSQ theory, 14 the Wumei Pill from Treatise on Cold Damage was used in the FCSQ treatment group. The authors analyzed the FCSQ characteristics only in the year of the study and stated that the Wumei Pill was effective for hypertension occurring in that year; they did not clarify the evidence for formulating prescriptions based on aspects of FCSQ theory. In terms of how FCSQ theory is applied, we can conclude that applications considering the characteristics of the "heavenly stems and earthly branches" are the most common in clinical practice. The various problems that occurred in designing interventions for FCSQ treatment groups suggest that the feasibility and repeatability of FCSQ interventions should be given more attention in future clinical research to provide high-quality evidence for assessing the clinical value of FCSQ theory.
For future clinical practice and research, it remains meaningful to explore how to apply FCSQ theory to guide disease diagnosis and treatment. There is a need for highquality trials to evaluate the clinical value of FCSQ theory and answer whether TCM diagnoses and treatments based on FCSQ theory are beneficial for improving effectiveness. 26 ) , to avoid various biases and to obtain reliable outcomes. Furthermore, the particularity of FCSQ clinical research should be fully considered. First, future work should select diseases that are strongly correlated with FCSQ. Second, it is important to design a reasonable control treatmentdA conventional TCM treatment without FCSQ is usually needed as a control intervention, and, if possible, a Western medicine treatment or placebo control is desirable. Third, the determination of FCSQ interventions should have sufficient justification, good operability, and repeatability. We recommend referring to well-recognized FCSQ formulae recorded in the early FCSQ literature, such as the therapeutic principles in the "seven great chapters" on FCSQ in Yellow Emperor's Canon of Medicine and the monograph on FCSQ theory, Sanyin Sitian Fang, produced during the Northern Song Dynasty. Corresponding intervention measures should then be determined in accordance with the specific characteristics of the "heavenly stems and earthly branches" during that month and year.
In this study, we systematically evaluated the clinical value of FCSQ theory based on 13 selected RCTs, finding that positive results were reported in all of the studies. Although there are many methodological shortcomings in the current literature and the value of FCSQ theory cannot be fully affirmed, its application value in clinical practice is undeniable. The present study provides a reference for the clinical application of FCSQ theory in TCM in the future. Only by combining the characteristics of FCSQ theory in TCM, adopting appropriate clinical research methods, designing reasonable study protocols, and following international guidelines for designing and reporting clinical research can we provide more substantial evidence for the clinical application of FCSQ theory.
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The emergence of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID- 19) led to a global pandemic affecting over 38 million individuals worldwide and resulting in over 1.09 million deaths to date. Though the virus causes multi-organ sequelae, it most commonly manifests as a respiratory disease ranging in severity from a mild upper respiratory illness to severe pneumonia, acute respiratory distress syndrome (ARDS), multiorgan failure, and death. 1, 2 Due to the recent emergence of SARS-CoV-2, risk factors for contracting the illness are poorly understood. Data from the initial wave of infections in China, Europe, and the United States suggest that older individuals and those with underlying comorbidities may be at greatest risk. [1] [2] [3] [4] Included in the latter group are patients who are immunosuppressed, either as a consequence of underlying disease or pharmacologic treatment. 5, 6 Inflammatory bowel diseases, including ulcerative colitis (UC) and Crohn's disease (CD), are debilitating immune-mediated diseases affecting nearly 7 million individuals worldwide. 7 Systemic immunosuppression through use of targeted biologics or small molecules is the cornerstone of effective IBD management. 8, 9 Consequently, the interplay between immunosuppression and COVID-19 infection in patients with IBD is a pressing clinical question.
Several studies have now been published examining the impact of IBD diagnosis on outcomes after COVID-19 disease. 10, 11 These have shown that immunosuppression is not associated with worse outcomes among those with COVID-19 disease and that outcomes in patients with IBD are comparable with those without underlying IBD. However, an important challenge in extrapolating those findings concluding that immunosuppression does not influence risk of acquisition of disease is the potential for inherent bias in the studies published thus far. Because testing for the SARS-CoV-2 virus is not universal in those with suspicious symptoms, it is plausible and indeed likely that the threshold for testing is lower in those with immunosuppression since it may more directly impact interruption of such therapy. In contrast, testing may be reserved for more severe illness in those not on immunosuppression and thus not deemed high risk. This would bias away from demonstrating harm with immunosuppression. However, one can surmise that this lower threshold for testing would introduce a bias in the opposite direction in estimating risk of disease acquisition inasmuch as the higher rate of testing in an immunosuppressed population would actually bias toward demonstrating higher risk of documented infection. Thus in the absence of universal testing, complementary studies examining impact of immunosuppression on COVID-19 risk and COVID-19 outcomes are both required to accurately impact our practice. The only prior study that has attempted to evaluate risk of disease related to drug exposure used the American Veterans affairs cohort and was limited by ability to examine only thiopurine and antitumor necrosis factor (anti-TNF) exposure but not that of other biologics or combination therapy. Furthermore, it consisted predominantly of older (mean age 63 years) male patients. 12 Consequently, there is an important gap in the literature examining the effect of novel non-TNF biologics and combination therapy on risk of SARS-CoV-2 virus acquisition and COVID-19 disease.
In this study, we aimed to use data from a large, multiinstitutional cohort of patients with IBD in Massachusetts, the state with the third highest number of cases of COVID-19 infections in the United States to accomplish 4 things: (1) define the risk of documented COVID-19 disease in patients on aminosalicylates, anti-TNF, and non-TNF biologics; (2) examine the impact of combination therapy on disease risk; (3) compare risk factors in an IBD cohort that underwent testing and were confirmed negative for the SARS-CoV-2 virus to account for selection bias in testing; and (4) define the impact of immunosuppression and comorbidity on disease outcomes. Defining this risk accurately is of critical relevance to the management of IBD and other immune-mediated diseases that rely on systemic immunosuppression for disease control.
This study included patients receiving care at 2 tertiary referral hospitals in Boston, the Massachusetts General Hospital (MGH) and Brigham and Women's Hospital (BWH), and other participating hospitals within the Partners HealthCare system. Partners HealthCare is the largest health care provider in Massachusetts and provides primary, secondary, and tertiary referral care to residents of New England. The study population was identified using the Partners Research Patient Data Repository (RPDR) and active query of gastroenterologists at MGH and BWH to find cases. Use of RPDR has been described in prior publications. 13, 14 In brief, RPDR is an automatically and continually updated data repository that warehouses information obtained from any health care encounter within the Partners HealthCare system, including all inpatient and ambulatory encounters, procedures and laboratory and radiologic tests that occur in any of the affiliated hospitals.
For this study, we identified eligible patients age 18 years and older with at least 1 International Classification of Diseases 10th edition (ICD-10) code for CD (K50.x) or UC (K51.x) between January 1, 2019, and April 25, 2020. In addition, to accurately define the denominator as patients actively receiving care for IBD, we also required at least 1 prescription for any of the following: (1) oral aminosalicylate (mesalamine, balsalazide, sulfasalazine); (2) immunomodulator (azathioprine, mercaptopurine, methotrexate); (3) biologic including tumor necrosis factor-α antagonists (anti-TNF), anti-integrins (vedolizumab), anti-interleukin 12/23 agents (ustekinumab); or (4) janus kinase inhibitor (tofacitinib) during this period. This approach of combining diagnosis codes and prescriptions demonstrated good accuracy for case ascertainment in prior studies of IBD. 15
The primary study outcome was development of COVID-19, defined as a positive polymerase chain reaction (PCR) test for SARS-CoV-2 on nasopharyngeal swab. Each positive case was reviewed, and diagnosis was confirmed by an attending gastroenterologist. During the study period, there was no screening of asymptomatic patients. Only patients who met criteria for significant symptoms (fever and respiratory illness) were referred for SARS-CoV2 testing. For each case, we extracted information on whether the infection was severe, defined as COVID-19 resulting in hospitalization, intensive care unit (ICU) stay, or death. Medication use at the time of development of COVID-19 disease was also ascertained for each case.
We extracted relevant covariates from the electronic medical record: age, sex, race, and type of IBD (CD or UC). Race was defined dichotomously as white or nonwhite, with the latter including those with missing or unstated race. We identified the presence of common comorbidities that could potentially influence COVID-19 outcomes, including asthma, diabetes mellitus (DM), hypertension, and obesity, 1 through ICD-10 codes for these conditions. We obtained information on medication exposures since January 2019 pertinent to the management of IBD. Patients were placed into ordinal categories of mutually exclusive therapeutic regimens, including aminosalicylates, immunomodulators, anti-TNFs (infliximab, adalimumab, certolizumab pegol, golimumab), vedolizumab, ustekinumab, tofacitnib, or combination biologic-immunomodulator therapy ("combination therapy"). We also assessed use of corticosteroids. Patients sequentially on multiple biologics during the study period were assigned to the category of most recent exposure.
The study was approved by the institutional review board of Partners HealthCare. Continuous variables were expressed as means with standard deviations and compared using t tests, whereas categorical variables were defined using proportions and compared using χ 2 square tests (with the Fisher modification when appropriate). First, we performed univariate logistic regression identifying factors associated with acquiring COVID-19 infection. Variables significant in the univariate analysis at P < 0.15 or those that had been previously described to modify risk for or outcomes of COVID-19 were included in multivariable regression models to identify independent predictors of infection. To ensure that the findings were not due to selection bias in referral for testing, as a sensitivity analysis we compared patients with positive SARS-CoV-2 PCR with those who tested negative. We then performed an analysis restricted to cases to identify predictors of a severe COVID-19 disease. Analyses were conducted using Stata 15.2 (StataCorp, College Station, TX).
The study included a total of 5302 patients with IBD with a mean age of 46.5 years (range 18-99 years). Just under half of the cohort were men (49%), and most were white (89%). Fifty-eight percent had CD. Hypertension was the most common comorbidity (21% of the cohort), followed by diabetes (6.5%), asthma (6.5%), and obesity (6.2%). The most common immunosuppressive regimen used was TNF-antagonist monotherapy in 29.7% of the cohort. The percentage of biologic users on combination therapy ranged from 10.5% among vedolizumab users to 23.0% of TNF-antagonist users. Just over one third of the cohort (35.3%) had received a prescription for mesalamine alone. Twenty percent had received a prescription for prednisone.
A total of 39 patients (0.7%) developed COVID-19 infection. Of these, 7 resulted in severe disease (7 hospitalized, 3 ICU, 1 death). To provide context, the number of cases in Massachusetts as of May 15, 2020, was 80,497 out of an estimated population of 6.9 million (rate of infection 11 cases per 1000 individuals [1.1%]). Table 1 compares the characteristics of IBD patients who developed COVID-19 to the rest of the cohort. There was no difference in age, sex, or race between the 2 groups. There was a trend toward fewer patients with CD among the cases (44%) compared with controls (58%; P = 0.063). Among the comorbidities, obesity was much more prevalent among cases (28%) compared with controls (6%; P < 0.001), but there was no difference in prevalence of diabetes, hypertension, or asthma. Older age was not associated with higher risk of COVID-19 infection in this cohort, likely reflecting the relatively young age distribution of this population.
We observed no effect of medication exposure on the risk of COVID-19 infection in patients with IBD. The frequency of infection among those only on aminosalicylate therapy was 0.64%, which was similar to 0.5% on immunomodulators, 1% on TNF-antagonists, and 1.2% on vedolizumab monotherapy. Four infections occurred in those on combination biologicimmunomodulator therapy, whereas none were noted in those on either ustekinumab or tofacitinib alone (Fig. 1) Table 1) . Table 2 compares patients who developed severe COVID-19 with those with mild disease. Those who developed severe disease were likely to be older (mean age 65.4 years vs 41.2 years; P = 0.001) and female (P = 0.02). They were also more likely to be obese (71% vs 19%), have diabetes (29% vs 3%), have hypertension (57% vs 9%), or have asthma (29% vs 6%; P = 0.078). Interestingly, the proportion of patients on any immunosuppression was lower in those with severe disease (29%) compared with those with mild disease (78%; P = 0.010). However on multivariable analysis, only older age (P = 0.018) and obesity (P = 0.033) were associated with severe disease, and immunosuppression use was no longer statistically significant (P = 0.27).
In the 6 months since COVID-19 was declared a global pandemic, much remains unknown about risk factors for disease. Although initial data suggested immunosuppression increases risk, this was based on small numbers of patients receiving systemic chemotherapy for malignancy and immunosuppression for organ transplantation. 5, 6 Those receiving targeted therapy for autoimmune disease were insufficiently represented in these cohorts to determine risk. The absence of robust data describing the risk of COVID-19 infections in this population and a body of evidence linking IBD treatments to increased risk of serious infections [16] [17] [18] [19] [20] have introduced substantial uncertainty into the management of patients on longterm immunosuppression. In this large cohort, we reassuringly identified no excess risk of COVID-19 infection among those on various systemic and gut-targeted immunosuppressive therapies for IBD when compared with those not on immunosuppression. We also identified no effect of immunosuppression on severity of COVID-19, including need for hospitalization and mortality. In contrast, other recognized comorbidities, particularly obesity, 1 increased risk of development of COVID-19 infection and severe disease in this population, consistent with prior studies. 21 Our findings expand upon the experience described in few published case series and cohort studies of patients with IBD. Regarding risk of acquiring COVID-19, a retrospective review of IBD patients tested for COVID-19 within a northern California health system demonstrated no association between immunosuppressive medication use and odds of a positive test result, but this analysis included only 5 positive patients. 22 Similarly, a combined analysis of French and Italian cohorts revealed no increase in risk of COVID-19 in IBD patients when compared with the estimated rate in the general population. However, this study lacked a clearly defined at-risk population to estimate association with different treatments. 23 Most other published studies of COVID-19 in IBD have been case series of affected patients, attempting to define predictors of severe disease. An Italian prospective observational cohort of 79 patients with a diagnosis of IBD and COVID-19 found no association between corticosteroid (OR, 4.94; 95% CI, 0.95-25.55), thiopurine (OR, 1.21; 95% CI, 0.22-6.40), anti-TNF (OR, 1.18; 95% CI, 0.47-2.97), or vedolizumab (OR, 0.53; 95% CI, 0.16-1.73) use and risk of COVID-related pneumonia. 24 There was also no association between corticosteroid or anti-TNF use and death. 24 Similarly, data from the international SECURE-IBD registry for COVID-19 infections reported that only 19% of patients on antitumor necrosis factor monotherapy required hospitalization and 1% died, rates which were lower than those observed for patients on aminosalicylate therapy (46% hospitalized, 7% died). 25 These findings may, in part, be a selection bias due to use of immunosuppression only in individuals considered "fitter." Though consistent with the SECURE-IBD registry, use of immunosuppression was more frequent among those with milder disease in our cohort; upon adjusted analysis, only age and obesity were independently predictive of disease severity. In contrast to their study, we did not find an association with corticosteroid use. However, this may be a reflection of the relative inaccuracy of prescription dates to define active steroid use, given its sporadic intermittent use.
The lack of an effect of immunosuppression on COVID-19 risk or severity may have several explanations. First, SARS-CoV-2 infects the human host by binding the angiotensin 1 converting enzyme 2 (ACE2) receptor, which is then cleaved by transmembrane serine protease 2 (TMPRSS2) to induce viral entry into the cell. [26] [27] [28] The ACE2 receptor is expressed in many organs, including type 2 surfactant-secreting alveolar cells of the lungs and gastrointestinal epithelial cells, with highest concentrations in the duodenum, terminal ileum, and colon. 29, 30 Burgueño et al recently demonstrated no significant difference in ACE2 or TMPRSS2 expression in colonic organoids derived from patients with ulcerative colitis as compared with controls, supporting that ulcerative colitis alone may not impact risk of COVID-19 infection. 31 However, expression of ACE2 was lower in patients on antitumor necrosis factor drugs, vedolizumab, ustekinumab, and steroids as compared with patients on no immunosuppression, 31 which may limit viral entry and subsequent severity. Second, by virtue of being grouped together in the high-risk category, it is plausible that patients on systemic immunosuppression may have practiced stricter quarantine measures and self-isolated more rigorously than those not on such treatments, decreasing their risk of viral infection. Third, COVID-19 has been associated with a cytokine storm, and patients with severe disease often demonstrate markedly elevated inflammatory cytokines such as interleukin (IL)-6 on presentation. 32 Indeed, in addition to antiviral therapy, one of the avenues being explored for COVID-19 treatment is targeted immunosuppression, including IL-6 antagonists, 33, 34 with some even proposing a role for steroids or TNF-antagonists. 35 There are several implications to our results and strengths to our study. To our knowledge, the present study is one of the largest cohorts to date examining the impact of immunosuppression on risk of COVID-19 infection. Our findings suggest that those on immunosuppression for IBD are not at higher risk for COVID-19, nor are they at risk for more severe disease. Given the reliance on immunosuppression for effective management of several immune-mediated diseases, our findings may provide broad reassurance to providers treating patients with these diseases and support existing professional society recommendations to continue immunosuppression in such patients during the COVID-19 pandemic. [36] [37] [38] [39] [40] However, it should also be acknowledged that our study period comprised primarily a time where most may have been self-isolating, and thus continued study is necessary once societies reopen and risk of exposure is higher. We readily acknowledge the limitations to our study. Due to lack of widespread availability of testing, it is possible that patients with mild symptoms may not have been tested and thus not captured as cases in our analysis. Second, we did not have granular information on dose of medications and relied on the presence of a prescription for the relevant drug in the past year. Patients who had self-discontinued treatment, particularly early in the pandemic, would not have been identified as nonusers. Third, we did not have the ability to examine diseaserelated factors, such as active inflammation, on COVID-19 risk. Finally, though we supplemented case ascertainment by actively querying treating providers, it is possible that some patients may have been tested outside our health system and their providers not notified.
In conclusion, immunosuppressive treatment for management of IBD was not associated with an increase in risk of COVID-19 infection in a large, multi-institution cohort. Though our findings suggest that cautiously continuing such treatments for IBD is warranted, further study is necessary during the next phase of the pandemic with re-integration of society in the setting of ongoing exposure risk.
Supplementary data is available at Inflammatory Bowel Diseases online.
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Coronavirus is a pathogen that causes respiratory illness. The current COVID-19 (SARS-CoV-2) pandemic has been caused by the same pathogen. These coronaviruses have also caused outbreaks previously including severe acute respiratory syndrome (SARS)-CoV and the Middle East respiratory syndrome (MERS)-CoV. Coronavirus (COVID-19) outbreak first emerged from the city of Wuhan, Hubei province, China in December 2019. Patients were admitted with acute pneumonia which later was identified as COVID-19 infection [1, 2] . Total of 1975 infected cases and 56 deaths were reported in China until 25 January 2020 [3] . In just next 5 days until 30 January, the number of positive cases rose to 7734. It showed how quickly the infection had spread. Overall, the disease mortality rate was reported to be 2.2% in China [4] . In the US, the first case of human-human transmission was reported on 22nd January 2020 [5] .
As of now, 4,178,156positive cases have been reported worldwide with 286,353 deaths while the USA, Spain, Italy, the UK and Russia have the highest of confirmed cases. In Pakistan, 32,673 confirmed cases have been reported with 618 deaths. In Islamabad capital territory 716, in Sindh province 12,610, Punjab 11,869, KPK province 4875, Baluchistan 2061, Gilgit Baltistan 457 and in AJK 86 cases have been reported [7] .
COVID-19 infection has an incubation period of about 5.2 days after which symptoms starts to appear [8] . It takes around 6-41 days from onset of symptoms to death having a median of 14 days [3] . However, this period varies depending upon the immune system and age of the patient [3] . Some common symptoms of COVID-19 infection include dry cough, fever, fatigue, headache, diarrhoea, sputum production, haemoptysis, lymphopenia and dyspnea [3, [8] [9] [10] .
China has taken some strict measures to control the outbreak. That includes a total shutdown of public places, public transport and isolation of suspected cases. Authorities had locked down the whole province of Hubei as of 27 January 2020. Residents inside and outside of Hubei province were asked to stay at home and practice self-isolation to avoid any physical contact with others. Fight against the pandemic continues in China as well as throughout the world [11] . The success of which largely depends upon the public's response towards the control measures which have been taken.
In South Korea, measures were taken as early as 3 January 2020 well before the first confirmed case. On 26 February, the government opened first drive-through testing facility. South Korea took a pro-active approach to mass testing and practicing self-isolation [12] . Whereas in the US, timely steps were not taken due to which the number of infected cases in the US rose drastically and became the country with the highest number of confirmed cases in the world. According to WHO, US has confirmed cases of 1,215,571 and 67,146 deaths [13] .
The case studies of China, South Korea and America showed that diseases surveillance pattern is linked with the behaviour of Governments and the response of the general public. Now, to contain the COVID-19 outbreak in Pakistan, public understanding of the disease must be evaluated so that an effective strategy could be made considering the public's awareness regarding COVID-19. In this current study, we have investigated the Knowledge, Attitude and Practices (KAP) among Pakistan residents regarding COVID-19 during the outbreak.
The current survey was conducted among the participants from Punjab, Sindh, Baluchistan, KP, Gilgit Baltistan and Azad Jammu Kashmir region of Pakistan.
Pakistan has a total population of 208,518,662 and bordered by India (east), China (northeast), Iran (west) and Afghanistan (northwest). It has a total area of 881,913 square kilometres (340,509 square miles) and 33rd largest country by area. Pakistan geologically overlaps both with Indian and Eurasian tectonic plates where it's Sindh and Punjab provinces lie on the north-western corner of the Indian plate while Baluchistan and most of the Khyber Pakhtunkhwa (KPK) lie within the Eurasian plate which mainly comprises Iranian Plateau. Gilgit-Baltistan and Azad Kashmir (AJK) lie along the edge of the Indian plate (14).
The study was approved by the IRB and Ethics Committee under project 'A community-based assessment of Knowledge, Attitude, Practices and risk factors regarding COVID-19 among Pakistanis residents during recent outbreak; A cross-sectional survey' and letter reference number Ref. # 2020-01-01/UMT.
The study design was a cross-sectional survey and conducted between March 01, 2020 to April 02, 2020. In this study during the lockdown (by using quick online Google form) for data collection concerning the awareness and knowledge of COVID-19 as well as the practices along with other hidden elements involved in the outbreak.
During COVID-19 pandemic to conduct a community based national survey was not possible during the study duration (1st March to 2nd April 2020), the data was collected online. Relying on the authors' networks with local people living in different areas of Pakistan, a questionnaire was posted/reposted to moments and groups of their WhatsApp, Facebook and emails accounts. This questionnaire comprises a brief introduction on the background, objective, procedures, voluntary nature of participation, declarations of anonymity and confidentiality, and notes for filling in the questionnaire, as well as the link and quick response of the online questionnaire.
To determine the validity and reliability of the research questionnaire, a pilot study of 20 participants was carried out and questionnaires were filled. Each questionnaire was divided into five sections which consisted of respective questions for the participants. The questionnaire comprised as (a) Socio-demographic characteristics (n = 9) of the respondents, such as education, occupation, gender, age, marital status and ethnicity (b) Knowledge regarding COVID-19 (n = 7), (c) Attitude (n = 19), Risk factors (n = 7) and (d) practices towards disease (n = 11).
Pakistani nationals aged 16 years or more who have acess to the internet and can understood the content of the questionnaire were the target group of the study. After agreeing to participate, individuals were requested to complete the questionnaire via clicking the link.
The questionairae was devolped according to guidelines for clinical and community management of COVID-19 by the National Institute of Health (NIH) of Pakistan (15), a COVID-19 knowledge questionnaire was developed by the authors. The questionnaire had 53 questions consisting of information related to clinical presentations, symptoms, transmission routes, preventive strategies and control of COVID-19. These questions were answered on a yes/no based responses.
Data were entered into MS Excel spreadsheet and a database was established. Knowledge, Attitude and Practices (KAP) scores were obtained by combining scores for their respective columns. Individual variables in each of KAP like symptoms, introduction to disease were scored based upon how many symptoms or sources one knows. To find the comparative performance of various groups in terms of their obtained scores for each of KAP, ANOVA or T/F Tests were performed.
A total of 1060 participants completed the survey questionnaire. After excluding 56 respondents who provided inadequate information required for study, the final sample consisted of 1004 participants. A total of 9 questions covered the demographic section of survey. The highest number of participants belongs to Punjab province (65.6%; n = 659) followed by Islamabad Capital Territory (ICT) (10.3%; n = 103), Khyber Pakhtunkhwa (KPK) (8.8%; n = 88), Sindh (8.3%; n = 83), Azad Jammu & Kashmir (AJK) (3.5%; n = 35), Gilgit Baltistan (2.2%; n = 22), and Baluchistan (1.4%; n = 14), respectively. Number of female respondents (63%; n = 633) were greater than male respondents (37.0%; n = 371). Among the age groups, 62.1% (n = 623) participants were between 21-30 age group, 29.9% (n = 300) were up to 20 years of age, and 8.1% (n = 81) were greater than 30 years of age. More of the participants were single (85.1%; n = 854), whereas13.9% (n = 140) were married. Nearly all the participants were Muslim (99.4%; n = 998). Among the sample, major native languages included Urdu (45.6%; n = 458), Punjabi (27.0%; n = 271), and Pushto (9.4%; n = 94) respectively.23.8%respondents had intermediate level education, 51.5% had graduation level and 24.7% had master and above level education. Most of the participants (52.9%; n = 531) were students, other professions among the sample include teachers (12.5%; n = 126), health care professionals (11.2%; n = 112), unskilled job (11.0%; n = 110), unemployed (6.0%; n = 60) and others (6.5%; n = 65) respectively. Majority of respondents belonged to middle class economic status (40.8%; n = 410) followed by poor class (20.1%; n = 202), and high class (10.6%; n = 106) while 28.5% (n = 286) participants did not respond on their economic status. The association of demographic characteristics were presented in Table 1 .
A total of 7 questions were solicited to check the knowledge of subjects towards COVID-19 pandemic. Of the study population, 866 (86.3%) of subjects were familiar with the viral outbreak, whereas, 44.4% (n = 445) were aware of COVID-19 pandemic. Among the respondents, 50.1% (n = 503) had knowledge of human-human transmission and 46.6% (n = 468) has seen COVID-19 patient. Only 2.9% (n = 29) of participants went to public swimming pools in last 15 days. 6.3% (n = 63) subjects' acquaintances had recent (last 15 days) international travel history. 54.7% (n = 549) of the respondents were not knowing that physical contact is the main cause of infection spread while 45.3% (n = 455) were aware (Table 2) .
To inquire about the attitude of participants towards COVID-19 pandemic, response on a total of 19 questions were collected in the survey. 44% of respondents were agreed that infected patients should be separated. Most participants were willing to receive disease inspection, free treatment, and to undergo quarantine if infected (80.7%, 87.6%, and 94.5% respectively). 61.6% of subjects (n = 619) considered going to the mosque as a factor for the spread of infection. Likewise, most of the respondents were of the view that health of other people around them is linked to their health, public events should be banned, and economic stability can improve health conditions (94.5%, 95.8% and 93.3% respectively). Moreover, 93.0%, 57.1% and 42.9% of participants showed a positive attitude for the requirement of masks and hand sanitizers, treatment facilities, and vaccination campaigns respectively. A considerable number of respondents showed positive attitude for suspension of an international flight, closure of shops, offices, schools, etc., and only to allow takeaways on restaurants and fast food points (77.9%, 56.6% and 92.9%, respectively). The results of the questionnaire relating to attitude were summarized in Table 3 .
Data was collected through seven questions regarding risk factors of respondents towards COVID-19 pandemic. Out of subject sample, 62.3% subjects, considered public gathering as a risk factor while, according to 78.4% subjects, lack of awareness is also a risk factor. Majority of the participants (80.3%, and 87.2%, respectively) considered asymptomatic onset and social, political and economic stability as a major risk factor. Moreover, for 64.4% and 68.7% respondents, exposure to people with a recent travel history and infected patients is a major risk factor respectively, while only 45.3% subjects enlisted physical/close contact as a risk factor for the spread of infection. The results relating to risk factors were summarized in Table 4 .
Practices 55.9%, 43.4% and 68.6% of respondents had exposure to unknown people, met people with an international travel history and their work include public dealing, respectively. On personal hygiene, 85.5% subjects wash hands frequently, 59.8% wash hands before eating and 92.6% wash hands after coming home and 50.5% covers face when sneezing or coughing. Among the subjects, only 7.5% were smokers, 59.3% were used to go to the mosque for prayers and now 77.2% has stopped going to the mosque for prayers. 92.8% of respondents practised maintaining safe physical distance Data of practices of participants regarding COVID-19 is depicted in Table 5 .
The F-test used for comparisons of all factors (Knowledge, Attitude, Risk, Practices) among provinces and according to F-test for all factors are statistically significant and showed that knowledge, attitude, risk factors and practices all are not same in all the provinces. The highest knowledge score was 3.06 which is in Sindh and KPK, whereas the second-highest (Table 6) . According to the current survey, knowledge score was statistically significant across provinces/territories, Age groups, marital status, occupation and economic status. The attitude was statistically significant across provinces/territories, age groups, marital status, mother-tongue, education, occupation and economic status. Risk factors were significant across provinces/territories, mother-tongue, education and economic status while practices were significantly differed across all demographic variables i.e. provinces/territories, gender, age groups, marital status, mother-tongue, education, occupation and economic status ( Table 6) .
The correlation matrix for knowledge, attitude, risk factors and practices scores were analyzed. The average score of knowledge is about 3 out of 6 which is exactly the centre of the score, and which suggested that 50% of people know COVID-19. The attitude average score was 14 out of 18 and showed that about 3 out of 4 respondents showed good attitude towards disease and similarly the average score of risk factors is 5 out of 7 and the average score of practices is 8 out 12.
The correlation matrix showed that all the relationship is statistically significant. The knowledge was positively correlated with attitude and practices whereas negatively correlated with risk factors. With the increase of knowledge increases attitude and practices increases whereas risk factor decreases. The attitude is negatively correlated with risk factor and positively correlated with practices and as attitude increases risk factors decreases and practices increases. The risk factor and practices were positively correlated with each other (Table 7 ).
COVID-19 is a respiratory disease which is caused by a novel coronavirus (SARS-CoV-2) and outbreak was started from Wuhan, China in December, 2019. The disease causing virus is highly contagious and declared pandemic by WHO. The main clinical symptoms of the disease include fever, dry cough, fatigue, myalgia, and dyspnea. In China, 18.5% of the patients with COVID-19 developed the severe stage, similarily global clinical data have shown that the overall case fatality rate of COVID-19 is 17% across the globe [6]. The mortality rate due to COVID-19 (2.3%) is much lower than those of SARS (9.5%), MERS (34.4%), and H7N9 (39.0%) in China [11] .
Pakistan, a developing country with limited resources and being a neighboring country to China and Iran, two hard-hit countries puts Pakistan at high risk [16] . In Pakistan, the COVID-19 fatality rate for closed cases is 16% which is . So, in Pakistan, researchers had earlier warned before the arrival of the first case that travellers coming from abroad specifically from hard-hit pandemic countries could pose a threat to spread of infection in Pakistan [17] . The SARS-Cov-2 virus has a zoonotic origin, bats are the natural hosts of the virus which transmitted to humans through intermediate host which is still not known [18] . This pandemic will have a very daunting impact on the world economy, in the year 2020; this pandemic will cause an economic loss of 1 trillion USD globally and might result in limiting the economic aid to internally displaced people (IDP's), refugees and asylum seekers [19] . It is well established that diseases spread are directly linked with population knowledge, attitude and practices towards disease. The current mortality rate is alarming and if disease spread is going to high in coming weeks in Pakistan it might go higher.
According to the current survey, knowledge score was statistically significant across provinces/territories, Age groups, marital status, occupation and economic status. Results of knowledge score of our study are concordant with another study conducted in China where residence place, age groups, marital status, education and occupation significantly differed. 11 Similar results were also reported among physicians, nurses, lab staff and academic individuals including faculty and students in Pakistan [20] . Our knowledge results are contrary to Zhong et al. [11] , regarding gender and educational variables. This indicates that in Pakistan, gender does not influence knowledge while education variable difference is due to the reason that data was electronically gathered hence most of the subjects were literate, and illiterate community cannot be incorporated in this study as they are handicapped to use such technology. The attitude was statistically significant across provinces/ territories, age groups, marital status, mother-tongue, education, occupation and economic status. Our results of attitude score are similar in educational level and provinces/territories with Zhong et al. [11] , while in case of occupation it is [21] and Zhong et al. [11] . Risk factors were significant across provinces/territories, mothertongue, education and economic status while practices were significantly differenced across all demographic variables i.e. provinces/territories, gender, age groups, marital status, mother-tongue, education, occupation and economic status. Correlation analysis revealed that knowledge is positively correlated with attitude and practices and negatively with risk factors indicating that if knowledge would increase, attitude and practices will also increase, and risk factors would be decreased. The attitude is positively correlated with practices and negatively with risk factors indicating that attitude and practices would increase or decrease simultaneously. While attitude with risk factors explains that if attitude would be higher the risk would be less and vice versa. Practices and risk factors are positively correlated indicating that maintaining practices to visit crowded places, smoking and will meet the unknown persons on daily basis it would increase risk while wash hands properly, maintain a safe distance and use masks reduces the risk factor.
In the present study, there is no significant relationship among gender, age and risk factors, while it is contradictory to the previous studies where the male has shown risky behavior as compared to females and different age groups were engaged in risk-taking behaviors variably [11, 22, 23] .
Findings of the present study suggested that the demographic factors are associated with KAP towards COVID-19 as were previously found for SARS studies in 2003 [11, 24, 25] . The current data was obviously over-representative of women, well-educated people, students, and the findings can only be generalized to literate Pakistani populations and is in accordance with Zhong et al. [11] .
There are a few limitations to the study. Due to limited access to the internet and online health information resources, vulnerable groups such as illiterate and rural people were missed. It is most likely that these groups may have poor knowledge, negative attitudes, and inappropriate preventive practices towards disease. These high-risk populations are very important to include in the study but due to lockdown in the country, it was not possible. The study was electronically conducted, so there is a limitation of participants representation regarding socio-demographic variables especially gender and education variables. Findings of this study suggest that Pakistani literate society in particularly women had good knowledge, optimistic attitudes, and appropriate practices towards COVID-19 during the rapid rise period of the COVID-19 outbreak. Besides, good COVID-19 knowledge is associated with optimistic attitudes and appropriate practices towards COVID-19, suggesting that health education programs aimed at improving COVID-19 knowledge help encourage an optimistic attitude and maintain safe practices. Due to the limitation in the representativeness of the sample, more studies are warranted to investigate the KAP towards COVID-19 among Pakistani residents of low socioeconomic status and education.
COVID-19 is pandemic needs extraordinary steps for its control. This study explains the perceptions of Pakistani population regarding COVID-19. Although people are aware of COVID-19 health education program should start to improve the COVID-19 knowledge, attitude, practices and risk factors among the illiterate or less educated community. More work or surveys should be done to impose the perceptions about general population across the country.
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INTRODUCTION SARS-CoV-2, or severe acute respiratory syndrome coronavirus 2 (1), is an emergent, zoonotic pathogen first identified in China in late 2019 (2, 3) . This enveloped, positive-sense single-stranded RNA virus is a novel Betacoronavirus (4) with phylogenetic proximity to SARS-CoV-1 (2, 3) . In humans, SARS-CoV-2 can cause asymptomatic infections to severe atypical pneumonia that can lead to death. Given its rapid spread in different countries, the disease, named COVID-19 (i.e., Coronavirus Disease 2019), was declared a Public Health Emergency of International Concern by the World Health Organization (WHO) in January 2020 (5) . In only 2 months, the virus spread to all continents, except Antarctica, and in March 2020, COVID-19 was characterized by WHO as a pandemic (5) . On August 3, 2020, SARS-CoV-2 has been present in 213 countries or regions and detected in at least 17 million people, while 690,000 individuals have succumbed to the disease (6, 7) .
According to the United States Agency for International Development (USAID), nearly 75% of all new emerging or re-emerging infectious diseases of the last century originated in animals, such as HIV, Ebola, avian influenza, and swine influenza (8) . Accordingly, the initial epicenter of SARS-CoV-2 was linked to possible contact with wild animals sold at wholesale seafood and exotic animal markets of Huanan, Wuhan, Hubei province, China (5) . Analysis of complete genome sequences of the new coronavirus isolated from patients during the initial stage of the outbreak in Wuhan showed only about 79% identity with SARS-CoV-1 (severe acute respiratory syndrome coronavirus 1), identified in China in 2002 (9, 10) , and 50% identity with MERS-CoV (Middle East respiratory syndrome coronavirus), identified in Saudi Arabia in 2012 (4, 11) . Interestingly, it revealed 96% identity with a bat coronavirus (BatCoV) found in Rhinolophus affinis (horseshoe bat), named RaTG13, sampled in Yunnan province, China, in 2013 (12) , and 91.02% identity with a coronavirus obtained from pangolins (Manis javanica) (13, 14) . This close phylogenetic relatedness of SARS-CoV-2 to non-human coronaviruses, in the absence of a known ancestral virus sample, strongly suggests a viral host jump from wildlife to humans, most likely from bats (12, 13, 15) . More detailed genomic analyses indicate that SARS-CoV-2 is a product of natural selection rather than laboratory manipulation and that an animal source was likely involved in the initial cases of human infections associated with the Huanan market (15) . Because contact between humans and bats is a rare event, it is also possible that a susceptible intermediate host species may have participated in the epidemiology of SARS-CoV-2, similar to what was observed with SARS-CoV-1 and MERS-CoV (16, 17) .
Coronaviruses (CoVs) tend to be species specific when it comes to hosts, which is determined by the interaction of the virus with specific host cell receptors (18) . The spike protein, a protruding glycoprotein of the membrane of CoV virions, mediates host cell adhesion and membrane fusion (18) . The amino acid sequence of the spike protein is what defines its ability to interact with different host cell receptors. For three of the human coronaviruses, HCoV-NL63, SARS-CoV-1, and SARS-CoV-2, the angiotensin-converting enzyme 2 (ACE-2) has been identified as the cell receptor with which the spike protein interacts (19) (20) (21) (22) . For the adhesion to occur properly, researchers have identified 69 amino acid residues at the receptor binding domain (RBD) of the spike protein that are key for its interaction with ACE-2 (22) . Although both SARS-CoV-2 and SARS-CoV-1 use the same receptor, their RBD is different at five out of six important amino acid residues. Surprisingly, only one of these residues was identical between SARS-CoV-2 and the BatCoV RaTG13, while all six are identical between SARS-CoV-2 and the pangolin CoV (23) . Thus, although the BatCoV RaTG13 is the closest relative to SARS-CoV-2 at the whole-genome level, the RBD residues critical for receptor interaction are actually identical to pangolin CoVs (23) . This finding is supportive evidence of a natural selection process during a viral host jump from animals to humans.
As detailed above, the amino acid sequence of ACE-2 is a determining factor of the host species range affected by SARS-CoV-2. During the search for an animal model of COVID-19, bioinformatic predictions and previous studies with SARS-CoV-1 indicated that non-human primates, ferrets, hamsters, and domestic cats were possible animal candidates to be explored (24) (25) (26) (27) (28) . Accordingly, experimental SARS-CoV-2 infection and clinical sign development have been successfully accomplished in non-human primates, ferrets, and golden Syrian hamsters (Mesocricetus auratus) (27, (29) (30) (31) (32) (33) . Experimental infection was also successful in cats, but the animals developed no clinical signs (31, 34) . In dogs, the intranasal inoculation of SARS-CoV-2 in 3-month-old beagles resulted in only two out of four experimentally infected animals developing neutralizing antibodies and no detectable viral RNA in organ tissues of one euthanized animal 4 days postinfection. Viral RNA was sporadically detected in the feces of these dogs a few days postinfection (31) . This same study shows that experimental infection of SARS-CoV-2 was not successful in pigs, ducks, and chickens (31) . Taken together, these results raise the possibility that companion animals, particularly cats and hamsters, may get infected with SARS-CoV-2 outside experimental laboratory conditions. As previously shown in a review on cell, tissue, and animal models for SARS-CoV-2 infection, non-human primates may be used for human clinical tests, while primary cell culture, primary tissue explants, and organoids may be applied for other human and animal approaches (35) .
With millions of people detected with SARS-CoV-2 worldwide, reports of companion animals possibly infected with the virus started to emerge. These animals were frequently owned by individuals with confirmed or suspected SARS-CoV-2 infection, raising concerns that an anthropozoonotic transmission occurred. Therefore, our aim is to review reported cases of animals naturally infected with SARS-CoV-2, particularly companion pets, shedding light on the role of these animals in the epidemiology of COVID-19.
Members of the Coronaviridae family have a positive-sense single-stranded RNA genome varying from 26 to 32 kilobases, the largest viral RNA genomes ever described. CoVs are enveloped viruses and identified in several species of birds and mammals, including humans. The Coronaviridae family is composed of two subfamilies (Letovirinae and Orthocoronavirinae) and four genera (Alphacoronavirus, Betacoronavirus, Gammacoronavirus, and Deltacoronavirus) found in the subfamily Orthocoronavirinae. The organization and expression of their genome are very similar, with 15 to 16 non-structural proteins (nsp1 to nsp16, with nsp1 being absent in Gammacoronavirus), codified by ORF1ab at the 5 ′ end, and four to six structural proteins, hemagglutinin-esterase (HE, found in some betacoronaviruses) spike (S), envelope (E), membrane (M), and nucleoprotein (N), which are codified by ORFs at the 3 ′ end of the genome (36, 37) .
In humans, CoVs primarily cause infections of the upper respiratory and gastrointestinal tracts, with clinical manifestations ranging from asymptomatic to severe or lethal (38) . Seven CoV strains are able to infect humans: HCoV-NL63, HCoV-229E (Alphacoronavirus), HCoV-OC43, HCoV-HKU1, SARS-CoV-1, MERS-CoV, and more recently, SARS-CoV-2 (all these in the Betacoronavirus genus) (36, 38) . HCoV-NL63, HCoV-229E, HCoV-OC43, and HCoV-HKU1 are distributed globally (39, 40), with seasonal and geographic variations. These are low-pathogenic CoVs associated with a variety of mild upper respiratory tract infections, occasionally affecting the lower respiratory tract, leading to pneumonia, bronchiolitis, or both (40) (41) (42) (43) (44) . Nonetheless, in the last two decades, highly pathogenic, zoonotic CoVs emerged. These are SARS-CoV-1, which emerged in China in 2002 (9, 10); MERS-CoV (11) , which was first detected in Saudi Arabia in 2012 (11) ; and SARS-CoV-2 identified in China in 2019 (2, 3) . These CoVs are highly pathogenic and may cause lethal disease, with variable mortality rates of about 10% for SARS-CoV-1, 34% for MERS-CoV, and from 1 to 7% for SARS-CoV-2. The epidemic of SARS-CoV-1 affected 26 countries, and more than 8,000 cases were reported, while MERS-CoV was identified in 27 countries, with more than 80% of the 2,494 cases reported in Saudi Arabia (10, 45). Currently, SARS-CoV-1 is not detected in any region of the world, and MERS-CoV cases are sporadically reported in Saudi Arabia (10, 45). SARS-CoV-2, on the other hand, is currently at epidemic peaks in many regions, with exponential growth of case numbers and fatalities globally (7).
Coronaviridae species affecting host species other than humans have been reported, causing respiratory, gastrointestinal, liver, kidney, or neurological diseases in a variety of domestic and wild animals, with no human infection by these coronaviruses ever reported. Among companion animals, canine coronavirus (CCoV) and feline coronavirus (FCoV) belong to the species Alphacoronavirus 1 with two serotypes (I and II), each occurring as either a low-virulence biotype that causes mild to silent enteric infectious and high-virulence, pantropic biotypes in dogs (a CCoV-IIa lineage) and cats (feline infectious peritonitis virus) (46, 47) . In addition, a betacoronavirus named canine respiratory coronavirus has been associated with respiratory disease in dogs (48) .
Among large animals, calves and adult cattle are susceptible to enteric and respiratory disease after infection by bovine coronavirus (a Betacoronavirus), while another betacoronavirus, equine coronavirus, has been associated with enteric disease in horses (49, 50) . Avian coronavirus (a Gammacoronavirus) has chickens as a natural host, infecting the trachea, lungs, kidneys, reproductive tract, and intestines in broilers, layers, and breeders with a wide range of serotypes (51, 52) . Moreover, swine acute diarrhea syndrome coronavirus (SADS-CoV), first reported in 2017, together with porcine epidemic diarrhea virus (PEDV) and transmissible gastroenteritis virus (TGEV) are alphacoronaviruses that cause highly lethal enteric disease in pigs (53) . Porcine deltacoronavirus (PDCoV) and the betacoronavirus porcine hemagglutinating encephalomyelitis virus (PHEV) also use pigs as hosts (54, 55) .
To understand how certain domestic animal species may be infected with SARS-CoV-2, it is crucial to investigate the underlying reason for the ability of the virus to enter host cells and establish infection. Current knowledge of the SARS-CoV-2 pathogenesis indicates that such event is made possible by the interaction between SARS-CoV-2 and the host ACE-2 protein, which acts as a receptor for viral adherence and membrane fusion (19) (20) (21) (22) . Supplementary Data and Table 1 show a multiple protein sequence alignment of ACE-2 of human, main domestic, and laboratory animal species and cross-species identity of the 22 amino acids of ACE-2 that physically interact with SARS-CoV-2 (22), respectively. Among putative pet animals, golden Syrian hamsters, cats, and rabbits diverge in only 3 of the 22 amino acids of ACE-2 responsible for the interaction with SARS-CoV-2, while dogs diverge in five amino acids (Supplementary Data and Table 1 ). However, the whole-protein sequence of ACE-2 of golden Syrian hamsters showed higher sequence similarity and phylogenetic relatedness to human ACE-2 than the rabbit and cat ACE-2 (Supplementary Figure 1) . Whether at the wholeprotein level or at the 22 interaction-defining amino acids, this sequence may be determinant of a successful infection, along with the expression of ACE-2 protein in different tissues and yet to be unraveled alternative receptors of SARS-CoV-2 in host cells. The link between structural properties of ACE-2 orthologs to SARS-CoV-2 spike protein has been already investigated (56) . In this study, non-conservative mutations in several ACE-2 amino acid residues have been associated with interrupted key polar and charged viral spike protein contacts, which may decrease the susceptibility to SARS-CoV-2 infection across different animal species. In addition, structural analysis of amino acid residues has suggested that changes in amino acid positions 30 and 83 may affect structural interaction of ACE-2 and SARS-CoV-2 RBD, differentiating non-susceptible from susceptible species (57).
The first report of SARS-CoV-2 infection in dogs occurred in Hong Kong, China, by the Hong Kong Agriculture, Fisheries, and Conservation Department (AFCD) (58) ( Table 2) . A 17year-old male Pomeranian with several comorbidities was asymptomatic and quarantined on February 26, 2020, after its owner was diagnosed with COVID-19 (58, 59) . On March 18, an asymptomatic 2.5-year-old male German shepherd dog tested positive for SARS-CoV-2 by RT-qPCR in nasal and oral swabs; the two dogs had detectable antibodies against SARS-CoV-2 (60, 61) . In addition, viral sequences were identical to the virus identified in the respective owner cases, suggesting humanto-animal transmission (72) . On June 1, in the Netherlands, neutralizing antibodies against SARS-CoV-2 were detected in an 8-year-old American bulldog with breathing distress, with a COVID-19-positive owner (62) . The animal was euthanized due to clinical worsening (71). In New York State, Richmond County, USA, two dogs tested positive to anti-SARS-CoV-2 antibodies (62). One dog showed signs of respiratory illness and severe lethargy associated with hemolytic anemia (62) . The other dog was asymptomatic. The owner of the two dogs tested positive for COVID-19 (62) . Both dogs are recovering (62) . In May 2020, a 7year-old male German Shepherd tested positive for SARS-CoV-2 by RT-qPCR, after 6 weeks with breathing distress (73). On July TABLE 1 | Cross-species identity of the 22 amino acids of the angiotensin-converting enzyme-2 (ACE-2) identified as directly involved in the physical interaction of ACE-2 and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as defined by Shang et al. (22) . ACE-2 Host 19 24 27 28 31 34 35 37 38 41 42 45 79 82 83 325 329 330 353 354 355 357 Total 11, 2020, the animal died with a diagnosis of lymphoma, which may have been a confounding cause for the respiratory signs (73).
Human S Q T F K H E E D Y Q L L M Y Q E N K G D R 22/22 Rhesus monkey S Q T F K H E E D Y Q L L M Y Q E N K G D R 22/22 Chimpanzee S Q T F K H E E D Y Q L L M Y Q E N K G D R 22/22 Syrian hamster S Q T F K Q E E D Y Q L L N Y Q E N K G D R 20/22 Domestic cat S L T F K H E E E Y Q L L T Y Q E N K G D R 19/22 Cow S Q T F K H E E D Y Q L M T Y Q D N K G D R 19/22 Sheep S Q T F K H E E D Y Q L M T Y Q D N K G D R 19/22 Rabbit S L T F K Q E E D Y Q L L T Y Q E N K G D R 19/22 Chinese hamster S Q T F K Q E E D Y Q L L N Y Q G N K G D R 18/22 Pangolin S E T F K S E E E Y Q L I N Y Q E N K H D R 17/22 Domestic dog S L T F K Y E E E Y Q L L T Y Q G N K G D R 17/22 Horse S L T F K S E E E H Q L L T Y Q E N K G D R 17/22 Pig S L T F K L E E D Y Q L I T Y Q N N K G D R 17/22 Ferret S L T F K Y E E E Y Q L H T Y E Q N K R D R 14/22 Mice* S N T F N Q E E D Y Q L T S F Q A N H G D R 14/22 G. horseshoe bat** S L K F D S E E N H Q L L N F E N N K G D R 13/22 Chicken S - T F E V R E D Y E L N R F E T N K N D R
Also, in Hong Kong, nasal and oral swab and fecal samples from a clinically healthy cat tested positive for SARS-CoV-2 by RT-qPCR (74) . The owner had been hospitalized with COVID-19 (63) . Until April 15, 2020, the Hong Kong Agriculture, Fisheries, and Conservation Department tested 17 cats from guardians positive for COVID-19, and only the cat mentioned above was positive (62) . In mid-March 2020, in Belgium, viral RNA from SARS-CoV-2 was detected in samples of vomit and feces of a cat with diarrhea, vomiting, and dyspnea, using RT-qPCR (64) . Despite the animal's guardian being infected with COVID-19, it was not possible to establish the level of identity between the genomic sequences of SARS-CoV-2 present in the cat and human (64) . This cat showed clinical improvement 9 days after the onset of symptoms (64). On April 22, the OIE, the Centers for Disease Control and Prevention (CDC), and the United States Department of Agriculture (USDA) reported that two cats from the New York I State in the USA, both presenting sneezing and nasal discharge, tested positive for SARS-CoV-2 by RT-qPCR (68, 69) . One cat is a 5-year-old Devon Rex, from Orange County, and the owner was positive for COVID-19 (75) . The clinical signs in the cat appeared after the owner showed COVID-19-compatible symptoms (75) . Another cat in the same household remained asymptomatic but was not tested for the presence of the virus (75) . The second positive 4-year-old cat was from Long Island (Nassau County) with outdoor access (75) . The animal has presented respiratory signs and lethargy and tested positive to SARS-CoV-2 RNA by quantitative RT-PCR. Three of five households have shown clinical signs related to COVID-19 but were not tested, and the cat is presumed to have been infected by someone at home or by a virus carrier (75) . The latest laboratory tests on the two cats have shown that they are clearing the infection and will likely have full recovery (75) .
On March 18, a case of a Belgian cat with a breathing problem, vomiting, and diarrhea was reported, with SARS-CoV-2 detected by RT-qPCR in vomit and feces samples (76). On April 17, a 9-year-old female cat of European breed from France was tested positive to SARS-CoV-2 RNA by RT-qPCR on a rectal swab. The animal showed clinical signs, such as anorexia, vomiting, and cough, 17 days after its owner has tested positive to COVID-19. Antibodies against SARS-CoV-2 have been detected in two serum samples taken 10 days separately. In addition, sequence analysis of cat SARS-CoV-2 has shown that it belongs to the phylogenetic clade A2a, similar to the French human SARS-CoV-2 (67) . In June, one cat from Minnesota and another one from Illinois, USA, tested positive for SAR-CoV-2, confirmed by USDA's National Veterinary Services Laboratories (77) . It is not surprising that cats develop clinical signs; SARS-CoV-2 penetrates the cell by binding to the ACE-2 receptor, and the ACE-2 receptor in cats has high homology with the human receptor (78) (79) (80) , as shown above. The coronavirus that caused the SARS epidemic (SARS-CoV-1) in 2003 also uses the ACE-2 receptor to enter cells (81) . Cats are susceptible to experimental infection with the SARS-CoV-1 and also became naturally infected during the SARS epidemic in 2003 (81, 82) . Recently, cats were experimentally inoculated intranasally with high doses of SARS-CoV-2 (31) . The animals showed no clinical signs, developed neutralizing antibodies, and eliminated viral RNA in the feces. At necropsy, infectious virus was found in the nasal turbinates, soft palate, tonsils, trachea, and lungs (31) . Experimentally infected cats transmitted the disease by air particles to susceptible cats (31) . Moreover, an experimental study has shown that SARS-CoV-2 was transmitted by virusinoculated cats to cats with no previous infection, after cohoused contact. After 24 days of inoculation, all the cats showed IgG antibody titers ranging from 5,120 to 20,480. Since no clinical signs were reported in this study, the authors speculate that cats may be a silent intermediate host of SARS-CoV-2 (34).
Experimental infection with SARS-CoV-2 is also possible in hamsters, ferrets, rhesus macaques (Macaca mulatta), cynomolgus monkeys (Macaca fascicularis), and African green monkeys (Chlorocebus sabaeus) (31) (32) (33) (83) (84) (85) (86) . Callithrix jacchus monkeys have been resistant to SARS-CoV-2 experimental infection, when compared with M. fascicularis and M. mulatta (87) . Experimental studies with rhesus macaques have shown mild disease as frequently observed in human cases (83) and suggest that primary SARS-CoV-2 infection protects against reinfection throughout early recovery days (88) .
In hamsters and ferrets, transmission occurred to other susceptible animals by air (31, 32) . To date, there are no reports of natural cases of SARS-CoV-2 infection in hamsters or ferrets (31, 32) . The Hong Kong Agriculture, Fisheries, and Conservation Department tested two hamsters from guardians positive for SARS-CoV-2, and both were negative (62) . Under experimental conditions, Syrian hamsters (M. auratus) have been successfully infected by SARS-CoV-2, and transmission between cohoused animals was observed by direct or indirect contact with blood, feces, saliva, and tears (27) .
On April 4, 2020, the US Department of Agriculture (USDA) announced that samples from a 4-year-old female Malayan tiger at the Bronx Zoo in New York City tested positive for SARS-CoV-2 by RT-qPCR (89) . The swab samples were collected and tested after two Malayan tigers, three Siberian tigers, and three African lions showed respiratory signs for a week (65, 89) . On April 17, the OIE confirmed that one of the African lions tested positive for SARS-CoV-2 by RT-qPCR (66) . Later on, all these animals and one asymptomatic Siberian tiger tested positive for SARS-CoV-2 by RT-qPCR of stool samples (90) . The five positive tigers live separately in the same enclosure (90) . The three lions live in an enclosure in another zoo area, and they occasionally interacted (90) . The Bronx Zoo also has one Malayan tiger and two Siberian tigers living in a distant enclosure (91) . These three tigers showed no clinical signs (91) . SARS-CoV-2 was identified and characterized in a Malayan tiger (92) . The seven symptomatic animals have improved and are expected to fully recover (91, 93) . In addition, SARS-CoV-2 characterization has shown distinct viral sources for tigers and lions, with similarities between tiger and zookeeper viruses suggesting human-animal transmission, but no identified viral source was found for the infection in lions (94) .
On April 26, 2020, the Dutch Ministry of Agriculture, Nature, and Food Quality communicated SARS-CoV-2 outbreak in two mink (Neovison vison) farms, after respiratory disease and increased mortality (70, 95) . Infection by SARS-CoV-2 has been reported in minks on a farm with 13,000 minks (95) . Additional infections were identified on a second farm with 7,500 adult minks (96) . Three minks with gastrointestinal and respiratory signs were euthanized (70) . Samples of manure, air, and dust collected from the vicinity of the farm are being tested for the presence of the virus (95, 96) . Cats from the farms will also be tested (95) . At least one worker tested positive for SARS-CoV-2 in both farms (70) . It is not surprising that minks are susceptible because they are from the same family (Mustelidae) as ferrets (Mustela putorius furo), and ferrets can be experimentally infected with SARS-CoV-2 and transmit the disease to other ferrets by direct or indirect contact (32, 33) . The infection in minks appears to be a case of human-to-animal infection, once viral sequences of two farms were related to human being sequences, but in separate introductions (70) . In addition, since March 2020, rabbit farms near infected visons have been investigated by the Dutch Ministry of Agriculture, Nature, and Food Quality due to possible susceptibility to SARS-CoV-2 (97).
Experimental transmission study has shown that pigs (Sus scrofa) and chickens (Gallus gallus) were not susceptible to SARS-CoV-2, since none of the animals seroconverted and all samples were negative for viral RNA after intranasal inoculation (98) . On the other hand, fruit bats (Rousettus aegyptiacus) have presented virus replication detected by RT-PCR, in situ hybridization (ISH), and immunohistochemistry (IHC) associated with mild rhinitis (98) .
It is important to emphasize that there is no transmission of SARS-CoV-2 from pets to humans to date and that transmission from people to pets is rare. In a study carried out by the Pasteur Institute (France) published in April 2020, 21 domestic animals were tested, including 9 cats and 12 dogs that lived in close contact with their guardians, a total of 20 veterinary students in France (99) . Among the students, two tested positive for SARS-CoV-2 by RT-PCR, and 11 out of 18 showed clinical signs of COVID-19 (99) . Among the animals, three cats showed respiratory and gastrointestinal symptoms (99) . Despite the proximity to infected guardians, no dog or cat tested positive for SARS-CoV-2 by RT-PCR nor showed antibodies to SARS-CoV-2 in an immunoprecipitation assay (99) . Despite the low sampling, the study suggested that the transmission rate of SARS-CoV-2 between humans and pets under natural conditions is probably very low, below a reproduction number of 1 (99) . So far, there is no epidemiological study with a large number of animals that allows estimating the percentage of dogs and cats in contact with people with COVID-19 that excrete the virus or develop antibodies.
Cats are known to be more susceptible to experimental infection with SARS-CoV-2 than dogs (31) . In 2016, 21% of New York State households in the USA had cats with an estimated total of 2,841,000 cats, and 21% of households had an average of 1.7 cats per house (100) . As of May 9, 2020, the New York State had 333,000 confirmed cases of COVID-19 (101) . If those cases were from different households, ∼103,000 cats would have been exposed to patients with COVID-19, and only 2 of these 103,000 cats tested positive for SARS-CoV-2 (101) . Cat population in the area that would have been exposed to the virus was estimated. Despite the impossibility of knowing how many cats have been tested, evidences have shown that clinical disease may be rare in cats. This suggests that transmission from people to animals is really rare.
There are two serological surveys with cats, one of which also includes dogs (102) . In an unpublished study, 11 of 102 cats had neutralizing antibodies against SARS-CoV-2, suggesting that under natural conditions, cats exposed to SARS-CoV-2 develop antibodies (103) . These samples were obtained after the outbreak of COVID-19 in Wuhan, China (103) . In another serological study also in the Wuhan region, antibodies to SARS-CoV-2 were investigated in 35 animal species (102) . The sampling included 15 pet dogs, 99 street dogs, 66 pet cats, and 21 street cats (102) . Close contact with a patient with COVID-19 was confirmed for at least three dogs in this study (102) . None of the dogs and cats had antibodies against SARS-CoV-2 (102). It is possible that the infected companion animals reported so far were in close contact with humans emanating high viral loads of SARS-CoV-2, had comorbidities or increased susceptibility to the virus, or had a combination of these factors. It is assumed that the risk of animals is greater at the beginning of the disease in people because this is the time when the viral load is higher (104) .
One must take into account that if a sustained transmission naturally establishes among individuals of the same species, SARS-CoV-2 might be led by natural selection to achieve a higher fitness in this new species; the consequences of this event remain unclear.
Many residents at the original epicenter of the Wuhan outbreak were forced to leave their pets behind when authorities removed people from their homes (105) . Reports suggest that owners left enough food and water for their pets to last for some days (106) . Several weeks later, many residents had not yet returned home. In China, animal welfare organizations estimate that in Hubei alone, tens of thousands of cats and dogs have been left behind, facing hunger and death (105) . The risk of pet abandonment may increase due to reports of SARS-CoV-2 in dogs and cats, associated to lack of reliable information ruling out dogs and cats as a source of infection. To investigate whether the abandonment of domestic cats protects people against SARS-CoV-2 infections, a computer model was created that simulates a small community of human households and cats (107) . A different number of cats were set free during the simulations, and the total number of infected people was recorded (107) . In the simulations, cats were chosen randomly, regardless of whether they were positive or not, to simulate people in panic abandoning their cats out of fear (107) . After 2,000 simulations, it was concluded that the number of infected people varies significantly according to the number of abandoned cats (107) . When no cat was set free, 51 people on average were infected (107) . For one cat set free, 55 people were infected. For five set free, 62 were infected. For 10 abandoned cats, 76 people in the community were infected. This model suggests that abandoning cats can increase the risk of infection among people. The model is still rather superficial, and some of the assumptions are questionable (107) . The likelihood of infection from one cat to another cat was considered to be the same as that of people to people, while transmission between different species is approximately half the probability (107) . These values are probably overstated when it comes to transmission between cats and transmission interspecies (107) . Still, this is a good example of a simulation that can assist in risk assessment and decision making and in the effect of changing some parameters on the incidence of new cases in human patients (107) .
HM, AS, AG, DB, and AB contributed to the conception and design of the study. HM, AS, LK, DB, and AB wrote the first draft of the manuscript. HM, AS, NN, LK, DB, PB, AG, CP-B, and AB wrote sections of the manuscript. All authors contributed to the manuscript revision and read and approved the submitted version.
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The current 2019 coronavirus disease pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major threat worldwide and especially to countries in southeast Asia (1) (2) (3) . A systematic review of 53,000 hospitalized patients indicated that 20.2% of COVID-19 cases developed severe disease with a mortality rate of ∼3.1% (4) . In the elderly and among those with comorbidities, such as cardiovascular disease, chronic kidney disease, and chronic obstructive pulmonary disease, mortality increases significantly (5) (6) (7) (8) . Although some drugs have been used to treat severe COVID-19 patients (9) (10) (11) (12) , no specific therapies have been approved by the US Food and Drug Administration. Development and deployment of a vaccine is therefore one of the most promising strategies in this crisis.
Vaccine development began in several research centers and pharmaceutical companies as soon as SARS-CoV-2 was identified as the causative agent and the first genome sequence was published. On March 16, 2020 , the first COVID-19 vaccine candidate, an mRNA-based vaccine developed by Moderna Inc, entered a Phase 1 clinical trial (NCT04283461) in the US and later a non-replicating vector-based vaccine, developed by China's CanSino Biologics was also tested in China (ChiCTR2000030906) (13) . Other vaccine candidates, including DNA-based vaccines, inactivated, live attenuated, sub-unit, and replicating viral vectorbased vaccines are also being developed (13) . It is unclear how effective these vaccines will be. If the COVID-19 vaccine resembles an influenza vaccine, effectiveness could be 50% or lower (14) . People may have strong preferences for a vaccine to be highly effective (15) , and a vaccine with a low effectiveness estimate could impact people's willingness to be vaccinated. It is also possible that individuals will perceive a pandemic vaccine to be less safe based on its newness or perceived lack of testing (15) . Safety perceptions could also influence vaccine acceptance (16) .
High vaccination coverage globally may be required to stop the COVID-19 pandemic. However, vaccine demand in low-and middle-income countries (LMICs) is less wellstudied and there may be different considerations from the population compared to high income countries (17) . LMICs may have less capacity to introduce new vaccines and may need to deal with citizenry who have hesitant beliefs (18) . Indonesia is a middle-income country with relatively low vaccine coverage and high vaccine hesitancy (18) (19) (20) . Some studies have been conducted to assess acceptance on new vaccines against emerging and re-emerging infectious diseases in southeast Asia, such as for dengue (21) (22) (23) (24) (25) , Zika (26) , and Ebola (27) . No study has been conducted on COVID-19 vaccine acceptance in the region. This study sought to assess the acceptance of a hypothetical COVID-19 vaccine among the general population in Indonesia. The results of this study might be important for the government to formulate the best approach to implement mass vaccination programs for COVID-19 in Indonesia, as well as other countries in southeast Asia region, in the future.
Currently no COVID-19 vaccine is available and therefore we framed the study questions around a hypothetical vaccine, in an approach that was similar to previous studies (21, 26, (28) (29) (30) . Due to limitations in doing face-to-face research during the current active COVID-19 outbreak in Indonesia, we did an online crosssectional study between March 25 and April 6, 2020. The target population was the adult population of Indonesia. The samples were recruited from seven provinces (Aceh, West Sumatra, Jambi, DKI Jakarta, Yogyakarta, and Bali) and all adults who were able to read and understand Bahasa Indonesia were considered eligible. Invitations to participate in the study, hosted by Google Forms, were distributed on the WhatsApp communication platform. This media and communication platform was chosen since 64% of the Indonesian population currently use this platform and the users are relatively varied across age groups and other sociodemographic characteristics. The participants were recruited using a simplified-snowball sampling technique where invited candidate participants were requested to pass the invitations to their WhatsApp contacts. The minimum sample size was 1,068, based on the conservative assumption that the acceptability rate was 50 with a 3% margin of error and a confidence interval of 95%. To recruit the samples, participants were purposefully selected to include both urban and suburban areas.
The survey was estimated to take ∼10 min to complete. To collect the information, a set of questions were constructed and developed. The questionnaire included sections on sociodemographic data, exposure to COVID-19 information, perceived risk of being infected with COVID-19, and acceptance of a vaccine. The questions were first pre-tested and were revised and finalized based on feedback from pre-testers.
The response variable was acceptance of a hypothetical COVID-19 vaccine in Indonesian population. To assess the acceptance, the respondents were provided with the following information: (a) a vaccine is currently not available for COVID-19, but we want study participants to think about a hypothetical vaccine; (b) the hypothetical COVID-19 vaccine would be developed and tested clinically in humans; (c) clinical trials would show that the vaccine had a 5% chance of producing side effects like fever, skin rash and pain; and (d) the government would offer it as a free and optional vaccine. To assess the acceptance rate of the vaccine, the respondents were given two scenarios with different vaccine efficacies (95 and 50%). Participants were asked to respond to the question of whether they would be vaccinated with a new COVID-19 vaccine for each scenario (i.e., for 95 and 50%). The possible responses were "yes" or "no." Some explanatory variables were collected. Sociodemographic characteristics included age, gender, educational attainment, occupation, religion, marital status, monthly income, and type of urbanicity. Age was grouped into five categories (< 20, 21-30, 31-40, 41-50, and >51 years old); educational attainment was grouped into junior/senior school graduates, diploma graduates, and university graduates/post-graduates; and type of job was divided into five groups (civil servant, private sector employee, entrepreneur, student, and retired). Individual monthly income was grouped into < 2.5 million Indonesian Rupiah (IDR), 2.5-5 million, 6-10 million, and more than 10 million (<US$ 154.7, US$ 154.7-US$ 309.4, US$ 371.2-$ 618.8, and >US$ 618.8 using an April 4, 2020 exchange rate). Urbanicity of respondents was divided into rural and urban. Respondents were also asked whether they were working as a healthcare worker (HCW) or not and whether they had heard about COVID-19 prior to the survey. Their perceived risk of being infected with COVID-19 within the next month was assessed on a scale of 0 to 100% using a question based off previous studies (31, 32) , where 0% indicates the lowest while 100% was the highest perceived risk. For statistical analysis the score was classified into five groups: 0, 10-20, 30-40, 50-60, and more than 60%.
A logistic regression model was employed to identify determinants of participants' acceptance of a COVID-19 vaccine. The analysis was conducted for both vaccine efficacies (i.e., 95 and 50%). In the first step, associations between explanatory variables and response acceptance were analyzed separately. In the second step, all variables with p ≤ 0.25 in the first step were included in the adjusted analysis. The significance of crude odds ratio (OR) from univariate analyses and adjusted OR (aOR) in multivariate analyses were assessed at α = 0.05. All analyses were performed using SPSS software (SPSS Inc., Chicago, IL, USA).
The protocol of this study was approved by the Institutional Review Board of the School of Medicine, Universitas Syiah Kuala, Banda Aceh (041/EA/FK-RSUDZA/2020) and the National Health Research and Development Ethics Commission (KEPPKN) of the Ministry of Health of the Republic of Indonesia (#1171012P).
We received 1,402 responses during the survey period; 43 of them were excluded due to incomplete data. More than half of the respondents (698/1,359; 51.4%) were among those aged 21-30 years old and 66.1% of them (898/1,359) graduated from a university ( Table 1) . Overall, 27.6% of respondents (375/1,359) worked in the private sector, 47.5% (645/1,359) earned < 2.5 million (equal to US$ 154.7) each month, and more than 75% (1041/1,359) lived in cities. Almost 40% (533/1,359) of the survey participants believed that they had a 0% risk of being infected with SARS-CoV-2.
If the vaccine was 95% effective, 93.3% participants (1,268/1,359) would like to be vaccinated when it is provided freely by government. However, this percentage decreased to 67.0% (911/1,359) if vaccine efficacy was 50%.
In the first scenario, 95% effectiveness, an adjusted analysis found that being a HCW and having a higher perceived risk were associated with higher acceptance; being retired was associated with less acceptance compared to civil servants ( Table 1) . Those who were working as HCWs were twice as likely to accept a COVID-19 vaccine, aOR: 2.01; 95%CI: 1.01, 4.00, p = 0.048. In addition, those with a high score of perceived risk to be infected (50-60%) had twice the odds of vaccine acceptance compared to those with no perceived risk to be infected in the next month (aOR: 2.21; 95%CI:1.07, 4.59, p = 0.032). Those who were retired were less likely to accept the vaccine compared to those who were working as a civil servant, with the aOR: 0.15 (95%CI: 0.04, 0.63).
With a lower vaccine efficacy (50%), being a HCW was the only characteristic associated with vaccine acceptance. Those who were working as a HCW had 1.57 times greater odds of accepting the vaccine compared to those who were working in non-medical sectors, aOR: 1.57; 95%CI: 1.12, 2.20, p = 0.009 ( Table 2) .
Vaccines are a key strategy to stop the escalation of the COVID-19 pandemic. As of April 8, 2020, there were more than 100 COVID-19 vaccine candidates being developed (33) . This vaccine development is proceeding at a fast pace; prior to March 30, 2020, two vaccine candidates had entered Phase 1 clinical trials (13) while on April 9, five vaccine candidates in total were in Phase 1 clinical trials (33) . In the region of southeast Asia, studies have been conducted to assess the acceptance of a vaccine against infectious diseases (21) (22) (23) (24) (25) (26) 34) . This present study was conducted to understand how the COVID-19 vaccine, when available, will be accepted by the general population in Indonesia, by asking individuals about a hypothetical vaccine-an approach used in many past studies (21, 26, (28) (29) (30) . Understanding vaccine acceptance in Indonesia is important, given the large population and because the country has relatively high vaccine hesitancy for existing vaccines and relatively low vaccination coverage (18, 19) . Characterizing how vaccine efficacy could impact acceptance is also important, given that actual or perceived vaccine efficacy could be relatively low.
Our findings indicated that when the vaccine is provided freely, 93.3 and 67.0% of participants would like to be vaccinated if the vaccine had 95% and 50% effectiveness, respectively. The acceptance rate for the first model (i.e., 95% efficacy) is far higher compared to acceptance of other new vaccines in southeast Asia (21, 22, 25, 34) . This indicates that a majority of the general population in the country are supportive of the COVID-19 vaccine. This is not surprising because this study was started on March 25, 2020, when the number of COVID-19 cases started to sharply increase in Indonesia; 790 confirmed cases have been reported (35) . It should be noted that the acceptance rate was measured under the presumption that the vaccine was provided freely by the government. Therefore, in the case that the vaccine needs to be purchased, or if it is not fully subsided by government, analyses assessing the acceptance at certain vaccine prices (i.e., willingness to pay) will need to be conducted not only in Indonesia but also in other countries in the southeast Asia region. We also note that it is unclear what the herd immunity threshold for COVID-19 is (36) , and 67.0% vaccination coverage may be lower than what is required to stop the spread of disease.
Our study indicated that HCWs were more supportive of a COVID-19 vaccine than non-HCWs. Self-protection and desire to protect family, friends, and patients have been the drivers of HCWs' decision to get vaccinated in previous studies (37, 38) . Since HCWs have more comprehensive knowledge about COVID-19, their relatively high awareness may lead them to protect themselves and not to transmit the virus to their family members. This might lead them to be more willing to accept the vaccine compared to those who working in non-medical sectors. In addition, our further analysis also suggested that the perceived risk of HCWs was higher compared to non-HCWs.
One important finding is that those who had a higher perceived risk to be infected with COVID-19 were more likely to accept the vaccine, but only for the 95% effective vaccine. Previous studies in Asia have found that perceived risk or perceived susceptibility to an infection is associated with positive support for vaccination (29, 30, 39) . Another study also found that high perceived risk was associated with COVID-19 vaccine acceptance among general community members in Saudi Arabia (40) and among HCWs in China (41) . Therefore, it is important to increase the perceived risk among communities since our study found that almost 40% of the respondents had a perceived risk of 0%. Low perceived risk may not only be correlated with vaccine acceptance, but also adherence to social distancing measures and other public health countermeasures. These relationships may be complicated-for example, an individual highly compliant with social distancing measures may perceive their risk to be low but still want to obtain a vaccine.
We also found that being retired had low acceptance compared to those who were working as civil servant. Lower vaccine acceptance among the retired population might be influenced by lower perceived risk. Although the elderly are more vulnerable to COVID-19, most of the retired population in Indonesia and indeed in southeast Asian countries have low mobility and spend more time at home with less travel. These behaviors may lead them to having a lower perceived risk of being infected with SARS-CoV-2, and eventually may lead to lower acceptance of a vaccine. Moreover, their acceptance might also be influenced by knowledge about the disease. Much of the information about COVID-19 is spread through social media or online media, which is less frequently accessed by older adults. Therefore, older adults might have less exposure to information about COVID-19 that could contribute to framing their risk perception. In addition, less social media use might also be associated with less knowledge among the elderly and this could affect their perceived risk and vaccine acceptance. However, this study did not measure respondents' knowledge of COVID-19 and we were unable to elucidate these relationships.
The study has several limitations. Generalizability of the survey results may be impacted by how we distributed the questionnaire. We used the WhatsApp platform, and so it may miss people from lower socioeconomic classes such as farmers, those with lower educational attainment, and those who were illiterate. According to UNESCO Indonesia, the literacy rate of adults (aged 15 and above) was 95.98% (42) and previous studies using community samples found that at least 96% of the community graduated from primary school (26, 43) . As reported in other online studies in Indonesia (44) (45) (46) (47) , selection bias could also be related to the sampling technique and differential access to internet infrastructure across the country, as some regions have better internet access than others. Finally, acceptance was assessed using a hypothetical vaccine, which may differ from the respondents' revealed preferences in a reallife situation.
Acceptance of the COVID-19 vaccine in Indonesia is influenced by the effectiveness of the vaccine. Acceptance is relatively high when the vaccine has a very high effectiveness, but it reduced to only 67.0% when the vaccine efficacy is 50%. If the COVID-19 vaccine has lower efficacy, governments will have to introduce more strategies to persuade their population to become vaccinated. In addition, since acceptance is associated with perceived risk for COVID-19, it is also important to increase the perceived risk in communities.
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: http://doi.org/10.6084/ m9.figshare.12477143.
The studies involving human participants were reviewed and approved by Institutional Review Board of the School of Medicine, Universitas Syiah Kuala, Banda Aceh (041/EA/FK-RSUDZA/2020) and National Health Research and Development Ethics Commission (KEPPKN) of the Ministry of Health of the Republic of Indonesia (#1171012P). The ethics committee waived the requirement of written informed consent for participation.
HH: conceptualization, methodology, software, data curation, formal analysis, resources, writing-original draft, writing-review and editing, project administration. AW: conceptualization, methodology, writing-review and editing. AY: methodology, writing-original draft, investigation, data curation, writing-review and editing, project administration. WW: methodology, investigation, project administration, data curation. SA: software, formal analysis, writing-review and editing. AG: investigation, project administration. AS: investigation. YR: writing-review and editing. HS: software, writing-review and editing. MM: project administration. All authors contributed to the article and approved the submitted version.
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Apoptosis is known to participate in various biological processes and is the basis for the meticulous elimination of potentially harmful cells, such as autoreactive immune cells that attack the body's own cells, or neurons that have failed to properly connect (Jacks and Weinberg, 2002) . Apoptosis also defends against infection and virus-infected cells. In contrast to necrosis, apoptosis is a programmed cell death. The apoptotic program can be triggered by ionizing radiation , chemotherapeutic anticancer drugs (Engels et al., 2000) and by natural product-derived supplements (Wieder et al., 2001; Khan et al., 2007) . The morphological characteristics include cell shrinkage, membrane blebbing, chromatin condensation, and nuclear fragmentation. Failures in apoptotic pathways can lead to uncontrolled cancerous growth. Thus, the proteins preventing the death of cancer cells are common drug targets. One important pathway in the apoptotic mechanism is the Fas-Fas ligand-mediated pathway. The Fas ligand is a cellsurface protein expressed by activated natural killer cells and cytotoxic T lymphocytes; it acts through Fas, which is an important cell-surface death receptor. The Fas ligand has a single transmembrane domain and is activated when ligand binding brings three receptor molecules into close proximity. The trimeric receptor complex attracts a protein called the Fas-associated death domain (FADD), which is an adapter that recruits and activates caspase-8. Cleavage of procaspase-8 induces the cleavage and activation of execution caspase-3, leading to apoptosis of mitochondrial-independent cells (Peter and Krammer, 2003) . Another important pathway is related to receive the death signals including the proapoptotic proteins (Bax and Bid) in the cytoplasm that bind to the outer membrane of the mitochondria to signal the release of cytochrome C with the assistance of Bak. Following its release, cytochrome C forms a complex in the cytoplasm with adenosine triphosphate (ATP) and Apaf-1. The complex activates caspase-9, which in turn activates caspase-3. The caspase-3 activation leads to apoptosis in a mitochondrial-dependent pathway (Prokop et al., 2000) .
Traditional herbal medicines have been used for centuries, some of which have proven to be clinically effective in the treatment of many kinds of cancers. The mechanisms of action of extracts or compounds from herbal medicines have been elucidated in different ways. After many years of research, certain compounds which have anticancer effects have been identified, such as, saponins (Luo et al., 2008) , polysaccharides (Ibrahim et al., 2008) , terpenoids (Jayaprakasha et al., 2008) , alkaloids (Magedov et al., 2008) and flavonoids (Topcu et al., 2008) . These kinds of compounds have cytotoxic effects on cancer cells, inhibit DNA synthesis, arrest cell cycle, modulate apoptotic and anti-apoptotic genes, or inhibit invasion and metastasis. Recently, black cohosh, the extract of C. racemosa, which is closely related to C. heracleifolia, has become increasingly popular as a dietary supplement in the United States for the alleviation of symptoms related to menopause (Radowicki et al., 2006) . The extract of C. heracleifolia has many uses, such as in apoptosis (Tian et al., 2007) , as an anticancer agent (Tian et al., 2006) or an anti-coronavirus (Kim et al., 2008) . It also has anti-allergic and estrogen-like activities (Kim et al., 2004) . Ferulic acid and isoferulic acid, both from C. heracleifolia, were reported as having an anti-inflammatory effect (Sakai et al., 1997; Hirabayashi et al., 1995) . To determine which component is responsible for the anti-cancer effect, several compounds isolated from C. heracleifolia were studied. Of these compounds, cimiside E showed a highly potential effect on apoptosis in AGS cells. In this study we focused on the apoptotic mechanism of cimiside E in AGS gastric cancer cells through cell cycle arrest.
The roots of C. heracleifolia were purchased and identified by Professor Je Hyun Lee, Dongkuk University in Kyungjoo, Korea. The dried roots of Cimicifuga Rhizome (10.35 kg) were percolated with methanol (MeOH) three times and concentrated in vacuo. The residue (1.43 kg) was suspended in H 2 O and partitioned successively with hexane, CH 2 Cl 2 , ethylacetate (EtOAc), and butanol (BuOH), yielding hexane (101.09 g), CH 2 Cl 2 (232.07 g), EtOAc, (115.93 g) and BuOH (112.24 g) soluble fractions, respectively. A portion of the EtOAc fraction (100 g) was subjected to a silica gel column chromatography eluted with a stepwise gra-dient of CH 2 Cl 2 : MeOH to yield ten fractions (E1~E10) ordered by their polarities. Fraction E7 was chromatographed again on a silica gel column and eluted with gradient mixtures of CH 2 Cl 2 and MeOH to give three subfractions (E7.1~E7.3). Then, E7.3 was chromatographed again on an RP-18 column eluted with a gradient mixture of MeOH and H 2 O to give two subfractions (E7.3.1~E7.3.2). E.7.3.2 was recrystallized with MeOH, resulting in pure cimiside E. The structure of cimiside E was verified by the comparison of NMR data with those in the literature ( Fig. 1) (Li et al., 1994) . The purity of the compound was assessed 98% based on the HPLC analysis. The HPLC analysis of cimiside E was accomplished on a Waters 2695 instrument (Milford, MA, USA) equipped with a refractive index detector (Waters 2414). An Alltech-Grom C 18 column (150 × 4.6 mm, 5 µm particle size, Rottenburg-Hailfingen, Germany) was used at 30 o C. Isocratic elution was carried out using acetonitrile : water (80:20) at a flow rate of 0.8 mL/min.
AGS cells (human gastric adenocarcinoma cells) were obtained from the American Type Culture Collection. RPMI 1640 medium, Dulbecco's phosphate buffer saline (D-PBS) and dimethyl sulfoxide were acquired from Sigma Chemical Co. Cell Counting Kit-8 (CCK-8) was purchased from Dojindo Laboratories. The nitrocellulose membrane (NC membrane) was obtained from Whatman GmbH. An enhanced chemiluminescence (ECL) detection kit was purchased from LabFrontier. Other chemicals and solvents were obtained from Aldrich Chemical Co. The primary antibodies for procaspase 3, Bax, Bcl-2, and β-actin and the secondary antibody were acquired from Santa Cruz Biotechnology (Santa Cruz). All of the samples, solutions and buffers were prepared in deionized water.
AGS cells were incubated in RPMI 1640 medium at 37 o C under 5% CO 2 in humidified air. The cells were seeded into 96-well plates at a density of 1×10 4 cells/ well and allowed to adhere for 24 h, also at 37 o C under 5% CO 2 . After incubation, cells were treated with compounds for 12, 24, and 48 h, and then 10 µL of CCK-8 solution was added to each well, followed by incubation for 2 h at 37 o C. The resulting color was assayed at 450 nm using an Emax microplate reader (Molecular Devices).
AGS cells (1×10 6 cells/well) were treated with cimiside E (30, 60, and 90 µM) for 6, 12 and 24 h. Adherent and floating cells were collected and washed with cold D-PBS. The cells were lysed with Triton X-100 lysis buffer (40 mL of 0.5 M EDTA; 5 mL of 1 M TrisCl buffer; pH 8.0; 5 mL of 100% Triton X-100; 50 mL of H 2 O), and incubated for 20 min on ice before being centrifuged. The supernatant was transferred into a new 1.5 mL Eppendorf tube and then extracted with a 1:1 mixture of phenol:chloroform (gentle agitation for 5 min followed by centrifugation) and precipitated in two equivalences of cold ethanol and one-tenth equivalence of sodium acetate. The precipitates were centrifuged, decanted and resuspended in 30 µL of deionized water-RNase solution (0.4 mL of water + 5 µL of RNase) and 5 µL of loading buffer for 30 min at 37 o C. All of the DNA was loaded on a 1.5% agarose gel containing ethidium bromide. After electrophoresis, the gel was visualized under a ultraviolet transilluminator.
The effect of cimiside E on AGS cell cycle phase distribution was assessed using flow cytometry. Briefly, cells (1 × 10 6 cells/well) were seeded in 6-well plates and incubated for 24 h. After treatment with cimiside E (30, 60 and 90 µM) for 3, 6, 24 h, cells were collected and washed with D-PBS. Then cells were centrifuged and the pellet was resuspended in 50 µL cold PBS, followed by an addition of 1 mL of D-PBS at room temperature. The full volume of resuspended cells was transferred to 4 mL of absolute ethanol at -20 o C by pipetting the suspension slowly into the ethanol while vortexing at top speed. The cells were restored in ethanol at -20 o C overnight. The cells were then collected by centrifugation. The pellet was washed with cold D-PBS, suspended in 500 µL PBS and incubated with 5 µL RNAase (20 µg/mL) at room temperature for 30 min. The cells were stained with PI (50 µg/mL) for 15 min and then analyzed by flow cytometry.
The Annexin V-FITC/PI apoptosis detection kit (BD Bioscience) was used to detect the effects of cimiside E. AGS cells (1 × 10 6 cells/well) were seeded in 6-well plates and incubated for 24 h. After treatment of cells with cimiside E (30, 60 and 90 µM) for 24 h, adherent and floating cells were collected and washed with D-PBS, then cells were centrifuged. The pellet was suspended with 1 × binding buffer (100 µL). The cells were stained with Annexin V (5 µL) and PI (5 µL), and incubated for 15 min at room temperature in the dark. After incubation, cells received 400 µL 1 × binding buffer and then were analyzed with FACS Vantage SE (Becton Dickinson) using CellQuest Software, which can determine the percentage of apoptotic cells. PI was excited at 488 nm, and fluorescence was analyzed at 620 nm.
AGS cells (1 × 10 6 cells/well) were treated with compound for 3, 6, 12, and 24 h. After incubation, total cytoplasmic extracts were lysed as described previously (Zhou et al., 2007) and SDS-PAGE was performed. Proteins were transferred onto NC membranes. After blocking with 5% skim milk, the membranes were incubated with primary and secondary antibodies, in series. Finally, the blot was developed using WEST-SAVE Up luminal-based ECL reagent (LabFrontier). The intensity of each band was quantitatively determined using UN-SCAN-IT TM software (Silk Scientific), and the density ratio showed the relative intensity of each band compared to the controls in each experiment.
AGS cells were incubated with compound for 1, 3, and 6 h. Total RNA was extracted using the Easy-BLUE TM Total RNA Extraction Kit (Intron Biotechnology). The RT-PCR was performed using the ONE-STEP RT-PCR PreMix kit TM (Intron Biotechnology) for 20 cycles, with each cycle consisting of 1 min at 94 o C, 1 min at 55 o C, and 1 min at 72 o C. The primers used for β-actin amplification were: sense 5'-AATCTG-GCACCACACCTTCTACA-3' and antisense 5'-CGA-CGTAGCACAGCTTCTCCTTA-3', the primers for FasL were: sense 5'-CAACTCAAGGTCCATGCCTC-3' and antisense 5'-AGATTCCTCAAAATTGACCAG-3', the primers for Fas receptor were: sense 5'-GACAA-AGCCCATTTTTCTTCC-3' and antisense 5'-ATTTAT-TGCCACTGTTTCAGG-3'. The RT-PCR products were separated by electrophoresis using a 1.5% agarose gel stained with ethidium bromide, and the gels were viewed under a UV transilluminator.
The results were expressed as means ± S.E.M. Differences in mean values between groups were analyzed by a one-way analysis of variance (ANOVA) and Student's t-test. For the septic shock assay, we used the log-rank test. Statistical significance was assessed as p < 0.05 [*p < 0.05; **p < 0.01; ***p < 0.001].
Cimiside E has a strong cytotoxicity on AGS cells. When cells were treated with cimiside E (30, 60 and 90 µM) for 12, 24 and 48 h, the IC 50 values were 28.7, 14.6 and 8.1 µM, respectively. The effect of cimiside E on cell viability is shown in Fig. 2 .
AGS cells treated with cimiside E (30 µM) for 24 h showed clearly condensed chromatin, and cells treated with cimiside E (60 and 90 µM) for 24 h showed chromatin condensation and nuclear fragmentation (Fig. 3) .
As shown in Fig. 4 , cells treated with cimiside E for 6 h at the concentration of 30 µM showed an unobvious DNA fragment ladder, and at 60 µM showed an obvious DNA ladder. Furthermore, cells treated with 4 . Cimiside E induced DNA fragmentation of AGS cells. Cells were treated with cimiside E (15, 30 and 60 µM) for 6, 12 and 24 h. To extract DNA, AGS cells were lysed with Triton X-100 lysis buffer. Then total DNA was loaded on a 1.5% agarose gel with ethidium bromide staining. After electrophoresis, the gel was visualized under a ultraviolet transilluminator. cimiside E over 6 h at each concentration of 15, 30 and 60 µM showed significant DNA ladders, which indicated that many of the cells were dying due to apoptosis.
The cells with DNA content in sub-G1 phase were apoptotic cells. As shown in Fig. 5A , the percentage of sub-G1 cells was 1.87, 3.97, 17.05 and 43.37% at 0, 30, Fig. 6 . Annexin V/PI analysis on cimiside E-induced apoptosis in AGS cells. The Annexin V-FITC/PI apoptosis detection kit (BD Bioscience Clontech) was used for detection of the effects of cimiside E. Cells (1 × 10 6 cells/well) were seeded in 6-well plates and incubated for 24 h. After treatment of cells with cimiside E (30, 60 and 90 µM) for 24 h, adherent and floating cells were collected and washed with D-PBS. After cells were centrifuged, the pellet was suspended by 1×binding buffer (100 µL). Then the cells were stained with annexin V (5 µL) and PI (5 µL), respectively, and incubated for 15 min at room temperature in the dark. After incubation, 400 µL of 1 × binding buffer was added and the cells were analyzed with FACS Vantage SE (Becton Dickinson), using CellQuest Software, which can determine the percentage of apoptotic cells. PI was excited at 488 nm, and fluorescence was analyzed at 620 nm. 60 and 90 µM for 24 h, respectively. The G2/M phase distribution was 14.46, 13.94, 18.50 and 20.31%, at 0, 30, 60 and 90 µM for 24 h, respectively. Cimiside E treatment induced G2/M phase arrest at 60 and 90 µM. However, the cells treated with cimiside E at 30 µM for 24 h had a different result. The data showed that it induced S phase arrest not G2/M phase arrest, and the S phase distribution was 27.48 and 33.00% at 0 µM and 30 µM for 24 h. To further confirm it (Fig. 5B) , AGS cells treated with cimiside E at 30 µM for 0, 3, 6 and 24 h were analyzed. The results showed that the S phase distribution was 24.49, 24.72, 26.82 and 35 .53%, respectively. Therefore, cimiside E induced S phase arrest at a low concentration (30 µM) and induced G2/M phase arrest at high concentrations (60 and 90 µM) in AGS cells.
Annexin V specifically binds to phosphatidylserine and was employed for determination of apoptotic cells. When PI is excluded from viable cells binds to DNA, it can stain the late apoptotic and necrotic cells. After AGS cells were treated by cimiside E (0, 30, 60 and 90 µM) for 24 h, cells were stained with annexin V/PI and examined under a fluorescence microscope. Early and late apoptosis and necrotic cells were distinguished. The corresponding quantities of total cell apoptosis and early apoptosis were 21.26 and 6.10%; 24.10 and 9.26%; 35.68 and 13.10%; 65.34 and 9.50%, respectively. The data demonstrated that apoptotic cells were found to be increased in a dose-dependent manner (Fig. 6) .
RT-PCR analysis indicated that cimiside E (30 and 60 µM) leads to the active expression of FasL at 3 h and Fas from 1 h (Fig. 7) .
Western blot analysis determined that the ratio of Bax/Bcl-2 expression is increased from 60 µM. The expression of mutant type (mt) p53 decreased from 12 h at 30 µM. The expression of procaspase 3 significantly decreased in a dose-dependent manner from when treated more than 30 µM (Fig. 8 ).
Cell proliferation is governed by a cell cycle, which is a target of many anti-cancer agents. Based on the result of viability assay, cimiside E has a strong cytotoxicity in AGS cells. When cells were treated with cimiside E (30, 60 and 90 µM) for 12, 24 and 48 h, the cell viability curve was like a log scale with dose at each time point, in accordance with characteristics of cell cycle specific chemotherapeutic drugs (Patrick, 2005) . The data from cell cycle analysis showed that AGS cells were arrested in S phase by cimiside E at a lower concentration (30 µM) and G2/M phase at higher concentrations (60 and 90 µM). Therefore, cimiside E is considered to be a cell cycle specific inhibitor. From the western blot analysis, the expression of mutant type p53 significantly decreased from 12 h at 30 µM, which can slow down the proliferation of AGS cells (Duan et al., 2008) . In addition, the ratio of Bax/Bcl-2 increased significantly at 24 h after treatment with 60 Fig. 7 . Effects of cimiside E on Fas and FasL expression in AGS cells. Cells (1 × 10 6 cells/well) were treated with cimiside E (30 and 60 µM) for 1, 3 and 6 h. The equal loading was confirmed by stripping the immunoblots and reprobing them for β-actin. Fig. 8 . Effects of cimiside E on mt p53, procaspase 3, Bax and Bcl-2 protein expression in AGS cells. Cells (1 × 10 6 cells/well) were treated with cimiside E (30, 60 and 90 µM) for 3, 6, 12 and 24 h. The equal loading was confirmed by stripping the immunoblots and reprobing them for β-actin. and 90 µM cimiside E. Therefore, cimiside E has an apoptotic effect on AGS cancer cells through mitochondrial-dependent and mitochondrial-independent pathways of cell cycle arrest. We propose the mechanism in which cimiside E inhibits AGS proliferation by cell cycle arrest in S phase and induces apoptosis through activation of the caspase cascade in both extrinsic and intrinsic pathways, including upregulation of Fas and FasL expression and increasing the ratio of Bax/Bcl-2 in AGS cells. Apoptosis and cell cycle arrest could be attributed to its anti-proliferative effects. These results suggest that cimicide E might be a promising anti-cancer agent.
In conclusion, clarification of the mechanisms of cimiside E on AGS cells and capturing the timedependency of dose-response curves are helpful for potential clinical extrapolation and it is thought to decrease the damage to normal cells in treating less than 15 µM for inhibiting cancer cell proliferation.
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been identified in bat populations for which the zoonotic potential is unknown, including novel influenza types and hepadnaviruses [26, 27] . As a result, there has been well-grounded speculation that owing perhaps to physiological, ecological, evolutionary, and/or immunological reasons, bats may have a "special" relationship with viruses [15, 28, 29] and be particularly good viral reservoirs with exaggerated viral richness [30] . Indeed, a recent intensive study found that a single bat species likely carries ≥58 different viral species from only nine viral families [31] . As well as the obvious first step of considering the zoonotic potential of newly identified bat viruses, further exploring the impacts of these findings and the opportunities they present for multiple research fields is necessary to capitalize on these discoveries. Poxvirus infections have recently been identified in bats, comprising part of the increase in viral families newly identified in this taxonomic order. Here, we review the current evidence of poxvirus infections in bats, present the phylogenetic context of the viruses within the Poxviridae, and consider their zoonotic potential. Finally, we speculate on the possible consequences and potential research avenues opened following this marrying of a pathogen of great historical and contemporary importance with an ancient host that has an apparently peculiar relationship with viruses; a fascinating and likely fruitful meeting whose study will be facilitated by recent technological advances and a heightened interest in bat virology.
There are three documented detections of poxviruses in bat populations under distinct circumstances (summarized in Table 1 ). The viruses were detected in animals from both bat suborders on three different continents. They had varied clinical impacts on their hosts and were phylogenetically dissimilar.
Genetic sequence of one bat poxvirus was detected at high prevalence during active surveillance on apparently-healthy African straw-colored fruit bats (Eidolon helvum) [32] . Metagenomic analysis of pooled throat swabs collected from E. helvum in Ghana in 2009 contained poxvirus sequences most closely related with Molluscum contagiosum (MOCV) a human-only pathogen ( Figure 2 ). Detected sequences were distributed across the MOCV genome and reconstructed sequences relating to 23 viral genes were deposited in GenBank as being derived from Eidolon helvum poxvirus 1 [32] . Retrospective analysis of throat swabs from individual bats revealed a high prevalence of this virus in the apparently healthy study population with 13% (n = 5/40) of swabs containing poxviral DNA. Notably, the detection of true poxvirus sequences in this metagenomic study, in which sequences related to multiple genes distributed throughout the genome were found and reconfirmed in individual throat swab samples, is distinct from the detection of poxvirus-like sequences described in other metagenomic studies performed on pooled bat feces, whose presence was ultimately attributed to the presence of other (non-pox) viruses or viral elements integrated into host genomes [33, 34] .
Between 2009 and 2011, a poxvirus associated with pathology (tenosynovitis and osteoarthritis) was detected in six adult big brown bats (Eptescicus fuscus, a microbat) sampled at a wildlife center in the North Western United States [35] . The clinical illness of the bats was progressive and ultimately led to their euthanasia. Histopathological examination of the joint lesions was indicative of poxvirus infection, which was confirmed by electron microscopy. The virus was successfully isolated on an African Green Monkey cell line (BSC40) and the genome was partially characterized (seven full protein coding sequences). Phylogenetic analysis revealed that the novel Eptesipox virus was most closely related with Cotia virus, a virus detected in sentinel suckling mice in Sao Paulo, Brazil in 1961 ( Figure 2 ) [36, 37] .
Finally, a bat poxvirus was again detected in a clinical setting, in South Australia in 2009. The virus was identified as an incidental infection during investigation of an outbreak of parasitic skin disease in a population of Southern bentwing bats (Miniopterus schreibersii bassanii, a critically-endangered microbat species) [38] . Bats presented with white nodular skin lesions that contained encysted nematodes. However, in one of the twenty-one bats examined, an independent (non-nematode associated) lesion contained intracytoplasmic inclusion bodies indicative of poxvirus infection, which was confirmed with electron microscopy [38] . No further confirmation or characterization of the virus was reported, and both the epidemiology and consequent conservation implications of poxviral disease for this species remain unknown.
The three detections of poxviruses in bat populations are distinct and inherently incomplete stories with very few common threads; high-prevalence detection in throat swabs from apparently healthy African megabats, severe joint disease in several North American microbats and, negligible though comorbid skin disease in an endangered Australasian microbat. Further to their varied clinical impact, the partial genetic characterization of the former two viruses shows that these viruses are genetically diverse. The two viruses are most closely related with the very distinct poxviruses, Molluscum contagiosum virus and Cotia virus respectively (Figure 2 ), and although only partially genetically characterized, a small (100 amino acids) region of overlap in their RAP94 proteins has only 62% amino acid identity (please see Table S1 in the Supplementary files). That this is as far as these new viruses can be contrasted demonstrates the dearth of information currently available for further investigation of poxviruses in bats.
The finding of poxviruses in bats is not unique among wildlife taxa (in fact it would have been more surprising had they not been found to carry poxviruses) and there is no reason to believe they would have greater zoonotic potential than other animal poxviruses. Poxviruses with varying zoonotic potentials have been found in a broad range of wildlife taxa including hundreds of bird species, reptiles, marine mammals, macropods, marsupials, monotremes, ungulates, equids, and primates [1, 2, 5, [39] [40] [41] [42] and there is currently insufficient evidence available to determine what the zoonotic potential of bat poxviruses might be on this spectrum. For example, although Eidolon helvum poxvirus 1 is closely related to MOCV, a human-only contagion, poxvirus-associated lesions mirroring MOCV-disease have also been found in horses, donkeys and a red kangaroo [41] [42] [43] . Similarly, the discovery of Eptesipox virus in North American brown bats is analogous to the discovery of the other North American poxviruses found in voles, skunks, raccoons and squirrels, which are also detected at high prevalence in their reservoir hosts [44, 45] . Notably however, in the initial Eptesipox virus report, the authors comment that poxvirus infection manifesting as musculoskeletal disease (osteomyelitis) has also been reported in human VARV and Vaccinia virus (VACV) infections [35] . However, given that no bat poxviruses identified to date are orthopoxviruses, and the little information available, it is clear that much more detail is needed before the potential threat of bat poxviruses to man can be commented on. Notably however, the two hosts in which poxviruses have been identified are widely distributed across their respective continents (Africa and North America) and both habit urban areas, so have ample opportunities for contact with potential spillover hosts (i.e., humans and domestic animal species).
To determine the zoonotic risk posed by bat poxviruses there are, as for other novel viruses, a number of obvious and relatively straightforward investigations that can be done. Full genomic characterization of these viruses to identify known and putative poxvirus host range genes (discussed further below) would be an obvious step. Similarly, testing the in vitro host range of isolated viruses such as Eptesipox virus would help inform whether human and further animal cell lines are permissive for infection (i.e., that they contain the necessary host factors to support infection and do not contain antiviral components that restrict infection). Serological and clinical surveillance of human populations for poxvirus infections in geographical regions near detection sites, and/or overlapping with bat home ranges would be a direct approach that would provide samples useful for evaluating multiple candidate zoonoses. Whether bat poxviruses pose a zoonotic threat will likely comprise part of the future research agenda as these investigations are prudent for the discovery of all novel viruses. However, our current knowledge on bat poxviruses does not allow us to make firm predictions about their ability to infect humans.
Irrespective of their potential role as zoonotic agents however, the study of poxviruses in bats opens unique avenues of highly relevant research for multiple research fields beyond the individual host-pathogen relationships. Further field (in situ), in vitro and in silico studies could elucidate the possible coevolution, cross species infections and mechanisms of host range restriction of bat poxviruses, the implications of which are relevant for bat ecologists, virologists and emerging infectious disease specialists (including those with a specific interest in bats) alike.
It is likely that comparative phylogenetics of bats and poxviruses would inform and deepen our understanding of origins and evolution of both elements. Bats and poxviruses are diverse host and pathogen taxa respectively and given their 0.5 million years of likely co-existence [46] , there is surely a vast amount of knowledge to be gained by studying the phylogenetic relationships between bats and poxviruses. Further sampling of bat populations for poxviruses would undoubtedly dramatically expand the poxvirus phylogeny, as has occurred subsequent to the study of other viral taxa in bat populations [47] [48] [49] [50] [51] [52] [53] . Comparative phylogenetics of bats and their poxviruses could differentiate between ancient co-speciation, or a more recent introduction and dissemination, of poxviruses among bat species. The two thus far partially characterized bat poxviruses are quite distinct from each other and are both relatively basal (i.e., have older most recent common ancestors with other extant viruses) in the poxvirus phylogeny when compared with other mammalian-infecting poxviruses. It is possible that if evidence of coevolution between bats and poxviruses were present, as has been suggested for the North American poxviruses [44] , this could inform the phylogenies of both bats and poxviruses which are complicated by convergent evolution and horizontal gene transfer respectively [54] [55] [56] . In addition to allowing the study of co-evolution, such studies provide the context for the identification of cross-species infections.
With concerted research effort to identify reservoir species of bat poxviruses and cross species infections of poxviruses in bats could be identified and would have important implications for both bat and zoonotic-disease specialists. Continued serological and molecular studies of naturally infected bat populations would allow the clinical effect and ecological impact of cross species poxvirus infections in bats to be assessed. We already noted that poxvirus infections across species barriers can devastate wildlife populations (e.g., squirrelpox, see introduction), an effect so severe that it was used to control introduced rabbit species in Australia in the 1950s [57] . White nose syndrome, a fungal pathogen causing massive die offs in North American bat populations, is an unfortunate contemporary example of the severe ecological impacts that emerging pathogens can have on bat populations [58, 59] . Hence, from an ecological perspective if a bat poxvirus, e.g., Eptesipox virus with its severe disease manifestations, were an emerging cross-species infection it would be useful to identify this rapidly, especially in already endangered species as is the case of the Southern bentwing bat in which a poxvirus was reported. Further to the conservation implications of such research, combining data regarding cross species infection and ecological aspects of host taxa (e.g., behavior, habitat, range overlap, host relatedness) will likely inform key concepts of virus sharing among bat species, as has been done with lyssaviruses [60, 61] .
Given the heightened interest in bat virology, further analysis of bat poxviral isolates from both within-and cross-species infections will allow for a deeper understanding of the extent and mechanisms of poxvirus host restriction. Many bat cell lines have now been developed [62] [63] [64] [65] [66] , and at least one of these allows productive poxvirus infection [62] . Such tools will allow the in vitro refinement of host range definitions beyond detection in the field. Furthermore, full genome sequencing information of poxviruses (now a comparatively easy and cost effective task) would facilitate the in silico identification of poxvirus host range gene orthologues, as recently done by Bratke and colleagues who performed a systematic survey for the presence of known poxviral host range genes on among chordopoxviruses [3] . Furthermore, applying new bioinformatics tools to genomic sequence information and host range data could facilitate the identification of novel host-range determinants, perhaps even unique to bat poxviruses [12, 67] . In addition, with the aforementioned in vitro tools in place, hypothetical host range genes can be validated, advancing our fundamental knowledge of poxvirus host range restriction.
Finally, and most speculatively, the identification of genes involved in poxvirus host range restriction in bats may represent a unique opportunity to study bat immunology, which may have broader implications for their confirmed roles as zoonotic reservoirs. Since genes that interplay with the host innate immune system, not those involved with cell entry, are typically responsible for host range determination in poxviruses [8, 9] , the identification of bat-unique poxvirus host range genes could facilitate the cognate identification of (possibly novel) host immune factors. This is particularly important for bats as they potentially have antiviral immunity distinct from our own, which seemingly allows them to harbor numerous human pathogens viruses asymptomatically [29] . Some preliminary evidence of this distinction existing for poxviruses is that in the single described report of infection of bat cell lines with poxviruses, bat cells were found to behave very differently from other mammalian cell lines, being susceptible to a highly attenuated strain of vaccinia virus [62] . With several bat genomes recently sequenced [68] and the capabilities of newer proteomic approaches, it is realistic that novel non-orthologous innate immune factors of bats (if they exist) could be identified. That these novel immune factors might then be candidate therapeutics against a range of viral zoonoses for which bats are the natural reservoir is an exciting, if not fantastical, point to ponder.
Recent advances in the study of bats and their viruses as well as the current biotechnological revolution leave us in a position to explore questions of virology as never before. The recent detection of poxviruses in some bat species has occurred consequent to a heightened interest in bats" role as viral reservoirs. These new findings enable us to ask many exciting and important questions about both bats and poxviruses independently as well as their ecological and evolutionary relationships. Integrating the new and exciting tools of the "omics revolution with traditional laboratory and field studies allow us to interrogate these questions as never before.
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limitations of text-based feedback, when it is used, and conclude that audio/video feedback could improve feedback, especially in blended and online courses. However, they point out that video feedback is under researched, especially in terms of instructor perceptions, which led them to conduct a mixed method study to examine students and instructors' perceptions of video and text-based feedback in a blended learning environment.
Online educators have experimented with video feedback for years (see Lowenthal & Mulder, 2017) , but Borup et al. were one of the first to conduct a comprehensive investigation of instructor and student perceptions of video feedback across multiple courses, instructors, and students. It is easy to get enamored with video. However, Borup et al. sought to compare perceptions of text and video feedback-recognizing benefits of both. While they found no significant difference between perceptions of quality and delivery, they did find that students and instructors thought text-based feedback was more efficient and provided more specific critiques than video but that video encouraged and provided more supportive and conversational communication. In the end, both students and instructors valued the efficiency of text feedback over the affective benefits of video feedback. Borup et al. highlight that while feedback is important, not all assignments require the same format, amount, or depth of feedback. They also point out that providing video feedback can take more time (for both the instructor and students) and might not always be appreciated by students. However, participants in their study, who were taking blended courses, acknowledged affective benefits of video feedback, which might be even more pronounced for students taking online courses in fully online programs-especially during an usually stressful time, such as a global pandemic when students might need and benefit from added affective support.
Based on this study, one could conclude that video feedback is not worth the time or effort. However, this would miss some key points Borup et al. make throughout their article. Students taking online courses often report feeling isolated or alone (Kaufmann & Vallade, 2020) , which is likely to increase in the coming months due to COVID-19. However, as Borup et al. found in this study, and previous research suggests, asynchronous video can help increase affective communication which can help establish and increase social presence (see Borup, West, & Graham, 2012; Lowenthal, 2014; Lowenthal & Dunlap, 2018) , which research suggests in turn can decrease loneliness and increase retention in online courses (see Boston et al., 2009; Liu, Gomez, & Yen, 2009 ). Therefore, even if providing video feedback takes instructors more time and some students might find it inconvenient to watch, I contend that the affective benefits alone may make it well worth the effort for all parties involved.
Feedback offered in a video feedback format, though, is not automatically effective or useful simply because it is in a video format. There are things instructors can do to improve their use of video feedback. First, be strategic about when and if you use video feedback by identifying which assignments students might benefit the most from video vs. text feedback. This might be assignments that are visual in nature (e.g., a multimedia presentation or website), dense or nonlinear (e.g., a spreadsheet), and/or assignments where formative feedback can be provided earlier in a course (e.g., on a rough draft of a paper) that can then help students make improvements for a final version of the assignment that is turned in later in the course. Second, identify the type of video feedback to provide. Learning management systems, like Canvas and Blackboard, enable instructors to give video feedback that records the instructor talking via a webcam. But as Borup et al. acknowledge, screencasting video feedback might enable instructors to be more specific with the feedback they provide by showing students what the instructors are commenting on which can in turn end up providing more detailed and rich feedback than text-based feedback. Screencasting video feedback, depending on how it is shared with students, can also be saved and referenced by a student even after a course is over, unlike video feedback recorded and stored in a LMS. [Note: Overtime, though, I suspect and hope that educational technology companies are likely to create new products that might combine the benefits of webcam and screencasting video feedback and even ways to add additional benefits of video feedback, such as the ability to comment or discuss feedback further.] Third, instructors should practice using video feedback to increase their comfort level, decrease technical issues, and ultimately improve their use of it. For instance, it is helpful to first review the assignment, then take notes on what to talk about and focus on, then do a sample recording to verify that everything is working correctly before recording the final feedback. Finally, instructors should focus on keeping their feedback relatively short (e.g., 3-5 min) to help offset efficiency issues instructors or students might encounter with video feedback; writing notes before hitting record can also help with this, as can keeping a list of recurring issues one might notice with previous students to address.
All research has limitations and constraints. Borup et al. do a good job of recognizing most limitations of their research. Readers should also keep in mind that this is just one study; further research is needed to better understand video feedback. The most notable limitations and constraints of this study, from my perspective, are due to context. This study was conducted in three 1-credit teacher education blended courses taught at a residential university. Instructors and students in fully online courses, and especially fully online programs, likely might have different perceptions of video feedback when this form of interaction might be one of the only one-on-one instructor-student interactions during a course. Also, older students completing a professional graduate program, in order for possible career advancement, might value video feedback (especially video feedback on relevant and authentic career related assignments) more than traditional college age students. Further, students might not be as invested in a 1-credit course as a standard 3-credit course. Also, the majority of students in this study were female; male student might value the affective benefits of video feedback even less. Different results might also emerge when using a different subject area where video feedback can be provided in a formative way earlier in a course (whether that be a rough draft of a paper, website, or piece of artwork) that then is later revised and turned in as a final project. The instructors in this study also appeared, for the most part, to be new to video feedback (some were even graduate students and likely inexperienced at teaching too); instructors with previous experience giving video feedback, who see the value in video feedback, might also respond differently as well as use it more efficiently and effectively.
Finally, video feedback might not be right for all instructors or all courses. Effective video feedback requires strong communication skills as well as a comfort level with being recorded, a quiet place to record (which can be challenging when quarantined), technical skills, and finally the time to do it (which can be challenging for high enrollment courses). Regardless of the context, the appeal of video feedback, as this study showed, might always be lost on some students who would prefer to quickly read text-based feedback than listen to recorded feedback or who might only care about their final grade.
Additional research in similar and different settings is needed to support the findings of this study. Further research also needs to be conducted to investigate not only what instructors and students think about video feedback but more on identifying better ways to provide video feedback in fully online courses and whether video feedback can improve student outcomes (see Mahoney, Macfarlane, & Ajjawi, 2019) . As colleges shift to digital, students must in particular learn to interact, communicate, and provide feedback in multimodal ways to help them in school and later in the workplace (Istenič Starčič & Lebeničnik, 2020); therefore there are opportunities for instructors to provide their students experiences in providing video peer feedback to other students in their courses. Finally, researchers need to investigate alternative ways to provide video feedback in high-enrollment courses, whether that be by providing general video feedback to the entire course based on general findings from grading an assignment, having students work on group projects that would result in having fewer assignments to provide video feedback on, or by randomly selecting student work to provide feedback on as general examples for the entire course.
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Wind energy is an infant industry in Africa while growing rapidly in Europe and other developed area of the world this source of energy (wind). It is one of the renewables energy that can aid Africa to meet its numerous energy needs for rapid population growth, urbanization, and can help to meeting the Paris Accord of halting global temperature rise above 1.5°preindustrial levels. This wind energy can enhance Africa capability to deliver cleaner, cheaper, and environmentally friendly energy with ensuring energy security, creating energy economy and reducing energy poverty Mohsin et al. 2018b; Mohsin et al. 2018a; . Most African countries face these challenges of growing energy demand, oil price volatility, CO 2 emissions levels, and national security risks due to overly consumption of fossil fuels (Moerenhout et al. 2019) . Despite these compelling reasons for Africa to scale up wind energy on the continent, the installed capacity of wind on the continent was paltry amount of 5464 MW in 2018 (Asim et al. 2020) . Today, Africa is sharing about 1% of the total global installed wind capacity. However, there has been a political commitment from the heads of states to scale up renewable energy sources (RES) on the continent with the formation of the Africa Renewable Energy Initiative (AREI), which aims to scale up RES capacity to achieve the sustainable development goals, by leapfrogging Africa to a low carbon development economy and economic growth. This initiative aims to install 10 GW by 2020 and 300 GW by 2030 (AREI 2017) . There are laudable initiatives aimed at scaling up wind and renewable energy technologies (RETs) in general Africa: The Africa-EU Partnership program, the African Union's Programme for Infrastructure Development in Africa (PIDA), Power Africa, the Africa Clean Energy Corridor and as well as multilateral, bilateral and civil commitments to scaling up wind energy on the continent (Ahmed and Bhatti 2019) .
In the course of the decade, Africa's population is expected to grow at 3% per annum, while its gross domestic product (GDP) would increase only by 1.4% until 2030 (GWEC Africa Wind Energy Handbook, 2019). However, even this growth cannot be achieved and sustained unless there are reliable, accessible, and cheaper sources of energy to meet the demands of an increasing population. In Sub-Saharan Africa, only 48% have access to electricity; this is hindering the advancements in their socioeconomic well-beings such as education, health delivering, access to clean water, and food. According to the first continental report of the implementation 2063 Agenda, household access to electricity has increased nominally to 63% in 2019 continent wide. Furthermore, for the continent to industrialize and create shared prosperity and transform the various sectors of the continent's economic structure, the role of energy is very important. Africa today generates about 81% of its electricity from thermal sources, which is very expensive and creates macroeconomic instability in many countries due to the import-based electricity generation (Morales and Hanly 2018) . So, this is not good for both economic as well as environment. Thus, mitigating these unbearable situations, wind energy is the panacea for them. It is the source of energy that can help Africa leapfrog to a sustainable electricity generation.
This study aims to contribute to existing research in many ways. First and for most, it uses an econometric approach to assess the determinants of scaling up wind energy on 17 African countries with wind installed generation capacity, using four thematic variables such as socioeconomic factors, energy security, policy factors, and country-specific factors. These factors have been further subdivided into GDP, energy import, energy use, and electricity consumption from non-fuel sources, wind capacity, CO2 Emissions levels, and electricity consumption. This study will contribute to a growing literature on the drivers of wind energy deployment on the African continent.
Secondly, the study focuses on the entire African continent, unlike Ogbe and Ogbe (2018) ; Komendantova et al. (2019); and Mukasa et al. (2015) who studied only Sub-Saharan Africa (SSA) and focused only on all RES, not wind energy only. This gap in literature gives the opportunity to analyze a full length of policy instruments such as tax incentives, FITs relevant to the deployment of wind energy on the African continent. The time period for this study has been taken between 2008 and 2017; while existing studies used not much longer time period. Finally, under the analysis using an econometric model, a panel data fixed effect technique was used to determine the effects of policy instruments and exogenous variables on the deployment of wind energy on the African continent. The fixed effect technique was applied because of the time-invariant geographic factor (country) that could correlate with the exogenous variables (Mohsin et al. 2019d; Mohsin et al. 2019a ). The study, therefore, confirms that GDP, energy use, energy import, electricity consumption, CO2, and electricity from the non-fuel sources are very significant in determining the scaling up of wind energy on the African continent. Surprisingly, none of the dummies for the policy instrument was significant in scaling up wind energy on the African continent. They had varied magnitudes of direction for their coefficients. These results are identical with several previous studies such as , (Bublitz et al. 2019) and (Ahmadi et al. 2020 ). The study is expected to provide a wider perspective on discourse regarding scaling up wind energy on the African continent to meet growing energy needs.
The rest of the paper is organized as follows: "Model for wind energy development in Africa" section gives a background to the study; "Data and methodology" section is research and methodology. The results of the panel model econometrics analyses are described in "Results and discussion" section. "Conclusion and policy implication" section ends the paper with conclusions and recommendations.
From the model below, it explains how integrated the various energy systems are in meeting the energy needs of African countries. The quantum of national resources, prices of crude at the global markets, energy demand, and the demand for energy services are exogenous to the model. The Africa continent is endowed with a lot of natural resources, which serve as a source of foreign exchange for them when they are exploited. These are fossil fuels like oil and gas, coal, etc. In the case of fossil fuels, it has subjected them to price volatility in the global markets, leaving most economies worse off (Asbahi et al. 2019; Sun et al. 2019a, b) . Those who do not have it, spend a huge amount of hard currencies to import it for powering their economies, and facing macroeconomic instability in the long run. For Instance, Ghana was projected to spend over a billion dollars in 2019 to import crude to power its thermal plants (Government of Ghana, 2019) . For Africa to move to a sustainable future, it has to develop its renewables resources, which are local, abundant, and cheaper than fossil fuels. But generating energy from this VRE comes with system challenges (Olsen et al. 2020) , known as the integration challenges and needs system planning and management to ensure its efficient adequate to generate to meet demand at the least the costs (Iram et al. 2019; Sun et al. 2020a; and Sun et al. 2020b ). On the other hand, the green boxes are endogenous to the model, that is, residential, transport, public services, power, oil, and gas models are all given in the model. The endogenous variables in the model have to adapt energy efficiency to consume electricity to ensure that the system is maintained. Actors in the electricity sector in Africa can ensure demand side responses like behind the meter solutions are implemented; consumers can use the smarter meter and purchase energy efficient products in the market. On the part of transport, Africa can build infrastructure for electric vehicles (EVs) that will do away with higher transport fares in the cities and electrify all public transport. Industry individuals can undertake distributed wind generation to free the grid of pressure and ensure regular supply and energy security. African countries need to modernize their tariffs' deigns as a demand response tool to ensure optimal energy consumption without any backlash from customers (Zhou et al. 2020) . Figure 1 shows the overall energy situation.
The wind industry in Africa is promising and looking forward. There is a growing number of African countries that have embraced wind energy and are taking practicable steps to generate power from this renewable source. For example, Egypt, Morocco, South Africa, Kenya, Ethiopia, and Tunisia are the leading economies which are driving wind capacity installation in Africa. The likes of Senegal, Ghana, Gambia, Chad, and Algeria are equally joining the wind bandwagon. There has been a political acceptance of RES in Africa and wind in general, with the establishment of the African Renewable Initiative (AREI) 2015. The drivers of wind energy in Africa are South Africa with 6360 MW of power from wind by 2030, that is, 69% from the IPPs, as part of the Renewable Energy Independent Power Procurement Program (REIPPP) (SEWEA 2019). With 1.2.GW wind energy capacity, Morocco is another country which is driver of Wind energy on the African continent. The wind energy program which was launched in 2010, they have decided to enhance wind energy production capacity over 2000 MW till 2020 (Government of Morroco, 2019). Africa is Egypt, which is blessed with superb wind speed, especially around the Suez Canal, which is one of the best areas in the World for harnessing energy. The wind speed sometimes range between around 8 and 10 m/s at height 100 M (IRENA 2018). Egypt targets 40% of RES to make its energy matrix by 2035.Under its distinctive feed-in, tariff program, which was launched in 2014,which seeks to encourage electricity generation from RES, targets 4300 MW generation. Ethiopia's current wind installed capacity is 324 MW (IRENA 2019). Furthermore, Kenya is a regional leader in the Eastern Africa Power Pool, with 335 MW installed capacity and another 350 MW expected to be procured by 2023 (GWEC, 2019) ( Table 1 ). Kenya has already awarded more than 1 GW of wind capacity under its prevailing feed in tariff rate. Mauritania has a current installed capacity of 34 MW (Chen et al. 2017 ). However, the country is endowed with an excellent wind speed along its northern coastline between 8.3 and 8.7 m/s, this even increases to 9 m/s in the Nouadhibou region (Mustapha et al. 2015) .
The framework above depicts the key variables used in the study. Each variable is being discussed in detail from the under listed. Certain key factors are vital drivers of wind energy development globally and in Africa, particularly. These are grouped into three thematic areas: socioeconomic, political, and country wise factors, as done by Olanrewaju et al. (2019) , Ogbe and Ogbe (2018) , Kilinc-ata (2016), Thapar et al. (2018) , Menz and Vachon (2006) , Aguirre and Ibikunle (2014) , and Marques et al. (2010) . Zhao et al. (2020) categorized these into pricing and non-pricing policies influencing wind energy development in China. However, Panse and Kathuria (2018) argue that geographical, bureaucracy, technical, and societal factors determine the investments' firms that make into wind power than technology (WTP) in India. Figure 2 shows the wind development index.
The dawn of the 1970s brought a significant development in the energy landscape, which saw increased oil prices, making nations started looking for alternative fuel sources. The oil price shocks were monumental and hence the push for the adoption of alternative renewable energy. The world has never looked back and adopted renewables to power homes. The Paris Accord of 2015, which was brought to being to help nations voluntarily and compulsorily commit to reducing global temperature below 1.5 pre-industrial levels, through their nationally determined contributions (NDCs), is another driver of the adoption of wind energy (Eickemeier et al. 2014 ). Prior to this, the 1970s were used for R&D purposes; countries were investing and researching new technologies for scaling up renewable energy sources likewind and solar. Another way to increase the mass deployment of wind energy is to replace feed in tariffs with auctions, which is very effective for utility-scale wind farm projects (International Renewable Energy Agency (IRENA) 2017). Obligations and traded certificates were ubiquitous in the 2000s. Feed in tariff (FITS) has become the practice for many countries to scale up renewable energy deployment (Kilinc-ata 2016). According to Nicolini and Tavoni (2017) , the tariff is effective in scaling up renewables; a 1% increase in tariffs leads to renewable generation between 18 and 26%. Hence, this study expects that underlined variable to positively relate to wind capacity addition. Zhao et al. (2020) argued in that feeds in tariffs are the most effective means to scaling up RES, considering factors such as fairness, cost-efficiency, responsibility, by using the dynamic efficiency model. In addition, tax incentives are equally very important in scaling up wind energy. For instance, India's domestic tax law gives a 10-year tax holiday
Energy security is defined as the low vulnerability of energy systems; the vulnerability of energy systems are viewed in three ways: robustness is reducing exposure to risks, such lack of resources, resilience is the ability of the system to recover from shocks, and sovereignty is when energy assets are being controlled by foreign actors (Jewell et al. 2016) . Literature is replete with energy security being a necessary condition for countries to develop renewable energy, especially wind energy (Olanrewaju et al. 2019; and Olanrewaju et al. 2019) . Energy import is used as a proxy for security. Implying, if the nation imports more of its energy, then it makes economic sense for the nation to diversify its energy mix to include wind energy, which is cost competitive and environmentally friendly. Wind energy, together with storage, can improve energy security by diversifying the energy mix and providing adequately and readily available electricity and fighting climate change (Eberhard and Dyson 2020) . Due to the issue of drought caused by climate change in certain parts of Africa, affecting the water levels of dams for hydropower, storage technologies with fewer CO2 emissions could use renewables as a baseload for power generation (Eberhard and Dyson 2020). Thus, this study anticipate energy security to positively correlate with wind capacity addition. As far as electricity consumption keeps increasing, the question of energy security comes to mind. Electricity forms the foundation for sound industrialization in any country. Hence, Africa's industrialization can jump start the economies to growth trajectories, if they generate enough to meet the need of industries to promote economic growth and development (Olanrewaju et al. 2019 ). Wind energy is seen as one that can help to achieve this objective on the African continent with ease since the continent has the potential technically and economically to generate power from wind. Shami et al. (2016) concluded wind energy could be harnessed by Pakistan to meet its power needs in the midst of generation deficit. Renewable constitute 25% of global electricity and project to grow to 50% by 2030 and almost a quarter to 100% by mid-century (McKinsey and Company 2019).
Referencing earlier works by Marques, Fuinhas, and Manso (2010) and Aguirre and Ibikunle (2014) CO 2 emissions level is used as a proxy for environmental factors. This is anticipated to have a direct correlation with wind capacity addition in Africa. Reducing emissions would help balance the socioeconomic system by redistributing social benefits coming from introducing a national carbon pricing system (Edenhofer et al. 2019) . International monetary fund (IMF) recommended the use of revenue-neutral tax subsidies scheme to promote the generation of cleaner electricity like the wind in member countries without increasing fuel prices (Principle and Practice 2019). Africa's part of total global emissions levels is anticipated to increase from 3% to 23% by 2100 (Lucas et al. 2015) . Africa must take steps to control its emission levels by using the clean development mechanism to generate its power from cleaner sources like wind (Purohit and Michaelowa 2007). However, Sei et al. (2016) contends that only about 2% of projects and 7% of certified emission reductions (CER) potential have the likelihood of reducing emissions and not overestimated. Thus, it satisfy the condition of "additionality concept."
Gross domestic growth (GDP) of a country determines the extent a country would invest in renewable energy and wind energy in particular. Countries with higher GDP are better off and have higher income levels and can afford to invest part of their GDP to wind or electricity consumption. Higher the GDP growth rate of a country, more the ability of it to spend money on electricity consumption. Electricity consumption per capita rate in Africa was about 483kwh in 2014, which is among the lowest in developing world. This is equal to electricity needed to power a 50-W light bulb in a year. Even if Africa achieves universal access, many people cannot still afford electrical gadgets to utilize the electricity generated and higher tariffs.
In view of this, there is a need to scale up wind energy, which is cheaper than fossil fuels. Wind energy development helps improve the economic well-being of rural dwellers, by increasing their earnings levels and employing more labor in the primary sector (Du and Takeuchi 2019) . Marques et al. (2010) argued that higher income or GDP means two things: the ability to bear regulatory costs, in the forms of fiscal measures and market costs, and the ability to spend more on alternative energies.
Energy use in a country is expected to have a direct link with overall wind capacity addition. It explains the various sectors of the economy, such as commercial, residential, transportation, and industrial consumption of energy. Zhao et al. (2020) argued that other than pricing and non-pricing factors, power demand, wind resources, and technology have a significant correlation with power development in China. Most African countries have high energy demand as a result of increasing population and urbanization. This makes it imperative for more energy to meet the demands of the populace. This, therefore, means diversifying the generation mix to include wind and other cheaper sources to meet this growing demand. More so, wind and solar PV energy are projected to become profitable to 2030, even without subsides (Bertsch and Di Cosmo 2018) , making it profitable for private sector investment in the wind industry.
Wind energy is a nascent industry on the African continent. For it to mature and enjoy the economies of scale, the sector has to be de-risked by instituting regulations that compensate for risks and entice private sector investments (Bertsch and Di Cosmo 2018) . Kenya, together with the African Development Bank (AfDB) and a private developer, built the largest wind farm on the continent on Lake Turkana. It was achieved through private and public participation (Kazimierczuk 2019) . By 2030, newly build wind farms would cost less than fossil fuel plants, establishing a tipping point for renewables (McKinsey and Company 2019). Africa has to join the bandwagon and have a piece of the pie. Eight African countries are counted as the world's well-endowed wind resource countries (Mukasa et al. 2015 ). Yet the industry is still underdeveloped. A study by Shrimali, Lynes, and Indvik (2015) asserted that the production credit is effective in scaling up the deployment of wind energy at the state level in the USA by 1.4 GW annually.
African countries generate about 81% of electricity from thermal sources ("GWEC Africa Wind Energy Handbook," 2018). This makes it expensive for electricity generation and places a burden on consumers. Because most of them are independent power producers, they would pass the costs on to consumers in the form of higher tariffs. This, therefore, calls for substituting fossil fuels for renewables. In justifying the costly nature of generating power from fossil fuel sources, Katuri (2018) found that the equity to debt ratio of 80% debt and 20% equity is a financial burden on the neck of operating thermal plants, due to the incidence of high debt on the capital structure. For instance, Ghana projects to spend a billion dollars in operating its thermal plants in 2019 (Plan 2019) . Ghana generates about 69.3% of its electricity from thermal sources (Government of Ghana, 2019). The relationship between the variable and wind capacity is anticipated to an inverse one. Table 2 shows the argument regarding variables.
The study uses panel regression to rigorously analyze the relationship between wind capacity additions in African countries and polices variables that would influence this relationship. For this purpose, country level data from 2008 to 2017 is used and country level individual fixed effects model and panel data models applied. Panel data models describe individual behavior both across time and across the individual. Thus, panel data controls for individual country level heterogeneity. It is important to consider the quality of the work being done to ensure the right interpretation of the regression output. As a result, the things that would have an impact are taken care (Khandker, 2005) . The fixed effect could be used due to the fact the unobserved heterogeneity is constant overtime. A panel data fixed effects' specification assumes that there is unobserved heterogeneity across individual countries captured in a model by the inclusion of an intercept term, that is, individual fixed effects are the remainder of variation in the regressand variable that cannot be explained by the regressors. Panel data is used to test the hypothesis that wind capacity addition in African countries is related to unobserved and observed heterogeneity in determining wind capacity addition in Africa. The unobserved variables are called fixed effects. Thus, panel data is used to derive consistent estimates of the coefficients of the parameters. In view of this, the country level fixed effect is important to control unobserved heterogeneity that also affects wind energy development in Africa (Olanrewaju et
Equation (1) can be written as a panel model:
Specification of the stochastic term:
where a i is the unobserved cross-section time-specific effects,γ is unobservable specific effects, and n it is the mutual cross section time affects series From Eq (2), X it contains the variables to be used on the model. Where
Equation (3) is written in its logarithmic form as below:
where LnWindcapa = wind capacity in each country measured in MW gdpgwrth = gross domestic product growth in each country measured in (%) Resxhydro = electricity capacity excluding measured in Gigawatts (GWh) Energyuse = energy use is measured in GWh/capita Energyimport = thousand barrels per day Electricrate = electrification rate measured in (%) Electricconsu = electricity consumption billion kwh CO2 = metric tons per capita electfrmfssfuel = electricity production from fossil fuel sources is measured in GWh/capita D10 i = dummy for tax incentives D11 i = dummy for feed in tariffs β 0 = the constant term β 0 ……..β 11 are the coefficients of the model ε it = the stochastic term, depicts other variables that determine wind energy addition in Africa but were not captured in the analysis
The similar approach adopted by Thapar et al. (2018) ; Menz and Vachon (2006); and Shrimali et al. (2015) for their panel set of data to investigate the relation of production tax credit with wind energy promotion.
Data A panel data of 17 countries in Africa with wind energy generation into the national grids were collected from 2008 to 2017. With about 170 observations were collected from different sources. The dependent variable is wind capacity addition in the 17 countries with installed wind generation. The explanatory variables were categorized into socioeconomic, country specific, and policy variables. The data was sourced from the World Bank and the International Renewable Energy Agency 2017, as well as the United Nations Statistics system. The 17 countries from Africa were selected because they generate electricity from utility wind sources since 2008, which was the base year for this study. A similar approach was done by Shrimali et al. (2015) on the state level in the USA. After conducting Hausman test and the Breusch-Pagan Lagrange Multiplier test, the fixed effects were the preferred model for the analysis. Thus, it provided consistent coefficients to the estimators. The detail of dependent and independent variable is shown in Table 1 along with their descriptive statistics.
The analysis of panel data results using fixed effect are shown in Table 4 , the descriptive statistics are shown in Table 3 .
After running the panel, data by applying Stata, the results of the fixed effects on the three thematic areas of socioeconomic, environment, and country-specific variables, under twelve explanatory variables including dummies has been generated. Here, six of the regressors were significant, and the rest were not significant in determining the development of wind energy in Africa. From the results arrived at, after conducting the analysis, it was realized that a socioeconomic variable of GDP is highly significant, explaining a strong correlation with wind energy capacity development in Africa. It has a p value of 0.005%. However, the relationship to wind capacity development is a negative one, with a coefficient value of [− 0.340]. It indicates a negative relationship with wind capacity development. As wind GDP increases, wind capacity addition reduces, .This is against an orthodox economics theory that energy and GDP growth tend to go in tandem with an increase in energy consumption. However, the UK is one economy that decoupled its energy consumption for about a decade and albeit a growth trajectory in its GDP (National Statistics 2019) (Syed 2019) .This is due to the fact that the structure of the economy has been changed over the years. The UK has outsourced its energy intensive industries. Another developing country that has reduced its energy intensity and yet increased its GDP over the years is Macau, a special administrative region of China. It has 761 Btu per dollar of GDP, yet it has one of the highest GDPs per capita in the world with $133,341 in 2015.The country's economy is dominated by the services sector, which is not energy intensive like steel and manufacturing (Phew research, 15). Ameen and Lalk (2019) used same method to study the development of wind energy in two Sub-Saharan Africa countries concluded the GDPs of Namibia and Mozambique have a direct correlation with wind energy development. This study is in line with the orthodox economic theory that GDP growth and energy demand move in sync. On the other hand, another environmental variable, electricity generation from renewable sources, excluding hydro, were not significant in determining wind capacity addition in Africa.
It has also been observed that other renewable sources for electricity generation instead of hydro have no impact on the wind based electricity addition in African continent. Furthermore, energy security variable like energy use is equally significant in determining the development of wind energy capacity in Africa. It came out significant after the analysis, with a p value of 0.090. This explains the various sectors of the economy and how they consume energy, that is, residential, commercial, transportation, and industry. Thus, it stands to reason that if all these sectors that form the nucleus of energy consumption are significant, then, there is the need to scale up wind energy in Africa for their consumption. The correlation is a positive one. Hence, if energy use increases by 1 MW, wind capacity will increase by 0.238 MW. In addition, energy import was significant in determining the development of wind energy in Africa. It is an energy security variable which is significant with a probability value of 0.034 and also has a positive correlation, with a coefficient of 1.002%. This implies that for every one thousand barrel of oil imported from a foreign country, about 0.034 MW of wind power could be installed in Africa. A study by (Dong 2012 ) confirmed this assertion, where wind capacity addition has a direction relationship with net energy imports, showing that energy import helps in developing wind capacity in Africa. This was anticipated. It is plausible that as a country aims to be energy reliant and sufficient will not continue to import energy when it can develop its local resources like wind, which is cheaper and cleaner for its domestic consumption. This is true in developing Africa, where energy poverty is high and importbased energy consumption lead to fiscal imbalance as well as macroeconomic instability in many countries. A very curious result was obtained for electrification rate or energy access on the African continent. It was not significant. Also, its correlation with wind energy capacity addition is negative. As more than 600 million people have no access to electricity, Africa is considered least electrified continent of this plant. This variable was expected to correlate directly with wind capacity addition. More so, electricity consumption was equally perfectly significant after the analysis. The probability value was perfect [0.000], suggesting a strong correlation between wind energy capacity addition and electricity consumption. The correlation is a direct one. The coefficient is [4.803 MW]. As electricity consumption increases, wind capacity addition increases. Of course, the variable that has dominated global political discourse, carbon dioxide (CO2) emissions have proven significant as was expected. CO 2 is highly significant after the analysis, which shows deploying wind will abate CO 2 emissions. It emits no CO 2 .
On the policy front, the results from the regression were startling. The dummies for feed in tariffs, tax, and licensing duration were not significant in determining the development of wind energy in Africa. This confirms the early literature by Staid and Guikema (2013) and found that the key drivers of wind energy capacity development across the US are geographical and physical, other than policy drivers. Furthermore, Zachmann et al. (2014) argumented that, innovation polices like public research development and demonstration and subsidies (RD&D) and deployment policies, would help in scaling up low-carbon technologies and that current wind deployment is as a result of RD&D that interacted with best patenting. Another study that leads credence to this argument of Thapar et al. (2018) which used panel data to analyze 16 explanatory variables on India and concluded that FITs and renewal purchase obligation (RPO) are not significant in influencing the growth of wind energy in India. Indeed, to support this study notion that tax is insignificant in scaling up wind energy in Africa. It is not only economically sustainable, but it distorts the market fundamentals and strains the national grid as well (Tax Credit for Wind and Solar, 2019). Perhaps the reason could be attributed to the fact that most countries are now adopting a competitive auction system against FITs to deploying renewables. In 2018, 48 countries adopted auctions, including African countries, an increase from 29 in the previous year (REN21 2019). The issue of climate change has dominated global discourse due to the negative impacts it has on the world, especially developing countries, rising temperatures, rising sea levels, hurricanes and typhoons, and the destruction of energy infrastructure (Cantelmo et al. 2019) . All these are caused by a climate that results from CO 2 emissions. Even though Africa's emission level is very negligible (Mukasa et al. 2015) , the impacts of climate change are global. Notwithstanding, Africa is already at the receiving ends of climate change through natural disasters in Mozambique and Zimbabwe and Malawi, which could cost their GDPs growth by a percentage point and about 1.6% loss in their consumption, as natural disaster prone countries (Cantelmo et al. 2019) .The power sector is the biggest emitter of CO 2 , and so decarbonizing the power sector through the adoption of wind energy would reduce CO 2 emission and meet the Paris goals of limiting global temperature rise by 1.5°pre-industrial levels (Chmi and Eea 2019) . Obviously, another variable that came out significant was electricity from fossil fuel sources. Indicating it determines the level of wind energy capacity addition in Africa. This means that as electricity generation from fossil fuels increases, wind capacity addition decreases BY 0.447 MW. This is economically true. In that, the continued consumption of fossil fuels would not give priority to African countries to invest in wind energy. There has to be a substitution effect so as to scale up wind.
The study examined the drivers to scaling up wind energy on the Africa continent, using three thematic variables of policy, socioeconomic, and energy security. Here a panel dataset used to analyze these variables at the country level. The study used the fixed effect mode to cater for time invariant heterogeneity among country and instrumental variables for policy to analyze the explanatory variables. Countries are 17 on the continent with utility-scale wind projects since 2008. The results exhibit different effects of the policy variables. FITs, tax, and licensing duration were not significant in scaling wind capacity in Africa. The absence of effects of wind capacity addition in Africa, especially the tax element, is in tandem with the argument raised by Tax credit for Wind and Solar (2019) in the USA, where they contend that the production tax credit is not sustainable economically and distorts market fundamentals and at the time straining the grid. Africa can take a lesson from and avoid these pitfalls in structuring the tax system for the wind industry in Africa. This is in sharp contrast to the numerous studies that suggest FITs have effects on scaling up renewables capacity like wind (Menz and Vachon 2006; Case et al. 2010; Nicolini and Tavoni 2017; and Dong 2012) . GDP was proved to have a significant effect of wind capacity addition on the continent but an inverse relationship. This was envisaged, but the correlation was not anticipated. Equally significant were CO 2 emissions, energy use, and electricity consumption. All these variables point to a correlation to wind energy capacity in Africa.
An unanticipated result was that of the electrification rate in the analysis, which came out not significant. The fact that Africa has not electrified many households makes this result surprising. Electricity access is very important for Africa so to create and sustain economic growth and development. The absence of the predictive power of the variable was not expected. The reason behind this could be that the rest of the variables are more important in scaling up wind energy than that of electrification. As electricity from fossil fuel sources is significant, it suggests that more wind energy should be generated and ditch fossil fuels. Another insignificant variable that came out after the analysis was energy generation from renewables excluding hydro sources. It was an unexpected result, as well. This variable being renewable should be significant to boost the RES drive on the continent. Hydro was excluded because it does not enjoy subsidies from the state. Now, the policy implications emanating from this study are that:
1. The study concludes that there are other factors rather than a policy that drives wind energy capacity in Africa. 2. The wind industry in Africa could create well-paying jobs ranging from manufacturing to construction, operation, and maintenance, as the study found GDP growth to correlate positively with wind capacity addition. 3. Future wind energy deployment has to be institutionally, technically, and regionally integrated and modernized grids to take VRE and to achieve synergy. It would enable the access of national boundaries between energy sectors. The Africa Clean Energy Corridor is a laudable project in the right direction. In the West Africa Clean Energy Corridor (WACEC), countries like Ghana, Burkina Faso, Cote d'Ivoire, and Togo have started integrating their power infrastructure. 4. African countries need to halt granting subsidies to fossil fuel companies and divert for renewables. The environmental and economic costs of such subsidies are damning. In 2013, 30 SSA countries granted subsidies worth $32 billion. Global subsidies to fossil fuel companies reached $300 billion in 2017, twice the support for RES electricity generation. 5. Africa has to maximize public-private sector financing and leverage on the partnership to catalyze finances for scaling up wind energy deployment on the continent. There are a number of such projects on the continent between the African Development Bank (AfDB) and many countries; for instance, the Lake Turkana Wind Farm in Kenya and the Tangier projects in Morocco. 6. Finally, public research development and demonstration (RD&D) is key to scaling wind energy in Africa. It should be within countries and regional blocs.
In conclusion, despite the robustness of the results, Africa faces many challenges in the energy sector after the COVID-19, such as the oil and gas boom and bust, climate change concerns, the need for governments to find stimulus packages to revamp their economies, and the growing acceptance of RES. Wind energy could come in handy in this regard to create jobs and shield the continent from economic headwinds. Future research could consider the impact of the COVID-19 on the wind industry in Africa. As this analysis is based to find the wind energy impact on African economy.
The limitation is that the wind energy industry in Africa is a nascent one, and there is a paucity of data and research regarding the wind energy drivers on the continent. Hence most references are research related to renewables in general.
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Viroj Wiwanitkit, MD Pune, India
The letter "Beware of Time Delay and Differential Diagnosis when Screening for Symptoms of COVID-19 in Surgical Cancer Patients" by Ghannam and Souadka 1 is very interesting. The authors conclude that "in low-risk COVID-19 urgent surgical procedures with an initial negative symptom screen, we recommend carrying out a new symptom screening before each patient movement." I agree with this suggestion. The patient might be asymptomatic and undergo an operation. The risk of disease transmission to medical personnel is possible. In Indochina, the case report of disease occurrence after operation is a good example. 2 Therefore, there is no doubt that preoperative screening is useful in the current COVID-2019 pandemic. However, the important consideration is what the good screening is. Symptomatic screening seems to be a poor screening tool because many patients can have no symptoms and transmit disease to medical personnel. The routine polymerase chain reaction test might be necessary. Finally, the cost-effectiveness analysis of the screening test implementation is an interesting issue for additional study. The high cost of the polymerase chain reaction test might limit the use in some poor, developing countries. The most important consideration is the universal precautions practice for any patient undergoing an operation regardless of screening result.
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Solvent detergent treatment of plasma was developed years ago at the New York Blood Center and has become a mainstay for improving the safety of plasma derivatives. The method was also used to prepare units of solvent detergent-treated plasma made from pools of about 2,500 donors but otherwise similar to ordinary fresh frozen plasma (FFP). This product is no longer available in the United States, but a similar product is used in some other countries. The solvent detergent method is effective for viruses with a lipid envelop such as HIV, hepatitis B virus, and hepatitis C virus (HCV) but does not activate nonenveloped viruses such as hepatitis A virus (HAV) or parvovirus.
Methylene blue, when added to plasma and exposed to visible light, can inactivate most viruses and bacteria 1-4 by generation of reactive oxygen species, mostly singlet oxygen. Methylene blue is not effective against intracellular viruses, and so the blood component must undergo leukocyte reduction as part of pathogen inactivation by methylene blue. The treated plasma can then be frozen and used much the same as FFP. There is some loss of plasma coagulation factors in the methylene blue treatment process, 3, 5 but methylene blue plasma is used routinely in Great Britain, Belgium, France, Portugal, Spain, and Denmark and is being considered for adoption by several other countries.
Amotosalen has a good safety profile in studies of general pharmacology, acute and repeated dose toxicity, genotoxicity, carcinogenicity, phototoxicity, reproductive and neonatal toxicity, and occupational safety. [14] [15] [16] [17] [18] [19] The toxicity of riboflavin has been well studied as a vitamin, and, when it is subjected to UV light, 4 breakdown products result that are normal breakdown products in the body. 9 The toxic effects of these and the amounts infused as part of pathogen-inactivated components have been well studied and are within safety limits. 20 The alkylator compound used for RBC pathogen inactivation seems to have a satisfactory toxicity, genotoxicity, and mutagenicity profile. 12, 16, 21, 22 Pathogens Inactivated All 3 of these compounds inactivate pathogens very effectively. Amotosalen inactivates 10 4 to 10 6 of enveloped and nonenveloped viruses, gram-negative and gram-positive bacteria, and protozoa 13,23-33 ❚Table 1❚. 34 Although prions are not inactivated by amotosalen, the risk of transfusiontransmitted prion disease is not known. The nonenveloped parvovirus is inactivated at least at the 10 5 level. 35 Riboflavin inactivates 10 4 to 10 6 of intracellular and extracellular HIV, West Nile virus (WNV), porcine parvovirus, Staphylococcus epidermidis, Escherichia coli, vesicular stomatitis virus, Staphylococcus aureus, Bacillus cereus, and Klebsiella pneumoniae. [36] [37] [38] [39] [40] [41] [42] [43] The alkylator used for pathogen inactivation of RBCs also has a very robust pathogen inactivation profile. 13, 44, 45 Because most commercial assays detect full-length and incomplete and, thus, noninfectious particles, it is difficult to determine the true level of infectivity in apparently healthy blood donors. The extent to which these pathogen inactivation processes are in excess of the levels of these pathogens that would be expected in an apparently healthy blood donor who would have passed the standard medical or health evaluation is difficult to conclude. However, it seems that these 3 compounds are very effective inactivating transfusion-transmitted pathogens, including those for which no prevention strategy is currently in place.
An additional benefit from the pathogen inactivation technology is the potential to eliminate the risk of transfusion-transmitted graft-vs-host disease (GVHD). Although the damage to or prevention of replication of nucleic acids is not damaging to the cells or proteins of interest for transfusion therapy, the process also prevents replication of lymphocytes in the blood components. [46] [47] [48] [49] [50] [51] [52] Leukocyte depletion is not necessary to achieve this effect, which means that transfused pathogen-inactivated blood components should not cause transfusion-related GVHD. This has been established in animal studies, although a classic randomized, controlled clinical trial may be difficult to carry out in humans. Some centers in Europe have discontinued irradiating pathogen-inactivated platelets produced with the amotosalen method and have not observed transfusion-related GVHD due to the use of these unirradiated products. 53, 54
Platelets treated with amotosalen have normal results of in vitro platelet function studies, including biochemical studies, aggregation, morphologic/hypotonic shock response, and surface markers. [55] [56] [57] [58] Amotosalen-treated platelets were as hemostatically effective as normal control platelets in a thrombocytopenic rabbit model. 59 A recent abstract 60 reported some platelet damage in vitro that was dependent on the UV light dose. From the data presented, it is difficult to tell how the dose and specific wavelength of light used relate to the light used in the amotosalen and riboflavin methods. Coagulation factor levels and routine laboratory tests of hemostasis in amotosalen pathogen-inactivated plasma are not different from the levels in untreated plasma. [61] [62] [63] Amotosalen is an effective inactivator of hepatitis B virus and HCV in a chimpanzee model. 64 Riboflavin-treated platelets also have essentially normal in vitro functional properties. 37, 41, 42, 65 Plasma treated with riboflavin for pathogen inactivation also has essentially normal levels of plasma coagulation factors. 66, 67 RBCs treated with the alkylator have normal in vivo test results, including morphologic features, osmotic fragility, potassium efflux, hemolysis during storage, adenosine triphosphate levels, 2,3-diphosphoglycerate levels, oxygen affinity, and RBC antigen strength. 12, 45 The posttransfusion survival of alkylator-treated RBCs was normal in mice 12 and dogs, 68 but there seemed to be a slight but not statistically significant decreased recovery.
Amotosalen-treated platelets given to healthy research subjects had slightly decreased recovery and survival. 69 In 13 thrombocytopenic patients, amotosalen-treated platelets had a slightly decreased posttransfusion recovery but were equally as effective as control platelets in correcting the bleeding time and time to the next transfusion. [70] [71] [72] Riboflavin-treated platelets have shown normal in vivo recovery and survival in studies of radiolabeled cells in healthy research subjects. 65, 73 Autologous amotosalen pathogen-inactivated FFP was equally effective as autologous untreated FFP in correcting the prothrombin time and partial thromboplastin time and elevating the levels of factors II, VII, IX, and X in healthy subjects treated with warfarin and then transfused with their own untreated or pathogen-inactivated FFP. 61, 74 RBCs subjected to pathogen inactivation by the alkylator have slightly decreased autologous in vivo recovery and normal survival. [75] [76] [77]
A prospectively randomized, controlled trial of amotosalen pathogen-inactivated buffy coat vs control platelets in 103 patients showed that both platelet products were effective in increasing the posttransfusion platelet count, and there were no differences in transfusion reactions or adverse events. 78 A prospectively randomized, controlled trial of amotosalen pathogen-inactivated apheresis platelets 79 vs untreated apheresis platelets in 645 patients showed equivalence of both products in control and prevention of bleeding and fewer transfusion reactions in patients receiving pathogen-inactivated platelets. 34 This is the largest clinical trial of platelets ever reported and was unique in that the primary end point was hemostasis rather than platelet count. Patients in this study 34 who received the pathogen-inactivated platelets had significantly lower posttransfusion corrected count increments and received more transfusions. However, these patients also received lower doses of platelets owing to processing losses. When the data for patients who received doses of pathogeninactivated platelets similar to doses received by control subjects were analyzed, the posttransfusion count increments were similar to those for control subjects, 80 indicating that much of the observed difference was due to a difference in dose. This observation was confirmed on a large scale in Europe where use of pathogen inactivation has not led to an increased number of platelet transfusions. 81 Although no overall difference in adverse reactions was seen in the SPRINT study, there were small but significant increases in several types of adverse reactions in patients receiving pathogen-inactivated platelets. 34 In a more detailed report of these adverse events, it does not seem that these pathogen-inactivated platelets represented a higher-than-usual risk for patients. 82 A phase 3 clinical trial of pathogen-inactivated FFP showed that improvements in hemostasis and laboratory test results were equal and not significantly different in 121 patients with acquired coagulopathies primarily due to liver disease. 83, 84 There were no differences in the use of blood components or in bleeding complications, indicating that pathogen-inactivated FFP was as effective as untreated FFP for the treatment of acquired coagulopathy. Pathogen-inactivated FFP has also been equally as effective as untreated FFP in patients with congenital coagulopathies 85, 86 and for replacement during plasma exchange for thrombotic thrombocytopenic purpura. 87 A phase 3 trial of alkylator pathogen-inactivated RBCs has been reported. 88 This trial was halted prematurely owing to the development of RBC antibodies in patients who were receiving multiple transfusions of similar pathogen-inactivated RBCs but in a different trial. The reported trial 88 involved 223 patients undergoing cardiovascular surgery, and even though the trial was halted prematurely, statistical analysis revealed that the end point had been met. There were no significant differences in a combined end point involving cardiac and renal function. Thus, the trial can be considered successful, although the specific pathogen inactivation method will not be used in the future owing to antibody formation in multiply transfused patients. The manufacturer has modified the pathogen inactivation method 44, 89 in a way that it believes will no longer lead to antibody formation and will soon propose to reopen the RBC trial using the new modified method.
A phase 3 clinical trial of a different pathogen inactivation method for RBCs was also begun and then halted prematurely owing to RBC antibody formation in recipients. That company elected not to attempt to resolve the antibody formation problem and has since gone out of business.
To summarize the current situation, pathogen inactivation is effective for buffy coat and apheresis platelets, and traditional methods of evaluating pharmacology, toxicity, and mutagenicity have given satisfactory results. A buffy coat platelet product (amotosalen) is being used in France, Germany, Belgium, Spain, Italy, Norway, Sweden, and Russia, and work to gain experience using the technology is underway in Switzerland, Austria, Luxembourg, and the Czech Republic. A trial of a second buffy coat platelet product (riboflavin) is under way in Europe and will be completed in late 2007. A phase 3 trial of apheresis pathogen-inactivated platelets was completed in the United States several years ago and results were submitted to the US Food and Drug Administration (FDA), but no decision about licensure has been forthcoming, despite more than 80,000 transfusions having been given in Europe. The phase 3 trials of FFP are completed. Recently, this product was approved in Europe and is being produced there. It seems that the reasons for development of alloantibodies in the RBC phase 3 trial are understood, the method has been revised, and preparations are being made to propose a new trial.
The shortcomings of our present paradigm for preventing transfusion-transmitted infections are as follows: (1) It applies only to known pathogens and transfusion-transmitted infections. ( 2) It does not address or prevent all currently known transfusion-transmitted infections. (3) It is reactive to the occurrence of new infectious agents and, thus, accepts that some patients will be harmed before steps can be taken to minimize transmission of the agent. (4) Current methods to detect and/or prevent transfusion of bacterially contaminated products are inadequate. (5) Many donors who do not pose a risk to patients are temporarily or permanently deferred because of the impreciseness of the present screening tests or deferral criteria.
There are several examples of these shortcomings. WNV is the first example. The blood banking-transfusion medicine community, industry, and regulators collaborated in a Herculean task of recognizing the problem, exploring donor deferral options, developing new tests, implementing them strategically, and creating a unique regulatory framework to enable this to occur in a time previously unimaginable. 90 These groups are all understandably proud of the accomplishment. However, during the summer of 2002, the mean risk of transfusion-transmitted WNV was 2.12 to 4.76/10,000 donations. 91 This implies that approximately 2,500 to 5,500 patients might have been infected (based on 12 million RBC transfusions). Of 23 patients described separately, 92
The cost-effectiveness of screening for WNV has been estimated as $897,000 per quality-adjusted life year for individual unit testing. 93 Impressive as this response is, none of this would have been necessary had our transfusion-transmitted infection paradigm been based on pathogen inactivation. No additional money would have spent on this problem, countless hours of meetings would have been unnecessary, blood bank operations would not have been disrupted and altered, suitable donors would not have been lost, and most important, patients would not have been infected or died as a result of transfusion-transmitted WNV infection.
A more recent example of a situation in which pathogen inactivation was used to intercede with a new infectious agent entering the blood supply occurred on the island of Le Reunion, a remote island in the Indian Ocean that is a department of France. A new epidemic of the RNA Chikungunya virus developed on the island, and more than 34% of the population became infected. 94 Although Chikungunya virus has not been reported to be transfusion-transmitted, its natural history is such that health officials believed that transfusion transmission was likely. Parenteral transmission by needle stick has occurred. Health and blood authorities believed it was not feasible to continue to collect blood owing to the widespread epidemic, so blood collection was halted on the island. An alternative was needed to maintain a blood supply. RBCs and frozen plasma were shipped from France, but owing to the distance and shipping time, it was not possible to provide platelets from France. Laboratory studies quickly established that amotosalen pathogen inactivation is effective against the Chikungunya virus, 95 so platelet pathogen inactivation procedures were put in place locally within a very short time. Platelets were then collected locally to meet the needs of the island. 96 Subsequent studies established that the outbreak was due to a new variant that may have enabled the virus to adapt to a new mosquito vector, 94 and there may have been as many as 2 million cases of Chikungunya virus infection worldwide in 2006. 94 The outbreak involved an African virus in an Asian mosquito, and the possibility that this virus, like WNV, could be carried to the Americas 94 has already come true. At least 37 cases are known in the United States, 97 and although these occurred in returning travelers, this could become an epidemic similar to that resulting from WNV.
A third example of the shortcomings of our present paradigm is bacterial detection. If pathogen inactivation were in place, there would have been no need for the American Association of Blood Banks standard requiring methods to reduce bacterial contamination of platelets. Even with current testing methods, 20 septic reactions have been reported in about 1 million units of platelets. 98 Thus, the complex, expensive, and only partially effective testing that has resulted would not be necessary. As with the WNV example, the cost of test development, regulatory activities, countless hours of meetings, operational changes, and complexity of resulting logistics have increased the cost of blood products. All would have been unnecessary with a pathogen inactivation paradigm, and the transfusion of bacterially contaminated products with resulting harm to patients that continues at present, despite testing, would be avoided.
A fourth example of the shortcomings of our current paradigm is cytomegalovirus (CMV). Although leukocyte depletion greatly reduces transfusion-transmitted CMV, it still occurs in about 1% of patients, 99 even after CMV antibody screening of donated blood. The growing use of hematopoietic cell transplantation, complex chemotherapy regimens, and organ transplantation increases the number of patients who should receive CMV-safe blood. This, in turn, places greater demands on the supply of CMV-safe blood. Pathogen inactivation could eliminate the need for continued testing for CMV antibody and, thus, avoid problems due to lack of CMV-antibody-negative blood components.
A fifth example of the difference between a proactive pathogen inactivation paradigm and our present reactive paradigm is testing for Trypanosoma cruzi. A test is now available, and testing of donors has been initiated by some blood organizations, although universal testing is not required by the FDA. Pathogen inactivation is effective against T cruzi 26, 27 and would make all of the test-related activity and costs unnecessary. More important, pathogen inactivation would have prevented the harm that has been done to some patients because our present transfusion-transmitted disease paradigm does not prevent transmission of T cruzi infection. Bacterial testing or adding a test for WNV or T cruzi, like the other infectious disease strategies in our current paradigm, is reactionary and accepts that patients are injured before preventive steps are implemented. Conversely, pathogen inactivation is a proactive approach to transfusion safety.
The benefits of pathogen inactivation must be considered in relation to these new steps that could have been avoided, existing known transfusion-transmitted diseases, and expected new threats to the safety of the blood supply. We cannot continue to add test after test and new donor criterion after criterion.
This body of work represents substantial progress, and pathogen inactivation has arrived at a realistic point. We all have a role in the evolution of this technology: industry, academia, the blood banking-transfusion medicine community, and regulators, but most of all, patients.
Industry has been able to generate substantial sums of money to develop pathogen inactivation to its present state. Developers have been exceptionally willing to share their results as indicated by the large number of resulting publications. This is in interesting contrast with the disappointing lack of publications from industry on hemoglobin-based oxygen carriers. Industry has the responsibility to continue thorough, careful development of pathogen inactivation technology, pursuing appropriate safety and efficacy issues. It has a responsibility to develop a product that can be implemented operationally in a realistic manner and at a cost that can be incorporated into transfusion therapy and the blood supply system. Academia has a responsibility to provide knowledge, expertise, advice, and research collaboration in the development of this technology as appropriate. These are small companies that can never have the breadth and depth of knowledge that exists in our universities. The companies have a responsibility to seek this knowledge, and we in academia should participate as appropriate in the development of these products.
The blood banking-transfusion medicine community has a responsibility to consider the potential of this paradigmchanging technology in a truly open-minded and, hopefully, imaginative way. Pathogen inactivation may be technically complex. However, the blood banking community has demonstrated the ability to implement complex processes. There were times when conducting radioimmunoassay or enzymelinked immunosorbent assay in the blood bank setting was considered impossible, but this occurred, and, in the process, it improved patient safety but increased costs. The most recent example, of course, is nucleic acid amplification testing. Initially, the concept of applying nucleic acid amplification and detection technology in a relatively standard way to test tens of millions of specimens was almost laughable. At the FDA-sponsored conference on this topic, 100 the concept of routine widespread nucleic acid amplification testing was greeted with considerable skepticism. Now, of course, complex nucleic acid amplification testing is done routinely although at a substantial increase in cost to eliminate but a few hundred cases of transfusion-transmitted infection. Thus, the transfusion medicine community has demonstrated its ability to implement impressive technologically sophisticated advances as a part of the existing paradigm.
As we blood banking-transfusion medicine professionals evaluate pathogen inactivation and its potential role in transfusion therapy and product preparation, it must be in the broad perspective of a paradigm shift. It may increase some production costs and alter our current operations; it might be inconvenient, at least for a while. This has been true of every major development in the past 50 years. For example, it is more expensive to produce components than whole blood, and apheresis platelets are more expensive and difficult to produce than whole blood-derived platelets.
A paradigm shift occurred with the introduction of apheresis rather than separation of units of whole blood for the production of blood components. Equipment and an entirely new way of evaluating donors for suitability had to be developed, new donor risks identified, and steps put in place to minimize these risks. This increased costs and created new risks to donors with apheresis instead of whole blood donation. Examples of risks of apheresis donation that are different from whole blood donation include citrate toxicity, cell depletion, air embolus, mechanical hemolysis, and others. 101 However, we adapted this new technology and moved to the paradigm of producing components at the donation site rather than in the traditional blood component laboratory. It seems likely that this trend will extend to more extensive bedside component production as instrument technology continues to evolve.
Regulators also have a responsibility in the evolution of pathogen inactivation. First, their expectations and requirements must be defined clearly and in advance so that the developers of this technology can see the course they must take to succeed. Regulators must be clear and consistent in adhering to these expectations and not change them frequently during product development. All pertinent regulators should be involved in establishing the expectations initially so that during product development, the regulators can speak with one voice and from a single point of view. The regulators' expectations should be scientifically sound and based on available data. However, some of the major benefits of pathogen inactivation are the elimination of existing transfusion-transmitted infections, thus improving patient safety while also eliminating some current activities such as bacterial detection, irradiation, CMV testing, and the likely prevention of new infectious threats to the blood supply. These must be incorporated into regulatory and risk-benefit decisions. Regulators must look beyond HIV, HCV, and human T-cell leukemia virus.
One aspect of pathogen inactivation may seem unique but is not different from other regulatory decisions regarding a new drug or biologic. The issue is the possibility of a very small risk or one that is not manifest until far into the future. Data from studies of the magnitude necessary for licensure will never be as extensive as what experience with a new agent or technology will provide after licensure. Therefore, regulators may be concerned that although data seem to be satisfactory, unexpected or unknown adverse events may occur when the agent or technology is applied on a large scale. The lack of effective postmarketing surveillance systems and the lack of "a systematic approach to identifying premarketing drug safety problems and turning them into high quality postmarketing studies" 102 further complicates difficult regulatory decisions. However, regulators must cope with this issue in all potential licensing decisions, and pathogen inactivation is not different fundamentally.
The issue then becomes the potential value vs unknown long-term risks. Two other approaches for postmarketing surveillance that might be useful in pathogen inactivation are the RADAR (Research on Adverse Drug Events and Reports) project to identify previously unrecognized adverse drug and device reactions 103 and the growing interest in hemovigilance. The benefit of pathogen inactivation is far beyond eliminating the small number of remaining traditional transfusion-transmitted diseases such as hepatitis and HIV. The benefits include the long list of the other transfusion-transmitted infections that are not prevented by present technology ❚Table 2❚, the remaining bacterial contamination problem, and the nearly certain expectation that more WNV-or Chikungunya virus-type situations will occur with emerging agents or changes in known agents. In addition, irradiation of blood components could be eliminated, as could testing for CMV and WNV, and the incidence of platelet transfusion reactions reduced. We are at the end of the usefulness of the present paradigm and must move to a new one. It is incumbent on all of us to consider pathogen inactivation in this broad context.
Many practical issues would need to be addressed for pathogen inactivation to be implemented in the United States. The only product that has been submitted to the FDA for licensure is platelets collected by apheresis. In the United States, many platelets are produced from whole blood, so physicians would need to decide whether to adopt a technology that would apply to only some platelets and possibly result in a dual inventory of platelets-some pathogen-inactivated and others not. This could present difficult issues in managing the dual inventory and raise the question of whether the pathogen-inactivated platelets should be used for certain patients and not for others. Implementation of pathogen inactivation might be an easier decision in centers that produce only apheresis platelets. The method for pathogen inactivation of whole blood-derived platelets that is approved in Europe is for platelets produced from buffy coats. It is not clear whether the United States would convert to buffy coat platelets to adopt pathogen inactivation. Canada is converting its platelet production to the buffy coat method, although for reasons other than pathogen inactivation. In the United States, there would be pressure to speed the conversion to apheresis platelets or for manufacturers to develop a method for pathogen inactivation of platelets produced with the platelet-rich plasma method unless the United States also converted to the buffy coat method.
This dual inventory would not be an issue for plasma, and, if pathogen-inactivated plasma were approved in the United States, use of the same technology for plasma and platelets would make adoption for both components more convenient. Amotosalen is applicable to plasma and platelets, and riboflavin should also be effective for both components. Thus, if both processes were approved, two suppliers would be available, which might alleviate some concerns about product availability. Many more units of RBCs are transfused than platelets or plasma, and the availability of pathogen-inactivated RBCs would have a huge impact on interest in implementing this technology.
The cost of pathogen inactivation will certainly be an issue. It is not the scope of this report to deal with cost analysis. However, pathogen inactivation might not be as large an increased cost as might be expected. In addition to elimination of the patient care costs of the diseases transmitted, transmission of agents not now tested should be prevented and patients spared new infections. The countless hours spent in developing strategies to deal with new agents would be avoided, and the huge costs of testing and loss of donors owing to false-positive screening test results would be eliminated. In addition, irradiation of blood products; testing for bacterial contamination of platelets; testing for CMV and, possibly, for WNV could probably be eliminated; and 7-day storage of platelets could be reconsidered. Because plasma is replaced with a platelet additive solution during the pathogen inactivation process, more plasma is available for fractionation, thus providing some revenue. Because plasma is removed and because pathogen inactivation stops cytokine synthesis, transfusion reactions to platelets are decreased, 34 thus improving patient care and reducing the costs of managing these reactions. It seems unlikely that most currently required transmissible disease testing would be eliminated, but potential future costs of screening for T cruzi, malaria, and Leishmania species could probably be avoided, and we would be prepared if an epidemic such as severe acute respiratory syndrome or avian flu should occur.
The group with the most concern about pathogen inactivation, however, is patients. They must be the primary focus of all of us in blood banking and transfusion medicine. It is our responsibility to provide adequate and safe transfusion therapy. We must pursue and embrace the developments that can contribute to this. We must recognize and accept that adoption of these improvements may be complex, disrupt our present routine operations, and pose operational or physical
Pathogen inactivation with solvent detergent has been used for plasma derivatives for years, and a pathogen-inactivated frozen plasma product is used in Europe presently. Substantial progress has been made in the development of pathogen-inactivated platelet, plasma, and RBC products. Safety profiles for the additives in these pathogen-inactivated methods are good. A platelet product is available in Europe, and more than 80,000 units have been administered to thousands of patients. A phase 3 trial of pathogen-inactivated platelets was completed in the United States several years ago, and a request for licensure has been submitted to the FDA. A clinical trial of a different pathogen-inactivated platelet product is under way in Europe, and this product has recently been licensed there. Pathogen-inactivated plasma (using methylene blue) is used in some European countries, and phase 3 trials of a different FFP product have also been completed. This product has been approved in Europe, and is beginning to be implemented. Three phase 3 trials of pathogen-inactivated RBC products were halted prematurely owing to antibody formation in some patients. However, before one of these trials was closed, an adequate number of patients had been entered to demonstrate clinical effectiveness of the pathogen-inactivated RBC product. The manufacturer believes the cause of the antibody formation has been eliminated and expects to reopen the RBC trial soon.
In vitro and in vivo data show that most pathogen-inactivated blood products are slightly compromised compared with untreated products. Most of our traditional methods of evaluating blood products have involved in vitro analyses and studies of in vivo survival in a small number of healthy research subjects and patients in relatively stable condition. In contrast, studies of pathogen-inactivated blood products have looked at the most important issue, which is clinical effectiveness. Platelet studies evaluated prevention or control of bleeding, not just platelet counts. RBC studies looked at clinical outcome, not just the change in hemoglobin level. Thus, at least to some extent, the information available about pathogen-inactivated products is better than that on which we have based existing transfusion therapy. Although to some extent these new pathogen-inactivated products are not the same as those we have used for years, they do not have to be the same. What they have to be is effective for patients. If pathogen inactivation represents a true advance, the blood banking-transfusion medicine community is creative enough to adopt the technology successfully. We blood banking-transfusion medicine professionals must anticipate and embrace change. Whether pathogen inactivation will prove to be safe and effective is still being determined, but experience with thousands of transfusions in Europe is encouraging. We must consider pathogen inactivation in the broad context of history, the shortcomings of our present paradigm, and the future of transfusion safety for patients.
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Although public health research is undoubtedly essential during a pandemic, 1 the line between research and public health activities is tricky in the best of times and can blur quickly in a public health emergency. 2 Elements common to both endeavors range from study design, to the collection and use of personally identifiable and protected health information, and to analysis techniques. Many point to the a priori purpose of a given initiative as a way to distinguish between research and public health activities. 3 Yet, even while public health practice focuses on assurance, assessment, and policy development, these activities might contribute to generalizable knowledge-the hallmark of research. For example, in 2010 following the Deepwater Horizon oil spill in the Gulf of Mexico, the U.S. Centers for Disease Control and Prevention (CDC) tapped into the National Poison Data System (NPDS) for the purpose of monitoring health impacts of people in the region (ie, surveillance as a public health activity). Nevertheless, the CDC's utilization of the NPDS post-environmental disaster also demonstrated the database's utility for advancing scientific understanding of how oil spill exposures affect human health (ie a resources for potential public health research with the primary purpose of contributing generalizable knowledge). 4 Additionally complicating the divide between research and public health activities 5 is the now widespread practice of banking of data and samples for secondary research use. During a public health emergency, research repositories are attractive, ready-made data resources and communication channels with large, and, ideally, diverse cohorts through which public health activities could be pursued expeditiously. Given that emergency responses 'tend to be nonresearch,' 6 what risks are posed by repurposing research infrastructure for public health activities?
The COVID-19 pandemic has already provided case examples highlighting key questions about the public health activities that seek to leverage existing research infrastructure. For research participants and collected nasal swabs with the goal of improving detection, monitoring, and control of influenza outbreaks in greater Seattle, Washington. On March 10, 2020, the New York Times 8 reported on SFS's ongoing efforts to assess retrospectively the prevalence of the 2019 novel coronavirus, SARS-CoV-2, 9 using nasal swab samples collected for research purposes during the 2019-20 influenza season. In early February 2020, SFS began petitioning the state, CDC, and U.S. Food and Drug Administration (FDA) officials for permission to use the SFS's existing sample bank to track COVID-19 spread. SFS participants had consented to the testing of their swabs for influenza and 'other respiratory pathogens (germs)' and to receiving these research results back from the study team, as well as for the secondary use of their data for research purposes. Through the consent process, SFS had alerted participants that Washington state law requires reporting of infectious diseases, including influenza, 10 but did not discuss the use of SFS's research infrastructure, including data or samples, for other public health activities. 11 After about 2 weeks of rebuff, and within the context of undeniable national spread of the virus and inadequate testing for it, the SFS team decided to test the samples without the explicit approval of public health authorities or regulators. The SFS team promptly identified a SARS-CoV-2 positive result and alerted local public health officials. The sample was rerun in the Washington state laboratory, where the positive result was confirmed, and the research participant was subsequently notified by public health officials. 12 Despite this apparent successful use of existing research infrastructure for public health activities, 13 CDC and FDA regulators ordered SFS to stop retrospective testing of their existing samples immediately but indicated that, with additional consent language clarifying the use of research study materials for public health activities, SFS could prospectively test participants for SARS-CoV-2. In the first few days of March, the University of Washington's ethical review board determined that, given the public health emergency, SFS had an ethical obligation to test all samples for SARS-CoV-2, citing that SFS already had consent from participants to test for another communicable diseases and return those results and, therefore, was already engaged in both research and public health activities. On March 9, 2020, state regulators again shut down retrospective testing by SFS. 14 SFS eventually completed its retrospective testing of samples, identifying 25 positive results across 2353 participants, including the first documented case of community transmission of SARS-CoV-2 in the USA. 15 The back and forth between federal and state authorities, the research team, and the overseeing ethics board, which eventually culminated in the Seattle Flu Study turning its resources toward a joint public health initiative announced March 23, 2020, 16 illustrates the complexity of the boundary between federally regulated research and public health activities 17 and highlights key concerns about the repurposing of research infrastructure and its use for public health activities. Firstly, what are the points researchers must consider as they contemplate either mining already collected research data during a public health emergency, or, as in the case of the SFS, undertaking new analyses on already collected samples in the name of public health response? Secondly, what are the considerations for reporting back to research participants types of information derived from public health activities not explicitly disclosed in the informed consent process? Thirdly, given the uncertainty of risks and benefits posed by public health activities, are there any additional concerns raised by legal mandates to disclose information derived from research sources to public health authorities at different governmental levels? These questions are particularly worthy of contemplation given the number of large research initiatives' data and sample banks that could potentially be called upon by public health authorities during this pandemic-including, notably, the National Institutes of Health's All of Us SM Research Program.
Most federally sponsored human subject research activities are governed by a set of regulations known as the Common Rule. 18 However, while public health research is governed by the Common Rule, public health activities 19 are among those deemed 'not to be research' and therefore entirely outside of Common Rule's reach. 20 This regulatory exception specifically acknowledges that public health activities may 'use information and biospecimens from a variety of sources,' including, presumably, from existing research studies or data repositories. Section 46.104(d)(4)(iii) further clarifies consent is not required for secondary use of research data or biospecimens for public health activities. So regardless of whether the data used for public health activities are data that have been previously generated for research or novel data generated from research samples, public health activities are legally considered 'not research.' Following from this exemption, the use of research data/specimens for public health activities does not require consent from the individuals to whom those data and samples originated. From this perspective, the SFS would not have needed additional consent of participants for SARS-CoV-2 testing had the SFS's SARS-CoV-2 testing been designated a public health activity. Arguments in favor of research data use for public health activities highlight the difference between the profound physical and emotional harms wrought by historical antecedents, such as the notorious U.S. Public Health Service Syphilis Study at Tuskegee, and the potential dignitary harms caused by data or samples previously derived from consented research participants being used for public health activities. And if the primary risk posed to research participants by public health activity use of their data is dignitary harm, researchers should correspondingly consider the privacy rights of participants (outside of those mutually agreed upon in informed consent) before proceeding with these activities.
The most influential health data privacy protections in the U.S. are codified by the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule. 21 All covered entities and their 'business associates' must follow the HIPAA privacy requirements, which generally covers people/entities providing healthcare, health insurance, or related services. Under HIPAA, outside of their use for care delivery, anyone wanting access to a person's records must obtain their explicit consent with a few very specific exceptions. One of the exceptions that allows for no-signature release of protected personal health information is the request of a 'public health authority.' 22 Within the regulations 'public health authority' is broadly conceptualized as a federal, state, or other territorial division's agency or authority (or their designee), whose mandate includes public health matters.
Notably, the U.S. National Institutes of Health (NIH), the largest funder of biomedical research in the world, 23 is authorized by law to assist as a 'public health authority' based on U.S. Department of Health and Human Services (HHS) interpretation dating back to at least December 2002. 24 As a public health authority, one might argue that the entirety of the NIH's research resources-whether NIH-funded researchers or participants are aware or not-might be accessible for use in public health emergencies unless other restrictions would preclude such use. Notably, the SFS, funded through the private Brotman Baty Institute for Precision Medicine, 25 under NIH's public health authority designation and was not designated as a public health activity by state authorities as it initially pursued SARS-CoV-2 testing. Of further interest with regard to privacy protections, during a pandemic, Certificates of Confidentiality-which are shields protecting identifiable sensitive research information from disclosure-are potentially penetrable, as disclosures are permitted if required by laws regarding the reporting of communicable diseases, necessary for the individuals' medical care, or done with the individuals' consent. 26 Although the human subjects research regulations are relatively clear-cut with respect to public health activities, the ethical considerations for the use of existing research infrastructure for public health activities might not be. Past examples of unethical practice of public health research drove the development of the current regulatory structures intended to protect human research subjects. 27 Almost two decades ago, Dr Nancy Kass set forth an ethical framework for public health practitioners to assess the implications of public health activities, distinguishing biomedical ethics (which relies heavily upon individual autonomy) and public health ethics (which emphasizes justice, among other principles). 28 Later Lee, Heilig, and White (2012) provided a compelling justification for the conduct of public health surveillance in the absence of explicit consent from individual patient-participants, 29 recognizing an ethical obligation to put any public health data collected to use and, similarly, the need to justify nonuse of data that has been collected ['to use the data we collect for public health benefit; not using the data for improving health must be justified' (at 42)].
As Felice Batlan highlights in her analysis of national security claims from the lens of public health emergency, 30 the power to define a 'public health emergency' and the ethical concerns raised by these powers are far from straightforward. These complexities are only compounded if individual researchers themselves-rather than designated public health authorities (such as the NIH as a whole) who/which are, at least, politically accountable-take it upon themselves to engage in public health activities, as did the researchers of the SFS who quietly defied state and federal guidance to continue their testing program. 31 When research resources have been funded by public tax dollars (such as NIH grants), even decisions regarding the well-intentioned donation of supplies and equipment (redirecting such items from research labs that were wound down as nonessential during the pandemic to support emergency medical 26 Compromising individual rights and interests for public benefit has a fraught and contentious history. Yet even the constitutionally protected right to privacy has long been recognized as not absolute but one that is (i) conditioned upon exercise of that individual right to privacy not interfering with another's enjoyment of the same right and (ii) subject to reasonable, proportional, and necessary constraints imposed by state and local authorities fulfilling their roles to ensure public health and safety and by federal authorities supplementing such public health responses when they are inadequate. 34 Moreover, there is a compelling argument that, although not yet widely recognized, there exists a constitutional right to public health. 35 This argument builds upon an acknowledgment that health has individual and collective aspects, as individuals alone 'cannot achieve environmental protection, hygiene and sanitation, clean air and surface water, uncontaminated food and drinking water, safe roads and products, or control infectious disease.' 36 In any case, considering vertical conflicts between local, state, and federal authorities and issues regarding preemption is essential to reconciling researcher obligations that seem to be inconsistent or in conflict within Public Health Law and Ethics: A Reader 2 (2nd ed. 2010)) (emphasis added). The interaction of and relationship between the right of privacy and right of public health are both interesting and important considerations; however, given such a discussion requires advanced legal analysis and involves complex legal theory, it has been left for discussion elsewhere.
the specific context of a public health emergency. Research repositories that cross jurisdictional boundaries could be particularly complicated in this regard when trying to ensure a uniform research experience as well as equitable distribution of risks and benefits. 37
Another dilemma highlighted by the SFS case is the considerations of reporting back to research participants' information that is not explicitly described in the informed consent process. Further complicating matters in the SFS's case was the fact that their SARS-CoV-2 test had not, at the time of their original proposal, undergone traditional regulatory review and approval. The majority of the SFS's laboratories, like many research laboratories, are exempt from the Clinical Laboratory Improvement Amendments of 1988 (CLIA) 38 and therefore generally are not authorized to return individual research results by the FDA. The FDA is the oldest consumer protection arm of the federal government and works to ensure that food, drugs, devices, biologics, and others are trustworthy. Nevertheless, since its inception, the FDA has been criticized for 'slowing the progress' of medical innovation 39 and for its perceived political bent. 40 An Emergency Use Authorization (EUA) under Section 564 of the Federal Food, Drug, and Cosmetic Act (FD&C Act) allows for the special use of unapproved medical products during some types of emergencies. 41 These are sometimes called 'medical countermeasures' (and include, for example, in vitro diagnostic tests, personal protective equipment, antivirals, vaccines, and biological therapeutics) that can be used 'to diagnose, treat, or prevent serious or life-threatening diseases or conditions' when there are 'no adequate, approved, and available alternatives.' 42 For example, in the case of SARS-CoV-2, HHS Secretary Alex Azar issued a determination on February 4, 2020, that COVID-19 'is a public health emergency and that circumstances exist justifying the authorization of emergency use of in vitro diagnostics for detection and/or diagnosis of the novel coronavirus.' 43 On February 29, 2020, the FDA issued guidance to 'accelerate the availability novel coronavirus (COVID-19) diagnostic tests developed by laboratories and commercial manufacturers during the public health emergency.' 44 This guidance stressed the importance of test validation, limits of detection, accuracy, and inclusivity; recommended the inclusion of a transparency statement that the test has been validated but FDA's independent review of this validation is pending on all results; and required laboratories to report positive results immediately to federal, state, and local public health authorities. 45 The return of research results has been a Catch-22 for this reason. If researchers share information that turns out to be inaccurate or misleading, they might be held liable for the erroneous disclosure. Alternatively, if researchers withhold information that could be considered clinically relevant, they might be liable for failing to disclose this information. Expert panels 46 have recommended that research results be returned with clear disclaimers regarding their potential limited reliability and validity, but participants might not fully appreciate these limitations. Liability concerns (at least those related to disclosing the information), however, seem reduced in the context of actions taken in immediate response to COVID-19, given the liability immunity declaration issued by the HHS. 47 While this immunity declaration unequivocally includes testing for SARS-CoV-2 within its scope of covered countermeasures, researchers do not categorically fall within the scope of covered persons. For immunity protection to be applicable, researchers would need to be recognized as 'qualified persons.' 48 It is possible, but not a given, that NIH-funded researchers could be within this category.
Additionally, when considering the return of unexpected research results derived from public health activities, what, if any, considerations should be given to participants right not to know, for example, in the case of SARS-CoV-2 antibody testing? While 'right not to know' considerations within the specific context of an oft-fatal infectious disease might seem a stretch, reporting such results might seem contrary to the 'no surprises' principle in biomedical research, (which essentially means that researchers should avoid data practices that fail to align with participants' understanding and expectations). 49 When asked, the many of participants from a variety of different types of research want and expect to receive results back from their research participation. 50 Given these expectations, is it necessary to obtain consent to return research results? In the past decade, 'right not to know' has been supported primarily in terms of incidental findings on genetic assay. 51 For many genetic conditions, there are no treatments. However, in the case of results generated as the result of a public health emergency, an individual's right not to know might be supplanted by the public good of informing them. If research resources are later used for public health activities, a question not definitively answered and likely requiring a case-by-case determination is whether reporting of those results should be treated pursuant to research norms (which historically have required consent) or public health norms (which prioritize information access to control the spread of disease over individual preferences).
Although the return of results might seem like a minor consideration, as 'back to work' certificates are being contemplated by many governments, the implications of whether and which SARS-CoV-2 results are to be returned should not be summarily dismissed by researchers or policy makers. 52 Such concerns underscore the need for a system of ethical board oversight or other structured consultation, to aid researchers in assessing the risks and benefits of using research resources for public health activities.
Finally, are there any additional reporting concerns raised by legal mandates to disclose to public health authorities at different governmental levels if consent has not been obtained specifically? Public health reporting varies from aggregate, potentially anonymous data (eg, disease prevalence) to fully identifiable data (eg, contact tracing). Because public health response toolkits include police powers and the ability to infringe upon individual civil liberties, there are understandable concerns regarding the numerous potential uses for research data that might be generated or seized during a public health emergency. For example, because of the immigration law implications (such as the Inadmissibility on Public Charge Grounds final rule), undocumented immigrants might be unwilling to risk seeking health care during the COVID-19 pandemic regardless of public statements from U.S. Citizenship and Immigration Services (within the Department of Homeland Security) that seeking services to test, treat, or prevent COVID-19 would 'not negatively affect' any individual in the Public Charge analysis. 53 The inclusivity of a research data set being contemplated for use as part of a response during a public health emergency might require careful consideration regarding whether doing so advances or impedes an equitable distribution of the benefits and risks not only of the public health surveillance itself but also (i) the actions taken and policies developed and implemented based on those results made possible with that research resource and (ii) the subsequent willingness to participate in research. 54 One example to highlight this dilemma is contact tracing. Public health authorities in other nations have adopted contact tracing to identify networks of exposed people. 55 Given that human subject research studies now commonly include connected devices which collect data that could be valuable in contact tracing, this is of particular concern. Researchers themselves struggle with appreciating the scope and implications of privacy concerns raised by the scope of big data research, 56 leaving ethics review boards and the participants they serve at a loss. 57 In the public health emergency context, these powerful data might only further obscure variables in the delicate calculus of individual risk and public benefit, underscoring the benefit of establishing formal consultation and review processes for public health activities that would use research data.
Both the volume and granularity of data collected in research repositories are orders of magnitude greater than it has ever been. However, utilizing these data-as well as the research infrastructure that supports them-in the name of public health response is not without risk. The differing legal and ethical obligations for research and public health activities are worthy of researchers' careful consideration even in the face of a public health emergency imposing powerful urgency constraints on decision-making.
To be clear, these tensions should not inhibit research from proceeding during a pandemic nor the transfer of research resources to public health activities per se. Rather, it is incumbent upon the research community, including biomedical legal and ethical scholars and practitioners, to reflect upon the many tensions experienced during the COVID-19 pandemic between public health initiatives (the infrastructure and support for which has been proven woefully inadequate in the U.S.) and biomedical research (the leveraging of which might be particularly useful in times of public health emergencies, regardless of the state of public health infrastructure) and consider the creation of a formal consultative process, so that, in the future, research infrastructure might be called upon both responsibly and swiftly to augment public health initiatives. Further, as ever larger and more diverse datasets are amassed, the lines between research and public health activities-not to mention clinical care-will continue to blur. The current pandemic highlights the need for each of these communities-researchers, public health authorities, and clinicians-to reconsider the legal and ethical bounds of their mandates and critically examine areas of overlap. Active engagement with policy makers is needed. Finally, it would be particularly prudent for the research community, equipped with its robust resources and good intentions, to think critically about how to avoid the research enterprise being simply an enabler for the continued neglect of public health in the U.S.
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Coronavirus disease 2019 (COVID-19), a novel respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in December 2019. Moreover, COVID-19 is highly contagious and quickly expanded into a pandemic, which put enormous strain on the public health system worldwide. As we know, the symptoms of the patients infected with SARS-CoV-2 vary from person to person, including asymptomatic infection, respiratory symptom, and acute respiratory distress syndrome [1] . Noteworthy, some patients had ocular manifestations including conjunctival hyperemia, chemosis, epiphora, or increased secretions [2] . A recent study reported that SARS-CoV-2 receptor angiotensin-converting enzyme 2 and entry protease TMPRSS2 was strongly detected in human conjunctival, limbal and corneal epithelium, indicating that human ocular surface might provides a potential entry portal for SARS-CoV-2 [3] . In order to understanding the relationship between SARS-CoV-2 infection and ocular diseases, estimating the prevalence of the COVID-19 in ocular disease patients is urgently needed.
The prevalence of COVID-19 in ocular disease patients is difficult to estimate. Firstly, the diagnosis of COVID-19 depends on viral RNA detection that tested by reverse transcription polymerase chain reaction (RT-PCR) usually in symptomatic individuals [4] , and the viral RNA detections in asymptomatic individuals are limited. A research in Spain showed that approximately one third patients infected with SARS-CoV-2 were asymptomatic [5] , which reminded us that there still many asymptomatic patients have been undetected and undiagnosed. Secondly, it is difficult that detecting SARS-CoV-2 RNA in tears sample of patients whose throat swabs showed positive result, even at the patients of COVID-19 with ocular manifestations [6] . Therefore, it is necessary to consider about utilizing serological assay to detect SARS-CoV-2 infection in the subclinical patients with ocular disease [7] .
The serological test, a validated assay for antibodies (IgG and IgM) against the SARS-CoV-2 viral, have advantage of easy serum sample collection and high throughput. Most patients with COVID-19 can detect antibodies between 7 and 14 days after diagnosis [8, 9] , and the antibodies still remain at high level at 4 month after diagnosis [10] . In this study, we assay the IgG and IgM antibodies in ocular disease patients undiagnosed COVID-19 (people have no symptom of COVID-19 and negative result for viral RNA testing) to estimate the seropositivity rate in different type of ocular disease.
We enrolled 1331 individuals with different ocular diseases but negative to SARS-CoV-2 RNA testing in Eye and ENT Hospital of Fudan University from February 2020 to May 2020. A total of 1331 individuals, including 34 xerophthalmia patients, 8 keratitis patients, 4 conjunctival cyst patients, 454 cataract patients, 38 glaucoma patients, 188 refractive error patients, 90 strabismus patients and 515 other ocular diseases patients, were enrolled.
Demographic data, including age, gender and the diagnosis of ocular diseases of each participant, were collected. The participants were screened for SARS-CoV-2 . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.
is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted September 23, 2020. . infection by a serological test for IgG and IgM antibodies against a recombinant antigen of the virus. For all study individuals, RT-PCR tests for viral RNA from throat swabs were conducted.
The Medical Ethics Committees of Eye and ENT Hospital of Fudan University approved this study, and the study adhered to the principles of the Declaration of Helsinki. Informed consent was obtained from all participants.
Throat swabs were collected and tested for SARS-CoV-2 RNA in a designated virology laboratory (KingMed Diagnostics, Shanghai, China) using the RT-PCR assay. Serum samples were collected in clinical laboratory in Eye and ENT Hospital of Fudan University. The IgG and IgM antibodies against SARS-CoV-2 spike protein and nucleoprotein were measured using a commercially available magnetic chemiluminescence enzyme immunoassay kit (Bioscience, Chongqing, China) according to the manufacturer's instructions. Antibody levels were expressed as the ratio of the chemiluminescence signal over the cutoff (S/CO) value. An S/CO value higher than 1.0 for either IgG or IgM was regarded as positive. If S/CO value higher than 0.7 but lower than 1.1, the serum sample will be retested. Previous study has been validated serological assay with serum samples [13] .
We conducted a serological survey testing the IgG and IgM antibodies against SARS-CoV-2 antigens in each participant of different ocular disease. The level of IgM and IgG antibodies are presented in Fig 1. We found the seroprevalence was 0.83% in total 1331 individuals with ocular diseases. Furthermore, seroprevalence in different type of ocular disease vary from 0% to 25%. Conjunctival cyst group had the highest seroprevalence up to 25%, the following is the keratitis group with the seroprevalence of 12.5%. We estimated a seroprevalence of 4.41% in cataract group, 2.94% in xerophthalmia group, 2.63% in glaucoma group, 2.22% in strabismus group, 1.60% in refractive error group, and 0% in other ocular diseases group (table 1) .
Then, we divided the all patients into three groups: ocular surface diseases group, no-ocular surface diseases group and visual optics diseases group and the seropositive rate were 1.91%, 0.36% and 1.45%, respectively (table 2).
Assessing the prevalence of COVID-19 in patients with ocular diseases will help us understand the relationship between ocular disease and SARS-CoV-2 infection. Our study evaluated the seroprevalence in patients with different ocular diseases, including xerophthalmia, keratitis, conjunctival cyst, cataract, glaucoma, refractive error, strabismus and others. We assessed the performance of the IgG and IgM from 1331 outpatients of SARS-CoV-2 RNA testing negative. In this study, the IgG and IgM antibodys we assayed are targeted to the nucleoprotein and a peptide from the spike protein of SARS-CoV-2 [11] .
The result of our study showed that total positive rate of IgM or IgG (0.83%) was . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.
is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted September 23, 2020. . close to the seropositive rate (0.8%) of community setting from several cities in china which reported by another serological study [12] . However, the seroprevalence was significantly high in specific groups contain keratitis group and conjunctival cyst group. Some clinical and scientific evidences indicated that human ocular surface is susceptible to SARS-CoV-2 [13, 14] . A recent case reported that a clinician wearing N95 mask but not protecting eyes was infected with SARS-CoV-2 [13] . An animal study showed that SARS-CoV-2 can infect patients via the conjunctival route in rhesus macaques [14] . Therefore, it is possible that patients with ocular diseases, especially ocular surface diseases such as keratitis and conjunctival cyst, manifest the SARS-CoV-2 receptor angiotensin-converting enzyme 2 up-regulation in ocular surface and more sensitive to SARS-CoV-2 infection [15] . Nonetheless, the infection mechanism of conjunctical route needs further researched.
Our study has some limitations. First of all, this was a single-center study. All of the individuals involved in our study were from Eye and ENT Hospital of Fudan University and the number of participant was not large enough, which might influenced presentation of the seroprevalence we estimated. Next, if samples were collected before infected individuals had serological response, the result of serological assay could produce false negative. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted September 23, 2020. . is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted September 23, 2020. . is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted September 23, 2020. . https://doi.org/10.1101/2020.09.22.20198465 doi: medRxiv preprint
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In the mid of December, a viral infection called coronavirus disease 2019 (COVID- 19) was initially identified in Wuhan City of China [1] and it is believed that human contracted it from wild animals. It has caused thousands of deaths around the world and World Health Organization (WHO) declared it as pandemic on March 11 [2] . COVID-19 infection lead to respiratory illness and has sign like flu, fever, cough, myalgia, diarrhea, and dyspnea [3] . It is a highly contagious and is transmitted via bodily contacts and a respiratory bead from the infected patients, which is now the main source of transmission of the disease. The existence duration for the virus can be up to 12 hours or even two days on a contacted surface [4] . The fatality rate is higher among the young children and elderly aged group ≥ 60 years [5] .
At present (as of April 14, 2020) the infected patient's population worldwide is recorded as 1,925,877 (1.9 million) with 119,719 deaths and 452,333 recoveries [6] , and it is expected that these statistics is increasing exponentially in the upcoming days.
In Pakistan the first two cases of COVID-19 appeared on 26 th February 2020, within 48 hours three more cases appeared from different cities around the country and there was no linkage between these patients. Gradually, these cases increased exponentially until 14 th April the cases were 5,716 with most cases of Punjab 2,826, 1452 cases, 800 cases, 233 cases, 231 cases, 131 cases, and 43 cases of Sindh, KPK, GB, Baluchistan, Islamabad and AJK respectively. With most effected cases the recoveries were recorded to be 1,378 with 96 deaths [7] . COVID-19 is pandemic and to control its spread, preventive measures be taken. For patients, all body fluids and electrolytes should be continuously checked with vital signs and to avoid further spread, they should be incubated with strict clinical measures under preventive guidelines [8] . The government need to find a strategy to fight this war in timely fashion, such as authorities took further measures of closing borders, suspending community services and schools, minimizing both domestic and international travels until further notice [9] . The purpose of these measures is to limit the chances of physical contacts among people, so that transmission of COVID-19 is controlled, as the incubation period for this virus is relatively longer than other viruses.
Due to the novel nature of the virus, there is greater uncertainty around the decision on optimal time of disappearance of this disease. Therefore, short term forecasting is extremely important even in the slightest hint for predicting the upcoming month for the better management of the societal, economical, cultural and public health issues [10] . In the past few months researchers have developed or employed existing mathematical and statistical methods to predict the number of COVID-19 cases and related outcomes. Fractional time delay dynamic system (FTDD) reflects good forecast agreements to the public data [11] . Generalized logistic model (GLM) indicates that the epidemic growth was exponential in china [12] . Based on prediction, situation will be worsened in entire Europe and USA will become the epicenter of new cases during mid of April 2020 [13] . Around 2 million people will be infected by the beginning of May if no measures are taken [14] . Predictions/estimates help to strengthen the strategies in order to prevent the pandemic from worsening. In this research study, we used the available data to forecast the number of confirmed COVID-19 cases, deaths and recoveries in Pakistan for upcoming month. This forecasting is aimed to help government institutions and policy makers as well as public in adopting new strategies and strengthening the existing preventive measures against COVID-19 pandemic. In addition, this study may help in reliving current socioeconomic and psychosocial distress caused by COVID-19 among public in Pakistan.
We obtained data for the number of daily accumulated confirmed cases of COVID-19,
The available data is limited and is affected by fluctuations i.e. highly variable cases were reported day by day. As a result, Cumulative data is used to predict the number of cases in Pakistan. The cumulative number of COVID-19 confirmed cases, deaths and recoveries are expected to show exponential growth over time. Therefore, we used the simple time series methods of Auto-Regressive Integrated Moving Average (ARIMA) Model [16] to forecast the number of cases, deaths and recoveries for upcoming month. The ARIMA model has higher fitting and forecasting accuracy than exponential smoothing [17] . It captures both the seasonal and non-seasonal forecasting trends. Due to the limited available data, we simply focus on nonseasonal models to describes the pattern (growth) over time. Hence, we assumed that the pattern of current cases will continue in the near future (at least a month). We believe that the ARIMA model, which is the combination of Autoregressive (AR) and Moving Average (MA) fits well to the nature of the available data and provide good forecasting for the short time series data. The forecasting and prediction intervals until the end of May is produced from the fitted model. In order to assess the model fit, parameters (p, d, q) are identified by Autocorrelation function (ACF) and Partial Autocorrelation function (PACF); whereas, p is the autoregressive term, d is the differencing order and q is the moving averages term.
Furthermore, ARIMA (p, d, q) results are based upon Akaike information criterion (AIC) which is a goodness of fit test such that model with minimum AIC is considered best. All statistical analyses were conducted using the R-library "forecast, tseries and zoo" [18] developed for fitting ARIMA model.
In Pakistan, the number of COVID-19 cases is now increasing exponentially, Figure 1 . Using 47 days data from 26 February 2020 -12 April 2020 and ARIMA model, we forecasted the data up to 31 st of May. As, we were dealing with timeseries and non-stationary data, it is observed that mean and variance of data is variable in nature. Therefore, double differencing is used, in order to stabilize (made stationary) the data by removing trends.
ARIMA (0,2,1), ARIMA (2,2,0) and ARIMA (1,2,1) is applied to produced plots for the number of confirmed cases, recoveries and deaths over time (days) as shown in 2, 3, and 4 respectively of Figure 1 . Results from the model revealed that the number of confirmed cases show a rapid exponential growth which may increase by 2.7 times compared to current cases until end of May 2020. The 95% prediction interval for confirmed cases is from 5681 to 33079 which are at much higher growth, Figure 2 . The results from the forecasting model for deaths revealed that deaths may be increased up to 500 at the end of May if the current mortality rate prevails. The 95% prediction interval for mortality is estimated to be 168 to 885, Figure 3 .
Similarly, the forecast model for recoveries showed an exponential growth. The model revealed that the number of recoveries will be possibly increased by 8 times at the end of May, with 95% prediction interval of 2391 to 16126, Figure 4 . Pakistan at higher rate as compared to the number of recoveries as the disease is spreading to a wider region of the country.
Similar kind of forecasts has been conducted by other researchers such as [10] but with slightly different method of the forecasting models and presentation of the results is not delivered in a simple way to be understood to a layman, while others are now planning to conduct or continue to conduct such a kind of analysis [19] . It is important to note that majority of the research studies are modeling the preparedness scenarios to inform planning rather predictions [20] , that is they informed the actions to be taken to slow the spread and prepare [23, 24, 25 ]. Yet, the results of this study suggest an increasing trend of COVID-19 cases and deaths for the upcoming month and we recommend continuation of the above or more stringent measures to contain COVID-19. We believe that the forecasts established by this study is useful for Pakistani government and public in making informed decisions and taking appropriate steps to prevent further spread of COVID-19 disease.
We assume that the analysis for this study is based on an accurate data recorded by NIH [26] in Pakistan and we used appropriate forecasting methods (timeseries modelling-ARIMA).
The modeling strategies is based on current trends and non-seasonal timeseries variations, following the patterns shown in Figure 1 ; assuming the data is accurate, and the trends will continue in the upcoming month of May. We used conventual statistical approaches AIC [27] for model assessment and selection. However, we acknowledge that our analysis is based on the assumptions and if the assumptions are not true, it may lead to an inaccurate forecast.
Furthermore, forecasting with timeseries modeling, requires enough historical data, which is not the case with our analysis, and there is always uncertainty associated with prediction as current patterns in the data may not be continued to future.
As Pakistan is a developing country, having a lack of medical facilities which resultantly is affecting the situation further no vaccine or medicine is developed yet to prevent or cure the COVID-19 pandemic permanently. The public health officials and government should take hard decisions to control the rapid increase of the COVID-19. Besides officials, the general public should keep social distancing and use precautions to ensure their safety and control the disease from further spreading.
We declare that none of the author has the competing or conflict of interest.
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The novel coronavirus SARS-CoV-2 causes Coronavirus disease 19 (COVID-19), an established global health crisis. 1, 2 The COVID-19 pandemic continues to take a significant toll on the global economy and healthcare infrastructure, and is attributed to more than 700,000 deaths worldwide; over 160,000 in the United States of America alone.
The number of infections, and resulting COVID-19-related deaths continues to grow at a staggering rate. Older individuals, and those with pre-existing conditions, are at the highest risk of death as a result of deleterious consequences related to SARS-CoV-2 infection. Moreover, negative outcomes associated with SARS-CoV-2 infection disproportionately correlate with minorities, likely due to a number of factors. 3 The magnitude of the COVID-19 pandemic has triggered a global response from researchers to identify therapeutics and/or prophylaxis capable of inhibiting, or slowing, infection and propagation of this deadly disease.
SARS-CoV-2 must enter host cells to replicate. Previous studies on SARS-CoV, which is closely related to SARS-CoV-2, provided insight into the mechanism of cell entry.
As an early step in the cell entry mechanism, the viral spike protein (S) on the surface of SARS-CoV binds the extracellular protease domain (PD) of angiotensin-converting enzyme 2 (ACE2), a protein on the surface of multiple cells, including cells in the lower respiratory tract. [4] [5] [6] [7] This recognition event is followed by membrane fusion leading to host cell entry. It was recently shown that SARS-CoV-2 also relies on an interaction between its spike protein and ACE2 to gain entry to the interior of human cells. Cryo-electron microscopy (cryo-EM) structural analysis of the complex involving the SARS-CoV-2 spike protein Receptor Binding Domain (RBD) and human ACE2 was recently reported (PDB code: 6M17), with an overall resolution of 2.9 Å and local resolution of 3.5 Å at the RBD / ACE2 binding interface (Figure 1a) . 8 Given the important role the Protein-Protein Interaction (PPI) between SARS-CoV-2 RBD and ACE2 plays in host cell entry, inhibition of this PPI has received attention as a target for therapeutic and/or prophylactic intervention. 9, 10 Regions on ACE2 closest to SARS-CoV-2 include the α1-helix (Figure 1b , blue) α2-helix (Figure 1b , orange) and the β3-β4 loop (Figure 1b, green) . Researchers have shown that a 23 residue peptide, consisting of ACE2 α1-helix sequence (I21-S43) tightly binds SARS-CoV-2 (KD ~50 nM). 10 However, relatively little is known about the molecular underpinnings that stabilize the SARS-CoV-2 / ACE2 complex. In an era when academic laboratories have been closed, or severely limited due to the COVID-19 pandemic, we sought to use multiple computational platforms, with an emphasis on servers that are available online to all researchers, to study the SARS-CoV-2 RBD / ACE2 complex examine the electrostatics and topology of the interface, and identify "hot-spots" -amino acids, or clusters thereof, that significantly contribute to the binding free energy of this therapeutically-relevant PPI.
We used the Knowledge-based FADE and Contacts 2 (KFC-2), a free server that compares favorably to Robetta, FOLDEF, HotPoint, and MINERVA, to predict hot-spot residues and/or clusters at the SARS-CoV-2/ACE2 binding interface. 11, 12 As a positive control in our study, we performed an analogous examination of the PMI / MDM2 complex (PDB code: 3EQS, Figure 1a) , which is well studied. 13 PDB files for these two complexes were loaded into the server, which revealed hot-spot residues at each interface. KFC accurately predicted hot-spot residues on the PMI peptide, which have been experimentally validated (Figure 2a) . 13 Specifically, residues F3, Y6, W7, and L10 were identified as hot-spot residues on the PMI peptide. Complimentary hot-spot residues L54, V75, V93, and I99 were identified as hot-spot residues on MDM2 (Figure 2a- were identified on SARS-CoV-2 RBD and T27, H34, D38, Y41, and K353 were identified on ACE2. For both complexes, KFC-a values were used, as these have been shown to have superior predictability outcomes compared to KFC-b values. 12 Satisfyingly, four of the five predicted hot-spot residues on ACE2 (T27, H34, D38, and Y41) are found on the α1-helix (Figure 1b , blue), and researchers have shown that this helix alone (as a chemically synthesized 23 residue peptide) binds SARS-CoV-2 RBD with a dissociation constant of ~50 nM. 10 Lysine 353 was also identified as a hot-spot residue, and is on the β3-β4 loop that neighbors the α1-helix (Figure 2d ). When paired with experimental results, demonstrating high affinity between ACE2 α1-helix and SARS-CoV-2 RBD, these results suggest that KFC-2 correctly identified residues at the interface critical to stability of the complex.
We next used BAlaS 14, 15 , a computational alanine scanning mutagenesis server, to predict the change in free energy (ΔΔG) associated with mutating interface residues to alanine. Our analysis focused on residues within 13 Å from the binding interface (set as default) and residues plotted in BAlaS analysis of the SARS-CoV-2/ACE2 complex resulted in the prediction of seven residues on ACE2 that contribute to the binding free energy of the complex (Figure 3c-d) . The following residues, and associated changes in free energy, were identified: (Figure 3cd) . As was the case with the initial hot-spot prediction, the majority of the residues predicted to stabilize the complex are on the α1-helix (D30, K31, H34, D38, Y41). As in the KFC-2 hot-spot prediction, K353, which is found in the β3-β4 loop that flanks the α1helix, was predicted as a stabilizing residue in the complex. Tyrosine 83, in the α2-helix (Figure 1b, Figure 3c-d) , was also predicted as a contributor to complex stability.
Predicted changes in binding free energies for all computational mutations, for both PMI / MDM2 and SARS-CoV-2 / ACE2, are available in the Supporting Information ( Figure S2 ).
We used the Adaptive Poisson-Botzmann Solver (APBS) 16 to generate electrostatic potential maps for the solvent-exposed surfaces of our positive control PPI (PMI/MDM2) and the SARS-CoV-2 RBD complex. As seen in Figure 4a -b, the positive control interaction is consistent with many PPIs, the driving factor for the PMI/MDM2 interaction is burying large, hydrophobic residues (most notably F3, W7, and L10) into a well-defined, largely hydrophobic, binding pocket. This results in relatively large changes in Gibbs' free energy, as a result of beneficial changes in entropy (desolvation) and enthalpy (e.g. van der Waals interactions, π-π stacking). The binding face of the SARS-CoV-2 RBD / ACE2 complex (Figure 4a) was characterized as well. The binding surface of ACE2 has a pronounced patch with increased hydrophobic character, relative to the remainder of the surface, which aligns with the α1-helix (Figure 4d) . Likewise, SARS-CoV-2 RBD presents a relatively shallow binding pocket with hydrophobic character, into which the α1-helix rests (Figure 4d) . In contrast to the PMI / MDM2 complex, neither the ACE2 or SARS-CoV-2 surface contain deep, largely hydrophobic binding pockets.
Collectively, this supports our hot-spot and computational alanine scanning mutagenesis studies. Compared to PMI / MDM2, more residues participate in stabilizing the complex; however, the magnitude of predicted stabilization is lower for each residue in the SARS-CoV-2 / ACE2 complex, compared to PMI / MDM2. We hypothesize that this is likely due to decreased burying of hydrophobic residues in the former, and increased hydrogen bonding and/or ion-paired interactions to stabilize the complex, relative to the later. KFC-2 hot-spot prediction revealed five residues each on ACE2 and SARS-CoV-2 RBD that are predicted to stabilize the complex; computational alanine scanning with BAlaS predicted seven residues on each protein, which when mutated, significantly alter binding energy. There is good agreement between the two methods; both servers predicted ACE2 residues H34, D38, Y41, and K353, and SARS-CoV-2 RBD residues Y489, Q498, and Y505 as important for complex stability (Figure 5 , residues highlighted with an asterisk).
Interestingly, while the structure of SARS-CoV RBD aligns well with SARS-CoV-2 RBD, with a root mean squared deviation (RMSD) of 0.68 Å over 139 pairs of Cα atoms 8 , mutations exist, including interface residues predicted here to stabilize SARS-CoV-2 RBD interactions with ACE2. For example, Y484®Q498, L443®F456, N479®Q493, and L472®F486 mutations at equivalent positions of SARS-CoV RBD and SARS-CoV-2 RBD, respectively, are observed. 7, 8 These mutations may change the affinity between SARS-CoV-2 for ACE2, relative to SARS-CoV, and likely alters the hot-spot geographies on the binding surface of SARS-CoV-2 RBD, compared to SARS-CoV. Electrostatic potential and topology of ACE2 and SARS-CoV-2 RBD surface areas that engage one another in the complex. Colored from -25 kT/e (red) to +25 kT/e (blue).
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In an attempt to improve personal protection against COVID-19 in locations such as in hospitals that are experiencing an insufficient supply of respirator masks [1] , the properties of surgical isolation material were tested for suitability in the production of FFP-2 respirator masks. The choice for this material was selected based on its filtering properties and on its availability in most hospitals, and the near-worldwide sales market. The properties were also tested following sterilization to allow re-use of the material. Finally, the potential speed of fabrication of a complete respirator mask was evaluated with the goal of rapid fabrication from basic materials in less than 5 minutes.
The transmission of surgical sterile isolation and wrapping material (Halyard Quickcheck H300, Owens & Minor, Inc.) was tested with a particle counter (SOLAIR 3100, Lighthouse Worldwide Solutions Benelux B.V.). The flowrate was set at 1.0 cfm flowrate, which is well above (4x) normal breathing and the transmittance of material for particles of 0.3 µm, 0.5 µm and 3.0 µm was measured. We used 1, 2 or 3 layers of the material and performed measurements on different samples of the tissue. For each particular sample, the test was repeated 4 times. Tests for splash resistance were performed with a water column pressure test. All tests were repeated following a steam sterilization procedure (5 min at 135 degrees Celsius and 2.0 atm. pressure). Some additional tests were carried out with the tissue reversed, or after wearing the respirator mask for 15 min.
With 3 layers of the material, a mean particle collection efficiency of 93.84 %, 99.45 %, and 99.99 % was achieved for particles of 0.3 µm, 0.5 µm and 3.0 µm respectively, which meets the criterion for FFP-2 respirator masks (summary results in Table 1 , complete results in Suppl. Data). With 2 layers of the material a collection efficiency of 88.23%, 98.31% and 99.98%, respectively, was achieved fulfilling criteria for FFP-1 respirator mask. When the transmission was tested after wearing the respirator mask for 15 min, the test results improved, i.e. collection efficiency went up, by about 20%.
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The copyright holder for this preprint this version posted April 15, 2020. With 3 layers of material, the splash resistance was 105 cm H2O, and for 2 layers it was 92 cm H2O. When tests were carried out with the tissue reversed, identical outcomes were obtained in all tests, both in particle collection efficiency and in splash resistance.
Following sterilization, the value for transmittance of 0.3 um particles dropped below requirements for FFP-2 requirements, but was sufficient for re-use as FFP-1. Transmittance for 0.5 and 3.0 um particles remained above FFP-2 requirements.
The sterile packaging material showed high filtration efficiency on the measured particle sizes. The best filtration values have been found for triple layers of unsterilized material. The 0.3 µm is generally seen as the most penetrating aerosol size [2] , which also corresponds to the particle filtration efficiencies found in this study. The triple material layers achieved a 93.84% average efficiency for this particle size, which is very close to the requirements of efficiency required for N95 and FFP2 respirator masks (95% [3] and 94% [4], respectively). The test for splash resistance was included to demonstrate the water resistance of the material, which is not a requirement for respirator masks, but contributes to protection against coughing and sneezing.
A possible respirator mask design with triple layer material (Figure 1 ) could be produced efficiently using conventional manufacturing methods and materials (aluminum, neoprene rubber and elastic). Additionally, in a qualitative test the breathability remained good and the fit was adequate (FT-30Fit-test, 3M).
Overall the material is suitable for the local fabrication of respirator masks for hospitals worldwide, where the current demand and supply chain limitations prevent a suitable supply of mass manufactured protective equipment. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted April 15, 2020. The sheet is folded to provide alignment with the face, and thereby ensure the respirator mask has an adequate fit when worn. The elastics (Resistance Band, Matchu Sport BV) is laser-cut to a width of 13/32 inch (10mm), and a length of 7 7/8 inch (200mm) and attached at the inside of the respirator mask. A single stitch line at the bottom ensures that the surface of the respirator mask stays separated from the mouth and allows to adjust the size of the respirator mask for -and by-anybody.
(B) For the nose clip a 0.5mm thick aluminum strips (Al 99.5%, 1050A) is used, cut to a length of 3 1/2 inch (90mm) and a width of 5/32 inch (4mm). A neoprene strip with adhesive is used to hold the noseclip in place, and adhered to the inner-top side of the respirator mask. The respirator mask was subjected to a qualitative fit-test (FT-30Fit-test, 3M).
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The copyright holder for this preprint this version posted April 15, 2020. . https://doi.org/10.1101/2020.04.10.20060632 doi: medRxiv preprint
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In Argentina the first case of the epidemic of Covid-19 was reported on March 3, 2020. As the WHO declared the disease as pandemic by March 11, 2020, health authorities decided to pose a mandatory lockdown since March 20, 2020 in order to prevent rapid propagation of infections and prepare the expansion of health infrastructure. After April 6, 2020, the government adopted a sequential easing of movements for selected economic activities combined with social distance measures, such as wearing masks and preserve the required distance between people.
Even though it is known that isolation and interventions that limit populations movements and contacts curb the spread, health authorities still do not know how the virus is spreading within the national borders and in specific territories, like towns, cities or densely populated areas. Also, as testing is limited, the proportion of asymptomatic is not known nor if contagion takes place during the pre-symptomatic phase of the disease. Besides the basic figures about confirmed cases, recovered or deaths, the development of local epidemiological indicators is still weak.
In infectious diseases, one of the key indicators is the serial interval (SI from now on), defined as the time from illness onset in infector (index or primary case) to illness onset in infectee (secondary case). This indicator contributes to the understanding of the transmissibility of the disease (Fine 2003) . Actually the SI is widely used to compute the effective reproductive number, that is the average number of secondary infections caused by each infector (Wallinga & Lipsitch 2007) . Estimates of the SI can only be obtained by linking the dates of illness onset between infector-infectee pairs. Thus, the main source of information emerges from clusters of infections. standard deviations in parenthesis reported 95% CI in brackets * The authors also provide estimations for 18 pairs with certainty about onset dates. U = unpublished, during peer review process Source: own based of references . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted June 20, 2020. . Up to date, available figures of SI for Covid-19 come from a few regions, the majority belonging to regions with an early outbreak (see Table 1 ). As Peak et al (2020) point out, more data about the serial interval is needed to evaluate interventions (contact tracing, selective quarantines, etc). If SI is overestimated quarantine interventions may be excessive. On the contrary, if SI is underestimated, interventions may be insufficient to curb the spread. At the same time, if SI is relatively short, symptomatic cases will emerge rapidly and health authorities will need to focus efforts in testing infrastructure and coordination. If SI takes longer it may be a signal of low asymptomatic transmission and less pressure on testing inputs.
Considering the incubation period, if transmission occurs mainly inside the households the date of exposition is uncertain and restricts the estimations. Only 6 empirical studies provide figures about the time since exposition to illness onset (see Table 2 ).
Between March 20, 2020 and May 8, 2020 36 cases were reported as positive for SARS-Cov-2 in Bahia Blanca city (Argentina). Local health authorities collected the date of illness onset and the date of exposure of each patient. As most of them emerged in clustered transmission it was possible to identify the infectorinfectee pair in the chain.
From the total confirmed cases, 13 of them were imported and 23 were local cases. In addition, 4 of 23 local cases (17%) were asymptomatic up to May 8, 2020.
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The copyright holder for this preprint this version posted June 20, 2020. . https://doi.org/10. 1101 We have 17 observations of individual serial intervals emerged in 7 clusters of patients and 15 individual observations about the incubation period in patients who reported the date of exposition to their infector.
Also, the date of exposition is probable in 3 cases, so we re-estimated the incubation period excluding those cases from the sample.
In most pairs (70%), the infectee is part of hospital staff and contracted the disease in workplace, in close contact with patients. For some of them (4 cases) the infector could not be clearly identified as more than one patient could have transmitted the virus. In those cases, we assigned the infector as the one exhibiting the closest period with the infectee´s illness onset. For that reason, following the procedure adopted by Nishiura et al (2020) , we split the sample of pairs between certain and probable observations. The subsample of certain pairs has 13 observations. We assumed the serial interval follows a Gamma distribution and time to symptoms is distributed as a Lognormal (Lesser et al, 2009 ). The parameters were estimated using the fitdist command from fitdistrplus package in R using the maximum likelihood estimator, accepted as the best method to estimate the time to event from patient data (Wallinga & Teunis, 2004; Bolker 2008) . Confidence intervals for the median were obtained using the quantile matching estimator.
We also estimate the mean SI from the sample of patients assuming uncertainty in probable dates of symptoms onset. This requires a Bayesian approach, based on a numerical technique known as Markov Chain Monte Carlo (mcmc). This procedure estimates a posterior sample of SI distribution, which is a kind of average between prior beliefs of the distribution (e.g Gamma) and observed data. The Bayesian approach can be more accurate in diseases with less known dynamics.
In the sample of 17 infectee-infector pairs we found that 2 patients became infected during pre-symptomatic phase as their infector manifested symptoms after the exposition. Also, in the sample of cases with incubation dates, 1 case got infected from an asymtomatic infectious. Taking togheter, the proportion of transmission before symptoms onset or from asymtomatic cases is 16.6% (3 cases between 18).
As the number of observations is modest and parametric estimation methods have asymptotic properties, we also checked results with bootstrapping techniques (see Supplementary Materials).
Findings are presented in Table 3 . The mean incubation period for symptomatic patients is 7.9 days (95% CI 4.6, 11.1) considering the sample of 15 cases patients and 7.5 days (95% CI 4.1, 10.9) if just the most certain cases (n=12) are considered. The median is 6.1 (95% CI: 4.1, 9.2) and 5.8 (95% CI 3.6, 9.3) respectively.
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The copyright holder for this preprint this version posted June 20, 2020. . https://doi.org/10. 1101 In addition, 97.5% of symptomatic cases will develop symptoms after 13.6 days from exposition (95% CI 10.7, 16.5). This results emerges from parametric boostraping. If re-sampling is non parametric, the figure decreases to 12.8 days (95% CI: 9.8, 15.9). In the reduced sample of most certain 12 cases is considered, 97.5% of cases will be ill after 14.5 days or 12.3 days, depending on boostraping method (parametric or non parametric. The upper limit of confidence interval increase to 17 days taking into account the results of the reduce sample. These estimations are useful to decide the extent of quarantine in exposed individuals.
Even when 14 days seems an appropiate length, adding 3 extra days could be more effective to limit spread.
The point estimation for the mean serial interval is 6.8 days (95% CI: 4.0-9.6). Considering only the most certain pairs, the mean serial interval is estimated at 5.5 days (95% CI: 2.8, 8.1). The estimated median serial intervals were 5.2 (95% CI: 3.0, 8.1) and 4.1 (95% CI: 2.0, 6.9) respectively. We found no substantive differences in the mean between the point estimations of parametric and Bayesian methods and also considering bootstraping (see Supplementary Materials). Nevertheless, Bayesian methods show higher mean and median for the SI in the reduced sample than the ones estimated without uncertainty. This finding narrows the gap between the SI and the incubation period. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted June 20, 2020. . https://doi.org/10.1101/2020.06.18.20134825 doi: medRxiv preprint Figure 1 plots the histogram of observations and fitted distributions. Estimations show better adjustment to observed data for the SI than for incubation period. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted June 20, 2020. . https://doi.org/10. 1101
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The World Health Organization (WHO) has declared that Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and the disease caused by it known as Coronavirus Disease 2019 (COVID-19) is here to stay for long. The rapidly spreading pandemic has swept the globe and is progressing relentlessly [1] .
The transmission of SARS-CoV-2 can occur through direct, indirect, or close contact with infected people through infected secretions such as saliva and respiratory secretions or their respiratory droplets, which are expelled when an infected person coughs, sneezes or talks. Respiratory droplet transmission can occur when a person is in close contact (within 1 m) with an infected person who has respiratory symptoms (e.g., coughing or sneezing) or who is talking or singing; in these circumstances, respiratory droplets that include the virus can reach the mouth, nose or eyes of a susceptible person and can result in infection. Indirect contact transmission involving contact of a susceptible host with a contaminated object or surface (fomite transmission) may also be possible.
Any person developing cough, fever, myalgia, headache, shortness of breath, Influenza-Like Illness (ILI), or non-respiratory symptoms indicates occurrence of possible viral infection. Subsequently, there were reports of anosmia/hyposmia and ageusia among many suspects from different countries. In the current situation, where high infectivity of the virus is leading to the rapid spread of infection, any diagnostic means which can detect the spread at the earliest will be valuable and can be helpful for effective containment of virus spread.
The clinical expertise of front-line otolaryngologists who have in-depth knowledge about rhinology and olfaction can diagnose these cases much early during screening and sampling suspects of COVID-19. Subjective olfactory assessment alone has poor reliability. Many clinical and research settings for the psychophysical analysis of olfactory dysfunction (OD) and gustatory dysfunction (GD) have utilized a validated olfactory test, which determines the odor threshold by identifying or discriminating one or more odor [2] . However, currently available objective psychophysical tests like Sniffin Sticks or University of Pennsylvania Smell Identification Test (UPSIT) [3] for testing this sensation are not accessible to majorities. Their application in the field set up for the mass screening of suspects may not be feasible in all the places.
Post viral olfactory dysfunction (PVOD) and gustatory dysfunction is a known phenomenon following viral upper respiratory tract infection (URTI). Many viruses, including Rhinovirus, Corona Virus, and Parainfluenza viruses, have been found in patients' nasal discharge, causing PVOD by a different mechanism. In case of COVID-19 however it is the direct damage to olfactory epithelium which leads to loss of smell sensation [4] .
This study investigated the correlation between the development of new-onset OD and GD by psychophysical testing among laboratory-confirmed COVID-19 positive cases.
This is a facility-based survey performed in screening facilities of quarantine centers for COVID-19. The suspects from outpatient clinics treating the cases of Influenza-like illness (ILI) and Severe Acute Respiratory Infection (SARI) were also included.
The study is carried out in five facility-based quarantine centers established under Nagpur Municipal Corporation, Maharashtra. These quarantine centers cater to COVID-19 suspects identified based on the following criteria: 1close contacts of confirmed COVID-19 positive cases 2. Patients presented with ILI from containment zones 3. International and inter-state history of travel with/out presumptive symptoms. Each quarantine center had about 150-200 occupants, and they were discharged from the quarantine centers based on a negative laboratory report or 14 days of stay, whichever is earlier. Also, the study enrolled patients attending the screening center of the tertiary care facility. Patients presenting with ILI /SARI like symptoms are subjected to further evaluations. We wanted to know the real-time frequency of OD and GDs in a cohort of suspects who have acquired COVID-19; hence the recruitment of cases from quarantine centers was done.
Administrative approval from concerned authorities and the Institute Ethics Committee is obtained before beginning the study. The patient's willingness to participate in the survey, readiness for follow-up, and agreement with the informed consent terms were confirmed beforehand.
Patients less than 2 years of age or more than 80 years of age, nasal polyposis, and any patient on intranasal corticosteroid spray are excluded from the study.
Data on participant demographic and clinical characteristics were collected in person and on the telephone using structured proforma. OD and GD are tested in eligible suspects using standard procedure before the sample collection for COVID-19. The status is tracked by the sample registration form (SRF), ID number extracted from the laboratory records maintained at the designated COVID-19 molecular diagnostic laboratory.
The olfaction was tested by asking subjects to identify the smell of particular odorant like crushed coffee beans and crushed camphor diskettes of a fixed weight. This was placed in a disposable test tube; the suspect was not allowed to see or touch the contents. The items so selected keeping in mind their regular usage among the population. Hence, improving the reliability of testing that particular sensation. In between the identification of two odors, the gustatory sensation was tested. The gustatory sensation was tested by asking the patient to identify the taste after instilling two drops of solution on the anterior third of the tongue by disposable 2 ml dropper. The sweet and salty solutions were prepared from glucose and salt of fixed dilution each time, respectively. The responses were documented in the datasheet.
For olfaction, if the suspect can identify either coffee or camphor affirmatively, then it is marked as identified. Those who failed to identify the smell are labeled as not identified. Hence, identifying the healthy sense of smell and anosmia, respectively. For a taste sensation, which is done in the same setup. The testing is done with sugar and salt solutions prepared and administered independently, and patients' responses were marked as it is done for the smell. Thus, a single observer collects all the data.
Data is entered in an Excel spreadsheet and analyzed using STATA 14 (StataCorp, College Station, Texas). Participant demographic and clinical characteristics are summarized as frequencies and percentages. Since age was not following the Gaussian distribution, it is summarised as median with Inter Quartile Range (IQR). Proportions of COVID-19 positivity rate and rate of dysfunction in smell and tastes are described as percentages with 95% CI. The rate of smell and taste disturbances between COVID-19 positive and COVID-19 negative individuals compared using the Chi-square test. The association of smell and taste dysfunction with COVID-19 status described as an adjusted odds ratio with 95% Confidence Interval. The confounding factors such as age and sex-adjusted through multivariate logistic regression analysis.
A total of eight hundred and thirty-two subjects screened at quarantine centers in 3 months between April and June 2020 were included in the study. Four hundred and twenty (50.5%) were males, and the median (IQR) age of the participants was 28 (13-40) years.
Six hundred and ninety-six suspects (83.6%) were asymptomatic. One hundred thirty-six suspects presented with at least one clinical symptom, including oto-rhinology related one. It was found that the majority of these, 57.3% (78/136) tested negative. (Fig. 1) The most frequently reported symptom was nasal blockade 62 (7.5%), followed by dry cough 54(6.5%) ( Table 1) .
Seventy-six of 832 suspects tested positive for COVID-19. The overall laboratory COVID-19 positivity, as reported after reverse transcription-polymerase chain reaction (RT-PCR) test, was 9.1% (95% CI: 7.3-11.3%).
Cough was the most common symptom accounting for 30 (39.5%) individuals, followed by nasal blockade in 24 (31.6%) cases as predominant presentations in confirmed cases. Patterns of other symptoms reported among confirmed cases are presented ( Table 1) .
One hundred and seventy eight (25.5%) and 168 (24.2%) suspect failed to identify the correct smell of coffee beans and camphor, respectively. While 90 (12.6%) and 96 (13.5%) suspects could not identify sweet and salty solutions, respectively, when asked to taste the solution to identify ( Table 2) .
Sixty two (81.6%) of 76 positive cases had smell dysfunction. And, 64/76 (84.2%) cases reported taste dysfunction upon psychophysical testing (Fig. 2) . The confirmed cases had three times more odds of having OD and GDs compared to negative suspects (Smelladj OR(95% CI):3.02 (1.67-5.57; tasteadj OR(95% CI):3.06 (1.61-5.88) ( Table 3 ). This suggests that COVID-19 positive cases were more likely to have new-onset OD and GDs, which is statistically significant (Table 4 ).
Many paucisymptomatic suspects od COVID-19 have reported dysfunctions of smell and taste as presenting complaints [5] . In this study, an easy to perform and administer screening test done for assessing OD and GD had an overall sensitivity of 92.1% and 81.6% among the confirmed cases of COVID-19, respectively.
Sometimes referred to as the forgotten cranial nerve, the olfactory nerve, and testing for its function is often overlooked in clinical practice. Besides, in the perspective of normal trans-nasal airflow, the odorant molecules reaching olfactory cleft, and in the absence of clinical features of intranasal diseases like in infectious rhinosinusitis, allergic or vasomotor rhinitis, or polyposis, up until now, patients with sensorineural viral anosmia have been infrequently seen in general practice and otolaryngology practice. Historically our knowledge about the neurotropic or neurovirulent viral infection affecting the olfactory system, is incomplete. Only the most severe cases may self-recognize the ongoing neurosensory dysfunction, and in remaining cases, it might manifest itself after a prolonged latency period [5] . Therefore, up until the COVID-19 pandemic, the low prevalence of sensorineural viral anosmia in various populations as a whole has made clinical research challenging. Lack of decisive infrastructures in performing neuroimaging studies, difficulties in obtaining histopathological tissue specimens, and an absence of viral culture techniques of infected olfactory neuroepithelium compounds the problems in studying this condition [5] .
The University of Pennsylvania Smell Identification Test (UPSIT) was administered to 60 confirmed COVID-19 inpatients by Shima T Moein et al. and concluded that the ODs of the variable extent was a reliable biomarker affecting 98% of the cohort studied [6] . In the current study, a psychophysical evaluation of these sensory functions was performed. Even though it is not confirmatory, baseline information about the alteration of these sensations can be easily obtained. The classification described in this study broadly categorizes the losses of olfaction and gustatory functions.
Using the COVID-19 anosmia tool developed by the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS), after analyzing 273 entries, it was suggested by Rachel Kaye and colleagues that anosmia may be a critical initial symptom and it may help to alert particular individual infected with SARS-CoV2 who may unknowingly transmit the virus [7] . This tool may be helpful to the attending healthcare worker to submit data regarding OD and GD in COVID-19 patients effectively. Further, testing of olfaction and taste, as suggested in this study along with the above COVID-19 anosmia tool, could fortify the evidence. It is observed that traditional clinical features, as seen in other URTI (e.g., Influenza, Rhinovirus, and Adenovirus), are often absent in patients with COVID-19. The silent progress of viremia fails to produce clinically significant nasal congestion or rhinorrhoea-i.e., a red, runny, stuffy, itchy nose. Instead, many cases have presented with newer onset loss of smell and taste. Hence, prompting this observation that the SARS-CoV-2 is a neurotropic virus that is site-specific for the olfactory system. Although known as a respiratory virus, coronaviruses are known to be neurotropic and neuroinvasive [8, 9] .
In any typical viral URIs, the resultant nasal obstruction caused by rhinitis precludes an individual from perceiving the flavor. However, in COVID-19, there is a direct viral injury to the olfactory neuroepithelium. Retro nasal olfaction, which is a combination of ortho-nasal smell and taste, and is a complex sensory process allowing us to perceive flavor, anything beyond the five tastes of the food: sweet, salty, bitter, sour, and umami [10] . The congestion in the nasal cavity during the ongoing episode physically blocks the entry of odor and flavor molecules to the olfactory cleft. In the current study, fifty-four positive cases of the 76 cases did not complain of nose blockage, suggesting that unlike other URTI, COVID-19 cases do not exhibit nasal congestion.
European multicentre study including 417 mild-tomoderate patients with COVID-19, Lechien et al. reported 85.6% and 88.0% OD and GD, respectively. In 11.8% cases, the loss of smell sensation was the first symptom to appear even before the appearance of any other symptom, suggesting OD may be an early indicator for early COVID-19 detection [11] . The onset and duration of these sensory losses could not be tracked in this study as data collection is done while screening suspects due to shortage of time. This may be a shortcoming in itself of this study. An objective analysis of olfaction and gustatory sensation and associated clinical characteristics with timely follow up will further enlighten the role of investigating chemo-sensory losses among COVID-19 patients.
During a naïve pandemic, using appropriate screening tools is an imperative need. The tool should be useful enough not to miss the positive cases as well as not to tag the unaffected individuals as cases in the context of prevailing stigma and exclusion of affected individuals. This study identifies the potential symptoms for inclusion in the checklist, and simple screening tests, as described, can be used in masses as an adjunct. Similarly, the application of this feasible smell and taste dysfunction tests could help the individual become alert and come forward for testing, especially in the containment region. Proactively getting isolated from others in the family when these symptoms arise or dysfunction occurs can help in limiting the spread.
In this study, testing of smell and taste dysfunctions had higher sensitivity in identifying recent-onset loss of sensations in COVID-19 cases. Hence, it may be used as a simple and cost-effective screening test.
Funding None.
Data Availability Data transparency. Consent for publication All authors provide consent to publish.
Ethical Approval Institutional Ethical Committee. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki.
Consent to participate Verbal informed consent of participant taken.
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Covid-19 pandemic, with millions of cases, has caused a huge socio-economic impact and impaired routine classroom teaching across the globe. 1 While the situation is still not out of danger, online solutions for teaching are rapidly emerging and being constantly improved by educators, institutions and educational associations like ASBMB. 2 As educators for over a decade, we have observed a reluctant behavior of students toward the online learning platforms in developing economies particularly due to poor internet connectivity, inferior technical know-how of the online tools, and hindered twoway communication between student and teacher. A recent surge in the user-friendly platforms such as Zoom, Google Meet, Cisco Webex, Microsoft Team and other options has shattered this reluctance and rapid turnout of students has been observed. With over a class of 200 students, we have been developing newer strategies and experimented with various formats of online platforms. Among the common modes that we used were, mode 1: conventional audio-delivery with PowerPoint slides on live platforms, mode 2: video and audio with animated graphics on live platforms, mode 3: recorded videos with audio and video support, and mode 4: Audio-visual oneto-one discussion and problem solving with conceptual understating. Provided the relatively inferior internet connectivity in remote parts of the developing countries, audio alone with animated PowerPoint slides (mode 1) gathered a better response with no absolute requirement of instructor video. However, the delivery was monotonous for most of the students who had access to better internet connectivity. In the second mode where both video and audio were delivered, the student connectivity with the instructor was better and the session was interactive, especially while answering questions of students where instructor's gestures had an impact. In mode 3, which was a prior recorded video, the learners appreciated the least disturbance and flexibility of learning but reacted negatively on the grounds of instructor-learner interaction. After observing the comments and feedback of learners, we practiced a hybrid approach that was a blend of above four modes, along with a popular and rapidly emerging flipped classroom strategy, 3 where students were provided with slides, questionnaire and supporting opensource links prior to the delivery of video lecture at least 24 h in advance. The student's queries were also made available to the tutor before the lecture stated. On the start of a routine online class, we started with format 1, and on completion of the concept, we switched to mode 3, with a final one-way resolution of previous day queries, followed by a two-way communication for clearing doubts for the current session. Our approach was tested for a topic carbohydrate metabolism with a 40-minute trial class on three different platforms, Zoom, 4 WizIQ 5 and Google Meet. 6 Although the platform did not have a much impact on the learning outcome as most of the impact was based on content and delivery, ease of access and preference to the specific tool could not be justified. Furthermore, internet connectivity is an issue with some regions of the developing economies which was observed as a major hurdle in the mode 1 and mode 4, pre-recorded videos with enough buffer time received a good feedback from the users. Additionally, during our proposed hybrid approach for users with poor internet last phase of interactive session was provided in recorded from for later use and text based
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The need to understand the current public health emergency due to COVID-19 and its context is well noted in Novel coronavirus 2019 (3 February). However, the interplay of simultaneous COVID-19, African swine fever, and avian influenza emergencies on global health and industries is constantly evolving and difficult to predict, and therefore warrants further scrutiny. Despite the unprecedented efforts to limit the current spread of COVID-19 by national governments and international stakeholders, the situation remains uncertain and critical, calling for a long-term cooperative effort on a global scale.
The COVID-19 outbreak in China was preceded by an animal health emergency and economic crisis caused by African swine fever. African swine fever is responsible for estimated losses of 55% of China's pigs, which is equivalent to 25% of the world's pigs by the close of 2019 (Rabobank, 2019; van der Zee, Bibi, & agencies, 2019) , creating an impact on China's swine industry that reverberates through the world's swine industries by extension (Levitt, 2020; Ma, 2019) .
To add a further dimension to an already complex global health situation, endemic avian influenza has recently resurged in China, including zoonotic H5N1 and H7N9 serotypes (Mendell & Cheng, 2020; OIE; Perrett, 2020) . While the current public health impact due to zoonotic avian influenza is not comparable with that due to COVID-19, the impact on the agriculture industry is considerable, as China is again one of the world's largest poultry producers.
Continuous presence of the virus in the wild bird population poses a constant threat of spillover into not only China's poultry industry but also into poultry industries globally.
While the economic impact due to the restrictions on trade and human and animal movements caused by these emergencies is evident, there are other aspects to this triad worth noting. As a consequence of the African swine fever epidemic, pig producers in China are shifting to the production of alternative proteins, namely poultry (Buholzer, De Nardi, Schuppers, & Sperling, 2020) . If biosecurity measures are not adapted accordingly, producers are at increased risk of avian influenza circulation, especially in backyard farms that are more vulnerable to disease incursion and more difficult for authorities to reach. An enzootic disease could be exchanged for a zoonotic disease with pandemic potential, with higher capability to spread faster globally and that is harder to control (Buholzer et al., 2020) . The upside is that restricted movement of pigs and pork products throughout China might slow the spread of African swine fever.
Although some provinces in Viet Nam and China have had no new cases over several weeks (FAO EMPRES, 2020) , only time will tell how the control of African swine fever in the region will fare in the face of COVID-19.
Although avian influenza is endemic in Asia, it is currently spreading widely into Europe. Outbreaks of H5N1 and H5N8 avian influenza viruses have been reported in the central eastern part of Europe since the beginning of January (ECDC, 2020). One emerging risk factor for the spread of virus is climate change, which could alter not only bird migration, but also influence the avian influenza virus transmission cycle through the prolonged persistence of the virus in the environment (Gilbert, Slingenbergh, & Xiao, 2008; Zhang et al., 2014) .
The extent to which people and animals are interconnected in today's globalized world implies that the assessment of emergency outbreaks in isolation is no longer sufficient. The diversion of attention, efforts and resources to control one emergency may result in the recrudescence of other diseases, especially in regions with limited resources. Further investigation into the impacts of co-existing transboundary diseases on the global health of people, animals and economy in a transdisciplinary approach is needed. Only then can the implications of this dynamic problem be understood and viable solutions be found.
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Despite being a member of the order Carnivora, the domestic dog is omnivorous in nature and consumes a considerable amount of dietary carbohydrate, including fibrous materials, commonly present in commercial pet foods. Dogs do not rely heavily on microbial fermentation as it pertains to energy requirements, but balanced and stable microbiota are critical for maintaining gastrointestinal health. Characterizing the canine microbiome is important for several reasons. First, similar gastrointestinal anatomy and physiology, dietary patterns, metabolic processes and intestinal disease etiology make the dog an effective human model for intestinal health and disease (as reviewed by Swanson and Schook, 2006) . Second, most pet dogs in developed countries are now treated as family, with many not only living in the home but also eating, sleeping and playing with their owners. This close proximity has relevance in terms of zoonotic disease. Several recent case reports have demonstrated a direct link between human illness and pet dogs (Ngaage et al., 1999; Sato et al., 2000) .
Bacteroidetes and Firmicutes are the predominant microbial phyla in the human gut (Eckburg et al., 2005; Gill et al., 2006) . Knowledge of the canine gut microbiome lags behind that of humans, but has improved recently with the increased speed and reduced cost of next-generation sequencing technologies (Suchodolski et al., 2009) . Recent sequencing data from our laboratories suggest that Firmicutes, Bacteroidetes and Fusobacteria co-dominate the colon of healthy dogs (Suchodolski et al., 2008a; Middelbos et al., 2010) . Suchodolski et al. (2008a) compared small and large intestinal populations and noted that Clostridiales predominated in the duodenum and jejunum, whereas Fusobacteriales and Bacteroidales were the most abundant bacterial order in the ileum and colon. Enterobacteriales were more commonly observed in the small intestine than in the colon, and Lactobacillales were commonly present in all parts of the gastrointestinal tract. Intestinal disease is often associated with alterations in small intestinal microbiota, some of which have also been identified in dogs. Results from several recent studies have identified distinct gut microbial populations in dogs with inflammatory bowel disease as compared with healthy controls (Xenoulis et al., 2008; Suchodolski et al., 2010; Allenspach et al., 2010) . Duodenal samples from dogs with inflammatory bowel disease had reduced species richness, were enriched with the Enterobacteriaceae family and also differed in Clostridiaceae, Bacteroidetes and Spirochaetes populations. These recent experiments have provided a strong foundation on which to build, although further experimentation with greater coverage is sorely needed.
Culture-independent, 16S rRNA gene-based techniques have greatly expanded our knowledge of bacterial phylogeny, but do not provide information pertaining to function. A metagenomics approach is advantageous because it provides a view of community structure (species richness and distribution), including fungi, archaeal and viral genomes, as well as functional (metabolic) potential (Hugenholtz and Tyson, 2008) . This strategy will enhance our understanding of host-microbe relationships, with application to host metabolism and disease. Recent metagenome projects have revealed the functional capacity of the gastrointestinal organisms in numerous species, including humans (Kurokawa et al., 2007; Turnbaugh et al., 2009) , rodents (Turnbaugh et al., , 2008 , cattle (Brulc et al., 2009 ) and poultry (Qu et al., 2008) . To our knowledge, however, the canine gastrointestinal metagenome has not been characterized and was the primary objective of this experiment.
Six healthy adult female hound-cross dogs (Canis lupus familiaris; Marshall Bioresources, North Rose, NY, USA) were used. All dogs were 1.7 years old (three pairs of littermates born within 5 days of each other) and had a mean body weight of 20.3 kg (individual body weight ¼ 17.9, 18.3, 18.7, 20.0, 21.6 and 25.3 kg) . The dogs were housed individually under environmentally controlled conditions (22 1C, 12-h light:12-h dark cycle) at the Small Animal Clinic of the University of Illinois, College of Veterinary Medicine. All animal care procedures have been described by Middelbos et al. (2010) and were approved by the University of Illinois Institutional Animal Care and Use Committee before conducting the experiment. Experimental diets were formulated to meet all nutritional recommendations for adult dogs provided by the Association of American Feed Control Officials, (2009). Primary ingredients of both diets included brewer's rice, poultry by-product meal, poultry fat, dried egg and vitamin and mineral premixes. The control diet (C) contained no supplemental dietary fiber, whereas the fiber-supplemented diet (BP) included 7.5% beet pulp in place of brewer's rice. Control and BP diets were similar in protein (29.7 vs 28.0%), fat (19.4 vs 21.0%) and ash (6.8 vs 7.1%) composition, but contained different fiber concentrations (1.4 vs 4.5% total dietary fiber). The complete list of dietary ingredients and chemical composition is presented in Middelbos et al. (2010) .
A crossover design with two 14-day periods was used. Dogs were randomly assigned to one of two diets in the first period and received the other diet in the second period. Dogs were fed 300 g of diet once daily, which was determined to meet the metabolizable energy needs of the heaviest dog based on National Research Council, (2006) recommendations. At each feeding, uneaten food from the previous feeding was collected and weighed. A 4-day collection phase followed a 10-day diet adaptation phase, during which fresh (within 15 min of defecation) fecal samples were collected from each dog. Fresh feces were immediately flashfrozen in liquid nitrogen and stored at À80 1C until DNA extraction.
Genomic DNA was extracted and isolated from fecal samples using a modification of the method of Yu and Morrison, (2004) and described by Middelbos et al. (2010) . After extraction, DNA was quantified using a ND-1000 spectrophotometer (Nanodrop Technologies, Wilmington, DE, USA). All six samples from each treatment were pooled on an equimolar basis.
Samples were subjected to pyrosequencing using a 454 Genome Sequencer using FLX titanium reagents (Roche Applied Science, Indianapolis, IN, USA). Both unassembled reads and assembled contigs were analyzed separately. Sequences derived from pyrosequencing were quality trimmed on the basis of N50 values. For unassembled analyses, the data set was depleted of sequences o200bp. For assembled analyses, a de novo assembly was performed using NGen (DNAstar, Madison, WI, USA) with a minimum match percentage of 90%, a mismatch penalty of 25, a match size of 19, gap penalty of 25 and no repeat handling. Contigs from each of the data sets were uploaded to MG-RAST (Meyer et al., 2008) and WebCARMA (Gerlach et al., 2009) and annotated. Unassembled reads were also loaded into MG-RAST and into IMG/ M ER (Markowitz et al., 2008) . Comparisons were made between the canine beet pulp (K9BP) and canine control (K9C) diet-assembled canine metagenome data sets (MG-RAST accession numbers 4444165 and 4444164, respectively), and contrasts were also evaluated against 5 MG-RAST publicassembled data sets that included chicken cecum A contigs (CCA 4440285), lean mouse cecum (LMC 4440463.3), obese mouse cecum (OMC 4440464), human stool metagenome (HSM 4444130) and human F1-S feces metagenome (F1S 4440939). Parameters were limited by a maximum e-value of 0.01, minimum percent identity of 50, minimum alignment length of 50 and raw score maximum of 0.3. Hierarchal clustering was performed using NCSS 2007 (Kaysville, Utah). Wards minimum variance clustering was performed using unscaled Manhattan distances according to the procedure described in the study by Kaufman and Rousseeuw, (1990) .
Although dogs normally consume low to moderate levels of dietary fiber and do not rely heavily on fermentation for meeting their energy needs, the presence of a stable gut microbial community is crucial for intestinal health. Next generation sequencing technologies have recently been used to characterize the identity and functional capacity of a variety of microbial communities, including the gastrointestinal tracts of mammalian species. To our knowledge, however, this is the first metagenomic data set generated from the canine gastrointestinal tract. Pyrosequencing generated a total of 1008341 sequences. Assembly of the 505 061 K9BP fecal metagenome sequences resulted in 422 653 sequences being assembled into 67 761 contigs with 1937 contigs 42 kb. The average contig length was 648 bp, with an average of six sequences per contig. Of the 503 280 K9C sequences, 424 522 sequences were assembled into 66 969 contigs with 2871 contigs 42 kb. The average contig length was 799 bp, with an average of six sequences per contig. The K9 metagenome projects were submitted to NCBI with accession numbers 38 653 and 38 651.
The sequences were also submitted to NCBI short read archive under accession number SRA008853.1.
For K9BP, 70.34% of the sequences evaluated were matched to SEED subsystems (using an e-value of 1e-5). There were 47,691 hits against the nonredundant protein database. For the K9C data set, 76.46% of the sequences matched SEED subsystems, with 51 205 non-redundant hits. Table 1 provides an overview of these phylogenetic computations. Both metagenomes had a similar microbial profile when viewed at major taxonomic levels. As expected, the Bacteroidetes/Chlorobi group and Firmicutes were the predominant phyla in our canine fecal samples, both of which represented B35% of all sequences. Proteobacteria (13-15%) and Fusobacteria (7- 16S rRNA gene-based (variable region three) pyrosequencing data from these same fecal samples highlighted the predominance of these similar phyla, but with a lower prevalence of Bacteroidetes (27-34%), Firmicutes (17-27%) and Proteobacteria (5-7%), and much higher prevalence of Fusobacteria (27-44%; Middelbos et al., 2010) . Although it is difficult to identify the source of variation between these methodologies, especially in Fusobacteria, biases involved with the generation of amplicons (for example, primer bias and so on) for the 16S rRNA gene-based method may have contributed to this discrepancy. In another recent study, in which near full-length 16S rRNA gene sequences were generated from a clone library of healthy canine colon samples, Firmicutes represented B40% of sequences, whereas Bacteroidetes and Fusobacteria both represented 30% each (Suchodolski et al., 2008a) . These recent studies suggest that the predominant phyla of the canine gut microbiome are similar to that of humans (Eckburg et al., 2005; Li et al., 2008) and mice (Ley et al., 2005) , both of which are also dominated by Firmicutes and Bacteroidetes. The significance of an enriched Fusobacteria Assuming that metagenome sequencing represented a random sample of read counts and that each group was independent of the other, it seems that K9C dogs had a greater percentage of Bacteroidetes, Fusobacteria, Proteobacteria, whereas K9BP had greater read counts of Bacteroidetes/Chlorobi and Firmicutes (Table 2) . Increased Firmicutes read counts in the current (metagenomic) data set were primarily due to decreased Clostridia in K9BP as compared with K9C, whereas changes in Proteobacteria were primarily related to Gammaproteobacteria. Despite the differences in overall read counts between the metagenomic and 16S rRNA genederived data sets, effects of dietary fiber on phylum prevalence were similar between them (Middelbos et al., 2010) . Microbial phylogeny is known to respond to dietary alterations, including the amount and type of dietary fiber or other bioactive food components, as demonstrated by recent experiments performed in mice (Turnbaugh et al., 2008) , rats (Abnous et al., 2009) and humans (Li et al., 2009b) . However, characterizing dietary-induced changes in the canine microbiome using high-throughput sequencing technologies has not been performed until now, and deserves more attention in future experiments.
Results of this study were compared with data sets within MG-RAST that had similar data characteristics, including sequence number, longest sequence and average sequence length (Table 3) . Paired data from studies were chosen, such as lean (LMC) and obese (OMC) mouse cecal metagenomes and two human fecal metagenomes (F1S; HSM). F1S was considered to be a healthy human fecal metagenome (Kurokawa et al., 2007) , whereas HSM was defined as human feces from a malnourished subject, as well as a chicken cecal metagenome (CCA) (Qu et al., 2008) . The results of such comparisons have inherent assumptions on the basis of the methods and version of the database used for generating the data and parameters used to assemble the data. Results were evaluated at the phylogenetic level ( Figure 1) and at the metabolic level ( Figure 2 ). Within the phylogenetic comparison based on a double hierarchical dendogram, the two canine samples clustered together and more closely with the healthy human and mouse metagenomes than with the obese mouse metagenome. The chicken cecum metagenome was the greatest outlier as might be expected. In all samples, the Bacteroidetes/Chlorobi group, Firmicutes and Proteobacteria were most abundant. The canine metagenome was most distinguished by its greater prevalence of Fusobacteria as compared with humans and mice, as can be seen in the heat map in Figure 1 . The heat map also demonstrates that the canine metagenome contained lower Actinobacteria and greater Fibrobacteres/Acidobacteria as compared with humans and mice. Finally, Spirochaetes were identified in all of the metagenomes, and Firmicutes were notably lower in the chicken cecal metagenome that was largely predominated by Bacteroidetes/Chlorobi. Similar clustering against mouse and human data was performed in IMG/M ER (http://merced.jgi-psf.org/cgi-bin/mer/ main.cgi). As Supplementary Figure 3 demonstrates, canine samples clustered together and were most similar to human gut samples, which also clustered together, and were followed by lean and obese mouse gut samples. Archaea constituted a minor part of the canine metagenome, representing B1% of all sequencing reads. No significant effect of diet on the distribution of archaea was observed. Independent of diet, two distinct archaeal phyla were identified. In the canine samples, Crenarchaeota and Euryarchaeota comprised 9 classes and 10 orders (Table 4) . Methanogenic archaea were the most abundant and diverse group.
The overall abundance of archaea within the human and mice metagenome was similar to that of dogs. Cluster analysis based on the cosine similarity coefficient revealed that the sample from HSM showed the highest similarity to the canine samples (Supplemental Figure 4) . Sample HSM had a high diversity of methanogens, comprising several classes (Methanobacteria, Methanococci, Methanomicrobia and Methanopyri). In contrast, human sample F1S clustered together with the mice metagenomes OMC and LMC. Although methanogens were also the most abundant group in these latter samples, they showed a lower diversity. In CCA, only one highly predominant operational taxonomic unit was evident, and this metagenome clustered separately. Compared with human, mice Archaea are commensal organisms in the intestine of ruminants and have also been described recently in the intestine of humans, with Methanobacteriales most commonly reported (Eckburg et al., 2005; Zhang et al., 2009) . To our knowledge, archaea have not been described in detail in dogs. Middelbos et al. (2008) demonstrated in vitro methanogenesis in canine fecal samples, but a phylogenetic characterization of the archaeal phylotypes has not been provided. There is no clear role for archaea in the intestine. Typically, they are considered commensals, but because of mutualistic interactions with other microorganisms they may contribute to pathogenicity (Conway de Macario and Macario, 2009). Methanogens reduce hydrogen into methane, promoting an environment that enhances growth of polysaccharide fermenting bacteria, leading to a higher energy utilization of the diet. Higher numbers of methanogenic archaea have been observed in obese humans (Zhang et al., 2009) . Methanogens have also been associated with periodontal disease in humans (Li et al., 2009a) . The true prevalence and medical importance of archaea will need to be determined in dogs.
A low abundance of fungi sequences was identified in the K9C and no sequences were observed in the K9BP data set. All fungi sequences were classified as Dikarya. Only three distinct phylotypes were identified, and all were at low (0.01%) abundance of the canine metagenome: Gibberella zeae PH-1, Neurospora crassa and Saccharomyces cerevisiae. Interestingly, the latter two phylotypes were the only ones identified in the OMC and CCA metagenomes, respectively. Fungi in the intestinal ecosystem have not yet been studied extensively in dogs. Using culture-dependent methods, only a few studies mention the presence of fungi in the canine gastrointestinal tract, including the stomach, ileum, colon and rectum, in B25% of dogs (Davis et al., 1977; Benno et al., 1992; Mentula et al., 2005) . Using a panfungal PCR assay, a higher prevalence of fungi DNA (76% of dogs) was reported in the proximal small intestine in healthy dogs and in dogs with chronic enteropathies (Suchodolski et al., 2008b) . In that study, a total of 51 different phylotypes were identified across 135 dogs, but the species richness within individual dogs was low, with the majority of dogs harboring only one phylotype. Fungi DNA was detected at significantly higher proportion in mucosal brush samples than in luminal content.
Using oligonucleotide fingerprinting of ribosomal RNA genes (OFRG), a high fungi diversity and four fungi phyla were observed in the intestine of mice (Scupham et al., 2006) . In that study, fungi were observed mostly adjacent to the colonic epithelial cells and to a lesser extent in fecal material. Scanlan and Marchesi, (2008) measured human distal gut fungi using culture-dependent and -independent methods, demonstrating the biases that occur with culture methods. Cultured fungi were predominantly of Candida origin, whereas those identified by molecular techniques included Saccharomyces, Gloeotinia, Penicillium, Candida and Galactomyces. Similar fungi phylotypes (Candida, Cladosporium, Penicillium and Saccharomyces) were identified in stool samples from patients with human inflammatory bowel disease and from healthy controls (Ott et al., 2008) . In that study, fungi represented a low percentage (0.3%) of the overall fecal flora. Colon biopsy samples contained a much greater diversity of fungi, with nearly five times more operational taxonomic unit reported in biopsies compared with stool samples (Ott et al., 2008) . We observed a low number of fungi phylotypes in dogs in this study. It is possible that fungi constitute only a minor fraction of the gut metagenome and the true diversity has been underestimated in this study. Deeper sequencing efforts will likely yield a more accurate characterization of the fungi ecosystem. It is also possible that fungi are less prevalent in luminal content and fecal material, compared with mucosal samples, as previously shown in dogs, mice and humans (Scupham et al., 2006; Ott et al., 2008; Suchodolski et al., 2008b) , and have been therefore underestimated in this study.
Less than 1% of all sequences were classified as being of viral origin (Table 1) . Only the orders Caudovirales and Iridoviridae were identified. Recent studies in humans revealed that the viral community in the gastrointestinal tract is highly diverse, with several hundred different phylotypes (Breitbart et al., 2003) . It is likely that a similar diverse viral community is present in dogs and cats, but their in-depth characterization will require deeper sequence coverage. Moreover, our approach allowed only the discovery of dsDNA. Future studies will need to survey for RNA viruses to complete our understanding of the viral intestinal ecosystem.
To our knowledge, this experiment was the first to use pyrosequencing and a metagenomics approach to characterize the metabolic capacity of canine gut microbiota and test the effects of supplemental dietary fiber. Approximately half (59.07% for K9C; 48.23% for K9BP) of all sequences in our data set were classified metabolically and are summarized in Table 5 (MG-RAST) and Supplementary Figures 5 and 6 (webCARMA). Beet pulp contains a mixture of fermentable and non-fermentable fibers and is commonly used by the pet food industry. Although phylogenetic changes were noted, the inclusion of 7.5% beet pulp did not greatly alter gene sequence number of any KEGG functional categories. The most represented functional categories included carbohydrates; protein metabolism; cell wall and capsule; cofactors, vitamins, prosthetic groups and pigments; DNA metabolism; RNA metabolism; amino acids and derivatives; and virulence. Microbial carbohydrate metabolism seemed to be unaffected by diet in the present study, as the relative sequence abundance of genes related to carbohydrate metabolism was not greatly changed between dogs and was comparable with those in the core metagenome reported in a previous study of monozygotic human twins (B12.75% compared with B12.00%, respectively; Turnbaugh et al., 2009) . However, certain subcategories of carbohydrate metabolism were affected by the addition of beet pulp to the diet. For example, genes related to L-rhamnose usage were twice as abundant in the K9C microbiome as compared with that of K9BP. Although these genes comprise a very small percentage of the total gene number identified (0.34% of sequences for K9C; 0.17% for K9BP), it suggests that the microbiota are being exposed to different carbohydrate concentrations when fed diets of different types or amounts of fiber substrates. Other genes related to carbohydrate metabolism, such as those related to mannose metabolism (0.54% for K9C; 0.58% for K9BP) and fructooligosaccharide and raffinose metabolism (0.29% for K9C; 0.21% for K9BP), did not reflect major differences between diets and may be due to very low dietary concentrations or low amounts present in the distal colon due to fermentation in the proximal bowel.
As a percentage of sequences, protein metabolism genes were enriched in K9BP. On further analysis, it seemed that K9BP had enriched protein biosynthesis and secretion. The largest changes within protein biosynthesis included regulation of transcription, tRNA aminoacylation (2.05% for K9C; 2.24% for K9BP) and universal GTPases (0.91% for K9C; 1.0% for K9BP). Because dogs fed the beet pulp diet (K9BP) likely had more available substrate for bacterial fermentation, this increase in protein biosynthesis simply may be the result of higher metabolic activity and/or growth of microbial populations present in this group. General protein secretion pathways were also enriched in dogs fed the beet pulp diet (0.4% for K9C; 0.51% for K9BP), but genes associated with amino acids and derivatives were unaffected by diet. Genes associated with protein degradation and protein folding seemed to be enriched in K9C.
Genes involved with the biosynthesis of vitamin K and the B vitamins were predominant in the cofactors, vitamins, prosthetic groups and pigments subsystem in the present study. Although Turnbaugh et al. (2009) . In the present study, this value is similar to that noted for RNA metabolism and DNA metabolism. Given that the values were not different between metagenomic samples, it would be reasonable to expect that the microbiota are replicating at the same rate in each microbiome. In fact, DNA replication comprises the largest percentage of genes identified for DNA metabolism (2.12% for K9C; 2.20% for K9BP). Further, the genes associated with bacterial RNA polymerase were similar between groups (0.56% for K9C; 0.62% for K9BP).
Of those pertaining to virulence, there were a wide variety of genes associated with resistance to antibiotics and toxic compounds. A high sequence number for multidrug efflux pumps was noted in both groups, with a numerically greater prevalence in K9C (1.65%) as compared with K9BP (1.51%). In Gram-negative bacteria, these pumps provide protection by actively exporting antimicrobial substances, and serve as one mechanism by which these bacteria can survive in the presence of antibiotics (Poole, 2005) . Several classes of multidrug efflux pumps exist, but all have great relevance to bacterial physiology, including antibiotic resistance, and are common drug targets (Vila and Martinez, 2008) . This class of genes will continue to have great application not only in canine health but also in that of humans as well, and is an area that deserves more attention in the future. Other resistance-related genes having the greatest sequence number were those associated with acriflavine (0.35% for K9C; 0.38% for K9BP), cobalt-zinc-cadmium (0.52% for K9C; 0.53% for K9BP) and fluoroquinolones (0.50% for K9C; 0.47% for K9BP). Acriflavine is a common antiseptic agent and its resistance is thought to be due to an overexpression of efflux pump genes. The broadspectrum antibiotics fluoroquinolones, including ciprofloxacin, levofloxacin and enrofloxacin, are commonly used in human and canine medicine, respectively. Sequences pertaining to Ton and Tol transport systems were also highly prevalent in both groups (1.01% for K9C; 0.97% for K9BP). The Ton system is an energy transducer and uses the transmembrane electrochemical gradient for nutrient uptake, whereas the Tol system is energy independent and seems to preserve the cellular envelope (Muller et al., 1993) . These transport systems are involved in the uptake of numerous nutrients (for example, vitamin B 12 ; iron), and also serve as a mechanism by which bacteriocins translocate into and kill competing bacteria (Alonso et al., 2000) . Finally, a few sequences for genes associated with iron scavenging were present, but very few pertained to adhesion or invasion mechanisms. Genes most prevalent in the cell wall and capsule subsystem were associated with biosynthesis of peptidoglycan (1.35% for K9C; 1.13% for K9BP), KDO2-Lipid A (0.65% for K9C; 0.63% for K9BP) and LOS core oligosaccharides (0.45% for K9C and K9BP). Rhamnose containing glycans (0.34% for K9C; 0.33% for K9BP) and sialic acid metabolism (0.73% for K9C; 0.69% for K9BP) also had a high prevalence.
To get a more in-depth view of the carbohydraterelated enzymes present in our data set, we subjected our samples to the carbohydrate-active enzymes database (CAZy; http://www.cazy.org) as described by Cantarel et al. (2009) . K9C seemed to be enriched with glycoside hydrolases, glycosyl-transferases (765 vs 560 sequences), carbohydrate-binding modules (236 vs 140 sequences), carbohydrate esterases (236 vs 140 sequences) and polysaccharide lyases (101 vs 53 sequences) (Supplementary Tables 2 and 3 ). This response was counterintuitive to our hypothesis that beet pulp would increase carbohydrate-related enzymes and requires greater focus in the future. Nevertheless, although total sequence number was different between samples, the percentage of each gene within its gene family was similar for each. Even though the fiber concentration of the dog diet is rather low, cellulosomes would be expected to have a predominant role in cellulosic and hemicellulosic catabolism, as noted in other species. To our knowledge, the cellulosomes present in canine gut microbiota have not been studied thus far and would be a worthy focus in future studies.
The double hierarchical dendogram used to cluster metagenomes on the basis of metabolic capacity (Figure 2 ) demonstrates that canine and human samples were clustered together according to the host system, with chicken cecum and mice samples being least similar to dogs. Because this experiment used a crossover design in a research setting, dogs and housing environment were constant, leaving diet as the only difference between samples. Thus, it may not be surprising that the prevalence of each functional group was very similar between the two canine samples. The heat map also demonstrates that the canine metagenome clustered most closely with the two human metagenomes, followed by the chicken cecum metagenome. The two mouse samples clustered together and were most different than canine samples. Interestingly, mouse samples had an enrichment of genes associated with phosphorus metabolism as compared with the other metagenomes. The chicken metagenome had a greater sequence number associated with sulfur metabolism, and fewer sequences associated with fatty acids and lipids, cell division and cell cycle and motility and chemotaxis.
To conclude, we present here the first metagenomics data set, including phylogeny and functional capacity, of the canine gastrointestinal microbiome. Our data demonstrate that the dominant bacterial phyla of the gut microbiome (for example, Bacteroidetes; Firmicutes) are similar to those of humans and rodent models. Archaea, fungi and viral sequences represented a minor portion of all sequences, but were present at levels similar to that of other mammalian biomes. Primary functional categories were also similar to those of other mammalian gut microbiomes and were associated with carbohydrates; protein, DNA and RNA metabolism; vitamin and cell-wall component biosynthesis; and virulence. Hierarchical clustering of gut metagenomic data from dogs, humans and mice demonstrated high phylogenetic and metabolic similarity among species. Although some alterations due to the inclusion of dietary fiber were noted, more drastic dietary changes (for example, source, type, or amount of macronutrients, including protein and dietary fiber) are likely needed to result in large effects in the canine gut metagenome. Although this experiment has provided a brief overview of the canine gut community, future studies are required to provide a deeper coverage and greater characterization of the metagenome of dogs in healthy and diseased states, of varying ages or genetic backgrounds, and/or receiving specific dietary interventions.
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1 Main Developments in 2019/2020
The CET is a part of DG Competition. Its staff consists of around 30 economists (mostly holding a Ph.D.) with a mix of permanent and temporary positions. The CET is headed by the Chief Competition Economist, an external academic who is recruited for a 3-year term. The current Chief Competition Economist is Pierre Régibeau, who succeeded Tommaso Valletti in 2019.
The CET has both a support role and a scrutiny role. As part of its support role, the team provides guidance on methodological issues of economics and econometrics in the application of EU competition rules. It contributes both to individual competition cases-in particular, those that involve complex economic issues and quantitative analysis-and to the development of general policy initiatives. It also assists with cases that are pending before the courts of the European Union.
Members of the CET who are assigned to specific cases have a specific and independent status within case teams and report directly to the Chief Competition Economist. As part of the scrutiny role, the Chief Competition Economist can report his opinion directly to the Director-General of DG Competition as well as to the Competition Commissioner, providing her with an independent opinion with respect to the economic aspects of a case before she proposes a final decision to the European Commission.
The CET is active in DG Competition's three main areas of policy: antitrust, merger control, and State aid.
Between January 2019 and July 2020, the European Commission took decisions in 13 (non-cartel) antitrust cases. Eight of these cases-involving Mastercard II, Google AdSense, Nike, Cross-border access to pay-TV, Mastercard and VISA 1 A detailed overview of DG Competition's activity can be found in its Annual Activity Report. The report also illustrates how DG Competition enforced the competition rules of the European Union in 2019. The 2019 Annual Activity Report is available at https ://ec.europ a.eu/info/publi catio ns/annua l-activ ity-repor t-2019-compe titio n_en. Inter-regional MIF, AB InBev, and Character merchandise-are listed and briefly discussed in Kotzeva et al. (2019) . The Qualcomm predation decision of July 2019 is reviewed in depth in Sect. 2 of this paper. The other four antitrust decisions adopted by the European Commission were: Broadcom of October 2019, 2 Film Merchandise-Universal of January 2020, 3 Meliá of February 2020, 4 and Romanian gas interconnectors of March 2020. 5 During the 2019-2020 period, the two most relevant ECJ rulings were UK Generics 6 of January 2020 and Budapest Bank of April 2020. 7 Both cases were requests for a preliminary ruling: The first one was made by the Competition Appeal Tribunal; the second was made by the Hungarian Supreme Court.
In UK Generics, the Court held that settlement agreements whereby a manufacturer of generic medicines undertakes not to enter the market or challenge a patent in return for transfers of value have the object of restricting competition if it is clear that the net gain from the transfers of value can have no explanation other than the commercial interest of the parties not to engage in competition on the merits, and unless the settlement agreement is accompanied by proven pro-competitive effects that are capable of giving rise to a reasonable doubt that it causes a sufficient degree of harm to competition.
The ruling in Budapest Bank is particularly relevant to allegations of anticompetitive conduct in so-called "multi-sided" markets-e.g., payment systems, digital platforms, etc-where the interactions between related, but distinct markets must be taken into account by the competition authority. In its ruling, the ECJ held that Article 101(1) allows the same conduct/practice to be considered anticompetitive both by object and by effect, but which conduct harms competition "by object" must be interpreted restrictively: An agreement that determines the amount of the Multilateral Interchange Fees (MIFs) cannot be qualified as a restriction by object unlessin view of the content, objectives, and context of the agreement-it can be considered sufficiently harmful to competition. If an agreement appears to pursue both a legitimate and an anticompetitive objective, the legitimate objective may disqualify the agreement as being anticompetitive by object and warrant the assessment of its effects.
The period 2019-2020 was further characterized by intensive activity across numerous antitrust policy fields. In particular, the European Commission launched Public Consultations on: the Review of the Market Definition Notice; the Vertical Block Exemption Regulation (VBER); the Horizontal Block Exemption Regulation (HBER); the Motor Vehicle Block Exemption Regulation (MVBER); and the Consortia Block Exemption Regulation (CBER). Further Public Consultations were launched on the initiative of collective bargaining for the self-employed, 8 and on the Inception Impact Assessment of the New Competition Tool. 9
Between January 2019 and August 2020, 600 merger investigations were concluded at DG Competition. The vast majority (453 cases) were unconditional clearances under a simplified procedure. 16 cases were abandoned in phase I. Of the remaining cases, 118 were concluded during a (non-simplified) phase I investigation and 11 during a phase II investigation. 10 Of the (non-simplified) phase I cases, 11 98 were cleared unconditionally, and 20 could be cleared in phase I subject to commitments. The phase II investigations resulted in one unconditional clearance, 12 seven clearances that were subject to commitments, 13 three prohibitions, 14 and two abandoned 8 See press release available at https ://ec.europ a.eu/commi ssion /press corne r/detai l/en/IP_20_1237. 9 See press release available at https ://ec.europ a.eu/commi ssion /press corne r/detai l/en/ip_20_977. 10 Mergers must be notified to the European Commission if the annual turnover of the combined business exceeds certain thresholds in terms of global and European sales. Notification triggers a 20-working-day phase I investigation. In the majority of cases, this follows a simplified procedure. If the transaction does not raise serious doubts with respect to its compatibility with the common market at the end of phase I, the Commission issues an unconditional clearance decision. If concerns exist but are addressed in a clear-cut manner by remedies that have been proposed by the parties, the transaction can be cleared conditionally in phase I. Otherwise, the Commission will start a 90-working-day phase II investigation. At the end of phase II, the transaction is either cleared (conditionally or unconditionally) or prohibited; the latter occurs if the Commission finds that the transaction would lead to a significant impediment of effective competition even after taking into account any commitments that have been proposed by the parties. Details on the European Union merger regulation are available at https ://ec.europ a.eu/compe titio n/merge rs/proce dures _en.html. 11 Detailed statistics on the number of merger notifications and decisions are available at https ://ec.europ a.eu/compe titio n/merge rs/stati stics .pdf. 12 transactions. 15 Therefore, 8% of cases were not cleared unconditionally during this period.
The CET was involved in all second-phase investigations as well as in many complex first-phase investigations. Analyses by members of the CET included, for instance, merger simulations, bidding analyses, price pressure analyses, quantitative market delineation, as well as conceptual contributions to the construction and testing of sound theories of harm.
In terms of broader policy themes, there is an ongoing debate about the fine-tuning of merger control instruments to the specific challenges that are faced by today's market environment: On the one hand, there have been calls for more flexible merger enforcement in the wake of Siemens/Alstom to permit the creation of European Champions. On the other hand, concerns have been raised about the increase in market power that has been observed in a significant number of industries. 16 In an important recent speech, Commissioner Vestager outlined the scope of the ongoing process of the evaluation of merger control. 17 She underlined the importance of effective merger control for European competitiveness and pointed to a number of initiatives aimed at optimizing its application in view of the current economic challenges. These include (among others) the following:
• the acceptance of Member State referrals of mergers below the EU's revenue thresholds with significant anti-competitive potential (e.g., potential "killer acquisitions" in pharmaceutical and digital markets); • material simplification of merger procedures to reduce the administrative burden for companies in situations where competitive concerns appear unlikely; • review and consultations on the substance of merger enforcement: e.g., through ex-post assessments of past enforcement and an open dialogue on current issues such as increased concentration and market power in digital markets.
In terms of court developments, the Commission faced a setback in the General Court's recent CK Telecoms decision, which overturned the Commission's prior prohibition decision in the UK mobile case Hutchison 3G UK/Telefónica UK. 18 In this judgment, the Court held that the Commission must meet a higher burden of proof in such cases than the balance of probabilities. Moreover, it found that, in horizontal mergers, the Commission must presume the existence of standard efficiencies that are said to flow from such transactions. The Commission has recently appealed the ruling to the European Court of Justice. 16 See the discussion in Kotzeva et al. (2019) . 17
Between January 2019 and July 2020, the Commission adopted 684 decisions in the area of state aid. Most of those decisions concluded that the actions were compatible with the Commission's criteria for justifiable actions or did not actually involve aid. 19 During this period there has been significant policy work. The Commission launched in early 2019 an evaluation of State aid rules: a "fitness check." 20 This is a process that reviews principally the rules under the State aid Modernisation package. This evaluation assesses whether the rules are fit for purpose and covers two regulations and nine guidelines, including: the General block exemption regulation Environmental and Energy guidelines; Risk Finance guidelines; and the Important projects of common European interest (IPCEI) guidelines. Also, the Commission has been revising the existing guidelines in the context of the greenhouse gas emission allowance trading scheme (ETS guidelines).
In addition, the COVID-19 outbreak has brought new challenges and the need for a flexible framework to channel State aid measures. A temporary framework (TF) was therefore adopted in March 2020 that addresses the serious economic disturbance caused by the pandemic while not jeopardising the level playing field in the internal market. A detailed analysis of the TF follows in Sect. 4 below. In June 2020, the Commission also adopted a White Paper that discusses the right tools to ensure that foreign subsidies do not distort the internal market. 21 In the area of banking, the Commission has authorised two recapitalisations: that of German Norddeutsche Landesbank-Girozentrale (NordLB) 22 and Romanian CEC Bank. 23 The Commission considered that the two transactions were in compliance with the market economy operator (investor) test since the expected remuneration of the State was considered to be in line with that expected by a private operator in similar circumstances. The Commission also authorised public support of EUR 3.2 billion for an IPCEI project for research and innovation in the common European priority area of batteries: a common project of seven Member States and 17 direct participants. 24 In the broadband market, the Commission authorised a 19 Detailed information related to the Commission's State aid activity are available at https ://ec.europ a.eu/compe titio n/publi catio ns/annua l_repor t/2019/part1 _en.pdf. The number of decisions has been abnormally high this year, also due to the significant number of COVID-19 related cases (see Sect. 4 below). 20 See also https ://ec.europ a.eu/commi ssion /press corne r/detai l/en/IP_19_182. 21 See also https ://ec.europ a.eu/commi ssion /press corne r/detai l/en/ip_20_1070. 22 25 The CET has been closely involved in the TF work streams, and significant cases (e.g., the Lufthansa, SAS, German recapitalisation scheme). The CET has contributed to the design of the TF, and in case work notably analysing proportionality needs, the appropriate remuneration as well as governance conditions in various cases. The CET has worked extensively on the energy sector: on policy work and also on individual cases. A significant contribution has been on recapitalisation cases (such as the banking cases mentioned above) as well as funding gap analysis for IPCEIs and the infrastructure project of Fehmarn Belt. 26
The Decision of 18 July 2019 on the Qualcomm (predation) case 28 is the European Commission's first predatory pricing case since the Wanadoo Decision of 2003. 29 It concerns the market for "baseband" chipsets of the third generation-Universal Mobile Telecommunications System (UMTS) chipsets-which are used in mobile devices (such as mobile phones, tablets, and "dongles") to enable calls and data exchange via the cellular network. 30 The Commission concluded that between 1 July 2009 and 30 June 2011, Qualcomm abused its dominant position in the UMTS chipset market by selling certain volumes of three of its UMTS baseband chipsets to two of its key customers-Huawei and ZTE-below cost, with the intention of foreclosing Icera: its most important competitor in the leading-end segment at the time. For this infringement of Article 102 of the Treaty on the Functioning of the European Union ('TFEU'), the Commission imposed a fine of EUR 242 million on Qualcomm. Qualcomm lodged an application for annulment of the Decision in November 2019, which is currently pending before the General Court.
During the investigated period, Qualcomm was the dominant developer and manufacturer of mobile communications technologies and baseband chipsets in a variety of standards-in particular, baseband chipsets that were based on UMTS. 25 Qualcomm's customers are device makers-original equipment manufacturers (OEMS)-that buy baseband chipsets and integrate them into their mobile devices before selling them to mobile network operators (MNOs) or wholesalers of electronic devices.
Icera-a semiconductor start-up that was founded in 2002 and was headquartered in Bristol (United Kingdom)--specialised in the development of UMTS baseband chipsets. In May 2011-towards the end of the period for which the Commission found predation-Icera was acquired by the US technology company Nvidia. In 2015, Nvidia decided to wind down its baseband chipset business, thus withdrawing the particular chipset technology that had been developed by Icera (so-called soft modems) from the market. This market exit led to a reduction in product variety and a possible slowdown in technological progress and therefore had a negative impact on consumers.
The Qualcomm case differs from previous European predatory pricing cases, such as the Wanadoo decision of 2003, mainly because almost all of the investigated prices were above average variable costs (AVC) but below long-run average incremental costs (LRAIC). By contrast, in the previous predation cases only part of the sales had been made at a price between AVC and LRAIC, whereas the price was below AVC for a significant volume of sales. In the Qualcomm predation case, the finding that Qualcomm's conduct was intended to foreclose Icera from the market was therefore an essential element of the Decision that complemented the results of the price-cost test. This finding of intent is based on a thorough analysis of Qualcomm's contemporaneous internal documents, which were supplemented by thirdparty information. The analysis of the documentary evidence gave a clear picture of the market environment around the period of the infringement and Qualcomm's desire to defend its dominant position by means of an abusive predatory pricing strategy against Icera.
While Qualcomm's conduct during the investigated period aimed at protecting Qualcomm's dominance in the entire UMTS chipset market-and in particular its strong position in the high-volume segment of baseband chipsets for use in mobile phones-its pricing strategy was selective: in terms of the market segment and also the customers that were affected by predatory prices.
First, Qualcomm's strategy focused on UMTS chipsets that offered advanced data rate performance: the "leading-edge segment". In this segment, Icera had started to gain traction in 2008/2009 due to: the software upgradability of its chipsets to leading-edge data rates; its smaller die size; and its competitive pricing. 31 31 Icera's ICE8040-based chipset was a "soft modem" chipset: Most of its baseband processing functionality was implemented in software that ran on a custom processor, as opposed to the conventional approach of designing and implementing these functions in silicon using a series of fixed-function silicon blocks. Icera advertised this soft-modem architecture as one of the main distinctive characteristics of its product, as it would enable the chipset to benefit from further performance upgrades and enhancements that would be delivered in the form of software upgrades. This meant that the ICE8040 based chipset could be enabled to support higher data rates by simple software update and therefore adapt to the future Second, Qualcomm's strategy focused on Huawei and ZTE: the two strategically most important customers for leading-edge UMTS chipsets during the relevant period. These two customers were the main OEMs of "mobile broadband" (MBB) devices at the time. 32 While the market for MBB devices was (and still is) relatively small compared to the mobile phone market, they were particularly important for the leading-edge chipsets that were supplied by Icera and Qualcomm.
By containing Icera's growth at the two key customers in the leading-edge segment, which consisted at the time almost exclusively of chipsets that were used in MBB devices, Qualcomm intended to prevent Icera-a small and financially constrained start-up-from gaining the reputation and scale necessary to challenge Qualcomm's dominance in the wider UMTS chipset market. Qualcomm was particularly concerned by Icera's threat because of the expected growth potential of the leading-edge segment due to the global take-up of smart mobile devices.
Thus, while only a small part of the UMTS chipset market was affected by belowcost pricing, this selective and targeted predatory strategy had an adverse impact on the entirety of the market that the strategy intended to foreclose. Moreover, Qualcomm's conduct also affected the contestability of future markets, beyond the UMTS chipset market on which the predatory attacks occurred. With revenues from MBB sales falling below Icera's targets, Icera was forced to scale back its R&D in voice functionality/LTE, which was crucial for Icera to be able to enter the LTE smartphone segment as scheduled by the end of 2011. Instead, Icera's entry into the LTE smartphone segment was delayed to February 2013, by which time Icera had already lost the commercial opportunity of being the first entrant in this segment; and its acquirer, Nvidia, eventually wound down Icera's modem operations in May 2015.
Predatory pricing cases are notoriously difficult to pursue, which may explain why they are "something between a white tiger and a unicorn". 33 At a conceptual level, economists have long struggled to come up with a convincing rationalisation of below-cost pricing that lives up to the standards of modern game theory. 34 The idea that predation may involve a dynamic strategy where market entrants can at first only compete on a sub-segment of the market, which may become the theatre of a predatory attack to protect future markets, has only recently been explored. 35 rollout of high speed packet access (HSPA+) networks without the need to replace any hardware in the process.
Footnote 31 (continued) 32 At the time covered by the investigation, MBB devices included in particular: tablets with cellular access; data cards with cellular access, typically in the form of USB sticks (also called "dongles"); wireless routers that rely on cellular networks to act as WiFi hotspots (also called "MiFi" devices); and other devices (e.g., laptops) that use embedded modules with cellular access. 33 Baker (1994) . 34 Motta (2004, ch. 7) . 35 Fumagalli and Motta (2013) .
At an operational level, the difficulty of establishing predatory pricing lies in the fact that "low" prices can arise both under predation and under a pro-competitive reaction to entry, with prices "naturally" declining as the competitive pressure experienced by the incumbent increases. In technical terms, this inherent ambiguity may lead to two types of errors: A Type I error consists in failing to identify a predatory attack when in fact it has occurred. If such a Type I error is likely to occur, this weakens antitrust enforcement and encourages unlawful behaviour. A Type II error consists in finding predation when in fact there was none. The problem with Type II errors is that they tend to have a chilling effect on competition, as incumbents may hesitate to react pro-competitively to entry for fear of triggering an antitrust investigation.
Different jurisdictions have tried to solve this conundrum in different ways. In the US, the legal standard for finding predatory pricing is based on the "Areeda-Turner" test, which requires that prices are below short-run AVC, and that recoupment is at least possible. 36 The legal framework applicable in the EEA builds on two different tests, known as the AKZO I and AKZO II tests. With respect to the relevant cost benchmark, the case law states that "first, […] prices below average variable costs must be considered prima facie abusive inasmuch as, in applying such prices, an undertaking in a dominant position is presumed to pursue no other economic objective save that of eliminating its competitors. Secondly, prices below average total costs but above average variable costs are to be considered abusive only where they are fixed in the context of a plan having the purpose of eliminating a competitor." 37 In other words, there is a presumption that prices below AVC are abusive (AKZO I). However, even prices above AVC (but below average total costs) may be found abusive, provided that there was exclusionary intent (AKZO II). The Qualcomm predation case discussed in this article falls squarely within this second category. While prices above AVC do not generally give rise to antitrust concern (as they are compatible with many forms of pro-competitive behaviour), they are not a safe haven in the EEA, as the existence of evidence on intent may give rise to a finding of abusive pricing nonetheless.
As explained above, Qualcomm's predatory pricing strategy was targeted at certain products and customers, which were indispensable for Icera's development prospects on the UMTS market and beyond, but represented only a small part of Qualcomm's product portfolio or turnover. The Commission therefore focused its price-cost test on those three chipsets and the two customers on which Qualcomm's predatory pricing strategy was based. The test was carried out in three steps, which are explained 36 For a critical assessment, see for instance Hovenkamp (2015) . in more detail below: (1) the reconstruction of the effectively paid prices; (2) the comparison of these prices with Qualcomm's AVC; and (3) the calculation of the non-variable production costs and the comparison of the prices with Qualcomm's LRAIC.
For reasons of legal certainty, the relevant cost benchmark for both the AVC and non-variable costs included in the calculation of LRAIC were the costs of the dominant undertaking (i.e., Qualcomm), not the costs of the foreclosed undertaking (i.e., Icera), as the latter would not normally be known with the necessary degree of precision to the dominant undertaking. Therefore, the Commission's price-cost test is equivalent to an "as-efficient-competitor" test: It indicates whether-under the assumption that Icera was as efficient as Qualcomm in producing the products under investigation-Icera could have survived in the market in the long run in the face of the prices that were charged by Qualcomm. 38
In the Statement of Objections of December 2015, the Commission had used Qualcomm's average prices from its formal accounting in its price-cost test. However, these data only partially reflected the unit prices that were effectively paid by Huawei and ZTE for the products that were under investigation. In addition to the realised revenues from the quantities that were sold at any given time, the accounting prices also included the release of reserves that had been created to cover possible (eventually non-realised) rebate claims for units that were shipped in previous quarters, which were therefore unrelated to the units that were shipped in the quarter in which the release was recorded. Following an in-depth analysis of the resulting distortions, the Commission considered that it was necessary to correct the accounting price data for these releases by allocating them to the sales to which they effectively related.
Furthermore, the Commission's investigation revealed two one-off payments that were made by Qualcomm to Huawei and ZTE, respectively. In Qualcomm's accounts, these one-off payments had been attributed to a specific chipset model. However, it was apparent from internal Qualcomm documents (sometimes supported by third-party documents) that these one-off payments were intended as a discount for certain quantities of other chipsets for which Qualcomm did not wish to reduce the price directly at that time. The Commission therefore allocated the oneoff payments in question to the specific sales that resulted from those documents, which significantly reduced the unit price effectively paid for the sales in question.
The effectively paid prices thus established were then cross-checked against relevant internal documents that reflected Qualcomm's plan to foreclose Icera from the UMTS chipset market. The price reconstruction carried out by the Commission made it possible to link each of the price points discussed in those documents to the actual transactions that had occurred at these prices. In doing so, the Commission 38 For an overview of cost benchmarking in predation cases, see Crocioni (2018) provided the necessary proof that the predatory pricing strategy that was envisaged in the Qualcomm documents had actually been implemented.
Since Qualcomm does not manufacture its chips itself, but outsources this to thirdparty chip manufacturers ("foundries"), the AVC was calculated on the basis of the unit prices that were invoiced by Qualcomm's foundries for the shipments of the respective chipsets to Qualcomm. In order to take account of the fact that not all chipsets were immediately resold but sometimes kept in stock for some time, the Commission reconstructed the respective stocks so as to allow for a meaningful comparison of the acquisition cost of any given chipset to the price that was charged for this chipset by Qualcomm in the quarter in which it was eventually sold.
As mentioned above, the unit prices effectively paid by Huawei and ZTE were always above the AVC calculated by the Commission, with very few exceptions. The legal standard to be applied is therefore the AKZO II standard: There may also be abusive pricing at levels that are between AVC and average total cost (ATC) if these prices were intended to foreclose a competitor from the market.
As in previous cases (see, for example, Wanadoo), the Commission considered LRAIC-the average of all (variable and fixed) costs that were incurred by Qualcomm in the production of the products under investigation-to be the most appropriate cost measure for the purposes of the price-cost test. LRAIC is below ATC because Qualcomm is a company that produces a large number of different products, of which only three specific chipset models were relevant for the implementation of its predatory pricing strategy vis-à-vis Icera. In the case of a multi-product company, in addition to the costs that can be attributed to the production of certain products, there are also genuine "common costs" (such as commercialisation or administrative costs) that could not have been avoided if a single product had not been produced. Such common costs are therefore not taken into account in the calculation of LRAIC, but would be fully included in the calculation of ATC. LRAIC is therefore a conservative cost benchmark as compared to ATC.
In order to calculate LRAIC for the investigated chipsets, the Commission relied, in addition to the AVC, on product-specific development costs that were obtained from internal Qualcomm documents. The latter costs do not vary with the short-run volume of sales (and are therefore not part of variable costs), but are unavoidable in the long run to achieve the entirety of the chipset sales under investigation. As most of these development costs are incurred before the sale of the chipsets to which they relate, the Commission had to allocate these development costs to the investigated chipset sales, with the use of a revenue-based allocation method. This approach takes into account the fact that leading-edge chipsets tend to generate the highest margins at the beginning of their product life cycle, since the innovative added value of these products is highest when they are first launched on the market.
In this context, if instead a quantity-based allocation were to be applied-as is common in business cost accounting-this would significantly increase the LRAIC for the products under investigation towards the end of their life cycle, when the sales volumes are still high, but margins tend to be much lower. As a result, costs would mechanically exceed prices in later periods, even though no predatory pricing may have been intended.
For innovative products whose margins are subject to such strong variations over the life cycle, a revenue-based allocation takes account of the impact of these life cycle dynamics on the calculated minimum margin in a realistic manner. This approach also allowed the Commission to take into account spill-over effects between two of the three products under investigation.
The Commission then compared the effectively paid prices with the respective LRAIC. This comparison was carried out on a quarterly basis for each of the three investigated chipset models and for each of the two key customers. The test showed that almost all sales to Huawei and most of the sales to ZTE were made at prices that were below the respective LRAIC. Qualcomm's total revenue from these predatory sales was well above Icera's total turnover in 2011 (the last year in the investigation period).
At the beginning of the period under investigation, Icera had already established a nascent sales relationship with ZTE, and so Qualcomm's strategy focussed mainly on Huawei: By selling at below-cost prices to Huawei, the latter was to gain a competitive advantage at the next level of the supply chain where chipset suppliers such as Qualcomm and Icera compete indirectly for orders of MNOs through the MBB devices of OEMs that incorporate their respective chipsets. Only later did Qualcomm extend its predatory strategy also to ZTE.
The established case law does not require the Commission to prove recoupment after a predatory episode. In the Qualcomm case, however, it was apparent from the dominant undertaking's internal documents that such recoupment was never envisaged, and would not have been possible, over the remaining life cycle of the investigated products. This is because (as was described above) the margins of chipsets in the leading-edge segment tend to fall rapidly after a short period of time, even absent any predatory pricing strategy. Instead, the "payoff" from Qualcomm's strategy was that Icera was prevented from entering the much larger and more profitable segment of smartphone chipsets, which would have resulted in a much more significant loss of profits for Qualcomm than that caused by the predatory pricing episodes on the smaller segment of MBB devices.
Yet, in addition to the price-cost test that was described above, the Commission also examined whether the two high-volume chipsets under investigation had eventually recovered their aggregated LRAIC when their total life-cycle revenues are considered. The main differences with the above-mentioned price-cost test were as follows: (1) The Commission took into account the whole life cycle revenues of the products, including sales in the period following the infringement period (when one of the two high-volume products was still on sale); (2) the Commission also took into account all of the revenues that were obtained from other customers of these two products (not only Huawei and ZTE); and (3) the Commission carried out the test not only for each chipset, but also at the level of the chipset family: The Commission pooled the revenues and the development costs of the two products. Thus, although this overall life cycle analysis took into account far higher revenues than the above price-cost test, the investigation showed that-even at the productfamily level-the two products did not fully recover their aggregate product-specific production costs (including development costs). This result does not depend on the specific assumptions that were made about the allocation of development costs and thus corroborates the result of the price-cost test in this case.
The sparse case law on predatory pricing cases-both in the EU and outside (e.g., in the US)-shows that such cases are usually characterised by high complexity, which often makes it much more difficult to pursue such forms of abusive pricing than other types of anti-competitive pricing practices. This is all the more the case where the industry under investigation is characterised by high fixed costs and relatively low variable costs, so that a price-cost test that is based exclusively on variable costs may not allow the identification of the existence of predatory prices in all cases.
The Qualcomm decision shows that-even in such inherently complex casesthe Commission strives to enforce rigorously the relevant competition rules so as to: tackle anticompetitive conduct; deter future abusive conduct; and, where possible, restore effective competition in the affected markets.
As announced by Qualcomm on the day of the adoption of the Qualcomm predation Decision, Qualcomm lodged an application for annulment of the Decision. 39 Qualcomm's appeal is mainly based on the following claims: (1) a lack of perceived competitive threat from Icera, since customers turned to Qualcomm's products not because of their price but because rival chipsets were (according to Qualcomm) technologically inferior, (2) a lack of precedent and economic rationale for the Decision's theory of harm, which is based on alleged below-cost pricing over a very short time period and for a very small volume of chips (see Sect. 2.2 above on the Commission's view of this rationale), and (2) a lack of anticompetitive harm to Icera from Qualcomm's conduct, given that Icera was later acquired by Nvidia and continued to compete in the relevant market for several years after the end of the alleged conduct (see Sect. 2.2 above on the Commission's view of the course of events). The appeal is currently awaiting judgment by the General Court.
In the context of AT&T/Time Warner and the recent publication of U.S. Vertical Merger Guidelines, vertical mergers have become a topic of intense debate again. 41 Against this background, this section describes the recent developments in the application of economic analysis in vertical mergers at the Commission. Section 3.1 discusses the Commission's general approach toward analyzing vertical mergers. Section 3.2 describes classes of cases where anti-competitive incentives for raising rivals' cost (RRC) are likely to dominate pro-competitive incentives for the elimination of double marginalization (EDM). Finally, Sect. 3.3 analyzes two specific mergers of this type in more detail, which the Commission assessed in the previous year.
The basic economic principles of assessing vertical mergers are set out in the Commission's Non-Horizontal Merger Guidelines. 42 Specifically, the Commission applies a three-prong test, which analyzes: (1) whether the merged entity has the ability to foreclose rivals; (2) whether the merged entity has an incentive to foreclose rivals; and (3) whether such foreclosure would lead to competitive harm in the downstream market. 43 From an economic perspective, the ability to foreclose requires that the input in question is a critical input: (1) that it is important for downstream competition and (2) that the merged entity has substantial market power over it. An incentive to foreclose requires: (1) that lack of access to the input would cause significant diversion from a foreclosed rival to the merged downstream business; and (2) that such diverted sales would be profitable for the merged entity.
Contrary to horizontal cases, measuring diversion ratios can be appreciably more involved in vertical cases. Indeed, in vertical cases a price increase for a critical input may not only cause diversion in the downstream market, but may also lead to switching in the upstream (input) market. When such input substitution is plausible, the diversion ratio to the merged entity's downstream business may therefore be significantly diluted. In practice, measuring the likelihood and magnitude of this effect is not always straightforward.
In some instances, firms' internal documents contain estimates of likely departure rates in the event of a loss of access to the input. In other instances, there may be empirical evidence from past price changes in the market. 44 However, such direct evidence is not always available. In its absence, the size of profit margins can be useful as an indicator for the relative importance of upstream and downstream substitution. For example, when upstream margins are large, whereas downstream margins are small, then this indicates that downstream demand is elastic whereas upstream demand is not. In that situation, it will be much easier for customers to switch the downstream product than the upstream product.
Finally, the third prong of the test requires that harm to competition and consumers is shown-not merely harm to competitors. This implies: (1) that the merged entity does not face significant competition from rivals that are not subject to foreclosure (e.g., other vertically integrated firms); and (2) that the upward pricing pressure (UPP) that is created by RRC is not completely offset by EDM or other efficiencies.
Recent literature has correctly pointed out that the price-increasing effect of RRC and the price-reducing effect of EDM are not fully separable effects, but influence each other. 45 From an economic perspective, both RRC and EDM result from the same post-merger profit optimization. While the upstream firm's desire to benefit its downstream partner generates incentives for RRC, the downstream firm's desire to benefit its upstream partner generates incentives for EDM. Consequently, the equilibrium values of RRC and EDM are interrelated. This is not simply a matter of "weighing the EDM efficiency against the RRC harm." When EDM is sufficiently large, then it reduces the very (equilibrium) incentive to engage in RRC. This follows because recaptured sales are less profitable for the merged entity when EDM has reduced downstream prices. As the above-noted papers show, this feedback effect can be so strong that the merged entity decreases not only its downstream prices in equilibrium but even decreases the upstream prices it charges to third parties. There is therefore no trade-off between EDM and RRC anymore, and all consumers benefit from the transaction.
One should be careful not to over-interpret this result, however. For example, it is based on models that assume an extreme form of pre-merger double marginalization. Concretely, all of the above papers assume that pre-merger mark-ups are so large that prices exceed the level that even an integrated monopolist would set. It is therefore not surprising that vertical integration leads to strong EDM in these models, as this permits the merged entity to reduce prices toward monopoly levels.
Indeed, in less extreme situations, the reverse result equally applies: If EDM is sufficiently small, then RRC may not only increase the upstream price charged to rivals but the integrated firm will also raise its downstream price. Hence, there is again no trade-off between EDM and RRC but instead all consumers are harmed by vertical integration. 46 45 See Das Varma and De Stefano (2020), Akgün et al. (2020) , and Sibley and Domnenko (2020) . 46
In order to assess the often-complex economic effects of vertical integration, the Commission has sometimes used economic models in its competitive assessment. Models that have been considered in recent case practice among others include: vertical arithmetic (VA); bargaining models; vertical gross upward pricing pressure indices (vGUPPIs); and merger simulation.
VA is the simplest form of quantitative analysis and is often submitted to the Commission by merging parties. It assesses the merged entity's incentives for total foreclosure based on: (1) firms' pre-merger margins; and (2) the expected diversion ratio from third parties to the merged entity's downstream unit in the event of a loss of access to the critical input.
VA is straightforward to apply. But unfortunately, it also has significant limitations: First, it will typically be more profitable for the merged entity to raise the price of the input instead of engaging in an outright refusal to supply. Second, even if the merged entity refuses to supply the input, post-merger prices will typically change as a result of the transaction (e.g., due to EDM). For this reason, VA can provide only indicative evidence about likely foreclosure incentives. 47 More advanced models that also permit assessing the merged entity's pricing incentives are the bargaining leverage model (for markets with negotiated prices) and vGUPPI analysis (for markets with posted prices). 48 These models operate in a similar fashion as price pressure models in horizontal cases. 49 They can be highly instructive to identify the core parameters that drive pricing incentives. Moreover, they permit quantifying the upward pricing pressure that may result from vertical integration.
The vGUPPI model also allows for a direct quantification of countervailing EDM incentives. Similarly, Shapiro (2018) illustrates how EDM incentives can be measured in the bargaining context. However, both approaches abstract from the feedback effects between EDM and RRC (as discussed in Sect. 3.1.1). This is because they are partial equilibrium models that calibrate pro-and anti-competitive effects separately, rather than jointly.
A complete balancing of pro-and anti-competitive effects-including feedback effects-in principle requires a full merger simulation. Such vertical models exist and have been applied, in particular in academic contexts. 50 However, such vertical simulations tend to be relatively complex due to the intricate interaction of upstream and downstream markets. As a result, they can be sensitive to seemingly innocuous parameter assumptions-e.g., as to demand curvature-that may be difficult 47 Specifically, VA tends to be too permissive if EDM is moderate (as VA underestimates partial foreclosure incentives). Conversely, VA tends to be too strict if EDM is large (as it does not account for EDM). 48 See Rogerson (2020) and Moresi and Salop (2013) , respectively. 49 See Valletti and for a recent survey. 50 E.g., see Crawford et al. (2018) and Sheu and Taragin (2020). to verify in merger proceedings. Therefore, their use in antitrust practice has so far been limited.
As the previous section has illustrated, a full balancing of EDM and RRC including feedback effects can be complex in vertical mergers. While economic models can help with such assessments, evidence for foreclosure is likely to be particularly robust when EDM is expected to be small (or absent). This section therefore portrays different classes of vertical mergers where EDM is likely to be of limited relevance. These classes are based on recent Commission case experience (we discuss two such cases in more detail in Sect. 3.3 below).
An important reason why RRC may significantly outweigh EDM can be that rivals rely on the critical input more often than the merging firm itself does. For example, in Deutsche Börse/LSEG, Deutsche Börse proposed to acquire a clearing house that was an essential input for competing stock exchanges. 51 Deutsche Börse itself, however, was already vertically integrated into clearing services. Hence, the transaction did not present any scope for EDM in this market. However, control of the clearing house would have permitted Deutsche Börse to increase materially the costs of its rivals. 52 As this case illustrates, diagonal mergers can lead to straightforward competition concerns without the need to engage in a complex balancing exercise. In the example of Deutsche Börse/LSEG, RRC incentives were substantial, and there was simply no scope for countervailing EDM.
A second class of cases with limited scope for EDM are situations where the critical input already has close to full market coverage. This was the case, for instance, in Telia/Bonnier Broadcasting (which will be discussed in more detail in Sect. 3.3.1 below). 53 In that case, the critical inputs were TV channels, to which the vast majority of potential viewers already had access pre-transaction. In such situations, the downstream firm cannot meaningfully expand demand for its upstream partner by reducing its price (at least as far as winning new customers is concerned). Instead, price reductions would merely cannibalize upstream sales that would otherwise have 51 Case M.7995 Deutsche Börse/London Stock Exchange Group (Commission decision of 29 March 2017). 52 The merging parties offered to divest the clearing house in question. This notwithstanding, the transaction was ultimately blocked due to competition problems in other affected markets. 53 Telia/Bonnier Broadcasting, supra note 17. been made via other distributors. Accordingly, EDM incentives are likely to be limited in such cases.
EDM is also likely to be small if the merging parties already have contractual arrangements in place that allow double marginalization to be overcome pre-merger. This was the case, for instance, in Wieland/Aurubis (which will be discussed in more detail in Sect. 3.3.2 below) . 54 In that case, the merging firms had a joint venture in place that already ensured that the input would be transferred to them at cost.
More generally, contractual solutions to avoid double marginalization include two-part tariffs and rebate schemes that ensure marginal cost pricing for incremental units. Note, however, that such contractual solutions may equally undermine incentives to engage in RRC. 55 Arguing that EDM is not merger-specific therefore requires an asymmetry in the contractual set-ups that relate to the merging downstream firm and independent competitors. 56
Finally, EDM is also unlikely to arise in vertical mergers when there is a significant horizontal overlap in the downstream market. 57 To see this, note that EDM is caused by the downstream firm's desire to expand sales for its upstream partner. However, when there is also significant upward pricing pressure due to a horizontal overlap, then this will tend to dilute or overturn the incentive to reduce downstream prices. 58
Finally, we present in more detail two important vertical mergers of the last year, which illustrate many of the concepts discussed in this section: Telia/Bonnier Broadcasting and Wieland/Aurubis. The former case was cleared subject to significant access remedies (including FRAND licensing terms), whereas the latter case was ultimately blocked. 54 Wieland/Aurubis, supra note 18. 55 E.g., in full information settings a two-part tariff may permit full extraction of the existing upstream market power. This leaves no scope for profitable RRC post-transaction. 56 See Sect. 3.3.2 for a discussion in the context of Wieland/Aurubis. 57 Wieland/Aurubis turns out to be an example for this type of situation as well, as will be discussed in Sect. 3.3.2 below. 58 E.g., the vGUPPI model permits a netting of pro-competitive EDM and upward pricing pressure (as measured by regular GUPPIs).
This case concerned the takeover of the leading private TV broadcaster in Sweden (Bonnier Broadcasting) by the leading Swedish telecoms operator that is also active in TV distribution (Telia). Specifically, Bonnier owned both the most important commercial free-to-air channel (TV 4) as well as leading premium TV channels with significant exclusive content (C More). The Commission's main concern in this case was that the merged entity would significantly increase the licensing fees for Bonnier Broadcasting's "must have" TV channels and thereby raise the distribution costs of Telia's downstream rivals.
As noted in Sect. 3.2.2, Bonnier Broadcasting's content was so ubiquitous in the affected geographic markets that the scope for EDM appeared modest at best. Conversely, the merged entity's RRC incentives were likely to be significant, since a potential blackout of Bonnier Broadcasting's TV channels was expected to cause significant switching of viewers away from foreclosed rivals.
In order to quantify the possible impact of increased bargaining leverage, the Commission used a calibrated bargaining model, which predicted a substantial postmerger increase in licensing fees. In applying this model, the Commission was able to rely on empirical estimates of the likely switching rates that would result from a potential blackout. These estimates were based on: (1) the parties' own internal estimates of likely customer switching after a blackout, and (2) measured departure rates following a contemporaneous natural experiment, since Telia had recently made the distribution of some premium sports content exclusive on its network.
As was mentioned above, this case was cleared subject to significant access remedies.
Wieland/Aurubis concerned the proposed merger of two copper producers with both vertical and horizontal links. Concretely, Wieland set out to acquire Aurubis's downstream rolled copper operations, which led to standard horizontal overlaps. Moreover, Wieland planned to take sole control of Schwermetall, an upstream joint venture with Aurubis that provided pre-rolled strip (an input) to both firms and also to downstream competitors.
The pre-merger joint venture allowed both Wieland and Aurubis to obtain prerolled strip at preferential conditions to avoid double marginalization. Third-party rivals were instead charged profit-maximizing prices. In other words, the transaction did not generate significant scope for EDM. On the contrary, the transaction was likely to raise downstream prices due to the significant horizontal overlap between Wieland and Aurubis in rolled copper production.
In addition, the proposed merger was likely to generate strong incentives to raise the upstream prices for pre-rolled strip toward Wieland's competitors. Pre-merger, Schwermetall had maintained operational independence from its parent companies with respect to third-party sales. This independence would cease after the transaction. Schwermetall was therefore likely to increase its prices, as this would benefit Wieland in the downstream market for rolled copper.
Since Wieland was not willing to address these concerns comprehensively, the transaction was ultimately blocked.
As of September 3, 2020, in the aftermath of the COVID outbreak, the European Commission had approved more than 317 national state support measures in more than 280 decision with a total estimated budget of close to EUR 3 trillion in COVIDrelated measures alone. 59 We first outline the main economic challenges of the crisis, and how the European Union has reacted so far, before focusing on the State aid temporary framework (TF) that has been adopted by the European Commission to address the need for support of the EU economy. While the TF preserves principles of State id, it also sets out more flexible rules to respond to the economic challenges that have been raised by the COVID outbreak.
The COVID pandemic's impact on health, society, and the economy is unprecedented in the history of the EU. Those effects are linked as the current economic crisis stems mostly from the changes in consumer behaviour that have been triggered both by the public's fear of contagion and by the public health measures that are aimed at containing the outbreak. The summer EU forecast foresees that the EU economy will contract by 8.3% in 2020. 60 The crisis is a mix of both supply and demand shocks. On the supply side, there have been disruptions in supply chains-including disruptions of transport networks when travel is severely restricted. Today's economy includes many interconnected parties, and a sudden break in some part of these chains can easily lead to cascading effects. 61 On the demand side, consumers purchase both less and differently, which leads not only to a decrease in aggregate demand but also to very large drops in some sectors and insufficient capacity in others. There is also considerable uncertainty about the future: When will the health crisis be resolved? Will there be long-term effects on the pattern of demand and on the organisation of production? Decreased demand and uncertainty lead to higher borrowing costs-especially for risky sectors of the economy-thereby exposing the financial vulnerabilities of firms and households. To this already grim picture one must add the possible accumulation of 59 This includes all measures that are related to the COVID crisis under various legal bases. 60 https ://ec.europ a.eu/commi ssion /press corne r/detai l/en/ip_20_1269. 61 See for example, https ://voxeu .org/artic le/covid -19-and-effec ts-socia l-dista ncing -econo my, where Luc Laeven argues and provide evidence that lockdowns impose large negative externalities on firms through input-output linkages, even for firms that are not directly affected by social distancing measures. non-performing loans in financial institutions, which might eventually endanger the stability of the financial system.
A fundamental goal of policymakers is to ensure that the negative shock from the new economic reality is short lived and that the economic linkages can be restored promptly: ensure that workers keep their jobs; viable firms do not go bankrupt; and banks can still provide lending.
On the monetary side, central banks have provided emergency liquidity to the financial sector. Long-term financing operations and targeted longer-term refinancing operations as well as asset purchase programme have been implemented by the ECB. 62, 63 On the fiscal side, the main policy response has been a mix of loans and grants (cash transfer, wage subsidies, tax relief) from the State to households and firms to help weather the liquidity challenges. This liquidity support is often granted at (very) preferential terms. Contrary to the last financial crisis, where financial institutions engaged in excessive risk taking, moral hazard is not a primary concern. Because the current crisis is unexpected and outside the control of firms and households, many feel that it calls for weak conditionality for the support that is provided.
But the crisis is not only about liquidity. The longer it lasts, the more it affects the earning and equity base of the companies. This calls for a recapitalisation framework, as with banks during the financial crisis, which would ensure the viability and survival of firms and jobs but also guarantee that taxpayers get a reasonable deal. The State would get shares or a return for the funds that it provides; hence the State could also have an upside potential for the solvency support it provides.
The EU response has been built mainly on the following pillars:
1. Flexibility to allow Member States (MSs) to use their own resources to address the impact of the crisis. This has been achieved by:
a. Adapting State aid rules to address economic disturbances from the COVID outbreak through the introduction of the TF. At a time of serious disturbance for the real economy it is crucial to establish flexible rules to ensure that funding can go where it is needed, under a common framework across MSs that thereby maintain a level playing field. 62 See for example, https ://www.ecb.europ a.eu/press /pr/date/2020/html/ecb.pr200 318_1~3949d 6f266 .en. html. 63 Some economists propose even more-far reaching monetary policy responses, such as direct, unrepayable funding by the central bank of the additional fiscal transfers that are deemed necessary; this is an intervention that is commonly known as 'helicopter money'; see "Helicopter money: The time is now", Jordi Gali, available at https ://voxeu .org/artic le/helic opter -money -time-now.
b. Using the escape clause for the Stability and Growth Pact: The European Commission temporarily waived the budgetary rules so that MSs could exceed the limits that are imposed by the Pact. 64 2. Agreement on EU resources to help MSs address crisis needs. Although borrowing levels of EU sovereigns remain at historical lows, there are substantial discrepancies in "firepower" across Member States. This is reflected in the estimated budget of COVID-19 related approved schemes. For example, more than 50% of the State aid that have been approved so far has been notified by Germany. 65 The use of common EU resources is aimed at to alleviating such asymmetries. The Next Generation EU-the COVID-19 recovery package agreement of July 2020includes EUR 390bn in terms of grants and EUR 360bn in loans to MS through the EU budget. The plan also envisages possible new resources and authorises the European Commission to borrow in the capital markets on the EU's behalf and therefore mutualises part of the COVID response. 66 There are still discussions on the exact conditionality framework. The arguments against risk mutualisation and weak conditionality focus on the moral hazard argument. Similarly to the case of firms and households, some economists have made the argument of limited moral hazard associated with this crisis that could apply to MSs. 67
The objective of State aid policy is to ensure a level playing field in the Internal Market where firms should compete on the merits rather than on the back of State support. The rationale is to avoid the emergence of "subsidy races" between Member States.
In the EU State aid architecture, national measures that constitute State aid 68 are not allowed unless there is a "compatibility basis". To tackle the consequences of the crisis there are two principal compatibility legal grounds: The first is on the basis of Article 107(2) (b) TFEU, whereby Member States may compensate undertakings for damage that is directly caused by the COVID-19 outbreak. However, the scope of this article is narrow. In particular, the damage should be directly caused by public health measures that preclude the recipient of the aid from carrying out its economic activity. 69 Economic impact that results from the COVID-induced economic crisis does not qualify under this article.
Aid that addresses the economic downturn from the COVID-19 outbreak is to be assessed under the different compatibility basis of Article 107(3) (b) TFEU, which allows support to remedy the broader economic disturbance that is brought about by the outbreak under a set of conditions that are set out by the European Commission. On 19 March 2020, only a few days after the outbreak of the crisis in Europe, the Commission adopted the TF that outlined the basic requirements for compatible State aid in these exceptional economic circumstances. 70 This framework has already been amended three times on 3 April 2020, on 8 May 2020, and on 29 June 2020. ,71,72
The aim of the framework is to address the liquidity and solvency needs of otherwise healthy undertakings due to the negative economic impact of the COVID-19 outbreak. This framework is only relevant for companies that operate in the real economy -and thus excludes financial institutions. 73 Importantly, the core principles of the TF are also consistent with the overall State aid architecture. In this sense, the TF is better thought of as an application of the standard State aid approach to specific circumstances than to a change in the standards of State aid policy. These core principles are:
1. More lenient treatment of small-and medium-size enterprises (SMEs), as compared to large enterprises. Distortions of competition are likely to be greater when State support is channelled to large enterprises since they are more likely 69 When aid meets the conditions of article 107(2) (b) TFEU, the Commission does not enjoy discretion as long as the conditions of this legal basis are fulfilled. These cumulative conditions are (1) the existence of a natural disaster or exceptional occurrence; (2) the natural disaster or exceptional occurrence has directly caused damage to the undertaking(s) receiving the aid; and (3) 2.7.2020, p. 3. 72 For completeness, the TF also includes measures to protect public health in the context of the COVID-19 outbreak, which is considered compatible on the basis of Article 107(3) (c) TFEU. 73 Contrary to the financial crisis-where specific rules for the financial sector were proposed -there are no TF rules for the banking sector, which seems resilient following the regulatory reforms that required banks to hold more and better capital, coupled with the necessary flexibility embedded in the regulatory, supervisory, and accounting frameworks (lower countercyclical buffers and reduced capital requirements, including Pillar 2 Guidance).
to compete across the EU and significantly affect trade. Also smaller companies, ceteris paribus, are more likely to be affected by the crisis since they are likely to have greater difficulties to secure sufficient financing from the capital markets. Therefore the conditions for large enterprises are typically more stringent than for Small and Medium Enterprises (SMEs) with higher remuneration for the State required in exchange for the support provided. 2. Only otherwise viable undertakings are eligible for support. Therefore, firms that were in financial difficulties before the crisis should not receive aid under the TF. This is to avoid channelling funds to inefficient firms, or firms that would have had to undergo a restructuring process even in the absence of the COVID-19 outbreak. There are other avenues for such firms to receive State support: They could receive damages under 107(2) (b) TFEU (see above), or under the traditional "rescue and restructuring" aid under the relevant guidelines. The latter option having more stringent conditions compared to the TF. 74,75 3. The level of remuneration for the State is not directly linked to the creditworthiness of the undertaking. This is because the aid provided is not targeted to provide funds to finance the companies' normal course of business and expansion plans but instead to weather a crisis that is beyond what companies could easily forecast in their normal course of business. 4. No aid should be conditional on the relocation of the beneficiary's activities from one EEA country to another. This is at the core of State aid control: to ensure that State measures do not lead to a race to the bottom to attract companies in their own territories. 76 5. Detailed transparency and monitoring rules are set out to ensure that information can be publicly available. 77
In what follows we focus on two main sets of measures: liquidity support, and solvency support. 78
The liquidity measures that are envisaged in the TF must be granted before December 2020.
There are four main measures: 74 Small and micro enterprises-companies with less than EUR 10 m turnover and/or balance sheet and less than 50 employees-were excluded from this restriction in the 3rd TF amendment. 75 EUR 800,000 per company, in the form of grants or loans, can be given with no further conditions (no remuneration for the State and no need to demonstrate the liquidity problems of the beneficiary). 79 The rationale of this measure is that for a relatively small level of support, and in light of the scale of the crisis, there can be a presumption of no significant impact on the internal market. The burden for ensuring reasonable and effective use of funds falls fully on MSs. This type of support can only be part of a scheme-not individual companies alone. Guarantees on loans: Companies can benefit from significant liquidity support, either in the form of State guarantees (so that they can raise funding from financial institutions at reasonable cost) or through direct State financing. 80 These two types of liquidity support can be combined but not cumulated: The loans that are received through either measure cannot jointly exceed the limits that are set out. These repayable instruments can be granted at attractive rates. As shown in the table below, the guarantee fees start at extremely low rates (0.25% during the first year for SMEs). The rationale for the low rates was that, for instruments that are repayable, the distortive effect in the Internal Market would not outweigh the challenges that have been brought forward by the COVID-19 crisis and the common interest to intervene. Even if remuneration is low, there is a minimum remuneration to ensure that firms do not take up these loans simply because it is an option that is available to them. Moreover, the fees are increasing over time to provide incentives for early repayment. 81 "bps" refers to "basis points": 1/100 of a percentage point.The TF allows a maximum guarantee coverage of 90%. 82 This implies that the financial institution that grants the loan should also have some "skin in the game" in order to limit moral hazard on their part. The maturity of the loans can be up to 6 years. Finally, there are upper limits to the amount of loans that companies can raise with the State guarantee: a proportionality test. These limits are company-specific since they are determined as a function of the annual wage bill, the turnover, or the liquidity needs of the beneficiary.
Subsidised loans essentially refers to senior loans that are granted by a State-or by State-owned entities such as State-owned banks-at favourable rates. The credit spread on these loans can be as low as the guarantee fees that were set out above. 83 79 See Sect. 3 .1 of the TF. 80 See Sect. 3.2 and 3.3 . of the TF. 81 The fees can be modulated based for example on the duration of the guarantee (shorter duration may justify lower rates) or guarantee coverage (lower guarantee coverage may justify lower rates). 82 It also allows guarantees that have different risk allocation where the State takes the first loss and the financial institutions take the second hit. In these situations, the guarantee cannot exceed 35% of the loan principal. 83 The base rate is set as the 1-year LIBOR rate on 1.1.2020 or at the time of notification.
The second amendment of the TF extends the set of allowable tools to subordinated debt. Because subordinated debt is junior to normal (senior) loans, firms that are supported in this manner can get additional financing from financial institutions: a leverage effect. At the same time, subordinated debt is not as risky and hence does not allow leveraging the balance sheet of the company to the same extent as does share capital. To reflect this "hybrid" nature, subordinated debt is considered as liquidity support up to some ceilings. Beyond those ceilings, subordinated debt is instead considered as a recapitalisation instrument (see below). For subordinated debt that is below the ceilings, a higher level of remuneration for the State is envisaged. 84 The TF applies only to companies that operate in the real economy-and thus excludes financial institutions. Hence, aid should directly benefit that are undertakings active in the real economy, whereas banks act merely as financial intermediaries that channel the aid. To meet this goal, banks should pass on the advantages of the State guarantees or the subsidised interest rates on loans to the final beneficiaries. 85 This pass-through can take the form of: higher volumes of financing; lower collateral requirements; lower guarantee premiums; or lower interest rates than without such public guarantees or loans. The safeguards to ensure maximum pass-through should be particularly strong in cases where the aid takes the form of a State guarantee on existing loans, since the terms that are offered by the bank would not be disciplined by competition for new loans. The responsibility for putting in place strong safeguards that ensure maximum pass-through of the aid from the banks to the borrowers lies with the Member States.
Because the COVID-induced crisis might be prolonged, the European Commission anticipated that "liquidity difficulties could turn into solvency problems for many companies." 86 Accordingly, a recapitalisation framework was introduced into the TF (Sect. 3.11 87 ) with the second TF amendment. Several companies-notably in the hardest hit sectors, such as transport-appeared likely to record losses that would significantly erode their equity base and put their solvency at risk.
To reduce the risk of insolvency, the recapitalisation section envisages the provision of equity and hybrid capital instruments to firms in the real economy. MSs can acquire newly issued shares (ordinary or preferred)-"COVID shares"-or provide hybrid instruments with varying degree of risk characteristics. Such instruments may be formally recognised as debt or equity but would typically have an equity component: Under some triggering event, they can be converted into equity. Such measures 84 To reflect the higher risk of subordinated debt as a liquidity instrument, there is a significant increase in the credit spreads of 200bps for large enterprises and 150bps for SMEs, as compared to senior loans; and the maximum amounts are lower than for senior loans (and even lower for large enterprises). 85 See Sect. 3 .4 of the TF. 86 https ://ec.europ a.eu/commi ssion /press corne r/detai l/en/ip_20_1269. 87 Or "chapter 11" in an unfortunate coincidence with US Chapter 11 bankruptcy procedure. can be granted until June 2021: This is later than the December 2020 deadlines for all of the other measures of the TF, both because solvency needs may arise with a lag and because such measures may require more planning than do liquidity measures.
Recapitalisation measures can have a very distortive effect on competition. Highly capitalised companies are able to obtain cheap financing in the markets and can therefore deploy aggressive commercial strategies. Consequently, if some firms are recapitalised but others are not, competition in the internal market might no longer take place on a level playing field. This concern justifies more stringent conditions on the commercial behaviour of the beneficiaries (governance conditions and distortion of competition measures) and stronger incentives to repay the aid. Accordingly, recapitalisation measures that exceed 250 m EUR need to be notified to the European Commission; and for these measures specific structural or behavioural commitments are required if the beneficiary has significant market power.
The European Commission has already dealt with a number of recapitalisation schemes and individual cases. Most individual decisions until now concern companies in the aviation sector. Indeed, the largest beneficiary of recapitalisation aid so far has been the German flag carrier, Lufthansa, with EUR 6 billion recapitalisation aid. Other individual cases include EUR 1 billion aid to SAS 88 and EUR 250 million to Air BalticRecapitalisations schemes have already been approved for a number of countries-e.g., Germany (Commission Decision of 25 June 2020, Germany: ment, innovation, or a systemic role-so that there are likely significant positive externalities from the provision of such aid. • The amount of the recapitalisation should also be proportional to the needs. 93 The aid provided must: (i) not exceed the minimum needed to ensure the viability of the beneficiary; and (ii) should not go beyond restoring the capital structure of the beneficiary to the one that predated the COVID-19 outbreak (December 2019). In practical terms, these are both forward-looking tests: The first leg of the test aims to ensure that the amount granted is limited to ensure that, in the foreseeable future, the company has a capital structure that would give it access to the capital markets. 94 The second leg specifies that the company should not have an improved capital structure (in terms of equity level or debt/equity) compared to the pre-crisis situation. • The recapitalisation instruments should provide support at preferential (aided) terms; however, there must be remuneration for the State, and this should increase over time to provide incentives for the companies to repay the aid. 95
For equity instruments, the capital increase should take place at a price that does not exceed the average share price of the beneficiary over the last 15 days (or the price that is established through an independent valuation if the company is not listed). Typically, capital increases in companies that face financial difficulties take place with a (significant) discount to the prevailing market price. The TF requires no such discount, which is the main element of support in the share capital instruments. However, the remuneration of the State increases over time. The beneficiary can redeem the aid if it buys back the COVID shares by paying the higher of the nominal amount injected plus a reasonable remuneration, or the current market price. Hence the State also has a potential "up-side". This "reasonable remuneration" increases over time to provide sufficient incentives to the company to redeem the aid as early as possible.
Finally, a step-up mechanism envisages the dilution of other shareholders if the COVID shares have not been redeemed (step-up mechanisms in years 4 and 6 for listed companies). 96 This mechanism provides incentives for the beneficiary to buy back the COVID shares to avoid the dilution effect.
For hybrid instruments, the remuneration is set on the basis of fixed credit spreads that, again, increase over time (from 225 to 250 bps in year 1 to 800-950 bps in year 8). These rates should be further increased to reflect the characteristics of the instrument, including the subordination and other modalities of payment (the deferral of coupon, etc.). 93 Point 54 of the TF. 94 Forecasted Net debt/EBIDTA and Equity/Assets are two ratios often examined in this respect. 95 Section 3.11.5 of the TF. 96 Point 61 of the TF requires a 10% increase in shareholding represented by the COVID-19 shares.
The German recapitalisation scheme is a good example 97 : Additional increases have been requested in cases where the hybrid instrument is perpetual in nature and is subordinated to some parts of existing equity and where the coupons can be deferred at the discretion of the beneficiary. In the special case of instruments that are perpetual and have discretionary coupon payments (which undermines the financial incentives of the beneficiaries to pay back the instrument), governance conditions-such as dividend bans and limits on executive pay-are typically imposed until the repayment of the instrument.
Finally, if the hybrid instrument is converted into equity, there is dilution of existing shareholders since the conversion takes place at a discount relative to market price.
• Governance conditions and distortion of competition measures. 98 Since recapitalisation measures can have significant distortive effects, an important ingredient of the TF is that supported firms should not engage in aggressive commercial expansion and should not take excessive risks. 99
In addition, for cases where firms receive recapitalisation aid of more than EUR 250 m and have significant market power in at least one relevant market, MSs must propose additional measures to preserve effective competition in those markets. These measures could be structural or behavioural. 100 The recapitalisation of Deutsche Lufthansa AG (DLH) is the first case where the MS submitted commitments to preserve effective competition. Due to the significant market power of DLH in the hub airports of Munich and Frankfurt, there are divestments of up to 24 landing/take-off slots/day at the Frankfurt and Munich hub airports and of related additional assets to allow competing carriers to establish a base of up to four aircraft at each of these airports. These measures would enable a viable entry or expansion of activities by other airlines at these airports to the benefit of consumers and effective competition. 101 Beneficiaries cannot advertise that they have received State aid (advertising ban). Also, large enterprises that receive such aid cannot acquire more than a 10% stake in competitors or other operators in the same line of business, including upstream and downstream operations: an acquisition ban. In exceptional circumstances, and 97 Commission Decision of 8 July 2020, Germany: COVID-19-Wirtschaftsstabilisierungsfonds (SA.56814 (2020/N)). 98 Section 3.11.7 of the TF. 99 Point 71 of the TF. 100 Point 72 of the TF. The concepts of relevant market and significant market power-which are traditional "antirust concepts"-are used in the TF. The rationale has been to prioritise the cases in which such divestments/behavioural commitments would be needed when the beneficiary has market power; and if so, require divestments in precisely these markets. 101 Concerning DLH, Germany injected EUR 6 billion in the form of a recapitalisation instrument in the company, in addition to State guarantees for a EUR 3 billion loan. Germany acquired around 20% of the Lufthansa's share capital, at significantly lower price than was prevailing at the time of the request of recapitalisation (injection of EUR 300 million). In addition, Germany provided EUR 4.7 EUR billion in the form of "silent" participations that are recognised as equity and EUR 1 billion that is recognised as debt. See https ://ec.europ a.eu/commi ssion /press corne r/detai l/en/ip_20_1179. without prejudice to merger control, beneficiaries may acquire a larger stake in operators upstream or downstream, if the acquisition is necessary to maintain the beneficiary's viability. The rationale of this acquisition ban is to prevent recipients of aid from engaging in a spending spree to acquire competitors or suppliers.
In order to provide incentives to repay the aid and to ensure that the aid does not end up enriching existing shareholders, there is a dividend and non-mandatorycoupon ban. There is also a limit on the remuneration of management, which cannot exceed the fixed part of his/her remuneration on 31 December 2019: a bonus ban. These bans would apply as long as the (the great majority of) aid has not been redeemed.
• Exit of the State: The TF provides strong incentives for the exit of the State in order to avoid a lasting "nationalisation" of the European economy. These incentives may be seen as a way to ensure the shareholding composition of the companies is not durably impacted by the crisis, while ensuring that the State receives sufficient remuneration. This is best exemplified by point 64 of the TF: If the State sells the COVID shares in the market, the governance conditions cease to apply after four years irrespective of the value of these shares-even if the State has lost part of its original investment. This ensures that there is a realistic way for exit of the State for equity instruments irrespective of uncertain future market developments. 102 Finally, if after six years (seven for non-listed companies) the COVID-19 recapitalisation by the State's has not been reduced below 15% of the beneficiary's equity, a restructuring plan in accordance with the Rescue and Restructuring Guidelines must be notified to the Commission for approval. Such restructuring plans require actions to ensure the viability of the company and may require burden sharing. 103
In times of serious disturbance of the real economy, normal State aid rules may be too restrictive or not specific enough to address the needs of the economy. The TF has been a necessary tool in ensuring that effective aid to companies in need can be channelled in a way that preserves the main principles of State aid. Liquidity and solvency support have been necessary ingredients of the national responses.
The current TF sets a comprehensive framework for such support. The more distortive types of aid must be accompanied by stringent conditions to ensure a level playing field among companies across the internal market. While the TF has a current deadline of December 2020, with the exception of the June 2021 deadline for 102 At the same time, if the market price is not sufficiently high to cover the nominal amount plus the reasonable remuneration, the governance restrictions apply for 4 years to ensure that there is a minimum period where beneficiary cannot engage into an acquisition spree or aggressive commercial expansion at the expense of competitors that may have not received such support. 103 Point 85 of the TF. recapitalisation measures, it cannot be excluded that the TF could be prolonged or adjusted after 31 December 2020-depending on the economic and public health developments.
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Dear Editor, The National Academy of Medicine defines health literacy as the degree to which individuals have the capacity to obtain, process, and understand basic health information needed to make appropriate health decisions. Most patients use the Internet as their initial source of health information (Swoboda et al. 2018) . Currently, there is an established body of misinformation surrounding coronavirus disease 2019 (COVID-19) (Ioannidis 2020) . Therefore, it is paramount that online health resources for COVID-19 are at an appropriate reading level; we aimed to assess their readability.
In a cache-cleared and location-disabled web browser, "coronavirus information" was entered in three popular search engines (Google, Bing, Yahoo!) on March 24, 2020, using five geographically representative virtual private network (VPN) locations in the United States and Canada (San Francisco, Miami, New York, Vancouver, and Toronto). Only websites in the first three search engine pages of each unique VPN location were included, as people are unlikely to proceed past this point (Eysenbach and Kohler 2002) . Public health, governmental (including regional and national), and foundational webpages which pertained to COVID-19 information for the general public were included. Webpages under 100 words, non-English articles, photos, videos, advertisements, news articles, and webpages not aimed at the general public (e.g., for healthcare professionals or businesses) were excluded. Each webpage was assessed by two independent reviewers. Any differences in data extraction were resolved by reevaluation until consensus.
The American Medical Association (AMA) and National Institutes of Health (NIH) have both recommended that reading levels of online health material should be at or below a sixth-grade level to be comprehensible to the general public (Fahimuddin et al. 2019) . Thus, five scores were used to estimate the grade level appropriate for reading each website: Flesch-Kincaid Grade Level (FKGL), Automated Readability Index (AMI), SMOG Index (SMOGI), Coleman-Liau Index (CLI), and Gunning Fog Score (GFS). The general grade level (GGL) was calculated by averaging these five scores. Flesch Reading Ease Score (FRES) applies a scale ranging from 0 to 100 with higher scores indicating easier readability (Abu-Heija et al. 2019) . Last, websites were categorized based on reading level: a GGL < 7 was considered easy; between 7 and 10, intermediate; and > 10, hard.
Of 428 webpages, 371 were excluded (330 were duplicates, 11 were < 100 words, 19 were not for the general public, and 11 were news articles). The mean GGL of the remaining 57 included webpages was 10.8. By stratifying readability of webpages with GGL, 70% were considered hard and 30% intermediate (Table 1) . Based on FRES, 82% were considered hard to read. None of the webpages were considered easy to read based on either GGL or FRES.
In conclusion, our results show that the readability of online resources for COVID-19 exceeds thresholds previously set by the AMA and NIH. Readability may be improved by
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In writing about the potential role of IFN in clinical medicine in 1967, Merigan [8] had added an addendum: "recently, a significant report appeared describing the induction of IFN and antiviral effects in animals with double-stranded synthetic ribonucleotide homopolymers." This report [9] , by Maurice Hilleman's group at Merck, was the first of the induction of IFN by what later could be hailed as the most potent inducer of IFN-b ever described, poly(I)7poly(C).
Guided by the discovery of poly(I)7poly(C) (figure 2) as a potent inducer of IFN [9] , we further examined the structural requirements to which polyribonucleotides should adhere to induce IFN production and resistance to viral infection. Our initial studies indicated that a stable secondary, preferably multistranded, structure was required for antiviral activity [10] . This antiviral activity of these polyribonucleotides could be dramatically enhanced by thermal activation [11, 12] , a remarkable phenomenon that has remained unexplored after all these years.
Starting from the alternating double-stranded RNA poly(A-U), we were able to significantly increase the IFN-inducing ability through substitution of the thiophosphate for the phosphate moieties [13] . The resulting poly(sA-sU) (figure 3) also gained increased resistance against degradation by nucleases, compared with that of its parent compound, poly(A-U), but the initial expectation that this modified RNA would ever aid in the fight against viral diseases [14] was eventually not fulfilled.
With poly(I)7poly(C) as the double-stranded RNA inducer of IFN, we [15] demonstrated that, in an animal model of virus-induced encephalitis (i.e., on intranasal challenge of mice with vesicular stomatitis virus [VSV], a rhabdovirus), the whole protective effect conferred by the double-stranded RNA could be accounted for by IFN production. In those early days of IFN (and IFN inducer) research, we also developed an animal (mouse) model for induction of tumors by Moloney murine sarcoma virus, which is still used today to study the in vivo antiretroviral activity and which allowed us to demonstrate the inhibitory effect of poly(I)7poly(C) on Moloney murine sarcoma virus-induced tumor formation [16] .
Later on, it was shown that, of the 2 strands of poly(I)7poly(C), the poly(I) strand plays the predominant role and that, for the induction of IFN, poly(I) and poly(C) may be added in sequential order-that is, poly(I) followed by poly(C) [17] assuming that, under these conditions, the double-stranded poly(I)7poly(C) complex would be assembled at the cell surface. Also, modifications in the poly(I) strand (i.e., 7-N substitution by a CH group) could be introduced without detrimental effects on the IFN-inducing ability of the resulting double-stranded RNA complex [18] . Moving in the other di-rection, by introducing modifications in the poly(C) strand (i.e., interruption of this strand every twelfth or thirteenth cytidine residue by uridine), poly(I)7poly(C) analogues such as poly(I)7poly(C 12 U) were constructed that still induced IFN while being subject to faster degradation by nucleases [19] . This [20] . At the cellular level, it induces IFN synthesis but inhibits host cell protein synthesis, and, at the host level, it stimulates host defense mechanisms but induces both local and systemic toxic side effects [20] . Recently, double-stranded as well as singlestranded RNAs have been postulated to interact with Toll-like receptors 3 and 7 (see, e.g., [21] ), but the authenticity of these interactions remains to be further established.
A landmark observation, which laid the basis for the later use of IFN-a in the treatment of hepatitis B, was made by Merigan's group in 1976 [22] , when they showed that parenteral (human leukocyte) IFN administration at a dosage between 3 6.0 ϫ 10 and U/kg/day was associated with a rapid and repro- 4 17 ϫ 10 ducible decrease in all Dane particle markers in 3 patients with chronic active hepatitis B. Long-term IFN therapy was associated with a marked decrease in hepatitis B surface antigen levels in 2 of 3 patients and a disappearance of e antigen in 2 of 2 patients. It was concluded that IFN may be useful in limiting carrier infectivity or eradicating chronic hepatitis B virus (HBV) infection.
Four drugs have been formally approved for the treatment of chronic HBV infections: pegylated IFN-a, lamivudine, adefovir dipivoxil [23] , and entecavir. Whether combinations of these drugs provide incremental benefit in the treatment of hepatitis B has not been established, although it deserves further exploration. Adefovir dipivoxil corresponds to the bis(pivaloyloxymethyl)ester of 9-(2-phosphonomethoxyethyl)adenine (PMEA; figure 5 ), a compound that was first mentioned for its antiviral properties in 1986 [24] . Adefovir dipivoxil has proved to be efficacious in the treatment of both e antigennegative and e antigen-positive chronic hepatitis B [25, 26] . It has been firmly established that adefovir acts as a chain terminator in the reverse-transcriptase (RNA-dependent DNA polymerase) reaction [27] , and this by itself could explain the reductions in HBV DNA titers achieved in vivo by the therapeutic doses used for adefovir dipivoxil (10 mg/day orally).
It should be mentioned in this context that adefovir (PMEA) has also been shown to enhance NK cell activity and IFN production, at least in mice [28, 29] , and more-recent studies with N 6 -substituted PMEA derivatives [30] have indicated that this type of compound can also stimulate the secretion of cytokines and chemokines. Whether such potential side effects could con- IFN-a (in its pegylated form), in combination with ribavirin, has become the standard treatment for chronic hepatitis C virus (HCV) infections. In a recent study, Hadziyannis et al. [31] demonstrated that patients infected with HCV genotype 1 required treatment with pegylated IFN-a2a (180 mg/week) plus ribavirin (1000 or 1200 mg/day) for 48 weeks, whereas patients infected with HCV genotypes 2 or 3 seemed to be adequately treated for only 24 weeks with the same dose of pegylated IFN and a lower dose (800 mg/day) of ribavirin. Therefore, at least in the long term, hepatitis C may be better managed by IFN and ribavirin when caused by HCV genotypes 2 or 3 rather than by genotype 1. The mechanistic basis for this differential behavior remains to be unraveled.
Of note, IFN has a strong antiviral effect on HCV, as we have demonstrated in the HCV replicon system in Huh-7 cells, in which IFN-a (intron A) was found to inhibit the replication of HCV (genotype 1b) at an EC 50 of 0.3 pg/mL, whereas no cytotoxicity for the host cells was noted at a 10,000-fold higher concentration ( figure 6 ). Ribavirin had relatively weak antiviral activity in the HCV (genotype 1b) replicon system (we have not yet examined the effects of IFN and ribavirin in HCV replicon systems with other genotypes). Thus, I surmise that IFN-a, which mainly acts as an immunosuppressant in the treatment of chronic hepatitis B, primarily acts as an antiviral in the treatment of hepatitis C, whereas ribavirin, which is best known for its antiviral properties, may be assumed to primarily act as an immunosuppressant in the case of hepatitis C.
In 1980, we succeeded in cloning human IFN-b and bringing it to expression through DNA recombination technology [32, 33] . Now, 20 years later, IFN-b has become the standard treatment for multiple sclerosis. It has been shown to be an effective treatment, in a dose-related manner, for relapsing-remitting multiple sclerosis in terms of relapse rate, defined disability, and all magnetic resonance imaging outcome measures [34] .
In a recent overview, Revel [35] noted that the role of IFNb in the treatment of relapsing-remitting multiple sclerosis is now well established, and its efficacy has been demonstrated unequivocally in large-scale clinical trials. Recent trials underline the importance of both dose and dosing frequency and indicate that, for improved efficacy in relapsing-remitting multiple sclerosis, IFN-b therapy should be administered frequently at the highest tolerable and, thus, most effective dose.
The mechanism of action of human IFN-b in the treatment of multiple sclerosis has not been firmly established but may more likely be mediated by an immunosuppressant rather than antiviral effect. Human IFN-b has traditionally been used in the treatment of multiple sclerosis, and human IFN-a has been used in the treatment of chronic hepatitis B and C. There are no scientific reasons to believe that it will not work the other way around, but direct comparative studies of IFN-a versus IFN-b in the treatment of either hepatitis B or C or multi- ple sclerosis have, to the best of my knowledge, not been performed.
IFN-a, -b, and -g have been found, in vitro, to be effective in inhibiting the replication of the SARS coronavirus (SCV) [36] . IFN-a effectively inhibited SCV replication, but with a selec-tivity index 50-90 times lower than that of IFN-b. IFN-g was slightly better than IFN-a in Vero cell cultures but was completely ineffective in Caco2 cell cultures.
In vivo, prophylactic treatment of SCV-infected macaques with pegylated IFN-a was found to significantly reduce viral replication and excretion, viral antigen expression in type 1 pneumocytes, and pulmonary damage [37] . Pegylated IFN-a may, therefore, be considered a candidate drug for the prophylaxis and therapy of SARS.
Should smallpox ever pose a threat following a bioterrorist attack with variola virus [38] , IFN and its inducers, among many other compounds (such as cidofovir [23] ), may be considered as a possible means to counteract such an attack. In this perspective, we had already shown in 1968 [39] that IFN and its inducers are able to strongly act prophylactically against poxvirus infections. In the vaccinia virus tail lesion model in mice, IFN and PAA were able to markedly suppress poxvirusinduced lesions, the most remarkable finding being that a single injection of PAA, 4 weeks before challenge with virus, was able to significantly reduce the number of vaccinia virus-induced tail lesions (table 1) [39] .
The filoviruses, Marburg and Ebola, are classified as category A biowarfare agents by the US Centers for Disease Control and Prevention. Most known human infections with these viruses have been fatal, and no vaccines or effective therapies are currently available [40] . The filovirus disease syndrome resembles that caused by other hemorrhagic fever viruses, necessitating studies in a biocontainment laboratory to confirm the diagnosis. Some progress has been made in developing vaccines and antiviral drugs, but efforts are hindered by the limited number of maximum-containment laboratories.
As mentioned by Bray et al. [41] , the recombinant B/D chimeric form of human IFN-a has proven to be highly protective against Ebola virus in mice: a single dose given on the day of challenge only delayed death, but a 5-to 7-day course of the same dosage, begun on day 0, 1, or 2 after infection, was highly protective. However, a recent trial of IFN-a2b therapy in Ebola virus-infected cynomolgus monkeys resulted only in a delay in the onset of viremia, fever, and illness; all animals finally died of the infection [42] .
That IFN may be effective in the treatment of filovirus (i.e., Ebola virus) infections could be anticipated from our initial results [43] on the protective effects obtained with IFN and IFN inducers (such as PAA) in newborn mice infected with VSV, a rhabdovirus related to the filoviruses. In fact, VSV could be considered a surrogate virus of the filoviruses, in that anti-VSV activity may be predictive of activity against filoviruses. This premise has been borne out with S-adenosylhomocysteine hydrolase inhibitors such as 3-deazaneplanocin A (figure 7); on the basis of its activity against VSV [44] , it was tested in treating Ebola virus infections in mice, and a single dose protected the mice against a lethal challenge with Ebola virus [41] .
How might 3-deazaneplanocin A exert its antiviral action against Ebola virus in vivo? On one hand, 3-deazaneplanocin is a potent inhibitor of S-adenosylhomocysteine hydrolase [45] ; on the other hand, 3-deazaneplanocin has been shown to massively stimulate the production of IFN-a in Ebola virus-infected mice [46] . Considering the unequaled potency of doublestranded RNAs in inducing IFN, I hypothesize that, as an Sadenosylhomocysteine hydrolase inhibitor, 3-deazaneplanocin leads to the accumulation of S-adenosylhomocysteine, which, being a product and inhibitor of methyltransferase reactions using S-adenosylmethionine as methyl donor, will inhibit these methylation reactions, including those that are required for the 5 -capping of the viral mRNA [45] . In the case of negativestranded RNA viruses (such as Ebola), this means that the positive-stranded RNA (transcribed from the minus strand by the RNA replicase) is not processed and remains attached to the negative-stranded RNA, thus resulting in increased double-stranded RNA formation and, consequently, IFN induction. Further experiments should be undertaken to validate this hypothesis.
IFN-a2b, pegylated IFN-a2b, poly(I)7poly(C), and poly(I)7 poly(C 12 U) (Ampligen) have been evaluated against Modoc virus encephalitis in a mouse model of flavivirus infections. All compounds significantly delayed virus-induced morbidity (paralysis) and mortality (due to progressive encephalitis). Virus load was significantly reduced, by 80%-100%, in serum, brain, and spleen of mice that had been treated with IFN-a2b, pegylated IFN-a2b, poly(I)7poly(C), or Ampligen (figure 8) [47] . IFN and double-stranded RNA inducers of IFN may, therefore, be considered for further studies of their potential in therapy for or prophylaxis against flavivirus infections in humans.
Similarly, IFN and the double-stranded RNA inducers of IFN may seem promising candidate drugs for therapy for or prophylaxis against coxsackie B virus-induced myocarditis (figure 9) [48] . Ampligen, at 20 mg/kg of body weight/day, was found to reduce by 98% the severity of coxsackie B3 virus-induced myocarditis in mice, as assessed by morphometric analysis. When poly(I)7poly(C) was administered at 15 mg/kg/day, it reduced the severity of virus-induced myocarditis by 93%. IFN-a2b and pegylated IFN-a2b were less effective and reduced the severity of virus-induced myocarditis by 78% and 66%, respectively.
IFN-a (whether pegylated or not) has acquired a definitive place in the treatment of chronic hepatitis B and C, as has IFNb in the treatment of multiple sclerosis. Further potential indications for pegylated IFN-a and -b include SARS, and those for pegylated IFN-a and IFN inducers, such as poly(I)7poly(C) and poly(I)7poly(C 12 U) (Ampligen), include filovirus, poxvirus, flavivirus, and coxsackie B virus infections.
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Due to the current lack of fast and reliable testing, one of the greatest challenges for preventing transmission of SARS-CoV-2 is the ability to quickly identify, trace, and isolate cases before they can further spread the infection to susceptible individuals. As regions across the U.S. start implementing measures to reopen businesses, schools, and other activities, many rely on current screening practices for COVID-19, which typically include a combination of symptom and travel-related survey questions and temperature measurements. However, this method is likely to miss pre-symptomatic or asymptomatic cases, which make up approximately 40% to 45% of those infected with SARS-CoV-2, and who can still be infectious. 1, 2 An elevated temperature (>100 degrees Fahrenheit) is not as common as frequently believed, being present in only 12% of individuals who tested positive for COVID-19, 3 and just 31% of hospitalized COVID-19 patients at the time of admission. 4 Smartwatches and activity trackers, which are now worn by 1 in 5 Americans, 5 can improve our ability to objectively characterize each individual's unique baseline for resting heart rate, 6 sleep, 7 and activity and therefore can be used to identify subtle changes in that users data which may indicate that they are coming down with a viral illness. Previous research from our group has shown that this method, when aggregated at the population level, can significantly improve realtime predictions for influenza-like illness. 8 Consequently, we created a prospective app-based research platform, called DETECT (Digital Engagement & Tracking for Early Control, & Treatment), where individuals can share their sensor data, self-reported symptoms, diagnoses, and electronic health record data with the aim of improving our ability to identify and track individual and population level viral illnesses, including COVID-19.
A previously reported study that captured symptom data in over 18,000 SARS-CoV-2 tested individuals via a smartphone-based app found that symptoms were able to help distinguish between individuals with and without COVID-19. 2 The aim of this study is to investigate if the addition of individual changes in sensor data to symptom data can be used to improve our ability to identify COVID-19 positive versus COVID-19 negative cases among participants who selfreported symptoms.
Any person living in the United States over the age of 18 years old is eligible to participate in the DETECT study by downloading the iOS or Android research app, MyDataHelps. After consenting into the study, participants are asked to share their personal device data (including historical data collected prior to enrollment), report symptoms and diagnostic test results, and connect their electronic health records. Participants can opt to share as much or as little data as they would like. Data can be pulled in via direct API with Fitbit devices, and any device connected through Apple HealthKit or GoogleFit data aggregators. Participants were recruited via the study website (www.detectstudy.org), media reports, and outreach from our partners at reported at least one symptom (12.5%), and of those 54 also reported testing positive for COVID-19, and 279 reported testing negative for COVID-19. The number of days per different data types and data aggregator system is presented in Table 1 , while the symptoms distribution for symptomatic individuals tested for COVID-19, or not tested is shown in Figure 1 .
The protocol for this study was reviewed and approved by the Scripps Office for the Protection of Research Subjects. All individuals participating in the study provided informed consent electronically.
Only participants with self-reported symptoms and COVID-19 test results were considered in this analysis. For each participant, two sets of data were extracted: the baseline data, which included signals spanning from 21 to 7 days before the reported start date of symptoms, and the test data, which included signals beginning the first date of symptoms to 7 days after symptoms.
Three types of data were considered from personal sensors: daily resting heart rate (DailyRHR), sleep duration in minutes (DailySleep) and activity based on daily total step count (DailyActivity). The daily resting heart rate is calculated by the specific device. 35 The total amount of sleep for a given day was based on the total period of sleep between 12 noon of the current day to 12 noon of the next day. When multiple devices from the same individual provide the same information, Fitbit device data was prioritized for consistency. Overlapping data were combined minute by minute, before aggregating for the whole day.
A single baseline value per individual was extracted for each data type by considering the median value over the individual's baseline data. This value is representative of a participant's "normal" before the reported symptoms. The baseline value was compared to the test data as follows:
The symptoms distribution for symptomatic individuals tested for COVID-19, or not tested is shown in Figure 1 .
A minority of symptomatic participants (30.3%) who tested for COVID-19 had an RHR greater than 2 standard deviations above the average baseline value during symptoms. Change in RHR on its own (Table 1) To evaluate the contribution of all the data type commonly available through personal devices, we combined the RHR, sleep, and activity metrics in a single metric (SensorMetric, Figure 2 .d).
This improved the overall performance from the three sensor metrics to an AUC of 0.72 [0.64 -0.80].
We also considered a model only based on self-reported symptoms (SymptomMetric, Figure 2 .e), along with age and sex. With respect to the previously published model, 2
When participant-reported symptoms and sensor metrics are jointly considered in the analysis (OverallMetric, Figure 2 .f), the achieved performance was significantly improved (p < 0.01), relative to either alone, with an AUC of 0.80 [0.73 -0.86].
Our results show that individual changes in physiologic measures captured by most smartwatches and activity trackers are able to significantly improve the distinction between symptomatic individuals with and without a diagnosis of COVID-19 beyond just symptoms alone. While encouraging, these results are based on a relatively small sample of participants.
This work builds on our earlier retrospective analysis demonstrating the potential for consumer sensors to identify individuals with influenza-like illness, which has subsequently been replicated in a similar analysis of over 1.3 million wearable users in China for predicting COVID-19. 8, 9 In response to the COVID-19 pandemic a number of prospective studies, led by device manufacturers and/or academic institutions, including DETECT, accelerated deployment to allow interested individuals to voluntarily share their sensor and clinical data to help address the global crisis. [10] [11] [12] [13] [14] The largest of these efforts, Corona-Datenspende, was developed by the Robert Koch Institut in Germany and has enrolled over 500,000 volunteers. 15 As different individuals experience a wide range of symptomatic and biologic responses to infection with SARS-CoV-2, it is likely that their measurable physiologic changes will also vary. [16] [17] [18] For that reason, it is possible that biometric changes may be more valuable in identifying those at highest risk for decompensation rather than just a dichotomous distinction in infection status. Due to limited testing in the United States, especially early in the spread of the COVID-19 pandemic, individuals with more severe symptoms may have been more likely to be tested. Consequently, the ability to differentiate between COVID-19 positive and negative cases based on symptoms and sensor data may change over time as testing increases, and as other upper respiratory illnesses such as seasonal influenza increase this fall.
The early identification of symptomatic and pre-symptomatic infected individuals would be especially valuable as transmission is common and people may potentially be even more infectious during this period. [19] [20] [21] Even when individuals have no symptoms, there is evidence that the majority have lung injury by CT scan, and a large number have abnormalities in inflammatory markers, blood cell counts and liver enzymes. 18, [22] [23] [24] As the depth and diversity of data types from personal sensors continues to expand-such as heart rate variability (HRV), respiratory rate, temperature, oxygen saturation, and even continuous blood pressure, cardiac output and systemic vascular resistance-the ability to detect subtle individual changes in response to early infectious insults will potentially improve and enable the identification of individuals without symptoms.
In the past, the normality of a specific biometric parameter, such as resting heart rate, duration of nightly sleep, and daily activity, was based on population norms. For example, a normal RHR is generally considered anything between ~60-100 BPM. However, recent work looking at individual daily RHRs over two years found that each person has a relatively consistent RHR, for them, that fluctuates by a median of only 3 BPM weekly. 6 DETECT, and similar studies, also represents the transitioning of research from a dependence on brick and mortar research centers to a remote, direct-to-participant approach now possible through a range of digital technologies, including an ever-expanding collection of sensors, applications of machine learning to massive data sets, and the ubiquitous connectivity that enables rapid 2-way communications 24/7. 27, 28 The promise of digital technologies is that their evolution will continue to bring us closer to identifying the best combination of measures and associated algorithms that identify infection with SARS-CoV-2 or other pathogens. However, it is equally critical to develop and continuously improve on an engaging digital platform that provides value to participants and researchers. This has proven to be extremely challenging with a recent analysis of 8 different digital research programs involving 100,000 participants have a median duration of retention of only 5.5 days. 29 Digital trials such as DETECT also do come with unique challenges to assure privacy and security, which can only be dealt with by effectively informing participants before consent, storing the data with the needed level of security and providing access to the data only for research purposes. 30 App-based contact tracing, which is not part of DETECT, is an especially sensitive and ethically complicated use of digital technology that can be used to address the pandemic. 31
Our analyses are dependent entirely on participant-reported symptoms and testing results, as well as the biometric data from their personal devices. Although this is not consistent with the historically more common direct collection of information in a controlled lab setting or via electronic health records, previous work has confirmed their value and their accuracy beyond data routinely captured during routine care. [32] [33] [34] Additionally, individuals owning a smartwatch or activity tracker and having access to COVID-19 diagnostic testing may not be fully representative of the general population. Finally, in the early version of the DETECT app we
were not able to track the duration or trajectory of individual symptoms, care received and eventual outcomes.
These preliminary results suggest that sensor data can incrementally improve symptom-only based models to differentiate between COVID-19 positive and negative symptomatic individuals, which has the potential to enhance our ability to identify a cluster before more spread occurs. Such orthogonal, continuous, passively captured data may be complementary to virus testing that is generally a one-off, or infrequent, sampling assay.
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The connection between body and mind shows well in the placebo effect (1) . In response to a placebo, positive expectations can lead to better health outcomes.
Conversely, there will be a nocebo effect if negative expectations lead to harms (2) . For example, fake surgery in orthopedics can relieve the pain just as much as its "real" variant (3) . It is important that those studies are conducted double-blind: neither the researchers nor the participants know who gets which treatment. Clinical studies with an informed consent that contains too much information about possible disadvantages can undermine the double-blind nature of the study. Participants who discover that they are receiving placebo have lower expectations for improvement (4) .
In infectious diseases, such as after infection with the new SARS-CoV-2 virus, the body reacts with an immune response. The extent to which this happens successfully, determines its cure. The wisdom Mens sana in corpore sano implies that a healthy mind also drives a better immune response. There is a lot of evidence for this immunological mind-body connection; psychological stress was associated in a dose-response manner with an increased risk of acute infectious respiratory illness (5) . Psychological well-being led to better survival in patients with cardiovascular disease or after infection by the human immunodeficiency virus (6) . More than 30 years of research on psychoimmunology shows that the mind influences all important immunological 4 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted June 7, 2020. . https://doi.org/10.1101/2020.06.05.20123018 doi: medRxiv preprint parameters (7) . It is therefore no surprise that vaccines work more effectively in psychologically healthy people (8) .
A very large sampled UK study showed that COVID-19 related deaths are associated with various risk factors: aged 70 or older, poverty, immunosuppressive conditions, cardiovascular disease, diabetes, obesity and being male (9) . Unfortunately, mental health factors such as anxiety, depression or substance use were not investigated. This leaves a gap in our knowledge.
This research aims to investigate the potential influence of mental health as a protective factor for COVID-19 related mortality in the general population. For the completeness and estimation of the relative importance, we incorporated some important risk factors associated with COVID-19 related survival such as older age, diabetes, cardiovascular disease and obesity.
A mentally healthy (MH) population is defined as the proportion of a countries population free from mental or substance use disorders. Along with other risk factors (cardiovascular disease, obesity, diabetes), the Global Burden of Disease report 2017 provided the data (10) . Because age stratification differs across countries, age-standardized estimates were taken. Totals of COVID-19 related survival (TCS) was estimated from publicly reported situational reports of countries as of end of May 2020 (11) . The final dataset included any country with data on psychological well being.
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The copyright holder for this preprint this version posted June 7, 2020. .
We calculated means and standard deviations for every variable, performed Shapiro and Wilk's W test to assess normal distributions, plotted histograms and normal plots (see plots in Appendix 1). We calculated the correlation coefficient to measure the degree of association. We did not perform the hypothesis test as the variables were not observed on a random sample; therefore also the 95% confidence interval was not calculated. However, to have some idea of estimate uncertainty, we did calculate a 95% CI for the main analysis: the correlation between mentally healthy rates and COVID-19 related survival rates. Variables were not normally distributed, so we used Spearman's rank correlation. It also allowed us to assess not linear association but a more general association. We calculated 100 2 , the percentage of the variability of the data that is explained by the association of the two main variables.
We explored inter-relationships among other variables too: aged 70 or older, cardiovascular disease, obesity and diabetes. A correlation matrix stated the value along with the number of observations. We plotted scatter matrix diagrams to visually inform an underlying trend.
Across 181 countries, the mean total COVID-19 related survivors per million was 999,955 (sd=120), median=999,995. The test of normality resulted in p-value < 6 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted June 7, 2020. . 0.001; the mean mentally healthy per 100,000 was 85,411 (sd=1,871), median=85,634. The test of normality resulted in p-value < 0.001 (Table 1) . is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted June 7, 2020. Table 2 8 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted June 7, 2020. In line with other research (in decreasing order); populations aged 70 or older, obesity and cardiovascular disease were the drivers worsening COVID-19 related survival. Our results did not confirm that diabetes is a risk factor (9,12,13) .
We found a weak to moderate association between mentally healthy populations and lower rates of obesity. This finding confirms results from a 13 countries survey, that found statistically significant obesity-mental disorder associations (14) .
This is the first study to assess the potential association between mental healthy populations and their chance of COVID-19 related survival. Thanks to the Global Burden of Disease study, we could cover mental health of 181 (93%) countries worldwide. All analyses were underpinned by scientific rationale and were performed using appropriate statistical methods.
Clearly, the external validity of findings to individual countries is limited. Findings should be interpreted cautiously because of the risk of confounding. Mental health data stemmed from 2017, so they do not describe prevalences today.
. CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted June 7, 2020. . https://doi.org/10.1101/2020.06.05.20123018 doi: medRxiv preprint However, we assumed that prevalences for mental disorders and substance use have remained fairly constant up to this day in most countries and therefore remain a valuable proxy for the current mental health rates. Still, the COVID-19 pandemic has lowered mentally healthy populations in some countries (15) (16) (17) ; but exactly how more data from other countries would alter our findings remains to discover. Attribution of death to a specific cause is often challenging and definitions of "COVID-19 death" vary across countries and sometimes even change within countries over time. Overall, some COVID-19 deaths may be missed, and others may be overcounted.
Many countries have policies that focus solely on the viral components of the COVID-19 pandemic. The emphasis lies on strictly physical factors in the prevention and approach. However, we were able to demonstrate that there is a weak link between psychologically healthy populations and a protection against COVID-19 related death. It is too early to make interventions based on this study only. However, the prudence principle applies: it is important to give preventive attention to a mentally healthy population in order to strengthen the chances of survival after viral contamination. Particular attention also seems to be needed for the overweight population. We found that they experience reduced mental health. A synergistic effect could occur so that their chances of COVID-19 survival further decrease. 1 in 7 people on this planet suffer from poor mental health or substance use and its association with covid-19 related survival makes improved mental health strategies urgently needed.
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Government agencies have the responsibility to make the large amounts of data, especially through primary care, available for research communities to better tackle the COVID-19 crisis. Doing so, individual patient data study would allow more valid and -if done on a large scale-also more precisely estimate the impact of mental health on COVID-19 survival.
Across 181 countries, a weak association was found between mentally healthy populations and COVID-19 related survival. This relationship explained between 2.6 and 18.5% of COVID-19 related survival. Sharing of patient mental health data would allow better understanding of the psychoimmunology of infectious diseases.
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The 27th Annual International Mammalian Genome Conference (IMGC) was held at the historic Colegio Fonseca in the beautiful city of Salamanca, Spain, between 15 and 18 September 2013. Organised by Elena de la Casa Esperon, Lluis Montoliu, Fernando Pardo-Manuel de Villena and Jesus Perez-Losada, the meeting attracted 148 scientists from 14 countries around the world. The conference commenced with a bioinformatics workshop and student satellite symposium followed by a welcome reception with tapas, a wonderful opportunity to savour local delicacies. The main meeting was divided into 11 sessions encompassing a wide array of topics including ageing and adult-onset disease modelling, human disease models, comparative genomics, population genetics and evolution, advances in genome manipulation, stem cells and development, and large-scale resources. The Verne Chapman lecture was given by Nancy Jenkins from the Methodist Hospital Research Institute, Houston, Texas. Following a fantastic four days of science, the conference came to a close with dinner at the historic Castillo del Buen Amor. Abstracts from the meeting are available online at www.imgs.org.
The conference began with the student satellite symposium with 16 talks from undergraduate students, PhD students and early post-doctoral researchers, with topics ranging from host response to viral infection to whole-genome ENU mutagenesis. Abstracts for student presentations are available at www.imgs.org. Sarah Leist (SO-9) presented her work using the collaborative cross (CC) to analyse the host response to influenza A virus infection. The theme of immunity was continued by Rashida Lathan (SO-13), who investigated the role of the innate immune response in mice resistant to rift valley fever. Several of the talks focused on sex chromosomes and meiotic recombination: for example, the work presented by John Calaway (SO-2) demonstrated multiple functional alleles for X-chromosome inactivation choice in mice, while Courtney Vaughn (SO-3) described the utilisation of immunostaining and chromosomal painting in the comparison of meiotic recombination rates. Other talks focused on the utilisation of the mouse as a model system for the analysis of human disease, including reports from Adrian Blanco Gomez (SO-10) using an Erbb2 breast cancer model to identify tumour genetic variants in response to anthracyclines and taxanes, and from Irfan Jumabhoy (SO-14) on the integration of mouse and human gene expression analysis in the pathogenesis of major depressive disorder. Morag Lewis (SO-15) explored regulatory networks in the developing inner ear in mice with mutations in Mir96, which cause deafness in both humans and mice. Elizabeth Adams (SO-5) characterised tissuespecific knockouts of Sec24c to define the role of this COPII component in mice. Maria del Mar Saez-Freire (SO-6) and Chen-Ping Fu (SO-8) both described the use of system biology approaches to further our understanding of murine genetics. Maria del Mar Saez-Freire used systems biology to identify commonalities between breast cancer and ageing using the C57BL/6 breast cancer-resistant strain and the FVB-susceptible mouse strain that overexpress cNeu under the MMTV promoter, while Chen-Ping Fu described her work utilising the MegaMUGA genotyping array to infer founder probabilities in admixed animals.
The four students judged to have given the best presentations were honoured with inaugural Lorraine Flaherty Awards, which included the opportunity to present their work during a plenary session in the main meeting. Andrew Bard (Wellcome Trust Sanger Institute, SO-7) presented his analysis on misexpressed olfactory receptor genes identified through RNA sequencing, qPCR and in situ hybridization. In vivo and in vitro approaches were conducted to screen candidate odour molecules and pheromones from animal excretions to identify ligands that activate the receptors. Benjamin Gamache (National Cancer Institute/National Institutes of Health, SO-12) described his research, targeting conserved multiple melanoma and murine plasmacytoma (PCT) with a drug combination. The combination reduced tumour burden and volume and led to increased survival rates in C57BL/6-Bcl2l1 mice. A distinct module of 126 genes that were cooperatively affected by both drugs was identified, and an Ingenuity upstream analysis showed that MYC is a potential core regulator of the synergistic transcriptional response. Andrew Morgan (University of North Carolina, SO-4) presented his work on the role of sex and genetic background on mammalian recombination in the CC. He showed that recombination rates are significantly concentrated at telomeres in male meiosis and that this indicates a temporally regulated sequence of events with recombination progressing from telomeres to centromeres in the male germline. Kart Tomberg (University of Michigan, SO-16) presented identification of a novel suppressor region for lethal thrombosis in the factor V Leiden mouse model. Through application of a sensitised whole-genome ENU mutagenesis screen, she identified a nonsynonymous single nucleotide variant in the Actr2 gene and a 6-Mb region on chromosome 3 which segregated with survival.
This year 77 posters were presented in two lunch-time sessions at the meeting. To provide all participants with the opportunity to present their data at the main meeting, all poster presenters were invited to partake in the 'Come see my poster session'. Each presenter was given one minute and one slide to promote their research and to encourage attendees to view their poster. Six young scientists were presented with awards for their poster presentations (Table 1) : Sonia Castillo-Lluva (P-15) described the role of Snai2 in different stages of breast cancer evolution; Lesley Everett (P-23/SO-11) provided insights into coagulation factor V and VIII secretion through analysis of Lman1deficient mice; Hazuki Takahashi (P-32/SO-1) presented characterisation of SINEUPs, a novel antisense noncoding RNA that can upregulate protein translation through a SINE element; Leandro Batista (P-5) presented his QTL analysis on the host's susceptibility to rift valley fever in mice; Okumura Kazuhiro (P-36) used Japanese wild derived inbred mouse strain, MSM/Ms to identify skin tumour modifier genes; and Hiromi Miura (P-44) presented the advantages and limitations of pronuclear injectionbased targeted transgenesis in the generation of knockdown mice. Abstracts from the poster presentations are available at www.imgs.org.
The first plenary session of the meeting focused on ageing and adult-onset disease modelling. Neal Copeland (The Methodist Hospital Research Institute, O-1) began the session with a lecture describing his group's efforts to identify drug targets that function in synergy with drugs targeting BRAF V600E melanoma. To elucidate this, they utilised a Sleeping Beauty transposon mutagenesis screen to successfully identify 1,232 melanoma candidate cancer genes. Kent Hunter (National Cancer Institute/National Institutes of Health, O-2) continued the oncogenic thread by investigating the mechanisms responsible for progression of metastatic disease. He described a susceptibility screen to identify polymorphic genes that influence the development of metastases in 26 different inbred mouse strains, and successfully identified a susceptibility gene for oestrogen receptor-negative breast cancer that mapped to the distal end of chromosome 6. Jesus Perez-Losada (Instituto de Biologia Molecular y cellular del Cancer, Universidad de Salamanca, O-4) presented work aiming to treat breast cancer in a more personalised manner. With the help of a backcross population of mice, he showed that it was possible to dissect different clinical pathophenotypes and identify the networked connections at the level of RNA expression, cell signalling and metabolic processes. Beverly Mock (National Cancer Institute/National Institutes of Health, O-29) demonstrated that mice, which spontaneously develop thymic lymphoma (due to constitutively active Akt), show a delay in tumour development and increased lifespan upon reducing expression of Mtor. Linda Siracusa (Thomas Jefferson University, O-31) showed how genetically similar strains of mice which differ in their susceptibility to an inherited polyposis that frequently leads to cancer can be used to identify genetic modifiers. Karlyne Reilly (National Cancer Institute/National Institutes of Health, O-32) completed the cancer-themed presentations by describing a locus that provides a male-specific modifier of susceptibility to glioma. This provides an excellent example of a genetic variant contributing to cancer susceptibility in a sex-biased manner, and could explain the fact that glioma is three times more likely to occur in males than females.
Several other talks in the plenary session on age-related disease focused on specific organ systems. Ron Konstanje (The Jackson Laboratory, O-3) reported a decline in renal function with age associated with mesangial matrix expansion (MME). To elucidate the underlying genetic basis, he described a genome-wide association mapping study using inbred mouse strains and identified a sequence within the 5'UTR of Far2 that resulted in a two-fold increase in the expression levels of the gene in mice with MME, thus identifying a novel pathway involved in agerelated kidney disease. Elisabeth Lodder (Academic Medical Center, Amsterdam, O-9) reported the mapping of a genetic network-modulating collagen deposition in mouse left ventricular (LV) myocardium. She combined empirical data of collagen amounts with genome-wide genotype and expression data, which resulted in the identification of collagen-QTLs (cQTLs) and underlying expression QTLs (eQTLs). Paul Potter (MRC Harwell, O-6) gave a brilliant overview on the Harwell ageing mutant screen, the first largescale project focusing on ageing phenotypes in mice. He gave a glimpse into how screens like this will contribute to the understanding of the interaction between genetic variation and pleiotropic effects of ageing. Assays covering the fields of diabetes and metabolism, behaviour, bone analysis, renal function, cardiac disease, liver function and sensorineural and clinical chemistry screenings are all being performed. Bridging from theory directly to application, Steve Brown (MRC Harwell, O-7) gave an impressive insight into his work on hearing-loss phenotypes arising from the Harwell ageing mutant screen. To date, 95 pedigrees have completed the auditory screening platform of which five show late-onset hearing loss. Two of these have undergone mapping and whole-genome sequencing, revealing distinct and novel genes for agerelated hearing loss.
Expanding on the theme of environmental influence on phenotype, Lisa Tarantino (University of North Carolina, O-8) used a cross between C57BL/6J and NOD/ShiLtJ mice to investigate the consequence of dietary deficiency during gestation on adult behaviour. Surprisingly, many behaviours remained largely unaffected, although changes were seen in novelty-induced locomotor activation and anxiety-related traits. Deb Cabin (McLaughlin Research Institute, O-5) presented her research to investigate the impact of every differing amino acid in the mouse and human alpha synuclein (SNCA) gene to determine their influence on pathogenicity. This work identified two variants that cause the development of synucleinopathies in mice, similar to the human A53T Parkinson's disease mutation.
The Verne Chapman lecture, entitled 'Harnessing transposons for cancer gene discovery', was delivered by Nancy Jenkins (The Methodist Hospital Research Institute, Houston, Texas). In a splendid overview of her careerspanning collaboration with Neal Copeland, she guided the audience through their use of a powerful insertional mutagenesis system based on the Sleeping Beauty (SB) family of transposons. By investigating the SB insertion site in melanomas with an inducible Braf mutation, it has been possible to identify over 1,000 candidate genes linked to cancer. Importantly, over 500 of these genes are enriched in mutations in human melanoma samples, suggesting that this approach offers clinically relevant insights into cancer genetics. Another thread of Jenkins' lecture was the combined mapping of genomic and metabolomic data to unravel metabolic pathways disrupted in hepatocellular carcinoma. The lecture concluded with an encouraging outlook: the intersection of cancer models with the rapid progress in cloning and sequencing technologies will ultimately aid the design of more effective treatment strategies for the plethora of human cancer forms.
The keynote lecture was presented by Paola Bovolenta (Spanish National Research Council, Madrid, Spain). Entitled 'Secreted frizzled related proteins: from development to neurodegeneration', she reviewed her work using the mouse ocular system (in particular the neural retina) to investigate the role of secreted frizzled related proteins in neurogenesis. In particular, she focused on the Sfrp1 -/and Sfrp2 -/mouse models with skeletal and facial defects and morphological abnormalities in the eye, and showed via ADAM10 and amyloid precursor protein the possibility of utilising Sfrp1 levels as an early marker for Alzheimer's disease.
An ongoing theme throughout the meeting was the growing use of the CC. The use of inbred mice presents a limitation, particularly in biological systems in which diversity is essential, like the immune system. The CC resource allows one to circumvent these problems, while still retaining genotypic control for reproducibility. Lisa Gralinski (University of North Carolina, O-12) utilised the CC mice to identify Trim55 as a novel contributor to SARS-CoVinduced vascular cuffing. In a large phenotypic screen using inbred-derived outbred rats (similar to the CC resource in mice), Amelie Baud (Wellcome Trust Centre for Human Genetics, O-18) provided an overview of how large-scale sequencing and informatic analysis is particularly useful in the search for genes regulating complex traits. She identified variants contributing to 31 different phenotypes, and furthermore that a number of phenotypes require the contributions of multiple QTLs. In a similar vein, Jianan Tian (University of Wisconsin-Madison, O-17) reported the identification and fine-mapping of a trans-eQTL hotspot in diabetic leptin knockout mice.
As is traditional at IMGC meetings, a number of presentations focused on mouse models generated by ENU mutagenesis. Simon Foote (Macquarie University, O-14) described a large-scale ENU screen for genetic attenuators of malaria through manipulation of the host. His screen opens up a number of possibilities for host-directed antimalarial therapies to mimic these genetic resistance mechanisms. Karen Svenson (The Jackson Laboratory, O-15) also made use of an ENU screen to look for genes affecting triglyceride levels, while her colleague, Laura Reinholdt (The Jackson Laboratory, O-41), identified an ENU-induced missense mutation in Kif18a that results in mitotic arrest in the developing germ line. Jabier Gallego (Seattle Children's Research Institute, O-36) examined the effects of DNA repair defects on the efficiency of ENU mutagenesis. One limitation of ENU is the achievable mutation frequency, which is approximately one sequence change for every million bases. By treating mice containing a mutation in the DNA repair enzyme Msh6 with ENU, he was able to show an increase in mutation frequency, thus increasing the efficiency of DNA mutagenesis to generate new disease models.
A consistent theme of the meeting was the utilisation of mice as excellent models for a diverse range of human diseases. Klaus Schughart (Helmholtz Centre for Infection Research, O-10) provided an overview of his group's studies into differing susceptibility to Influenza A infection in mouse knockouts of various genes, including the wellstudied Rag2, interferon-induced genes and proteases. Most mutants were more susceptible, but Tmprss2-deficient mice were highly resistant to infections with H1N1 virus. A new model of retinal degeneration Slc9a8 was presented by Ian Jackson (MRC Human Genetics Unit, University of Edinburgh, O-27), which was shown to be due to misregulation of endosomal pH in the retinal pigment epithelium. Monica Justice (Baylor College of Medicine, O-30) described a spectacular study, screening for attenuators of the Mecp2 null phenotype in a mouse model of Rett Syndrome. Her results highlighted a link between cholesterol synthesis pathways and Rett Syndrome disease pathogenesis. This work has direct clinical applications, as many drugs targeting this pathway already exist. Moreover, it raises the tantalising possibility that neurodevelopmental disorders may be treatable. David Beier (Seattle Children's Research Institute, O-40) presented characterisation of defects in Nek8-deficient mice showing abnormal specification of developmental patterning, polycystic kidney disease and impaired response to replication stress. Rami Khoriaty (University of Michigan, O-28), however, raised a note of caution in interpreting mouse models of human disease. He gave a fascinating talk on how and why phenotypes for mice and humans carrying Sec23b mutations appear so different. Using an elegant series of tissuespecific knockouts, he showed that the difference is at least partly due to a shift in the tissue-specific functions of SEC23B during evolution.
Advances in bioinformatic analysis highlight the importance of murine models in analysing genetic variations associated with disease in the human population. Jim Crowley (University of North Carolina, O-22) used highthroughput RNA sequencing (RNAseq) analysis to show that pervasive regulatory variation underlies complex genetic traits in mice. Richard Mott (Wellcome Trust Centre for Human Genetics, O-24) examined the scope of parent of origin effects in complex traits using outbred mice and identified 21 non-imprinted genes with parent of origin effects impacting on hippocampal expression. Steven Munger (The Jackson Laboratory, O-23) reported bespoke Seqnature software that constructs individualised transcriptomes for RNAseq read mapping from F1 hybrid mice. He showed that alignment of RNAseq reads to individualised diploid transcriptomes, increases read mapping accuracy, improves transcript abundance estimates and corrects erroneous biases.
Significant deviation from expected Mendelian inheritance ratios (transmission ratio distortion, TRD) has been observed in both plants and animals. TRD can have significant effects on allelic frequency, including fixation of an allele via selective sweep. John Didion (University of North Carolina, O-26) reported extreme TRD of chromosome 2 in the CC and diversity outbred (DO) populations in favour of a wild-derived allele, WSB/EiJ. He presented evidence that the observed TRD was caused by a novel female meiotic drive system in mice, which has given rise to a selective sweep in the DO in the absence of changes in organismal fitness. He also showed that the meiotic drive system is under genetic control of unlinked modifier alleles. John Didion was presented with the Verne Chapman award for outstanding oral presentation by a student or postdoctoral researcher (Table 1) .
The plenary session on genome manipulation highlighted some new technologies in genetic engineering, with a particular focus on increasing efficiency. Edward Ryder (The Wellcome Trust Sanger Institute, O-33) described a system for recombining LoxP sites, using a cell-permeable cre recombinase in place of traditional CMV-cre systems in early mouse embryos. This method resulted in rapid allelic conversion at high frequency and minimised the use of experimental animals, resulting in a significant reduction in cost and time. In addition, Cristina Vicente Garcia (Centro Nacional de Biotecnologia, Spanish National Research Council, presented the utilisation of biological algorithms in the identification of genomic insulators, and it is hoped that this will aid understanding of genomic organisation and gene transfer technologies.
From this year's host country, Davide Seruggia (Centro Nacional de Biotecnologia, Spanish National Research Council, O-34) identified two chromatin insulators in the mouse genome located in between three differentiallyexpressed genes: Nox4, Tyr and Grm5. He went on to examine the ectopic functionality of the mouse Tyr insulator using chromosome conformation capture (3C). The presentation concluded with an introduction to the exciting prospect of CRISPRs/Cas9 genome editing technology, as they attempt to engineer nucleases to produce targeted inactivation of Tyr insulators.
Meiotic recombination was a major topic during the final day of the conference, with a focus on Prdm9 and its high mutability rate. Laia Capilla (Institut de Biotecnologia i Biomedicina, Universitat Autonoma de Barcelona, O-38) used the Barcelona Robertsonian mice to analyse meiotic recombination and Prdm9 genetic variability. This wild house mouse population exhibits natural variation in the number of diploid chromosomes, providing a model organism for comparative recombination events. Petko Petkov (The Jackson Laboratory, O-37) analysed mice with various combinations of Prdm9 alleles to examine the underlying cellular mechanisms of hotspot sites of recombination, suppression and quantitative regulation. Christopher Baker (The Jackson Laboratory, O-39) examined the role of PRDM9 modification in hotspot chromatin organisation and showed that PRDM9-trimethylated nucleosomes are organised in a symmetrical manner around a central nucleosome-depleted region. Furthermore, meiotic crossing over is constrained here, further displaying an integral role of Prdm9 in meiotic recombination events. Zdenek Trachtulec (Institute of Molecular Genetics of the ASCR, Prague, O-25) also utilised the Prdm9 allele to determine the compatibility of Prdm9 alleles in (PWD x B6) F1 sterile hybrids.
The mammalian genetics community is well served by a number of large collaborative resources. In the final session of the meeting, updates were provided on the status of several ongoing projects. Thomas Keane (Wellcome Trust Sanger Institute, O-44) discussed the second phase of the Mouse Genomes Project (http://www.sanger.ac.uk/mouse genomes/), an effort to sequence the genomes of 17 inbred mouse strains. Having catalogued the genetic variation in the strains, they are now beginning to assemble complete genomes using long-range optical mapping. Gary Churchill (The Jackson Laboratory, O-43) introduced the DO population, a stock of mice derived from the eight founder strains of the CC that have been outbred for 14 generations. This multi-founder cross not only promises to provide a high-resolution resource for genetic mapping of complex traits, but also offers unique challenges for analysis. Daniel Gatti (The Jackson Laboratory, O-47) described an analytical pipeline to reconstruct the individual DO genomes from microarray data, enabling the mapping of phenotypes to candidate gene lists. Michael Dobbie (The Australian Phenomics Facility, The Australian National University, O-45) presented a new library of missense and nonsense alleles in the mouse (The next-gen mouse and the missense mutation library) and its utilisation in delivering new resources to further understanding of human disease. The international mouse phenotyping consortium (IMPC, http:// www.mousephenotype.org/) was represented by Hugh Morgan (MRC Harwell, O-46), a self-described 'datawrangler', who is part of the team responsible for analysing and annotating the vast amount of data being generated from the standardised phenotyping of knockout mice. Carol Bult (The Jackson Laboratory, O-48) described KOMP2 and the utilisation of KOMPute, a computational prediction of gene function and phenotypes. Elizabeth Bryda (University of Missouri-Columbia, O-42) took the theme away from mouse models and provided invaluable information regarding the rat resource and research centre.
The 28th IMGC is being organised by Karen Svenson and Ron Korstanje and will be held in Bar Harbor, Maine on 26-29 October 2014. The Verne Chapman lecture will be presented by Nobel Laureate, Bruce Beutler, and other presentations by established and budding scientists from around the world promise to make this another exciting meeting focused on cutting-edge research in the fields of mammalian genetics and genomics.
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The Coronavirus Disease 2019 ("COVID-19") has emerged rapidly as a respiratory disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for an outbreak that took place in December 2019 in Wuhan, China [1] . Due to the highly contagious nature of this novel coronavirus, Hubei and other provinces in China have adopted several unprecedented measures to control the transmission of COVID-19 including the suspension of public transportation, restricted access to communities, closure of public spaces, and management such as hospitalization and isolation of confirmed and suspected cases [2] . Chinese residents living both in and outside Hubei had been required to stay at home to self-isolate since 27 January 2020. By 15 April 2020, this virus had reached a total of 213 countries, resulting in more than 1.9 million laboratory-confirmed infections and 120,000 deaths [3] . Consequently, more than 40 countries and areas including Italy and regions in the United States have started implementing similar lockdown and "shelter in place" measures as those in China since 1 April. Even though most supermarkets and grocery stores remain open during the isolation period, food supply as well as safe and adequate access to foods have become major concerns regarding the essential needs among the general populations due to the restrictions of transportation, self-reduction of outside activities, and lack of enough labor force, especially in areas severely affected by COVID-19. On 31 March, the United Nations stated that COVID-19 has threatened the food supply chain globally, and it is estimated that this situation may worsen in April and May [4] .
Foods contain essential nutrients and important phytochemicals that not only support basic biological functions in living organisms, but also exert protective and complementary effects on preventing and treating diseases including infections [5] [6] [7] . Although no nutrients have been scientifically proven to specifically benefit the prevention or treatment for COVID-19, a balanced and diversified diet is, undoubtedly, crucial in maintaining a properly functional immune system and providing sufficient nutrients for recovery [8, 9] . However, as above-mentioned, restriction in social activities and mobility impose potential barriers in people's access to food. On the other hand, when a stressful situation of this magnitude arises, people often experience substantial changes in their emotions, which may subsequently lead to modifications or development of some dietary behaviors such as seeking relief or cure from certain foods [10] . Those alterations in activities and behaviors during a pandemic period collectively influence and potentially impair food diversity. Currently, little is known about the dietary diversity during COVID-19 pandemic.
China has been experiencing a rapid growth of online food ordering and delivery services in recent years. According to "Chinese Restaurant Super Digital Time Insight 2020", in 2019, the total value of food delivery service reached 727.4 billion Chinese yuan [11] . Especially, in the recent self-isolation and "stay at home" time, online food shopping has gained in popularity because of its apparent role in reducing unnecessary person to person contact. In China, delivery services including food delivery have resumed since 28 January, and by early February, most delivery services have gone back to normal and cover most parts of China [12] . People are able to purchase not only processed foods like fast foods and restaurant takeout, but also fresh produce (i.e., fruits and vegetables), fresh meat, and grains via online food ordering and delivery services, thereby possibly increasing food accessibility. For this reason, proper measurements and evaluations are needed to investigate the potential benefits of this relatively novel and modern approach for food purchasing in maintaining dietary diversity during isolation time.
To the best of our knowledge, no study has reported on dietary diversity during isolation time in China and other areas. This study was conducted via a quick online survey to assess dietary diversity among Chinese residents during the time of isolation and "staying at home" due to COVID-19 and to explore its associated factors.
This cross-sectional study was composed of a questionnaire-based survey conducted in March via Chinese e-questionnaires using Wenjuan xing (Wenjuan xing Tech Co. Ltd., Changsha, China), a widely used online platform in China and distributed via the most common social media used in China "Wechat" (Tencent Inc. Shenzhen, China). A multistage sampling method was used. We purposefully selected and included people living in Hubei Province, the hard-hit area by COVID-19 outbreak in early 2020, China and people living in north, south, and central China. Then, the "snowball sampling" method was used to recruit more participants. To identify the respondents' attitude in completing the questionnaire, one question "Did you seriously look through the questions and answer the questions according to your actual situation" appeared in the middle part of the questionnaire. A total of 2021 Chinese residents participated in this survey. The inclusion criteria were (1) living in Mainland China, and (2) aged from 18-80 years old. The exclusive criteria were (1) people infected with COVID-19, (2) who have disease which impacts of normal eating, and (3) who did not seriously respond to the questions in this survey. After all the data had been collected, the final analysis included 1938 participants (people who did not seriously respond to the questions (n = 10), who were living outside Mainland China (n = 12), who were aged <18 y or >80 y (n = 55), who were infected with COVID-19 (n = 2), or who had missing data on key questions (n = 3) were excluded. One participant self-reported no food intake in the past several days was also excluded). The geographical distribution of participants is displayed in Figure 1 .
This cross-sectional study was composed of a questionnaire-based survey conducted in March via Chinese e-questionnaires using Wenjuan xing (Wenjuan xing Tech Co. Ltd, Changsha, China), a widely used online platform in China and distributed via the most common social media used in China "Wechat" (Tencent Inc. Shenzhen, China). A multistage sampling method was used. We purposefully selected and included people living in Hubei Province, the hard-hit area by COVID-19 outbreak in early 2020, China and people living in north, south, and central China. Then, the "snowball sampling" method was used to recruit more participants. To identify the respondents' attitude in completing the questionnaire, one question "Did you seriously look through the questions and answer the questions according to your actual situation" appeared in the middle part of the questionnaire. A total of 2021 Chinese residents participated in this survey. The inclusion criteria were (1) living in Mainland China, and (2) aged from 18-80 years old. The exclusive criteria were (1) people infected with COVID-19, (2) who have disease which impacts of normal eating, and (3) who did not seriously respond to the questions in this survey. After all the data had been collected, the final analysis included 1938 participants (people who did not seriously respond to the questions (n = 10), who were living outside Mainland China (n = 12), who were aged <18 y or >80 y (n = 55), who were infected with COVID-19 (n = 2), or who had missing data on key questions (n = 3) were excluded. One participant self-reported no food intake in the past several days was also excluded). The geographical distribution of participants is displayed in Figure 1 . [13] . Bubble size in the bubble plot represents the sample size of every investigation point.
The questionnaire contained four parts: socio-demographic characteristics, household food diversity, sources of the food (methods for purchasing or obtaining food), and specific dietary behaviors to cope with COVID-19.
The number of confirmed cases by 31 March in each province in China was obtained from the Distribution of COVID-19 Report that is accessible on the Chinese Center for Disease Control and Prevention website (imported cases not included) [13] . The isolation status (still working outside [13] . Bubble size in the bubble plot represents the sample size of every investigation point.
The questionnaire contained four parts: socio-demographic characteristics, household food diversity, sources of the food (methods for purchasing or obtaining food), and specific dietary behaviors to cope with COVID-19.
The number of confirmed cases by 31 March in each province in China was obtained from the Distribution of COVID-19 Report that is accessible on the Chinese Center for Disease Control and Prevention website (imported cases not included) [13] . The isolation status (still working outside home, self-isolation at home, close contact isolation, and infected with COVID-19) and frequencies of outside activities were also recorded.
We evaluated dietary diversity using Household Dietary Diversity Score (HDDS), a measure that reflects household food accessibility [8] . In total, the intakes of 12 food groups over the last 24 h (food eaten outside and at home) were investigated including (1) cereals; (2) roots and tubers; (3) vegetables; (4) fruits; (5) meat, poultry, and offal; (6) eggs; (7) fish and seafood; (8) pulses, legumes, and nuts; (9) dairy products; (10) oils and fats; (11) sugar and honey; and (12) miscellaneous such as condiments, snacks, and beverages. Values for each food group were assigned as "0" or "1", "0" for not-consumed and "1" for consumed in the last 24 h. Proportions of participants who consumed each food group were calculated. Also, the total scores of 12 groups were calculated for estimating the dietary diversity, which could range from 0 to 12. A higher score indicates a higher dietary diversity.
To investigate food sources during isolation time, we asked participants to select from four of the most common approaches to obtain or purchase different kinds of foods (12 food items in the HDDS) based on the ones that they had used. The four approaches were (1) using food stored in house before self-isolation; (2) purchasing food from traditional markets and grocery stores in person; (3) using online food ordering and delivery services (including purchasing both raw ingredients and prepared meals from restaurants); and (4) dependent on government-or community-based food distribution.
We also explored certain dietary strategies that participants adopted to cope with COVID-19 by using several "yes" or "no" questions such as "whether participants increased consumption of vitamin C, probiotics, any other kinds of dietary supplements, Chinese herbs, vinegar, and alcoholic beverages or not". In addition, one open question was used to identify any other previously unspecified foods consumed to cope with COVID-19.
Participants answered the questionnaire anonymously. Informed consent was obtained from participants who confirmed their willingness to participate voluntarily prior to the survey.
Data were analyzed using the software SAS version 9.4 (SAS Institute, Cary, NC). HDDS were presented as means ± standard deviation (SD) and median (25th, 75th percentiles) and were tested using the independent T-test and Variance analysis. The proportions of participants who consumed each food group in the last 24 h were presented as numbers (percentage). To explore the participants' behaviors in acquiring foods, we first calculated the propensity of choosing different approaches for obtaining or purchasing foods among our participants. For each food group, there were four pre-defined approaches (in-house storage, in-person grocery shopping, online shopping, or government and community-based food distribution programs) to obtain the food. We gave one point when participants purchased or obtained food from each food group with one of the four approaches. The total propensity score of utilizing each approach to obtain or purchase 12 groups of food for individual participants could range from 0 to 12. Based on the total propensity scores of each approach, major patterns of purchasing and obtaining foods were identified with the Hierarchical Cluster and K-means clustering method. We first randomly selected 30% of participants that were then used in the hierarchical cluster analysis to determine the proper number of clusters. Three clusters were identified by K-means cluster analysis. People in cluster 1 showed dependence on in-person grocery; people in cluster 2 depended on both in-person grocery and in-house storage; and people in cluster 3 showed more dependence on online food ordering and delivery services.
HDDS was divided into two groups based on its median (high (>=median) and low (<median) HDDS). Logistic regression was used to model the associations among HDDS, participants' characteristics, approaches for food purchasing/sourcing, and certain dietary strategies to cope with COVID-19. We adjusted for potential socio-demographic confounders (age, household average annual income, and geographic region) in the fully adjusted models. A p-value < 0.05 was considered statistically significant in all analyses.
The heat map of the geographical distribution of COVID-19 cases in Mainland China and the bubble plot of study sample sizes were created using R version 3.6.3 with the packages "ggplot2", "maptools", "rgdal", and "sp" [14] . The base map was obtained as a shape file from the National Fundamental Geographic Information System, China. Cumulative numbers of confirmed cases of the COVID-19 were calculated at the province (autonomous regions or municipalities directly under the central government included) level and coded with color. The lighter the color, the fewer the cases. Bubble sizes in the bubble plot proportionally represent the numbers of participants at each sampling point.
A total of 1938 participants were included in the analysis. The overall average HDDS was 9.7 ± 2.1, median (25th to 75th) is 10 (8 to 12). Proportions of participants who consumed each food group in the last 24 h are shown in Table 1 . The cereals group had the highest consumption, whereas the fish, legumes, and miscellaneous had relative low consumptions.
Compared to people aged above 45, those aged from 18-45 years have a diet with a lower diversity score. Living in urban areas was associated with a significantly higher HDDS than those living in rural areas. Meanwhile, the HDDS increased with family income ( Table 2 ).
During the isolation time, the most common food sources were in-house storage and in-person grocery shopping. The participants' choices of approaches to obtain or purchase foods during isolation are shown in Figure 2 . The most frequently purchased foods for in-person grocery shopping were fruits (80.1%), vegetables (77.2%), and eggs (71.8%). A total of 55.9% people used online ordering and delivery services at least once. Miscellaneous food (such as condiments, fast food, and snacks) (26.2%), fruits (26.2%), and dairy products (22.8%) were the most commonly purchased foods via online food ordering and delivery services, whereas oil and fats and sugar and honey were the least purchased.
During the isolation time, the most common food sources were in-house storage and in-person grocery shopping. The participants' choices of approaches to obtain or purchase foods during isolation are shown in Figure 2 . The most frequently purchased foods for in-person grocery shopping were fruits (80.1%), vegetables (77.2%), and eggs (71.8%). A total of 55.9% people used online ordering and delivery services at least once. Miscellaneous food (such as condiments, fast food, and snacks) (26.2%), fruits (26.2%), and dairy products (22.8%) were the most commonly purchased foods via online food ordering and delivery services, whereas oil and fats and sugar and honey were the least purchased.
There were 722 (37.7%) participants intentionally consumed dietary supplements, Chinese herbs, or specific foods because of COVID-19. A total of 31.2% of participants consumed various dietary supplements or Chinese herbs (18.2% for vitamin C, 11.7% for probiotics, 8.0% for other dietary supplements, and 9.6% for Chinese herbs) to cope with COVID-19. Meanwhile, there were 10.6% and 16.0% of participants who once purposely consumed alcohol and vinegar to cope with COVID-19.
HDDS was further divided into two groups based on its median value (HDDS = 10) and used as a binary outcome (<10 = 0 = low HDDS; >=10 = 1 = high HDDS). Logistic regression was used to explore the associations among HDDS and the factors listed in Table 3 . We found that people who lived in the places where laboratory confirmed COVID-19 cases were above 500 or in the Hubei Province had significant lower odds of high HDDS. Isolation status, frequencies of outdoor activities, and frequencies of going out to purchase food were not associated with HDDS. Based on K-means clustering analysis, participants were clustered into three groups. People in cluster 1 showed dependence on in-person grocery shopping for food; people in cluster 2 depended on both in-person grocery and in-house storage; and people in cluster 3 depended mostly on online food shopping. HDDS was not associated with dependences on different approaches to purchase food. Interestingly, people who reported adoptions of certain dietary behaviors to cope with COVID-19 had higher odds of being in the high HDDS group than people who did not report doing so.
As a declared Public Health Emergency of International Concern, COVID-19 has rapidly spread from Wuhan, Hubei to other parts of China and countries worldwide. This pandemic imposes enormous challenges on the health system, economy, and food supply globally and locally [4, 15] . Meanwhile, COVID-19 and subsequent measures to prevent its spread have substantially changed people's lifestyle. There have been several studies reporting on people's behaviors during pandemic such as consciously avoiding crowded places and wearing masks [16] . On the other hand, psychologically, people may feel anxious during outbreaks of infectious diseases, which impacts their sleep quality and other health related quality of life [17] . Nonetheless, there are not many, if any, studies that have examined dietary diversity during an epidemic or a pandemic. We believe that the current study is the first to report dietary diversity among Chinese residents during the COVID-19 pandemic period. Our study showed an overall good dietary diversity in the study sample, though there was a reduction in diversity in places where more COVID-19 cases were confirmed. To our best knowledge, this is also the first study to explore potential factors associated with dietary diversity in a pandemic. We found dietary diversity did not vary across different approaches to obtain or purchase foods, which provides evidence supporting that online food ordering and delivery services could achieve a similar dietary diversity as in-person groceries and in-house storage do. In addition, several specific dietary behaviors were identified during the COVID-19 outbreak and they contribute to higher odds of high dietary diversity.
To ensure a good nutritional status during lockdown, as early as 8 February, the National Health Commission of China published the "Dietary Guidelines for the Prevention and Treatment of Novel Coronavirus", which advocates a diverse diet for the general public [18] . The World Health Organization (WHO) recommends that "If you must stay at home, maintain a healthy lifestyle-including proper diet, sleep, exercise and social contacts" [19] . However, the degree to which people have followed these recommendations is unknown. In this study, we focused on dietary diversity and found an overall relatively high diet diversity (average HDDS = 9.7 ± 2.1, 25th to 75th were 8 to 12) when the "shelter in place" was in effect in China (the current study was carried out in March). This number is higher than the HDDS reported pre-COVID-19 in Indonesia (9.1), South Africa (8.0), and rural Cambodia (4.7) [20] [21] [22] . The HDDS is usually used to reflect food accessibility [8] . Access to food is a critical component of food security and plays a vital role in health and health disparities [23] . Several studies have demonstrated that the HDDS is inversely associated with the risk of malnutrition. For instance, one study in South Africa showed that children with high HDDS (>8) had a significantly lower wasting rate [21] . In Ethiopia, when the HDDS drops below four, adolescents are likely to suffer from underweight [24] . It is encouraging that the HDDS reported in the current study suggested an overall good food accessibility and low risk of malnutrition among the Chinese residents surveyed during the COVID-19 pandemic.
Among the 12 food groups assessed in the HDDS, fish, legumes, and miscellaneous foods had relatively low consumption during the last 24 h. Miscellaneous foods include most seasoning, snacks, beverage, and instant meals that can be highly processed. They tend to be deprived of essential nutrients, are energy dense, and are less healthy compared to freshly home-made meals [25] . Many studies have shown that the high consumption of such foods contributes to excessive weight gain and increased risks of chronic conditions such as cardiovascular diseases and obesity [26, 27] . These pre-existing conditions have been reported to increase the severity of COVID-19 infection and potentially worsen the disease outcome [28, 29] . Noteworthy, in our study, the consumption of miscellaneous food was relatively low (56.9% participants), which may lower the total dietary diversity score. However, as discussed above, low consumption of processed food may also bring potential health benefits. Further investigations are needed to measure the consumption of processed foods and its effects on health during disease outbreaks. Insufficient intake of fish and legumes in the Chinese population were also observed in a previous study conducted before the COVID-19 pandemic [30, 31] . However, due to cultural preferences in the Chinese population for fresh foods that are likely to be negatively affected by the lockdown policy, it is unsurprising that the intake of food like fish and seafood, whose tastes and flavor largely depend on the freshness of the raw materials, may decrease [32] . To improve the residents' access to fresh fish, Wuhan city implemented a working program to promote the consumption of fresh fish in every local community on 12 March [33] . Legumes including fresh beans, soybeans, and pulses provide fiber, protein, vitamins, minerals, and phytochemicals such as phytosterols that have been suggested to modulate immune system and exert protective effects against inflammation and oxidative stress [34, 35] . In addition, because legumes and fish are both excellent sources of high-quality protein and low in fats, interventions and policies are needed to encourage the inclusion of these two food groups to achieve more balanced and diversified diets rich in nutrients, in particular, during pandemics like COVID-19.
Participants in this study were distributed across 31 provinces and cities in China. We observed a slightly lower HDDS among people living in the areas where more COVID-19 cases had been confirmed. Similar concerns were raised in the areas hit hardest by Ebola in 2014 and 2015. In Guinea and Liberia, where food became unavailable and food insecurity rose rapidly, people shifted toward a less nutritious diet with limited diversity [36, 37] . Those findings indicate that areas with high incidence of infectious diseases like COVID-19 should pay more attention to dietary diversity, especially in the areas where people are required to self-isolate at home and food supply mostly depends on government or community-based food distribution programs. Meanwhile, more novel strategies should be developed to meet the needs of adequate and diverse food supply in this particular time.
As reported by the study participants, in-house storage and in-person grocery shopping were still the major sources of food supply during lockdown. Meanwhile, online food ordering and delivery services have gradually become an important method to purchase food in the daily lives of Chinese residents [11] . In this study, 55.9% participants used online ordering and delivery services at least once. The clustering analysis grouped study participants into three clusters based on their methods for purchasing or obtaining foods. When comparing the HDDS among people with different preferences for purchasing foods, we found that participants who purchased food primarily via online food shopping, or who depended on in-house storage and in-person grocery shopping, or purchased the most food in person from grocery stores had similar HDDS. In addition, we observed that fruits and dairy products were the most common food purchased via online services, which are also the food groups recommended in the Chinese Dietary Recommendation responding to COVID-19 [18] . Therefore, online ordering and delivery services may serve as a feasible solution to sustain stable food supply and adequate food access in the COVID-19 pandemic as it can maintain dietary diversity and potentially reduce the spread of virus by limiting person to person contact. On 10 February, the Chinese State Administration for Market Regulation promulgated specific regulations corresponding to the online food ordering and delivery services, which requires checking the deliveryman's temperature daily, disinfecting the equipment, requesting staff wear gloves and masks during delivery services, etc. [38] . These requirements may be helpful in curtailing the COVID-19 pandemic, but further evaluations on their effectiveness in slowing the growth of COVID-19 cases are still needed. Furthermore, other potential concerns on food delivery such as the risk of food contamination should also be taken into consideration.
Disease outbreaks often influentially impact health-related behaviors. Joseph et al. reported that comparing health-seeking behaviors in the post-and pre-SARS epidemic period in 2003, people were more likely to adopt a healthier diet, especially among those who were worried about contracting the virus [39] . Interestingly, our study found that 31.2% of our participants intentionally consumed vitamin C, probiotics, and other dietary supplements to cope with the novel coronavirus outbreak. Meanwhile there were 10.6% and 16.0% of participants once purposely drinking alcohol and vinegar, respectively. These behaviors are likely to be caused by rising concerns in this stressful time of COVID-19 pandemic. Intriguingly, we observed higher HDDS among participants with those behaviors. We infer that it may be because the people who have these behaviors may also pay more attention to diet. However, it should be noted that none of these behaviors has been officially recommended and they are not supported by rigorously tested scientific evidences. For instance, the idea of drinking high liquor to prevent viral infection emerged soon after several Chinese scientists announced that 75% medical alcohol could inactivate the virus. Although the Chinese government had already dismissed this rumor since 22 January [40] , there were still more than 10% of the studied population purposely drinking more alcohol. This behavior has also been reported in many other countries. According to the report from Tasnim News Agency on 27 March, there have been at least 2197 people poisoned and 244 deaths in Iran due to the consumption of toxic alcohol (methanol based beverage) that was believed to prevent COVID-19 by some people [41] . Another interesting phenomenon is that 16% of the studied participants had drunk more vinegar to fight against the virus, which could also be seen in 2003 during the SARS pandemic [42] . Unfortunately, no scientific evidence has proven the effectiveness of drinking vinegar in lowering the risks of viral infection or mortality.
Based on the online survey methodology, HDDS was used in this study for its convenience, and to some extent, it could reflect the food accessibility and predict the risk of malnutrition. However, it does not quantify the amount of actual food intake and, therefore, we could not estimate the level of nutrient sufficiency or deficiency. Additionally, according to a validation study, the current components of indicators in HDDS do not provide a reliable way to reflect the household-level access to food [43] . No previous Chinese study has used this indicator, so the reliability was unknown in the Chinese population. In addition, the HDDS was designed with an interview methodology and there is no pre-test of its efficiency on self-completion. The e-based questionnaire may also lead to selection bias. The majority of participants in the current survey were young and highly educated. Elders and people with relatively low socio-economic status could not be easily reached in this study, however, they are often the more vulnerable groups during the COVID-19 pandemic. Further studies should focus on these populations and provide specific strategies to ensure their nutritional status. Another unfortunate limitation in current study is that we could not obtain the anthropometric data, hence the direct health outcomes could not be observed. The impacts of dietary intake during pandemic on health such as weight change and immune functions need to be evaluated.
This study reported on dietary diversity in Mainland China during the COVID-19 pandemic and revealed a generally good dietary diversity among the Chinese residents studied. However, people living in areas with a high number of confirmed COVID-19 cases had a lower HDDS. Several dietary behaviors used to cope with COVID-19 were identified including increased consumption of vitamin C, probiotics, other dietary supplements, alcohol, and vinegar. People with these behaviors had a higher HDDS. During lockdown, in-house storage and in-person grocery shopping were the primary ways to obtain food. There was no difference in the HDDS among people who depended more on in-person grocery shopping, in-house storage, or online ordering and delivery services to obtain or purchase foods.
Based on the current study, we have proposed the following recommendations. (1) Evidence based dietary recommendations and health education are needed to encourage a more balanced and diversified diet and to prevent inappropriate eating behaviors, especially in areas severely impacted by COVID-19 and the lockdown policy. (2) Cautiously monitored and regulated online ordering and delivery services could serve as a feasible method for food purchases, which ensures dietary diversity.
(3) More studies are urgently needed to identify potential nutritional concerns for different populations with various health conditions and socio-demographic characteristics during pandemics and provide corresponding strategies.
Author Contributions: A.Z. designed the research. A.Z., and Z.L. wrote the manuscript. A.Z., J.Z., and Z.R. performed the statistical analyses. Y.K., S.H., and Y.M. collected the data; Y.Z. participated in the discussion and revised the manuscript. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
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To the Editor,
We read with interest the study by Chu et in upper respiratory tract (URT) specimens. 1 At our institution, we similarly had a case of a healthy 33-year-old female HCW who developed fevers after working several weeks in clinical assessment areas including the COVID-19 ward where appropriate personal protective equipment was used. Despite high suspicion for COVID-19, two nasopharyngeal swabs (NPS) tested negative on days 2 and 4 of illness using a laboratory-developed assay targeting genes for the envelope (E) protein and RNA-dependent RNA polymerase. 2 Nevertheless, she continued home self-isolation given ongoing symptoms.
In the 2nd week of illness, she developed anorexia, nausea, and vomiting but still lacked respiratory symptoms. Due to persisting suspicion for COVID-19, a third NPS and paired 1 ml saliva specimen was collected on illness day 9. NPS was tested on another platform using the cobas® SARS-CoV-2 test (Roche) targeting E and Orf1a genes. Saliva was tested using the LightMix® ModularDx SARS-CoV (COVID19) E-gene assay (TIB Molbiol). This third NPS tested
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The plant family Brassicaceae (Cruciferae) comprises over 330 genera and~3700 species with a worldwide distribution [1] [2] [3] [4] [5] . Numerous crops are derived from this family, including vegetables (Brassica and Raphanus), ornamentals (Matthiola, Hesperis, and Lobularia), spices (Eutrema and Armoracia), and medicines (Isatis). Based on sequenced genomes, several model species have been developed for diverse studies, including Arabidopsis thaliana for molecular function studies, Brassica for polyploidization and whole-genome duplication (WGD) studies, and Eutrema salsugineum for abiotic tolerancerelated studies. However, genetic biosynthesis of the major active compounds in medicinal plants of this family remains poorly investigated.
Isatis indigotica (2n = 14) belongs to tribe Isatideae in lineage II of the family 3,6-10 . This species is widely cultivated in China as an important medicinal plant because its dried leaves and roots are used as a traditional Chinese medicine for curing diseases and viruses [11] [12] [13] . The major active compounds isolated from this species comprise terpenoids, lignans, and indole alkaloids [14] [15] [16] [17] . These compounds were confirmed to have antiviral 18, 19 , antibacterial 20 , anti-inflammatory 21, 22 , and antileukemia 23, 24 functions. Previous studies based on transcriptomes revealed a few candidate genes involved in the biosynthesis of active compounds in this species [25] [26] [27] [28] . However, the limitations of transcriptome quality and integrity hinder the identification of all candidate biosynthesisrelated genes.
In the present study, we used single-molecule sequencing combined with high-throughput chromosome conformation capture (Hi-C) technology to assemble the genome and construct the pseudochromosomes of I. indigotica. Based on homolog searching and functional annotations, we aimed to identify candidate gene sets involved in the biosynthesis of putative active components. The candidate genes and genomic resources recovered here will be critically important for further experimental verification and artificial syntheses of the active compounds of this medicinal plant in the future.
The genome size, genome repeat size, and heterozygosity rate of I. indigotica were estimated using K-mer analysis. The 19-mer frequency of Illumina short reads with the highest peak occurred at a depth of 94. The genome was estimated to be 279.90 Mb in size with 48.99% repeats, and the heterozygosity rate was estimated to be 0.44% (Supplementary Table S3 and Supplementary Fig. S3 ). In addition, the genome size of I. indigotica was estimated to be~305 Mb based on flow cytometric analyses using Vigna radiata as the internal standard (Supplementary Fig. S2 ).
We sequenced and assembled the genome of I. indigotica using single-molecule real-time (SMRT) sequencing technology from Pacific Biosciences (PacBio) and anchored the assembled contigs to seven pseudochromosomes using Hi-C techniques. The final chromosome-scale genome was 293.88 Mb in length with 1199 contigs (contig N50 = 1.18 Mb), a scaffold N50 = 36.17 Mb, and a maximum pseudochromosome length of 38.25 Mb (Table 1, Supplementary Table S4 , and Supplementary Fig. S4 ).
The completeness of the genome assembly was evaluated using Benchmarking Universal Single-Copy Orthologs (BUSCO) 29 . Of the 1440 plant-specific orthologs, 1416 (98.33%) were identified in the assembly, of which 1400 (97.22%) were considered to be complete (Supplementary Table S5 ). The assembly base accuracy was also assessed based on Illumina short read mapping. In total, 99.97% of the clean reads were mapped to the genome assembly, and 94.55% of them were properly mapped (Supplementary Table S6 ). The base error percentage of the genome assembly was estimated to be 0.000081% (Supplementary Table S7 ). All these evaluations indicate the high completeness, high continuity, and high base accuracy of the present genome assembly.
Repetitive sequences were identified using a combination of ab initio and homology-based approaches. In total, we identified 53.27% of the assembled sequences as repetitive sequences, including 34.67% retrotransposons and 7.37% DNA transposons. Long terminal repeat (LTR) retrotransposons were found to account for 30.09% of the genome (Supplementary Table S8 ). We annotated proteincoding genes by combining transcriptome-based, homology-based, and ab initio predictions. Finally, we predicted a total of 30,323 genes, of which 5973 had alternatively spliced transcripts. The average transcript length and coding sequence size were 2693 and 1387 bp, respectively, with a mean of 5.50 exons and 1.39 transcripts per gene (Table 2) . Overall, 29,522 genes (97.36%) were assigned functions, and 76.16% and 91.69% of these genes had homologies and annotated proteins in the Swiss-Prot and TrEMBL databases. Further functional annotations using InterProScan estimated that 95.86% of the genes contained conserved protein domains, and 87.32% of the genes were classified by Gene Ontology (GO) terms, with 29.41% mapped to known plant biological pathways based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database (Supplementary Table S9 ).
Evolution of chromosome structures in Brassicaceae has been traced and established through comparative chromosome painting techniques using BAC probes of the A. thaliana genome 4, 30 . Using these techniques, Lysak and (Fig. 1a) . Six tribes (Calepineae, Coluteocarpeae, Conringieae, Eutremeae, Isatideae, and Sisymbrieae) of expanded lineage II were found to derive from a common ancestor with the Proto-Calepineae Karyotype (PCK; n = 7). Among these tribes, three (Eutremeae, Isatideae, and Sisymbrieae) displayed an additional whole-arm translocation in the second and seventh chromosomes (translocation PCK, tPCK; n = 7) 32-34 (Fig. 1a) . ACK and PCK shared five similar chromosomes. Thus, they might descend from a common ancestor; alternatively, PCK may have evolved from ACK.
To determine whether the I. indigotica genome sequence also supported tPCK structure in Isatideae, we compared the seven pseudochromosomes of I. indigotica with the A. thaliana genome by LAST and MCScanX. We Table S10 ). The I. indigotica genome has good collinearity in each GB compared with the A. thaliana genome and is consistent with tPCK structure in both order and orientation ( Fig. 1 and Supplementary Figs. S5, S6). Furthermore, we carried out sequence alignments between the genomes of I. indigotica and the other three species that might also display tPCK structure (Sisymbrium irio for Sisymbrieae, E. salsugineum for Eutremeae, and Schrenkiella parvula for unassigned genera) using LAST. Our analyses suggested that these four species have similar chromosome structures (Supplementary Figs. S7-S9). However, we found obvious inversions in the S. parvula genome and low continuity of sequences in the E. salsugineum and S. irio genomes. These comparisons suggest that the present I. indigotica genome was better assembled in terms of both accuracy and continuity than others with tPCK structure.
We clustered the annotated genes into gene families among I. indigotica and eight other Brassicaceae species with Cleome hassleriana as the outgroup. A total of 24,382 I. indigotica genes (80.41%) clustered into 18,900 gene families, of which 10,826 (57.28%) gene families were shared with nine other species and 896 (4.74%) were I. indigotica specific ( Fig. 2c and Supplementary Table S11). We selected 822 single-copy gene families among 10 species to construct a phylogenetic tree, which showed that I. indigotica was sister to S. irio. We further estimated the divergence time between them as 15.86 (12.71-19.20) million years ago (Mya) (Fig. 2a) . The relationships of all 10 species are consistent with those from previous phylogenetic analyses 3,6-8, 10 .
Then, we used synonymous substitution rates (Ks) between collinear paralogous genes to identify potential WGD events, based on the assumption that the number of silent substitutions per site between two homologous sequences increases in a relatively linear manner with time. A density plot of Ks values for the collinear gene pairs suggested that I. indigotica experienced a recent WGD event with a peak value of~0.76, consistent with At-α-WGD for all Brassicaceae species 8, 35, 36 . An independent WGD event was identified for B. rapa after its divergence from I. indigotica at Ks = 0.30-0.34, previously reported as a Brassiceae-specific triplication (Br-α-WGD) 8,37-39 (Fig. 2b) . Whole-genome alignment among the I. indigotica, A. thaliana, and B. rapa genomes carried out by LAST also confirmed the collinear relationship and these WGD events. For each genomic region of I. indigotica, we typically found one matching region in A. thaliana and three matching regions in B. rapa. These comparisons suggest that I. indigotica did not experience an independent WGD event after At-α-WGD (Supplementary Figs. S5, S10).
The expansion and contraction of gene families play critical roles in driving phenotypic diversification and enhancing special traits in plants. We discovered 1357 expanded and 3074 contracted gene families in I. indigotica relative to S. irio (Fig. 2a) . Tandem duplication was the main contributor to the gene family expansions. GO enrichment analysis of tandem repeat genes suggested that they were enriched in defense response to virus, indole biosynthetic process, lignin biosynthetic process, flavone synthase activity, and glucosyltransferase activity, some of which might be involved in the biosynthesis of active compounds in I. indigotica (Supplementary Table S12 ). We also performed GO enrichment analysis of the contracted gene families, and the results showed that they were enriched in proton export across plasma membrane, proton-exporting ATPase activity, regulation of stomatal movement, and defense response to other organism (Supplementary Table S13 ), which are probably related to the environmental adaptation of the species.
Based on the KEGG database, GO classification, and the suggested biosynthesis pathways, we used a combined method of homolog searching and functional annotation thaliana GB boundaries were derived from a previous study 34 to identify candidate genes for the biosynthesis of three types of active compounds, namely, terpenoids, phenylpropanoids, and indoles, in I. indigotica [14] [15] [16] 25, 40, 41 . Sterols are the major terpenoids in I. indigotica, mainly comprising β-sitosterol and daucosterol 42 . β-Sitosterol was reported to play a critical role in curing lung inflammation 43 , while daucosterol can inhibit cancer cell proliferation 44 . A total of 59 genes in the present genome, which encoded 31 enzymes, were identified to be involved in terpenoid and sterol biosynthesis (Supplementary Table S14 ). Based on the functional annotations of these genes, the biosynthesis pathway of β-sitosterol is nearly complete and daucosterol can be further synthesized from β-sitosterol by glucosyltransferases (Fig. 3a) . In addition, the intermediate product geranyl diphosphate can be used not only to synthesize sterols but also to produce secologanin for monoterpene indole alkaloids in numerous medicinal plants such as Catharanthus roseus 45 . However, we annotated genes only with geraniol 10-hydroxylase activity (GO: 0102811). The lack of other related genes may account for the absence of secologanin and other related monoterpene indole alkaloids in I. indigotica. Table S15 ). The identified putative pathway mainly comprises the biosynthesis of isovitexin and lariciresinol, while their glycosides were further synthesized by glucosyltransferases (Fig. 3b) . Indole alkaloids comprise another active component of I. indigotica [48] [49] [50] with important anti-influenza, anti-inflammatory, and leukocyte inhibition effects 11, 23, [51] [52] [53] . Based on the KEGG maps and previously suggested pathways 25,54,55 , we identified 32 genes that encoded 11 enzymes involved in the biosynthesis of indole alkaloids (Fig. 3c and Supplementary Table S16). Because of the lack of downstream pathways, other genes for indole alkaloid biosynthesis in I. indigotica need further identification. It should be noted that numerous genes involved in the biosynthesis of the three major types of active compounds increased in copy number because of tandem duplication, for example, geranylgeranyl diphosphate synthase, cinnamate 4-hydroxylase, 4coumarate-CoA ligase, and indole-3-pyruvate monooxygenase ( Fig. 3 and Supplementary Tables S14-S16).
Continuity and completeness are important indicators of genome assembly. PacBio-based genome assembly plus error corrections based on Illumina data could greatly improve continuity and completeness [56] [57] [58] [59] . Our genome assembly of I. indigotica by this strategy showed a highly resolved result with an N50 = 1.22 Mb and longest contig length = 8.99 Mb. In addition, we used Hi-C data to cluster the contigs into seven pseudochromosomes with a final scaffold N50 = 36.17 Mb and longest chromosome length = 38.25 Mb. The completeness and high quality of the present I. indigotica genome were further confirmed by BUSCO and comparative chromosome analyses 32 . A total of 97.22% of the genes examined by BUSCO were complete, and the chromosome structure of I. indigotica was consistent with the tPCK type. We constructed the phylogenetic relationships of I. indigotica based on genomic data and found that I. indigotica of Isatideae is sister to S. irio of Sisymbrieae among the sampled species, consistent with the results of previously published phylogenetic analyses 3, [6] [7] [8] 10 . Based on the phylogenetic results, we identified expanded and contracted gene families in I. indigotica. The expanded genes in this species were mainly derived from tandem duplications and were obviously enriched in some secondary metabolite pathways. Based on homolog searching and functional annotation in our high-quality genome, we further identified candidate genes for the biosynthesis of three main classes of active compounds in I. indigotica: terpenoids, phenylpropanoids, and indole alkaloids. These candidate genes complete or replenish gene sets for biosynthetic pathways of these compounds concentrated in I. indigotica [25] [26] [27] [28] (Fig. 3 ). In addition, we found that in some synthesis steps, the copy number of enzyme-coding genes increased to two or more because of tandem duplications. The increase in copy number may drive the production of major active compounds in I. indigotica and account for its excellent antibacterial and antiviral activities because gene expansions are responsible for enhancing a special trait or the origin of a new trait [60] [61] [62] .
Overall, in this study, we present a high-quality genome for I. indigotica. We further identify or replenish candidate genes for biosynthesis pathways of the active compounds in this medicinal plant. These genes and genomic resources will provide a solid basis for future biosynthesisrelated studies.
We initially extracted high-quality total DNA from fresh young leaves of a 2-month-old plant artificially cultivated in the greenhouse using the cetyltrimethylammonium bromide method. We used a SMRTbell Template Prep Kit 1.0 (PacBio, Menlo Park, CA, USA) to construct the DNA libraries for PacBio long-read sequencing and sequenced them on a PacBio Sequel system. We obtained a total of four SMRT cells with 39.94 Gb of sequencing data (coverage of 142.71×) from the PacBio Sequel platform and generated a total of 4.30 million subreads with an N50 read length of 14.9 kb (Supplementary Table S1 and Supplementary Fig. S1 ). We also prepared paired-end Illumina libraries using an Illumina Genomic DNA Sample Preparation Kit and sequenced them on an Illumina HiSeq X Ten system for error correction and K-mer analysis and generated a total of 37.50 Gb of data and 31.79 Gb of clean data (Supplementary Table S1 ).
We initially estimated the genome size of I. indigotica by flow cytometry with Vigna radiata as the reference 63 . We then used clean Illumina short reads to calculate K-mers (Illumina DNA short read size of 19 bp) by Jellyfish v.2.2.9 64 to confirm the genome size. The sequencing depth was estimated by determining the highest peak value of the frequency curve of the K-mer occurrence distribution. We used SMRT Link pipeline v.5.1.0.26412 to process the polymerase reads into subreads with readScore = 0.75 and minSubReadLength = 500 and used Canu v.1.6 65 to correct errors of the PacBio subreads and assemble the corrected reads into contigs after trimming low-quality bases using WTDBG (https://github.com/ ruanjue/wtdbg). We corrected the assembled contigs by using 270 bp PE Illumina data by Pilon v.1.13 66 and finally obtained a 293.83 Mb contig-scale assembly with a contig N50 of 1.22 Mb. The genome contained 1162 contigs, and the longest contig was 8.99 Mb with a 38.18% GC content. These contigs were further anchored to chromosomes by the Hi-C technique.
We grounded~3 g of fresh young leaf tissue into powder in liquid nitrogen for Hi-C experiments and constructed a Hi-C library following Louwers et al. 67 with chromatin extraction and digestion and DNA ligation, purification, and fragmentation. Finally, we obtained a total of 79.43 Gb of clean reads for Hi-C analyses by the Illumina HiSeq X Ten platform. We first carried out a preliminary assembly by splitting contigs into segments of 100 kb on average and mapping the Hi-C data to the contigs using BWA v.0.7.10-r789 68 in order to correct contig errors. We then used LACHESIS software 69
We identified repetitive elements through both RepeatModeler v.1.0.10 and RepeatMasker v.4.0.7 70, 71 . RepeatModeler employed RECON and RepeatScout to predict interspersed repeats and then obtained the consensus repeat library. RepeatMasker recovered the repeats in the I. indigotica genome through a homologybased repeat search using the ab initio repeat database and Repbase. The overlapping repeats belonging to the same repeat class were combined according to their coordination in the genome. The overlapping repeats belonging to different repeat classes were then split into different types.
To improve gene prediction, we further obtained transcriptomes by sequencing high-quality RNA from mixed fresh leaf, flower, and stem tissues and sequenced them by the Illumina HiSeq X Ten platform. We removed adapters and discarded reads with >10% N bases or reads having more than 20% bases of low quality (below 5) using NGS QC Toolkit v.2.3.3 72 and finally generated 19.87 Gb of clean data. We assembled the de novo and genomeguided transcriptomes with clean reads by Trinity v.2.4.0 73 . We also mapped the RNA-sequencing (RNAseq) reads to the assembled genome to obtain the mapping rate through HISAT2 v.2.1.0 74 to evaluate the completeness of the genome.
We run PASA pipeline v.2.1.0 75 to align the transcripts to the assembled genome to carry out ORF prediction and gene prediction. To train the HMM model for Augustus, we extracted complete, multiexon genes, removed redundant high-identity genes (cut-off all-to-all identity of 70%), and finally generated the best candidate and low-identity gene models for training. We aligned the RNA-seq data to the hard-masked genome assembly by HISAT2 74 77 and searched with an e value of 1e −5 . After filtering lowquality results, gene structure was predicted using GeneWise v.2.4.1 78 . We combined the results from PASA, Augustus and GeneWise to generate the final protein-coding gene set using EVidenceModeler v.1.1.1 75 . To obtain the untranslated regions and alternatively spliced isoforms, we used PASA to update the gff3 file for two rounds and obtain the final gene models.
We annotated the functions of the predicated genes against public databases by NCBI BLAST+ v.2.2.31 77 with a cut-off e value of 1e −5 and maximum number of target sequences of 20, including the Swiss-Prot and TrEMBL databases 79 . Best-hit BLAST results were then used to define gene functions. We used InterProScan v.5.25-64.0 80 to identify motifs and domains by matching against public databases. We identified GO annotations by using Blast2GO v.4.1 81 according to the blast results and combined them with InterPro GO entries. We mapped the existing GO terms to enzyme codes by Blast2GO and submitted the predicted proteins to the KEGG (Kyoto Encyclopedia of Genes and Genomes) Automatic Annotation Server (KAAS) 82 to obtain KO numbers for KEGG pathway annotation.
We used protein sequences of I. indigotica and eight other Brassicaceae species (Arabidopsis thaliana, Capsella rubella, Brassica rapa, Brassica napus, Raphanus sativus, Schrenkiella parvula, Sisymbrium irio, and Eutrema salsugineum) with the outgroup species Cleome hassleriana for same-family gene clustering. For genes with alternative splicing variants, the longest transcript was selected to represent the gene. Similarities between sequence pairs were calculated using BLASTP v.2.2.31 77 with a cut-off e value of 1e −5 . Additionally, OrthoMCL v.2.0.9 was used with default parameters to assess gene family membership based on overall gene similarity combined with Markov Chain Clustering (MCL) v.14-137 83 .
We extracted single-copy orthologous genes from the ten species by OrthoMCL and aligned the resulting protein sequences by MAFFT v.7.313 84 . Then, we used Gblocks v.0.91b 85 to extract the conserved sites of multiple sequence alignments and constructed a phylogenetic tree by RAxML v.8.2.11 86 . We used C. hassleriana as an outgroup and performed 1000 bootstrap analyses to test the robustness of each branch. We used the Bayesian relaxed molecular clock approach in MCMCTREE of PAML v.4.9e 87 to estimate divergence time. We calibrated this tree based on the estimated divergence times in the TimeTree database 88 Gene families that had undergone expansion or contraction were identified in the eight sequenced species using CAFE 89 . The CAFE parameters included a p value threshold = 0.05 and automatic searching for the λ value. The algorithm in CAFE takes a matrix of gene family sizes in extant species as input and uses a probabilistic graphical model to ascertain the rate and direction of changes in gene family size across a given phylogenetic tree.
To examine WGD in I. indigotica and B. rapa, we extracted all homologous proteins between these two species and A. thaliana using an all-to-all search in BLASTP v.2.2.31 77 with an e value cut-off of 1e −9 . We used MCScanX 90 with default parameters to identify collinear blocks, each containing at least five collinear gene pairs. To infer WGD events, we used the downstream MCScanX script add_ka_and_ks_to_collinearity.pl to calculate the Ks values between collinear genes among these three genomes. We further performed whole-genome alignment of the three species by LAST v.946 91 and constructed a dot plot by the downstream program last-dotplot.
Identification of tandem repeat genes in the I. indigotica genome was based on three criteria: (1) two or more genes had more than 70% identity and 70% coverage according to BLASTP; (2) the pairwise gene distance was <100 kb; and (3) there were no more than 10 genes lying between the repeat genes on a single scaffold 92 . The genes identified in this way were subjected to functional analysis using GO enrichment.
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The Coronavirus disease (COVID- 19) pandemic and its related efforts of containment have generated a worldwide health crisis impacting all sectors of human life. At its initial stage of inception, with the number of people affected by the disease being minimal, it did not reflect threats of such enormous capacity 5 wherein the majority of the cases were resolved spontaneously. With gradual progression of time, COVID-19 was declared as an outbreak by the World Health Organization (WHO) with an extremely high-risk potential of affecting millions of lives in all countries, especially ones with weaker health systems. The virus is deadly due to two basic reasons-firstly, it is novel with no vaccines discovered,
Transmission Level 2 Transmission Level 1
Transmission Level N (Epidemic) and medical image processing techniques to combat the COVID-19 pandemic presenting an extensive review of the state-of-the-art frameworks developed by employing these technologies.
In a desperate attempt to combat the COVID-19 pandemic, researches have 55 been initiated on scientific studies in all directions, and DL integrated with medical image processing techniques have also been explored rigorously to find a definite solution [4, 5] . Numerous research publications have been published with similar objectives, as shown in Table. 1. The uniqueness of the present work lies in its effort to emphasize significant DL and image processing tech- the text contents, mentions that "it is the process of combining and associating information from one or multiple sources to provide useful information for the detection, identification, and characterization of a particular entity". In ML and DL applications, the availability of large-scale, high-quality datasets plays a major role in the accuracy of the results. Information fusion helps to integrate 80 multiple datasets and use them in the DL models to achieve enhanced accuracy in predictions. As an example, computed tomography (CT) images from Xi'an Jiaotong University and Nanchang First Hospital and Xi'an No. 8 Hospital have been integrated as part of Information fusion to be fed into the AI and DL models [6] . Similar information fusion has been observed in [7] where X-ray images 85 of the lung from Dr. Joseph Cohen's GitHub repository have been augmented
with Chest X-ray images available from the publicly available Kaggle repository.
In [8] , X-ray image datasets from GitHub, Cohen, Radiology Society of North America (RSNA), and Italian Society of Medical and Interventional Radiology (SIRM) were associated and used fed into the CNN for detecting COVID-19. In 90 the later sections of the text, similar references can be visualized pertaining to applications of information fusion in order to fill the lag of data unavailability and still continue to generate predictions of enhanced quality.
It is important to understand that the pandemic is at its peak where exist-5 J o u r n a l P r e -p r o o f ing medical facilities are overwhelmed. The emergency departments, intensive 95 care facilities have been stretched beyond their regular capacity to serve the ever-growing population of patients. In such a crisis, the healthcare providers and also the patient family members need to make rapid decisions with minimal information. The phenotype of the COVID-19 disease starts with mild or no symptoms at all, yet rapidly changes its course to making patients extremely where there are shortages of radiologists due to an overwhelming number of patients [10] .
After conducting an extensive background study, it is evident that there is not many surveys conducted emphasizing the applications of DL frameworks and image processing in the prediction of COVID-19 cases. The present pandemic situation across the globe has impacted millions of lives. Thousands and 6 J o u r n a l P r e -p r o o f thousands of people are getting affected by this highly contagious disease lead- 125 ing to questions on survival and sustainability of the human race [11] . The only way to contain the disease is to detect the disease at its initiation, barring others from getting infected. This requires accelerated diagnosis without associated health hazards. The traditional approaches fail to provide the same due challenges pertinent to detection time, cleaning needs after each use of the 130 diagnostic machinery and availability of resources. The use of ML approaches eliminates these issues and also detects faster. ML approaches, if used more predominantly, can lead to containment of the disease and reduce mortality.
The paper thus provides comprehensive information on various DL implementations in COVID-19 using real-time as well as publicly available image 135 datasets. The unique contributions of our study are mentioned below:
• The survey includes basic information on COVID-19 and its spread, which establishes the motivation and need for accelerated disease prediction ensuring containment of the disease in smart cities.
• The role of DL applications in medical image processing is discussed in 140 detail in support of its capability in COVID-19 predictions.
• The recent works on DL and image processing implementations in COVID-19 are discussed explicitly.
• The datasets, methodologies, evaluation metrics, research challenges, and the lessons learned are included from these state-of-the-art research works 145 in addition to the future directions in controlling the pandemic in smart cities.
The rest of this work is organized as follows. Section 2 presents fundamental information on COVID-19, DL and expresses the general motivation towards the ing. Section 6 summarizes the aforementioned reviews highlighting the lessons learned and enlisting the recommendations guiding towards the future direction of research. The paper is concluded in Section 7.
J o u r n a l P r e -p r o o f
This section presents the fundamentals of COVID-19, DL, and an overview 160 of the adoption of DL to process and analyze medical images from the existing literature.
At the outset, multiple pneumonia cases were being registered in the Wuhan adapt to multiple data types across different domains. Fig. 2 depicts various techniques used in DL. DL replicates the functioning of human brain in filtering information for accurate decision making. Similar to the human brain, DL 220 trains a system to filter the inputs using different layers to aid the prediction and classification of data. These layers are like layered filters used by the neural networks in the brain where each layer acts as a feedback to the next layer.
The feedback cycle continues until the precise output is obtained. The precise output is formed by assigning weights in each layer, and during training, these 225 weights are adjusted to get the accurate output.
DL techniques can be categorized as supervised, semi-supervised, and unsupervised. In supervised learning, the model is trained with a known inputoutput pair. Each known value constitutes an input vector and the desired value, which is referred to as the supervisory signal. The method uses existing 230 labels to predict the labels of the desired output. Classification methods use supervised learning [32] and can be applied to scenarios to identify faces, traffic symbols, recognizing spam in a given text, converting speech to text, etc.
Semi-supervised learning is an in-between technique of supervised and unsupervised ML methodologies. The training data in Semi-supervised learning 235 consists of labeled and unlabelled values. Semi-supervised learning falls between unsupervised learning and supervised learning. The unlabeled data, when used in conjunction with a small amount of labeled data, can produce a considerable improvement in learning accuracy. There exist certain scientific assumptions related to DL techniques [33] . The first being, data in proximity to each other 240 have the same label. Second is the cluster assumption, where the data in the cluster share the same label. The third being, the data is restricted to a limited dimension rather than the complete input space. Unsupervised learning deals with knowing the inter-relations among the elements of the data set and then classifying the data without using labels. Some of the algorithms following these 245 techniques are clustering, anomaly detection, and NN. Clustering is the principle of identifying similar elements or anomalies in a data set [34] . This anomaly detection of unsupervised learning is widely applied in security domains [35] .
Most of the DL techniques use Artificial Neural Network (ANN) for feature processing and extraction. Feedback technique is used for the learning mech-250 anism [36] where-in each level updates its input data to form a summarized representation. The term deep in DL technique refers to the number of layers required for the data to be transformed. A Credit Assignment Path (CAP) is used during this transformation process. In the case of a feed-forward NN, the depth of CAP is calculated by the number of hidden layers in addition to the 255 number of output layers.
In the case of a Recurrent Neural Network (RNN), there might be more than one signal which traverses multiple times in a layer, and thus the CAP depth cannot be determined [37] . One of the predominantly used techniques of NN for image processing is CNN [38, 39, 40] . In CNN, the feature extraction technique 260 is automated and is performed during the training on the images making DL the most accurate method for image processing domains. RNN works similar to CNN, but the difference is that RNN is used for language computation. RNN uses the concept of feedback loops where the output of one layer is fed as the input of the next layer. RNN can be used for datasets which involve time-series 265 [41] , text, financial data, audio, video, etc.
Generative Adversarial Networks (GANs) works on the concept of the generator network and the discriminator. The generator network produces fake data while the discriminator differentiates fake and real data. These two networks work towards improvising the training process, and thus GANs are mostly 270 used in an application that requires the generation of images [42] from the text.
Google's inception network introduces inception block to compute convolutions and pooling operations that run simultaneously for the effective processing of complex tasks. This is an advanced level of DL used in automating the responsibility involved in image processing [43] .
DL can be applied in varied domains, which involve the processing of a vast set of data. DL has great potential in smart cities as a huge amount of data will be generated in smart cities due to digitization [44, 45] . The evaluation of DL techniques relies on two parameters: firstly, the enormous amount of data size to be processed and, secondly, the massive computational power. DL also aids 280 in the faster analysis of complex medical images [42] for rendering an accurate diagnosis. DL is popularly implemented in the health care sector for broad data interpretations [46] , aiding early diagnosis of diseases, thereby reducing manual workload. The following section provides an overview of DL applications for medical image processing.
Advances in medical science have significantly changed health care over the last few decades, allowing doctors to identify and treat diseases more effectively [47] . But doctors, similar to any human beings, are also prone to errors. The scholarly credentials of a doctor lie not only in the individual's level of intelli-290 gence, but the way they treat the problems of patients and the associated type improving the strength of a doctor in diagnosing and treating patients [49] . The effectiveness of ML algorithms depends on the types of features extracted and 295 data representation. ML algorithms primarily face two key challenges, one being efficiency in scanning all high-dimensional datasets and secondly training of the model to find the most appropriate task [50, 51] . DL has been one of the commonly used techniques that guarantees a higher degree of accuracy in terms of disease prediction and detection. Applications of DL techniques have intro- [52, 53, 54] . CNN is one of the most preferred algorithm popularly used 305 in image processing and analysis [40] . The authors in [55] reviewed various DL methods for medical image processing and have inferred the use of DL in object identification, image categorization, segmentation, etc. In the medical domain, DL for image processing is used in various departments such as ophthalmology, neurology, psychotherapy, cancer detection, and cardiology. The authors have 310 also enlisted the unresolved research challenges in DL relevant to image analysis.
In the current scenario of patients and medical stakeholders maintaining electronic records, AI has aided easing the medical image processing. The authors in [56] reviewed various AI techniques that can be implemented for medical image analysis. The authors from diverse literature found that CNN has been 315 widely used for this analysis, along with big data techniques for processing. The authors also highlighted the main challenges of the unavailability of high quality labeled data for better interpretation.
Classification is often termed as Computer-Aided Diagnosis (CAD). Classi-320 fication plays a significant role in medical image processing. During the classification processing phase, one or even more images are taken as input samples, and a single diagnosis factor is generated as an output which classifies the image [57] . In 1995, the authors in [58] used DL to classify lung nodules. The detection procedure involves 55 chest X-ray images, two deep-neural hidden layers. Using 325 this test, the radiologist noticed 82% of lung nodules. In [59], the author's used multi-scale DL approaches to identify lung nodules in CT images. The experimentation process comprises of three hidden layers, which take the CT images as input and provide a response to the output layer of the lung nodule. In [60] , the authors introduced a CheXNet DL model with 121 convolution levels, 1,12,120 330 chest X-ray images provided input dataset to diagnose 14 different forms of lung diseases. Using this examination, the radiologist states the CheXNet algorithm exceeds the range of F1-metric efficiency. In [61] , the authors developed a model by training 10-layer CNN with three completely integrated layers on around 90,000 fundus images to diagnose Diabetic Retinopathy (DR). Experi-335 mental tests attain 95% sensitivity and 75% accuracy on 5,000 testing images.
Another related research in [62] employed IDx-DR version X2.1 to train 1.2 million DR images for identifying DR. Results indicate that the built design can achieve a 97% sensitivity and 30% increase in specificity. The work in [63] pro-posed a multi-layer CNN for the classification of skin lesions. The multi-layer 340 CNN is trained with a variety of high-resolution images. Results from the publicly available dataset of skin lesions reveal that the proposed model achieves a better accuracy rate than the other existing models.
In the classification, the images are fed to CNN, and the contents of the 345 image are revealed. After the image classification is done, the next step in the detection of the disease is the image localization, which is responsible for placing the bounding box around the output position, which is called as classification with localization, the term localization here refers to figuring out the disease in the image. The localization of anatomy is a crucial pre-processing phase in a 350 clinical diagnosis that enables the radiologist to recognize certain essential features. During recent years, several research works have been conducted using DL models to localize the disease. For example, in [64] , the authors presented a model for the classification of organs or body parts using a deep CNN. The CNN was trained with 4298 X-ray of 1,675 patients to recognize the five organs of The proposed model as a whole is more accurate for the localization of diseases in heterogeneous organs. In [67] , the authors used 3D CNN for landmarking in medical images. Spatial Configuration-Net (SCN) architecture was used to combine accurate response with landmark localization. Experimental evalua-370 tion of 3D image datasets using CNN and the SCN architecture provides higher accuracy. The work in [68] developed a model that helps to localize the fetal in the image. During this process, CNN was trained to recognize up to 12 scan planes and a network model designed to detect fetal accurately. Experimental tests achieved 69% precision, 80% recall, and 81% accuracy.
Creating accurate ML models capable of classifying, localizing, and detecting multiple objects in a single image remained a core challenge in computer vision [69] . With recent advancements in DL and computer vision models, medical image detection applications are more comfortable to develop than ever before.
Object detection allows for the recognition and localization of multiple objects within an image or video. Object detection is a computer vision technique that is used to identify instances of real-world objects. Object detection techniques train predictive models or use matching templates to locate and identify objects.
Object detection algorithms use extracted features and learning algorithms to 385 identify object type instances. Object detection is a key technology behind applications such as video surveillance, image retrieval system, and medical diagnostics [70] . The work in [71] proposed the Marginal Space DL model for object detection. Adaptive training patterns is used for achieving better performance in Deep NN layers. The approximate position, boundary delineation, 390 incorporated with a DL model, find image outline segmentation. The experimental method includes 869 patients, 2891 aortic valve images, delivering 45.2%
better performance compared to other previous models. Another work in [72] Another interesting work in [74] proposed a novel lung cancer detection model. This process encompasses two steps.
Step one detects dubious pulmonary nodules using a 3-D NN. The second step encompasses cancer detection by collecting the finest five nodules and integration into the leaky noisy-OR
Image Segmentation in medical image processing plays a crucial role in dis-415 ease diagnosis. Image segmentation divides a digital image into several fragments. Medical image segmentation aims to make digital images simpler and more comfortable to examine. The output of medical image segmentation is a collection of medical segments covering the whole medical image [77] . Many inter-disciplinary techniques are currently being used for processing medical 420 data for obtaining better accuracy in diagnosis. The authors in [78] propose a
Image registration is a method for converting datasets to a single coordinate 455 model. Image registration plays a vital role in the area of medical imaging, biological imaging. Registration is necessary to analyze or integrate data from several medical sources. Usually, a medical technician is supposed to display several images in different directions to reduce the visual contrast between im-19 J o u r n a l P r e -p r o o f ages [82] . The medical technician is often expected to manually classify points 460 in the image that have significant signal variations as part of a sizeable anatomical structure. Medical image registration saves a lot of time for doctors and physicists. To address the shortcoming of the manual registration process, DL implementations in the image registration process have improved the productivity of the image registration process [83] . 465 More than half of cancer patients undergo radiation therapy, making it one of the most prevalent cancer treatments [84] . When the number of patients rises, more doctors and more patients will be assisted by medical image processing.
Elastix is fully automated 3D deformable registration software, and its application can enhance the radiotherapy process in radiation oncology departments for the prostate, 93% for the seminal vesicles, and 87% for the lymph nodes.
In [85] , the authors proposed a multi-atlas classifier to enhance the accuracy In [86] , the authors used a Self-supervised learning model to establish 3D- Table 2 .
This section discusses the potential of DL in medical image processing in order to combat the COVID-19 pandemic implementing four strategies. The strategies are outbreak prediction, the virus spread tracking, coronavirus diagnosis and treatment, vaccination, and drug discovery, as shown in Fig. 4 .
X-ray is used to diagnose pneumonia and the basic stage of cancers. But 515 CT scan is a more sophisticated technique that can be used to detect minute changes in the structure of internal organs, and it uses X-ray as well as computer vision technology for its results. X-ray fails to detect diagnosis related of DL based approaches, as discussed in [88] .
In CT images, an X-ray rotates and captures images of a particular section, from varied angles. These images are stored in the computer and further analyzed to create a new image that eliminates all overlapping. These images help doctors understand internal structures with enhanced clarity getting the complete idea about size, structure, density, texture, and shape of the same.
Thus CT scan is considered to be an effective diagnostic technique than Xray. The chest CT or X-ray fails to differentiate between COVID-19 and other cold-related symptoms. The chest CT or X-ray mostly detects the presence of an infection, which could be the consequence of any other disease as well.
Also, the COVID-19 disease is extremely contagious, and the uses of imaging
The world faced an unprecedented global health crisis due to the outbreak of COVID-19 [90, 91] . The simple epidemiological and statistical models have attracted considerable attention from the authorities with regard to COVID-19 detection and predictions. It is also a known fact that governments and other technology, and AI (with ML and DL) [95] . It is an established fact that DL has gained immense momentum in the field of ML with its implementations across all sectors of human life [96] . As an example, in the case of data-centric studies such as computer vision, DL methods have proved to be extremely successful in providing optimal solutions [97, 98] .
In December 2019, when people were waiting for the New Year celebration of 2020, few cases of typical pneumonia caused by a novel coronavirus (2019-nCoV) [112] were reported in Wuhan, China. The work in [113] revealed that a significant number of people were infected from the wet animal market in Wuhan city, considered the zoonotic origin of the COVID-19. Eventually, multiple 650 cases got spread across China, and the world is giving it the status of a global outbreak [114] . There have been attempts made to identify a host reservoir or intermediate carrier that initiated the spread of COVID-19 from animals to humans [115] . The authors in [116] considered two species of snakes as a possible reservoir of the COVID-19, whereas another study [117] rejected the possibility. information -the number of confirmed infectious cases, death tolls, and recoveries are also available at the Johns Hopkins University dashboard [127] . Later, WHO also launched a COVID-10 dashboard [21] , which operates on ArcGIS.
HealthMap [128] is also a dashboard that holds a collection of information from various sources. Aarogya Setu mobile app [129] provides official data of COVID- [130] . A DL-based system was designed to ensure an easy decision for doctors to detect COVID-19 instances of infected pneumonia early enough to control the epidemic.
Coronavirus is not a single virus but a group or family of multiple viruses.
Once a patient is infected with coronavirus, the symptoms could be similar to normal cold infection or severe respiratory syndromes. As an example, Severe diagnosis is observed to be significantly 80%-90% better than RT-PCR while having 60%-70% specificity on the low side [138] . as an alternative examination [140] .
Interestingly, the work in [141, 142] presented a comparison between ultra- diagnosing COVID-19 cases with distinct manifestations. [145] . The work in [146] proposed a detailed guidance report with useful tools to support COVID- Although DL has gained immense momentum, popularity and has generated impressive results with simple 2D images, there exist limitations in achieving a similar level of performance in medical image processing. Research work in this regard is still-in-progress and some of the lessons learned are mentioned below:
• One of the most inhibiting factors is the unavailability of large datasets 965 with high-quality images for training. In this case, synthesizing of the data is a possible solution so that the data collected from varied sources could be integrated together
• The majority of the state-of-the-art DL models are trained for 2D images.
However, CT and MRI are usually 3D and hence add an additional di- implemented on these images
• The non-standardized process of collecting image data is one of the major issues in medical image processing. It is important to understand that with 975 the increase in data variety, the need of larger datasets arise to ensure the DL algorithm generates robust solutions. The best possible way to resolve this issue is the application of transfer learning, which makes preprocessing efficient and eliminates scanner and acquisition issues.
The challenges and issues pertaining to DL implementations for medical image processing for controlling COVID-19 pandemic in smart cities are enlisted below:
• Privacy -Availability of COVID-19 high-quality images and larger datasets is a major challenge considering the privacy of patient data.
• Variability in Outbreak Pattern -The outbreak of the data has followed complex pattern and extreme variation in behavior across various countries and hence reliability of the prediction diseases get added as an additional challenge.
• Regulation and Transparency -Countries across the globe have adopted 990 strict protocols in regulations to be complied pertinent to sharing of COVID-19 data, one of the major protocols clearly states that minimum data and specimens to be collected from patients in the minimum amount of time. Thus this makes it more difficult to analyze.
• Variability in the testing process across various hospitals is also an impor-995 tant concern leading to non-uniformity in data labels. Identification of an appropriate DL technique to exclusively and specifically detect COVID-19 with optimum accuracy still remains as a visible challenge.
Moreover, the coronavirus genome has been completely sequenced based on the data collected from thousands of patients suffering from the disease across the globe. This genome sequence has been extremely beneficial, especially due to the fact that the COVID-19 virus has a higher mutation rate. The present diagnostic tests help to identify specific genes from the virus, and the test accu-1005 racy depends on target areas of the relevant genomes. The effect of the mutation on the diagnostic tests is alarming and there exists a high possibility of generating a "false negative" for a patient actually suffering from the disease. These diagnostic tests provide their diagnosis based on the scrutiny of the coronavirus genes which often vary as the disease spreads from one human to another [166] .
in the case of transfer learning, the same can be achieved with limited labeled dataset [167] . In this COVID-19 pandemic situation, availability of dataset, furthermore labeled ones, is an obvious challenge and hence transfer learning has immense potential to serve the purpose of COVID-19 detection. As an 1030 example, the study by [168] can be referred to where X-ray and CT images of COVID-19 cases were collected from the GitHub public repository. These where radiology imaging datasets have been found to be prevalent. But utilization of these implementations in real-world medical practice cases is a major concern that dictates the immediate need for benchmarking frameworks for the evaluation and comparison of the existing methodologies. These frameworks should enable the use of computational hardware related infrastructures consid- processing. We believe that the COVID-19 outbreak will be ending soon with 1100 help from DL and image processing techniques as well as many other technologies such as biomedicine, data science, and mobile communications. We also hope that our work is a good source of reference and can drive many novel studies on DL and medical image processing in the battle against the COVID-19
outbreak.
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Racial/ethnic inequities in US COVID-19 mortality are now widely documented: death rates are substantially higher among non-Hispanic Black (NHB), Hispanic/Latinx, and American Indian populations compared to non-Hispanic whites (NHWs). 1 There is also evidence of socioeconomic gradients in COVID-19 mortality, meaning residents of economically deprived neighborhoods experience the highest mortality and those in the wealthiest neighborhoods experience the lowest. 2 It is unclear, however, whether NHWs in high-poverty neighborhoods experience elevated mortality, or whether people of color living in wealthy areas are relatively protected. Discussions of racial/ethnic groups in relation to COVID-19 often lack context about the modifiable social and economic processes, rooted in structural racism, that lead to inequality. 3 Exploring the role of socioeconomic position in COVID-19 mortality in combination with race/ethnicity can help lead to a more detailed understanding of the specific processes that result in health inequities.
There are a number of key limitations to prior research on socioeconomic gradients for COVID-19 mortality, particularly because individual-level mortality data from 2020 are still largely unavailable to researchers. Without such data, it is difficult to determine whether socioeconomic gradients exist within racial/ethnic groups and whether these gradients are similar across groups. Additionally, prior studies of socioeconomic gradients in COVID-19 outcomes have rarely distinguished between populations residing in institutions versus households. This is a concern because a high proportion of COVID-19 deaths (exceeding 50% in many states) occur among persons in nursing homes. 4 While neighborhood-based measures such as poverty rates can serve as meaningful proxies for socioeconomic position for residents of households 5 , it is unclear whether the same is true for populations in intuitions (e.g. if nursing home's location in a high-poverty area, it may not indicate that its residents tend to be economically deprived).
For COVID-19 mortality, one prior study found that the full (institutional and household) population exhibited a weaker social gradient than the household population alone. 6 Analyses that do not differentiate between the two populations are likely capturing artifacts related to the geography of nursing home siting rather than the population distribution of COVID-19 by socioeconomic position.
. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted October 6, 2020. . https://doi.org/10.1101/2020.10.04.20206318 doi: medRxiv preprint This cross-sectional study characterizes race/ethnicity-specific socioeconomic differences in COVID-19 mortality for using a unique individual-level, open-access dataset on mortality in Cook County, Illinois (population = 5.2 million, about half of which resides in Chicago). It excludes deaths attributed to nursing homes and other institutions, restricting to deaths among the population in households. Informed by prior research on the population distributions of chronic conditions and mortality 7-10 , we hypothesized that COVID-19 mortality rates would exhibit socioeconomic gradients within each racial/ethnic group.
We obtained data on deaths due to COVID-19 that were reported in the Cook County, Illinois Medical Examiner Case Archive as of September 14, 2020. 11 The case archive includes cause of death fields along with demographic characteristics and geography, including an already geocoded "incident location" which, for COVID-19, corresponds to the place where the illness was first noted. We geocoded incident locations for which there was a non-missing street address but missing latitude and longitude. We identified deaths for which COVID-19 was indicated in one or more cause of death fields and had a race/ethnicity of NHW, NHB, or Hispanic/Latinx. There were too few deaths occurring among other racial/ethnic groups to be meaningfully analyzed.
The case archive did not have a field to indicate deaths linked to institutions. We identified these deaths for exclusion through (1) nearest-neighbor matching incident location centroids to skilled nursing facility centroids (using a distance cutoff of <250 meters) based on a statewide facility licensing database in Illinois, which contains data on licensed nursing homes and rehabilitation centers 12 ; (2) flagging incident locations that included "nursing home", "rehab", or similar in the street address field, or that shared coordinates with such a location; and (3) investigating, via web searches, any incident location appearing three or more times and flagging it if it was a nursing home, rehabilitation center, assisted living home, or . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted October 6, 2020. . https://doi.org/10.1101/2020.10.04.20206318 doi: medRxiv preprint hospital (according to state data, 97% of nursing home-related COVID-19 deaths in Cook County occurred in nursing homes with at least 3 total deaths 13 ).
We used the geographic coordinates for each non-institutional incident location to determine its census tract, a geographic unit akin to neighborhoods. The 2018 American Community Survey provided census tract poverty rates (% of the population living below the federal poverty level) and population denominators for rate calculations. Poverty quartiles ranged from >21.4% for tracts with the highest poverty rates to <6.6% for those with the lowest. We aggregated the data such that each row contained the sum of all deaths and the sum of the residential population for a given poverty quartile, racial/ethnic group, age category, and gender. We calculated adjusted mortality rates and 95% confidence intervals (95% CIs) for each racial/ethnic group and poverty quartile using direct standardization in Stata version 16 (Stata Corp., College Station, Texas), adjusting subgroups to the age and gender distribution of the full study population. We calculated mortality rate ratios and 95% CIs using standard methods, 14 with analyses for the entire study population and also stratified by age group for the younger (0 to 64 years) and older (≥65 years) populations.
As of September 29, 2020, the Cook County, Illinois Medical Examiner reported 5,216 total deaths due to COVID-19. The first death occurred on March 16, 2020 and the most recent occurred on September 27, 2020. We excluded 2,880 deaths (414 were not geocoded with precision, 184 had incident locations outside of Cook County, 2,113 were associated with nursing homes or other institutions, 146 were an excluded or missing race/ethnicity, and 3 were missing age or gender), yielding 2,336 included deaths (Table 1a) . Of included deaths, the mean age was 68 years (standard deviation = 15 years) and 62% were men.
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The copyright holder for this preprint this version posted October 6, 2020. . https://doi.org/10.1101/2020.10.04.20206318 doi: medRxiv preprint
The adjusted COVID-19 mortality rate for the total study population (N = 4,762,460) was 49.0 per 100,000 (95% CI: 47.1, 51.0). While the NHB population experienced the greatest number of deaths and highest crude mortality rate, its adjusted mortality rate (77.1 per 100,000; 95% CI: 72.0, 82.2; Figure Rate ratios comparing mortality in the highest-versus lowest-poverty quartiles within racial/ethnic groups of all ages were: 4.1 (95% CI: 3.3, 5.2) among NHWs, 1.6 (95% CI: 1.2, 2.2) for the NHB population, and 2.1 (95% CI: 1.5, 2.8) for the Hispanic/Latinx population. Socioeconomic gradients were present within all three racial/ethnic groups at both age ranges ( Figure 3 ). For the younger age group (<65 years), the mortality rate for NHWs in the highest-poverty quartile was 13.5 times that of NHWs in the lowestpoverty quartile (95% CI: 8.5, 21.4). Younger NHWs in the highest-poverty quartile had an adjusted mortality rate (37.8 per 100,000; 95% CI: 28.0, 47.6) similar to that of younger NHBs in the highestpoverty quartile (33.1 per 100,000; 95% CI: 28.2, 38.1). In contrast, younger NHBs and Hispanic/Latinx people in the lowest-poverty quartile had mortality rates nearly three times that of younger NHWs in the same quartile. For the older population (≥65 years) the mortality rate among NHWs in the highest-poverty quartile was less than that of even the lowest-poverty NHB and Hispanic/Latinx subgroups.
. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 6, 2020. . https://doi.org/10.1101/2020.10.04.20206318 doi: medRxiv preprint
Our analysis of household-related COVID-19 mortality in Cook County, Illinois identified new evidence of economic inequities within racial/ethnic groups. At both younger (<65 years) and older (>65 years) ages, COVID-19 mortality rates among NHWs, NHBs, and Hispanic/Latinx people exhibited social gradients by census tract poverty quartile. In the highest-poverty neighborhoods, younger NHWs and NHBs had similar mortality rates. In the lowest-poverty neighborhoods, however, younger NHBs and Hispanic/Latinx people had far higher rates than younger NHWs. For the older population, NHWs in the highest-poverty quartile were less likely to die of COVID-19 than even NHB and Hispanic/Latinx people in the lowest-poverty quartile.
One limitation of our study is that we were not able to remove the population residing in institutions from the denominators in rate calculations because census tract-level data were unavailable in the American Community Survey. However, census data for the state of Illinois show that <7% of people ages Our findings suggest racial/ethnic inequalities in COVID-19 mortality are partly, but not entirely, attributable to the higher average socioeconomic position of NHWs relative to the NHB and Hispanic/Latinx populations. Within poverty quartiles, there may be persistent racial/ethnic differences in COVID-19 risk factors for exposure (e.g. due to occupational hazards and residential crowding) and infection fatality rates (e.g. due to comorbidities and health care access/quality). Future research on health equity in COVID-19 outcomes should collect and analyze individual-level data on the potential mechanisms driving population distributions of exposure, severe illness, and death. In many US jurisdictions, death certificates already contain useful data on educational attainment and employment by . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 6, 2020. . https://doi.org/10.1101/2020.10.04.20206318 doi: medRxiv preprint occupation and industry, but these have not yet been made publicly available for the time period of the COVID-19 pandemic. Such data, available in a timely manner, would permit better understanding of these observed patterns and help guide prevention strategies.
Blaser is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 6, 2020. . 1 0 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 6, 2020. .
. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 6, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 6, 2020. . T a b l e 1 a . M o r t a l i t y d u e t o C O V I D -1 9 i n C o o k C o u n t y , I l l i n o i s b y r a c e / e t h n i c i t y a n d c e n s u s t r a c t p o v e r t y r a t e ( N o n -H i s p a n i c B l a c k , N o n -H i s p a n i c w h i t e , a n d H i s p a n i c / L a t i n x p e r s o n s ) . .
It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 6, 2020. M o r t a l i t y d u e t o C O V I D -1 9 i n C o o k C o u n t y , I l l i n o i s b y r a c e / e t h n i c i t y a n d c e n s u s t r a c t p o v e r t y r a t e ( N o n -H i s p a n i c B l a c k , N o n -H i s p a n i c w h i t e , a n d H i s p a n i c / L a t i n x p e r s o n s ) . A g e s 0 t o 6 4 , p o p u l a t i o n i n h o u s e h o l is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 6, 2020. l e 1 c . M o r t a l i t y d u e t o C O V I D -1 9 i n C o o k C o u n t y , I l l i n o i s b y r a c e / e t h n i c i t y a n d c e n s u s t r a c t p o v e r t y r a t e ( N o n -H i s p a n i c B l a c k , N o n -H i s p a n i c w h i t e , a n d H i s p a n i c / L a t i n x p e r s o n s ) . A g e s ≥ 6 5 , p o p u l a t i o n i n h o u s e h o l is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 6, 2020.
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Measles is an acute febrile illness caused by a virus that belongs to the family paramyxovirus in the genus Morbillivirus. It is characterized by fever (as high as 105 °F) malaise, cough, coryza, and conjunctivitis, followed by a maculopapular rash [1] . The rash usually appears 14 days after exposure and on the 3rd-5th day of clinical illness which spreads from head to trunk to lower extremities [2] . Measles is usually a mild or a moderately severe illness. However, measles can result in complications such as pneumonia, encephalitis and death. Post infectious encephalitis may occur in approximately one per 1000 reported measles cases. [3, 4] . In Childhood measles, approximately two to three deaths may occur for every 1000 reported measles cases [4] .
The annual incidence of measles in Sri Lanka during 1951-1960, 1961-1970 and 1971-1980 varied from about 20 to 47,18 to 38 and 12 to49 per 100,000 population respectively [5] . In 1982, this figure rose to 87/100,000 population. Following this outbreak, measles vaccine was introduced into the Expanded Programme of Immunization (EPI) of Sri Lanka in 1984, with recommendations to be administered at 9 months of age [5] . Morbidity and mortality of measles were reduced remarkably since then and by 1998, the prevalence rate was 0.5/100,000 population [5] . However, from October 1999 to June 2000, 15,204 suspected cases of measles were reported [5] . Among the clinically confirmed cases, 114/100,000 population occurred in less than 9-monthold age group followed by 81/100,000 population in the 15 to 19-year-old age group. Nearly 54% of the cases were above 15-year-old age suggesting a gradual shift of the disease to the older age groups [5] . During this outbreak, vaccination history was available in 3728 clinically confirmed cases. Of them 60% had not been vaccinated; 10% in the 5 to 9 year-old age group, and 38% in the 10 to 14-year-old age groups and of those who were above 15 years of age,more than 80% had not been vaccinated against measles [5] . There were 5 deaths, giving a casefatality rate of 0.1% [5] . The ages of those who died were 9 months and 4, 5, 17, and 24 years. Therefore, it was suggested that despite high immunization coverage, additional susceptible persons could be expected to join this non-immune cohort because the vaccine is only 85% effective [3, 4, 6] . Therefore, a second dose of measles vaccine was introduced to all children at the age of 3 years since 2001 in combination with rubella vaccine [MR (Measles and Rubella vaccine)]. In 2011 however MMR [Mumps, Measles and Rubella] vaccine was introduced at the age of 1 year and 3 years replacing measles vaccine at 9 months and MR vaccine at 3 years [7] . Furthermore, in March 2012, an additional immunization programme was instituted to cover the age group 4-21 years with view to cover all those who are likely to have had no or single dose immunization [7] . This is because, the "Revised Measles, Rubella, Congenital rubella syndrome elimination targets: September 2015" intends to eliminate measles from Sri Lanka by the year 2020 [8] . After 12 years of introduction of MR vaccine, from 2nd quarter of 2013 to 1st quarter of 2014, an island wide outbreak of nearly 4690 cases were reported from the country [9] . Of which, nearly 26% had been in the less than 1 year of age and nearly 38% had been in the age >12 years [10] . During this outbreak, 101 measles suspects were reported from Anuradhapura Teaching Hospitalin North Central Province of Sri Lanka, and 73/101 (72%) of them had been more than 12 years of age. Of the 73, nearly half were more than the age 29 years. Authors suggest change in the immunization schedule in 2012 as triggering factor for this outbreak [11] .
During the period, June 2014 to March 2016, 110 patients with measles were reported from the Colombo North Teaching Hospital (CNTH), Ragama, Sri Lanka and included 68 patients less than 12 years of age and 42 above 12 years of age (unpublished hospital data). Of them, we report clinical and demographic data of 12 adults with measles who presented to the Professorial Medical Unit of CNTH and 2 patients who were admitted to a Private hospital in Ragama in order to highlight several considerations that was thought important when dealing with adult patients with measles infection.
A retrospective study was carried out recruiting 14 adult patients with confirmed measles infection who were managed at the Professorial Medical Unit, Colombo North Teaching Hospital, Ragama, Sri Lanka during June 2014 to March 2016. Demographic and clinical data were retrieved retrospectively using a predesigned questionnaire with the help of ward records. Some other relevant data were later obtained by interviewing patients during their clinic visits and by telephone conversations.
Fourteen adult patients;8 males,with median age 32(range 25-48) years,presented with high fever, headache, severe body aches, a severe sore throat and a dry cough for 2-3 days duration. They complained of severe sore eyes around the 4-5th day associated with intense tearing. Examination revealed variable degree of posterior cervical lymphadenopathy and in 6 of them, typical Koplik's spots were noted in the buccal mucosa on the 3-4th day of illness. The eyes were injected around the 4th day and progressed to develop red eyes over the next few days (Fig. 1) . Five of them developed sub-conjunctival haemorrhages. The patients with severe conjunctivitis had photophobia and intense tearing requiring treatment by ophthalmologists. Around the 5th day of clinical illness, they developed a discrete maculopapular rash starting in the forehead and the face which spread to involve the upper chest, back and the limbs including palms and soles by the 7th day (Fig. 2 ). Almost all patients developed a dry cough on the 3rd day and 8 developed severe intractable cough and wheezing with the chest examination revealing wide spread coarse crackles and polyphonic rhonchi. In investigations on 3rd-4th day; the white cell count ranged 2.2-6.2 × 10 3 /dL with neutrophils ranging 34-53% and lymphocytes 35-55%. The lowest platelets ranged 96-152 × 10 9 /L. The C-reactive protein levels (CRP) ranged from 14 to 56 mg/dl. Almost all of these patients had derangements in the liver functions with ALT (Alanine aminotransferase) median (range) 246iu/L (128-367) and AST (Aspartate aminotransferase)178iu/L (96-236) with normal serum bilirubin and alkaline phosphatase levels. Around the 5-7th day, eight patients had coarse crackles wide spread over the lung fields, rises in the white cell counts (9.3-11.5 × 10 3 /dL; N 65-78%), high CRP levels (24-110 mg/dL) and chest radiographs showing bilateral patchy opacifications (2-5 mm) suggestive of varying degrees of lower respiratory tract involvement and required management with intravenous cephalosporins (cefuroxime or cefotaxime). Altogether, the illness lasted up to about 10 days and had high fever spikes ranging from 102 to 104 °F for about 6-7 days in a majority of cases. The fever regressed with the fading of the rash and was followed by peeling of the facial skin and the palms and soles. All 14 patients were positive for measles IgM antibodies confirming the diagnosis. They were negative for dengue NS1 Ag. On further questioning none of these patients knew whether they had measles immunization as a child nor had immunization records available with them. Furthermore, they were not aware of recent recommendation of immunization for those who were above 25 years of age. When questioned whether they would have obliged to obtain such immunization, they raised doubts as to whether such immunization is really necessary at their age. While only 10 of themhad heard of measles, 8 thought it was an illness in the childhood and adults had nothing to do with it. Furthermore, two patients had regular foreign travel to regional countries for business or occupation related purposes, one had travelled to India on Buddhist pilgrimage several occasions over the last four years. None of the others have travelled outside the country. While one patient who arrived for follow up visit had become aware that the receptionist in his private company had been ill with a similar illness about two days prior to his illness, none of the others were aware of such illness among their work mates or among other associates. However they were travelling in public transport very often for daily needs. The last patient to be included in the cohort was a sister of a final year medical student who had been doing the paediatric clinical appointment at the time she developed the illness.
Eradication effort has to permanently eliminate a pathogen everywhere in the world thereby removing the risk of reintroduction and re-establishment. Elimination, on the other hand, focuses on reduction to zero incidence of a certain pathogen in a given area, with active measures to prevent pathogen re-establishment from other areas after elimination. During an elimination process, once an infection is driven to very low levels, the ecology of pathogens may change requiring different surveillance and control strategies [12] . Susceptible build-up, waning of immunity, increase in the age of infection, non-compliance of individuals with control measures, pathogen change and emergence of resistance as a result of intensified efforts all become increasingly important during the final stages of such programmes [12] . Therefore, in order to achieve targets for elimination of vaccine preventable highly contagious illnesses such as measles, in addition to the maintenance of vaccination integrity, all other likely contributory factors for the illness in the community needs to be timely identified and intervened.
CNTH is the only tertiary care institution in the Gampaha district of the Western Province of Sri Lanka. Although it does not represent the status of hospitals in the whole of Sri Lanka, Western Province or the Gampaha district, the two hospitals included here are likely to represent the basic infrastructure facilities that are available in most of the government hospitals and the private sector hospitals. Firstly, the adult patients who presented to both hospitals had at least 3-4 days of admission until the diagnosis was made. The patients who were admitted to CNTH were kept in a busy medical unit, among most other patients with either acute or chronic ill health. The reasons for the delay in the diagnosis included non-awareness of its occurrence, unfamiliarity of clinical illness among adults and non-specific nature of the clinical illness that mimicked any other common acute tropical febrile illness.
Since all these patients were above 25 years of age it is likely that they had no or partial immunization against measles by natural mechanisms or through National Immunization programme. During the acute phase of illness (first 4 days) all these patients presented with an illness that mimicked acute dengue or any other common acute febrile illnesses in the tropical setting. Although they were negative by NS1 antigen they were kept under close monitoring as almost all of them had reducing or low platelet counts and derangement in hepatic enzymes. Although the development of the facial rash together with red tearing eyes suggested the possibility of measles, its diagnosis was delayed at least in the first few patients due to unfamiliarity of the illness in adults. It mimicked chikungunya fever in some cases due to severe arthralgia and the non-specific nature of the rash and its pattern of involvement [13] . Furthermore, a similar clinical illness seems to occur in Zika virus infection [14] although it is yet to be documented in Sri Lanka.
Almost all of these patients were managed in a busy clinical setting and amongst other patients with acute or chronic illnesses such as diabetes mellitus, chronic liver disease or chronic kidney disease where immune deficiency is known to occur. In multi-specialty tertiary care centers there is a possibility of transmission to immunecompromised and pregnant patients as well as to nonimmune staff who may in turn care for high-risk patients [15] . Although we were not made aware of any occurrence of measles among patients or the ward staff who had close contact during the management of these patients, influx of patients with measles to busy multidisciplinary tertiary care centers during community outbreaks of measles have resulted in nosocomial outbreaks [16, 17] .
Early diagnosis of measles and isolation of such patients would be the most ideal strategy in order to prevent spread and occurrence of spread to other nonimmune patients or health care workers. However currently there are no early diagnostic facilities available for measles and there are no isolation facilities available in CNTH or most other major hospitals in Sri Lanka. Furthermore, it is very unlikely that such facilities would be realistic in most hospitalsof developing countries such as Sri Lanka. It is well known that acute febrile illnesses that occur in the tropics such as measles, dengue fever, typhoid fever, leptospirosis, and severe acute respiratory syndrome (SARS) can be confused with each other [18] . At presentation, these febrile illnesses share similar clinical features, including headache, myalgia, and rash. In the case of dengue fever clinical features of dengue haemorrhagic fever, such as bleeding and plasma leakage, are seen after the initial febrile phase is subsiding, typically after the third or fourth day of fever. Similarly rash of measles although non-specific, appears after the 4th day of the illness. Therefore illnesses with similar characteristics, such as dengue, leptospirosis, measles, etc. have been found difficult to discriminate on the basis of any clinical algorithm alone [18] . Therefore, the most important strategy to diagnose measles at a very early stage would be to develop molecular/antigen based rapid diagnostics with high sensitivity and specificity. However, it is very unlikely that such diagnostics would be developed and made available, cost effective or realistic for illnesses such as measles due to its low incidence and low mortality figures.
Although the most likely reason for measles infections in these adult patients would be the on-going low level measles infection in the community, we feel that it is important to consider other likely source of the measles virus especially in the adults. Such sources could be related to acquisition of the virus through foreign travel although none of these patients or their close contacts had a history of foreign travel closer to their being ill. This is because such infection is likely to introduce non-native genotypes of the virus resulting in severe outbreaks [19] . Furthermore potential for introduction of new virus-genotypes should be kept in mind asworld travel is rapidly expanding for many purposes such as for education, employment and tourism. Travel has been shown to cause importation of infections such as SARS, chikungunya, dengue and Zika virus to many parts of the world resulting in outbreaks or establishment of these infections in various geographical regions [20, 21] . Therefore, there is always a risk of transmission of illnesses like measles between countries.
The combination of molecular epidemiology and standard case classification and reporting seems to be very sensitive means to describe the transmission pathways of measles. Virologic surveillance in order to monitor the viral genotypes in a particular country or region over time seems very important in order to interrupt the transmission of endemic measles [22] . In order to address these issues, the Epidemiology Unit of Sri Lanka has implemented due measures to obtain comprehensive data collection from patients with measles including obtaining blood samples for genetic isolations [23] . However, it was noted that such operations have either been unaware of or slowed down due to sporadic nature of measles among the adult patients (unpublished data). Therefore, intensified public awareness, periodic reminding of medical institutions and implementation of proper monitoring systems may be warranted in order to achieve current goals towards elimination of measles by the year 2020.
In conclusion, clinicians who deal with adult patients should be made aware of the possibility of measles infection among acute febrile illness and be reminded of the symptomatology of measles in adults. Furthermore, it would be essential to understand the community implications of these sporadic cases of adult measles towards the ongoing efforts on eradication of measles both locally and globally. While availability of early diagnostic facilities would help in management of patients, isolation of the virus and genotyping are likely to play an important role in implementing effective immunization and help achieving the targeted elimination of measles by the year 2020.
Abbreviations SARS: severe acute respiratory syndrome; EPI: Expanded Programme of Immunization; MMR vaccine: mumps, measles and rubella vaccine; MR vaccine: measles and rubella vaccine; ALT: alanine aminotransferase; AST: aspartate aminotransferase; CRP: C-reactive protein; CNTH: Colombo North Teaching Hospital.
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Hintergrund Die Augenhornhautspende unterliegt gesetzlichen Regelungen, die die Sicherheit und Qualität des Gewebes sicherstellen und dem Empfängerschutz dienen. Bei neu auftretenden Krankheitserregern muss die Spenderprüfung angepasst werden.
Am 31.12.2019 wurde die World Health Organisation (WHO) über Fälle von Pneumonien unbekannter Ätiologie (China) informiert. Das verursachende Virus wurde als "severe acute respiratory syndrome coronavirus 2" (SARS-CoV-2) bezeichnet. Am 11.03.2020 erfolgte die Einstufung als eine Pandemie durch die WHO.
Die deutsche Bundesoberbehörde für Gewebeeinrichtungen, das Paul-Ehrlich-Institut, fordert präventive Maßnahmen bei der Prüfung der Eignung möglicher Spender. Diese beziehen sich auf bestätigte Kontakte mit SARS-CoV-2infizierten Personen und zurückliegende bestätigte SARS-CoV-2-Infektionen [1] . Eine erweiterte Spenderprüfung liegt im Ermessen der Gewebeeinrichtungen. Alle Spenden der Deutschen Gesellschaft für Gewebetransplantation gGmbH (DGFG) werden entsprechend einer strikten Risikobewertung unterzogen.
Derzeit ist die Gefahr einer SARS-CoV-2-Übertragung durch Gewebetransplantationen nicht bekannt.
Im Rahmen der Corona-Pandemie stellt sich die Frage, ob und mit welchen diagnostischen Möglichkeiten die Sicherheit der Hornhauttransplantate erhöht werden kann. Daher wird durch die MCH bei allen Gewebespendern routinemäßig postmortal ein gepoolter Nasopharynx-/ Konjunktivaabstrich mittels qRT-PCR auf SARS-CoV-2 getestet.
Im vorliegenden Fall ließ das schwach positive PCR-Signal aus dem prämortalen Abstrich vermuten, dass die Infektion der Spenderin mit SARS-CoV-2 bereits weitestgehend abgeklungen war. Wahrscheinlich hatte die Spenderin keine oder nur leichte Symptome, da sowohl die Anamneseerhebung im Krankenhaus als auch durch die Gewebeeinrichtung unauffällig war. Bedingt durch den im Grenzbereich liegenden CT-Wert des positiven prämortalen Tests ist das negative Ergebnis des postmortalen Tests nicht unerwartet. Die jeweiligen CT-Werte der einzelnen Tests (. Tab. 1) entsprechen den in der Literatur beschriebenen Daten [2] . Ein falsch positives Ergebnis erscheint daher sehr unwahrscheinlich, allerdings kann eine Probenkontamination nicht vollständig ausgeschlossen werden. Die erneute Prüfung der prämortalen Abstrichproben war aufgrund fehlender Rückstellungen nicht möglich.
Zum aktuellen Zeitpunkt wurden über 50 Spender mittels postmortalem Nasopharynx-/Konjunktivaabstrich getestet, bisher waren alle Ergebnisse negativ. Dies könnte aus der Tatsache resultieren, dass alle potenziellen Spender einer strengen Risikobewertung unterzogen werden und zudem die allgemeine Infektionsrate in der Spendenregion sehr gering ist. Im Netzwerk DGFG ist dies der einzige Fall, bei dem eine SARS-CoV-2-Infektion detektiert wurde.
Das Risiko der Virusinfektion über eine Gewebetransplantationistbishernicht einzuschätzen. Die Eignung vorhandener Tests für die postmortale Analyse ist unklar. Allerdings zeigten erste Untersuchungen an COVID-19-verstorbenen Patienten, dass SARS-CoV-2 in Kornea und Konjunktiva bei einem Teil der Patienten nachgewiesen werden kann, wenn auch mit vergleichbar geringerer Virus-RNA-Konzentration [3] . In einer anderen Studie mit geringerer Fallzahl konnte SARS-CoV-2 an okularen Geweben und intraokularen Flüssigkeiten nicht nachgewiesen werden [4] . Analysen zur Infektiosität von PCR-positiv getesteten Proben ergaben, dass die Virusanzucht aus Proben mit einem CT-Wert >24 und >8 Tage nach Symptombeginn nicht erfolgreich war [5] . Durch Analysen zur Korrelation von Viruslast und Anzüchtbarkeit der Viren in Zellkultur als Maß der Infektiosität lassen sich Grenzwerte ableiten, ab denen nur sehr geringe bis keine Infektiosität besteht. Das Robert Koch-Institut (RKI) hat empfohlen, dass ab einem CT-Wert >30 eine Kontrolluntersuchung zur Beurteilung weiterer Maßnahmen veranlasst wird [6] . Aktuell muss man davon ausgehen, dass eine Übertragung des Virus über transplan-tierte Gewebe wie Augenhornhautpotenziell möglich ist. Aufgrund der Anamneseerhebung fallen symptomatische Patienten als Gewebespender aus, sodass Patienten der präsymptomatischen Phase und symptomfreie Patienten als Risikogruppen verbleiben. Inwieweit diese Patienten ein Übertragungsrisiko darstellen, ist bisher unklar. Daher wäre es für den Empfängerschutz von Bedeutung zu wissen, ob ein Spender mit SARS-CoV-2 infiziert ist.
Dieser Fall zeigt deutlich die diagnostische Lücke der verwendeten Testmethoden, da mit weitestgehend identischen Methoden das Virus 45 h nach dem ersten Test nicht mehr nachgewiesen werden konnte. Erste Hinweise deuten darauf hin, dass bei einer SARS-CoV-2-Infektion spezifische Antikörper erst nach der Serokonversion ab dem 7. bis 14. Tag nachgewiesen werden. Der IgA-positive, aber IgGnegative Serumbefund spricht für eine akute oder kürzlich durchgemachte Infektion mit SARS-CoV-2. Der alleinige Antikörpernachweis ist daher nicht zur Akutdiagnostik empfohlen, sondern ergänzend zur Bestätigung eines positiven PCR-Abstrichtests. Die Verwendung von Antikörpertests sollte u. a. unter der Kenntnis der Spezifitätsund Sensitivitätswerte des verwendeten Testsystems erfolgen [6] . Auch der verwendete Antikörpertest besitzt einen begrenzt positiven Vorhersagewert [7] . Über welchen Zeitraum SARS-CoV-2-spezifische IgM-, IgA-und IgG-Antikörper detektiert werden, ist bisher unklar, zumal im Nasen-Rachen-Raum trotz auskurierter COVID-19-Erkrankung weiterhin Virus-RNA nachweisbar sein kann. In Vergleichsuntersuchungen bei infizierten Patienten mit milden vs. schweren Symptomen wurden bei mild verlaufenden SARS-CoV-2-Infektionen erst 8 Tage nach Symptombeginn IgA-Antikörper nachgewiesen, wobei eine Korrelation zwischen der Intensität der Symptome und des Beginns des Nachweises bestand [8] . In Fällen mit schwachen Symptomen kann der Nachweis für IgG-Antikörper ausbleiben oder verzögert sein.
Der in dieser Arbeit vorgestellte Fall verdeutlicht folgende Fakten: Im Fall der symptomarmen bzw. -freien Patientin zeigt sich deutlich die Wichtigkeit der routinemäßig durch die Kliniken durchgeführten Abstriche bei Aufnahme der Patienten, da der richtige Test zum richtigen Zeitpunkt durchgeführt werden muss [9] . Mit dem vorgestellten Fall kann keine Aussage darüber getroffen werden, ob der postmortale Abstrichtest für eine Prüfung auf SARS-CoV-2 geeignetist.Hierfürfehltdervalide Nachweis, dass mit dieser Methode postmortal eine Infektion mit SARS-CoV-2 sicher festgestellt werden kann. Ob ein vorgeschlagener Test der entnommenen Augenhornhaut bzw. des Kulturmediums mittels qRT-PCR [10] für einen SARS-CoV-2 Nachweis geeignet wäre, bedarf weiterer Analysen.
Nach der Serokonversion [9]
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The novel coronavirus SARS-CoV-2 has fueled a global pandemic, with more than 37 million confirmed COVID-19 cases and 1 million deaths as of October 12, 2020 [1] . Transfusion of convalescent plasma from recovered individuals with a mature antibody response has been successfully used for post-exposure prophylaxis and treatment during other disease outbreaks, including two other coronaviruses: severe acute respiratory syndrome (SARS-1) and Middle East respiratory syndrome (MERS) [2, 3] . In response to the SARS-CoV-2 pandemic, many countries and blood collection agencies rapidly established COVID-19 Convalescent Plasma (CCP) collection, processing, and distribution programs during the first half of 2020, with several clinical trials underway. Preliminary evidence suggests that CCP is a safe treatment for COVID-19 [4] , and ongoing randomized controlled trials are evaluating its efficacy [5] . Because CCP is a new and unique blood product, limited data are available regarding the operational challenges of CCP collection and distribution programs during an epidemic.
Using data from Vitalant, a nonprofit that collects approximately 14% of the US blood supply, we developed a simulation model of CCP donor recruitment, donation collection, testing, and distribution processes. In this paper, we use our simulation to evaluate how epidemic trajectory, donor recruitment and retention, collections capacity, and demand impact ability to meet competing priorities of current clinical demand and stockpiling CCP for future use in 11 different U.S. states. Our aim was not to replicate CCP collections in each state but rather to analyze and gain insights into the diverse set of drivers of a successful CCP program.
We ran our simulation for eleven epidemic trajectories while varying parameters related to CCP donor recruitment and return, collections capacity, and demand. Epidemic trajectories were based on calibrated state-level SEIR epidemic models developed and published by 'COVID Act Now'
[6]. We included 10 states with the highest cumulative per-capita COVID-19 hospitalization rate as of August 31, 2020 (New Jersey, New York, Massachusetts, Illinois, Louisiana, Connecticut, Indiana, Mississippi, Virginia, and Maryland) and California, which had the highest overall number of COVID-. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted October 27, 2020. ; https://doi.org/10.1101/2020.10.25.20219170 doi: medRxiv preprint 19 hospitalizations during this period. We excluded Washington D.C. despite having the highest estimated per-capita hospitalization rate because it had fewer than 10,000 total hospitalizations.
For each state we estimated daily hospital admissions and discharges from three reported outcomes in the COVID Act Now state-level models (hospital beds required, deaths, and infections by day) using a method described in the appendix. We ran 10,000 simulations of a 200-day period beginning on the date of the first discharge of a COVID-19 patient and calculated two daily outcomes: (1) the percent of CCP collection capacity utilized and (2) the percent of CCP demand unmet. In each simulation, we sampled seven input parameters related to donor recruitment and return, collections capacity, and CCP demand using uniform distributions.
Our simulation model consists of two linked components: (1) a microsimulation of the donor recruitment, return, collections and CCP screening processes and outputs a number of usable units collected by day (2) a production model that accounts for production lag, demand, distribution and inventory.
In the simulation, potential CCP donors (agents) entered the model at discharge from hospital and become eligible for CCP donation 14 days later. Across simulations, we varied the probability a recovered individual would be willing to donate CCP from 10% to 90%, and we varied capacity for new donor recruitment from 0.2 to 2 new donors each day per apheresis machine. Willing donors who were recruited each day entered the donor pool. Each day, donors in the pool would be selected randomly and scheduled for donations, subject to a collection capacity. Scheduled donations could be incomplete due to donor deferral for other reasons (2% probability) or failed or incomplete donation (1% probability). Completed donations could be removed from the CCP supply due to testing positive for disease markers (0.2% probability), not meeting the SARS-CoV-2 antibody release criterion (8% probability), or testing positive for HLA antibodies (9% probability for female donors). These probabilities were based on data from the first seven months of Vitalant's CCP program. Donors were eligible for another plasmapheresis donation after 7 days and remained eligible until 180 days post-discharge. For each donor, we sampled the minimum number of days until a subsequent donation from an empirical distribution fit to Vitalant CCP donation data. We developed separate distributions for time to . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted October 27, 2020. ; https://doi.org/10.1101/2020.10.25.20219170 doi: medRxiv preprint return for the donor's second, third, and fourth-or-greater donation, respectively, based on differences in return donation propensity observed in the data ( Figure S1 ). We assumed that donors who do not return by 130 days would never return: 57%, 31%, and 11% of donors never returned for a second, third, or fourth-or-greater donation, respectively.
In each state we varied the per capita number of apheresis machines from 4 to 55 per million residents. We assumed that each machine could support on average 3.5 CCP collection procedures per day and that 50% of machine capacity would be available for CCP collections. We based the range of per-capita apheresis machines on three states where over 90% of apheresis donations are collected by Vitalant: Colorado (8 machines per million residents), South Dakota (34 machines per million residents), and North Dakota (55 machines per million residents).
We calculated daily CCP demand from the estimated daily hospital admissions and 3 parameters: the probability each hospitalized COVID-19 patient requires CCP (varied from 10% to 45% of patients), the number of CCP units required per patient (varied from 1.5 to 4 units), and the average delay from admission to receiving CCP transfusion (varied from 1 to 5 days). In the simulation, the daily number of CCP units produced and any existing inventory was used to meet demand. If the available CCP exceeded demand it was added to inventory and available to meet future demand.
For sensitivity analysis, we performed a separate set of simulations in which we also varied donor return. To do so, we fit an exponential distribution to the probability a donor returns by ! days from their last donation of the form
We set ! & (the minimal return time) to 7 days in line with current practice, and fit . (the exponential rate parameter) and ' (the asymptote limiting donor return) to Vitalant data using maximum likelihood estimation. As before, we used separate distributions for the second, third, and fourth-or-greater donations. To vary return time, we added a scaling factor / as follows:
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This distribution leads to greater return when / > 1 and less donor return when / < 1. In sensitivity analysis we varried / from 0.5 to 2.25 only in the distribution for second donations.
To assess the sensitivity of the total percent demand unmet to each parameter, we regressed each parameter on the outcome using locally estimated scatterplot smoothing (LOESS) regression for each state. We then predicted the outcome at the 1st, 25th, 50th, 75th, and 99th percentile of each input. We assessed the degree to which the predicted outcome changed depending on the quantile of parameter used to predict it, an indication of how sensitive the ability to meet demand was to the parameter (or how important the parameter was). We developed an easy-to-use web-based modeling tool, available at https://vitalantri.shinyapps.io/ccp_model. All code is open-source and publicly available [7] .
19 patient discharge by 2 weeks, reflecting the delay in donor eligibility ( Figure 1 ). In periods when discharges fell sharply, capacity utilization fell more gradually. In more than 50% of simulations across all states, percent capacity utilized never exceeded 75% of available machine time, indicating that fully utilizing available collection capacity may be an important challenge.
In most simulations, states met most of the demand for most of the period despite relatively low capacity utilization ( Figure 2 ). Demand was more likely to go unmet during early increases in hospitalizations, particularly in states with very steep hospitalization increases (e.g., New York).
Most of the demand was met in most simulation for states with more gradual increases (e.g., Virginia and California). In states with two epidemic peaks (e.g., Louisiana, Indiana) demand was mostly met during the second wave using inventory stockpiled during the downswing from the first peak.
The sensitivity of percent demand unmet to uncertain parameters is plotted in Figure 3 for four states and in Figure S2 for the other states. Apheresis machine capacity was a strong determinant of the percent demand unmet. Given that we assumed recruitment capacity was proportional to the number of machines, some of that benefit could be attributed to increased donor recruitment. Both the fraction of hospitalized patients requiring CCP and the number of units . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 27, 2020. ; https://doi.org/10.1101/2020.10.25.20219170 doi: medRxiv preprint transfused per patient were more important parameters than the delay from admission to CCP administration. The scale multiplier on donor return did not substantially impact ability to meet demand. In most states the probability COVID-19 recovered individuals were willing to donate was the most important donor-related parameter. However, the daily donor recruitment capacity was more important in New York and New Jersey. Both these states experienced very early, steep epidemic trajectories that yielded many potential CCP donors, which may explain why capacity to recruit was a more important parameter than willingness to donate.
While donor willingness to return was not a driver of outcomes in our simulations, the percentage of donors deferred or unwilling to return increased to very high levels over the simulation period in all states ( Figure S3 ), indicating that it could be important over a longer time horizon and when insufficient CCP donors are recruited during initial epidemic peaks.
Unexpectedly, our analysis suggests that blood centers may struggle to fully utilize capacity and meet demand for CCP collections, particularly during rapid increases in the epidemic. In periods when demand is not quickly growing, blood centers can likely meet demand even when capacity utilization is fairly low. While ability to meet demand was sensitive to several parameters, epidemic trajectory was most important ( Figure S4 ). Our simulations also demonstrated that having inventory on hand before an increase in demand greatly increased ability to meet demand.
The evidence base for CCP, and both operational practices and regulatory policies are evolving rapidly. Our simulations were informed by Vitalant's CCP program, which may differ from that of other blood collectors. We further assumed an early start to and stable efforts in recruitment and collection, rather than a gradual ramp-up. Despite these limitations, our analysis reveals key drivers of the ability to utilize capacity and meet demand for CCP during an epidemic.
. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 27, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 27, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 27, 2020. ; https://doi.org/10.1101/2020.10.25.20219170 doi: medRxiv preprint . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 27, 2020. The published 'COVID Act Now' model output time series do not include new recoveries or hospital admissions and discharges. However, these can be estimated from the variables that are provided:
Given the following identities: is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 27, 2020. ; https://doi.org/10.1101/2020.10.25.20219170 doi: medRxiv preprint By assuming that the proportion of recoveries that represent discharges from hospital is equal to the proportion of infected individuals that are hospitalized, we can obtain the number of discharges from hospital by day:
Once we have estimated the number of discharges by day, we are able to obtain the number of new hospital admissions by day:
To estimate the number of ICU admissions by day, we assumed that: ICU admissions $ = < * ⋅ admissions $ + < ' ⋅ admissions $!+ . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted October 27, 2020. ; https://doi.org/10.1101/2020.10.25.20219170 doi: medRxiv preprint Figure S2 Sensitivity of percent demand unmet over simulation period to seven parameters. Seven states shown here; other four states are shown in Figure 3 . The predicted percent demand unmet based on five quantiles of each parameter is plotted. Greater distance between plotted points indicates greater sensitivity to that parameter.
Total percent demand unmet . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
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In Brief Cai et al. demonstrate that phosphorylation of the catalytic subunit PDHA on Ser295 and S314 by AMPKa is essential for the maintenance of pyruvate dehydrogenase complex activity and TCA cycle. Activation of AMPKa-PDHA axis predicts poor metastasis-free survival in breast cancer patients and facilitates tumor lung metastasis.
Cancer-related death is largely attributed to metastasis, which involves multiple steps of biological processes (Steeg, 2016; Wirtz et al., 2011) . Although metastasis is life threatening, it is extremely challenging for disseminated cancer cells to successfully seed metastases from their primary site (Chambers et al., 2002) . During this risky process, cancer cells encounter tremendous crisis, including anoikis and shear stress-induced apoptosis in systemic circulation (Douma et al., 2004; Reymond et al., 2013) , hyper-oxidative stress when colonizing at the distant organ (Piskounova et al., 2015) , as well as metabolic stress when exposing to new inhospitable environments (Kim et al., 2017; Senft and Ronai, 2016b) . Only less than 0.02% of metastatic cancer cells, once getting into the circulation, could survive in the secondary site (Chambers et al., 2002; Luzzi et al., 1998) . It has been proposed that metabolic reprogramming confers metastatic cancer cells to adapt to hostile environments with metabolic stress (Celià -Terrassa and Kang, 2016) and oxidative stress (Wu et al., 2014) .
The role of cancer metabolism in cancer progression and metastasis starts to emerge. Accumulating evidence reveals that cancer cells display distinct metabolic states with respect to their normal counterparts. They often utilize aerobic glycolysis known as Warburg effect to generate energy, building blocks, and NADPH to maintain redox balance for their survival and proliferation. Such metabolic reprogramming, which is believed to play important roles in cancer progression and metastasis, could be partly due to the defect in mitochondria TCA cycle and/or mitochondria functions resulting from the mutations of TCA cycle enzymes (Mullen and DeBerardinis, 2012) . Therefore, it is thought that defect in mitochondria activity may be a common event associated with Warburg effect and cancer progression. However, such concept has been challenged and may need to be revisited, because recent studies demonstrated that mitochondria activity is fully functional in cancers on the basis of 13 C-labeled metabolomic analysis (Corbet and Feron, 2017) and that PGC1a (peroxisome proliferator-activated receptor gamma coactivator 1-alpha), which could induce mitochondrial biogenesis and oxidative phosphorylation, promotes metastasis (LeBleu et al., 2014) . Mitochondria TCA cycle also generates energy and building blocks for cells to maintain their survival, but hyperactivation of TCA cycle was previously considered to produce excess reaction oxygen species (ROS) that is otherwise toxic to cells; however, more recent reports also suggest the essential role of certain TCA intermediates, such as oxaloacetate (OAA) and a-ketoglutarate (a-KG) in detoxification of ROS (Sawa et al., 2017) . It is currently unclear about what exact roles the mitochondria TCA cycle plays in cancer progression and metastasis.
AMPK is a classical energy sensor activated under diverse stresses, such as metabolic and oxidative stresses (Hardie et al., 2012) . It activates ATP-producing pathways but limits ATP-consuming pathways in response to metabolic stress. As such, its function is tightly regulated, and the defect in its function is associated with aging process and multiple metabolic disorders (Burkewitz et al., 2014; Ruderman et al., 2013) . AMPK is thought to serve as a tumor suppressor because of its role in suppressing oncogenic mTORC1 activation (Shackelford and Shaw, 2009) , and the fact that numerous anti-cancer agents, such as metformin (So snicki et al., 2016) , phenformin (Appleyard et al., 2012) , and resveratrol (Puissant et al., 2010) , could all activate AMPK. However, some studies revealed that AMPK may promote tumorigenesis by maintaining redox balance and inducing Akt activation (Han et al., 2018; Jeon et al., 2012) . Therefore, the role of AMPK in cancer regulation is controversial. Interestingly, AMPK deficiency renders cancer cells more vulnerable to stresses, including metabolic stress and cell detachment, which are critical barriers needed to be overcome during cancer metastasis, although the underlying mechanisms are not well understood (Ng et al., 2012; Saito et al., 2015; Svensson and Shaw, 2012) .
Pyruvate dehydrogenase complex (PDHc), as a rate-limiting enzyme complex for maintaining TCA cycle, catalyzes pyruvate to acetyl-coenzyme A (Ac-CoA) and links glycolysis to oxidative phosphorylation (Sun et al., 2015) . This trimeric complex consists of rate-limiting E1 (pyruvate dehydrogenase, composed of catalytic a [PDHA] and regulatory b [PDHB] subunits), E2 (dihydrolipoyl transacetylase [DLAT] ), and E3 (dihydrolipoyl dehydrogenase [DLD] ), and the integrity of this complex is critical for PDHc activity (Zhou et al., 2001) . How PDHc activity is maintained is currently not well understood. It was previously shown that PDHA S293 phosphorylation serves as a negative signal for PDHc activation, and the removal of PDHA S293 phosphorylation is necessary for PDHc activation (Patel et al., 2014) . However, the molecular basis of how PDHA S293 phosphorylation serves as a barrier for PDHc activation is unclear. Moreover, little is known about what physiological cues may prevent and/or antagonize PDHA S293 phosphorylation.
Although dysregulation of PDHc leads to multiple metabolic disorders and neurodegeneration (Brown, 2012) , its role in cancer progression and cancer metastasis is still elusive. Previous study reported the PDHK1, which phosphorylates PDHA and suppresses PDHc activity upon hypoxia, displays oncogenic activity in certain cancer contexts, such as lung cancer (Hitosugi et al., 2011) , implying tumor suppressor function of PDHc. However, more recent publication indicated that depletion of PDHc E1 b subunit (PDHB) resembles Warburg effect with impaired PDHc activity but compromises breast cancer growth (Yonashiro et al., 2018) . Therefore, the role of PDHc in cancer regulation appears to be controversial. In this study, we aimed to dissect the role of PDHA, the critical rate-limiting catalytic subunit of PDHc, in cancer metastasis and its underlying mechanisms.
The TCA cycle maintenance is affected by mitochondria homeostasis, which is dynamically regulated by mitochondria biogenesis and mitophagy (Palikaras et al., 2015; Senft and Ronai, 2016a) . Interestingly, mitochondria biogenesis and mitophagy are known to be regulated by AMPK (Marin et al., 2017; Pei et al., 2018) . AMPK is widely believed as a tumor suppressor for its role in repressing mTOR activation (Shackelford and Shaw, 2009), although oncogenic activity of AMPK in certain tumor contexts is also reported (Han et al., 2018; Jeon et al., 2012) . Surprisingly, overexpression of AMPK was associated with shorter metastasis-free survival in breast cancer cohort (Figure S1A) . Because AMPK regulates cancer cell survival under metabolic stresses (Saito et al., 2015; Svensson and Shaw, 2012) , which are critical barriers needed to be overcome during cancer metastasis, we hypothesized that AMPK may be a critical player for cancer metastasis by empowering cancer cells to adapt to diverse stresses in the metastatic microenvironments. To address this question, we generated 4T1 orthotopic model by inoculating 4T1 breast cancer cells into mammary fat pads that develop spontaneous metastasis to lung and harvested both primary tumor and metastatic tumor tissues for immunohistochemistry (IHC) staining ( Figure 1A) . Notably, by staining p-AMPK (T172), AMPK activity was higher in lung metastatic tumor than primary tumor ( Figure 1A) , indicating that AMPK activation may be essential for metastatic adaptation of metastatic processes. In support of this notion, impairment of AMPK activation by AMPKa1 depletion ( Figure S1B ) abolished cancer lung metastasis using 4T1 orthotopic metastasis models ( Figure 1B) . However, the primary tumor growth was not significantly affected upon AMPKa1 deficiency in 4T1 cells ( Figure S1C ). By using tail vein injection metastasis model, AMPKa1 depletion also impaired lung metastasis in multiple cell models, including 4T1, 231, and Hep3B (Figures 1C, S1D, and S1E). Because AMPK activity is elevated in metastatic tissues where metastatic cancer cells frequently encounter metabolic stresses, we determined whether the impaired metastasis upon AMPK ll Article deficiency resulted from the failure of cancer cells to adapt to stressful conditions during the colonization process. Indeed, AMPKa1 knockdown rendered cancer cells more vulnerable to metabolic stress ( Figure 1D ) and enhanced apoptosis upon glucose deprivation (Figures S1F and S1G). Oxidative stress is another critical barrier preventing disseminated tumor cells from surviving in distant organ (Piskounova et al., 2015) . AMPKa1 knockdown also conferred cancer cells more sensitive to oxidative stress (Figures 1E, S1H, and S1I). Thus, AMPKa1 is critical for cancer cell survival under diverse stresses, thereby protecting metastatic cells from stress-induced cell death and maintaining cancer metastasis.
Although glycolysis via glucose utilization for the generation of energy and building blocks is considered as a major strategy for cancer cell proliferation and survival, this mechanism is likely impaired during cancer metastasis processes where metastatic cancer cells constantly experience metabolic stress and/or oxidative stress in the secondary site (Piskounova et al., 2015; Senft and Ronai, 2016b) . It is conceivable that metastatic cancer cells will need to rewire their metabolic demands from glycolysis to TCA cycle for the production of energy and building blocks, thereby allowing metastatic cancer cells to survive in the distant site (Pascual et al., 2018) .
Because activation of AMPK renders cancer cells to survive better under glucose deprivation, where TCA cycle may become a key strategy for cancer cell survival, we speculated that AMPK may be crucial for maintaining TCA cycle. Indeed, metabolomics study revealed that several key intermediates in TCA cycle, such as a-KG, fumarate, and oxaloacetate, were markedly decreased in AMPKa1 knockdown cells (Figure 2A ). Impaired a-KG level was also observed in multiple AMPKa1 knockdown cells and AMPKa1 À/À a2 À/À mouse embryonic fibroblasts (MEFs) (Figure 2B) . Moreover, ATP level and oxygen consumption rates (OCRs) were declined in AMPKa1-deficient cells (Figures 2C and 2D) . Thus, AMPKa1 is critical for TCA cycle maintenance.
However, the expression level of TCA cycle enzymes and other enzymes regulating the connection between TCA cycle and other metabolic pathways were not affected upon AMPK deficiency ( Figures S2A and S2B) . We also ruled out the possibility that AMPK regulates TCA cycle acting through its known targets, such as PGC1a functioning in mitochondria biogenesis (J€ ager et al., 2007) and ACC (acetyl-CoA carboxylase) involved in lipogenesis, a process squeezing acetyl-CoA needed for TCA cycle (Minokoshi et al., 2002) , as depletion of PGC1a or ACC failed to compromise TCA cycle, as indicated by a-KG and ATP level ( Figures S2C and S2D ). We then speculated that AMPKa1 may maintain TCA cycle partly through orchestrating glucose uptake (Wu et al., 2013) , because glucose is one of the major nutritional sources providing pyruvate for TCA cycle. AMPKa1 knockdown reduced glucose uptake and multiple metabolites from glycolysis, including pyruvate (Figures S2E and S2F) . However, the level of lactate, as final product of glycolysis, remained unchanged ( Figure S2G ), indicating AMPK may favor pyruvate shunting through TCA cycle instead of converting it to lactate.
To address whether AMPK maintains TCA cycle through directly facilitating pyruvate metabolism, we performed 13 Clabeled pyruvate-and glutamine-tracing experiments. Notably, the level of TCA cycle metabolites (citrate, fumarate, malate, and succinate) incorporated from 13 C-labeled pyruvate was reduced in AMPKa1 knockdown cells ( Figure 2E) . However, the level of corresponding TCA metabolites derived from 13 Clabeled glutamine was comparable between control and AMPKa1 knockdown cells ( Figure 2E ). Collectively, our data suggest AMPKa1 is an essential regulator for TCA cycle maintenance through controlling pyruvate metabolism.
PDHc Activation and TCA Cycle by AMPKa1 Are Required for Cancer Metastasis Pyruvate is located at the crossroads of glycolysis and TCA cycle, and its metabolic fate is mainly controlled by lactate dehydrogenase (LDH) and PDHc. The former facilitates glycolysis by converting pyruvate to lactate, although the latter maintains TCA cycle by catalyzing pyruvate to Ac-CoA ( Figure S3A ). LDH activity remained unchanged upon AMPKa1 knockdown ( Figure S3B ), but PDHc activity was impaired in AMPKa1 À/À a2 À/À MEFs and AMPKa1 knockdown cells ( Figure 3A ). As a consequence, the level of Ac-CoA, a direct product of PDHc from pyruvate, in both whole-cell lysates and mitochondria was markedly reduced in AMPKa1-deficient cells ( Figure 3B ). Thus, AMPKa1 is essential for maintaining PDHc activity.
Similar to AMPKa1 depletion, knockdown of PDHA, the catalytic subunit of PDHc, specifically impaired cancer metastasis to lung, but not primary tumor growth, using 4T1 orthotopic metastasis model (Figures 3C and S3C) and 231 tail vein injection metastasis model ( Figure 3D ), underscoring the fundamental role of PDHc in tumor metastasis. Remarkably, introduction of constitutively active PDHA (PDHA S293A), which restores PDHc activity in AMPKa1-deficient cells, but not wild-type (WT) PDHA, fully rescued the defects in TCA cycle, indicated by ATP and a-KG ( Figure 4A ), and tumor metastasis ( Figures 4B, 4C , S3D, and S3E). Thus, AMPK acts through PDHc activation to facilitate cancer metastasis. Data are means ± SEM from 5-7 mice for metastasis assays and means ± SD from 3 independent experiments for other assays. *p < 0.05 and **p < 0.01. See also Figure S1 . Please cite this article in press as: Cai et al., Phosphorylation of PDHA by AMPK Drives TCA Cycle to Promote Cancer Metastasis, Molecular Cell (2020), https://doi.org/10. 1016/j.molcel.2020.09.018 Activation of PDHc by AMPKa1 Empowers Tumor Cells to Survive under Various Stresses PDHA depletion also heightened the sensitivity of cancer cells to metabolic stress ( Figure 4D ), similar to AMPKa1 loss. Introducing active PDHA in AMPKa1 knockdown cells rescued cancer cell survival under metabolic and oxidative stresses (Figures 4E and 4F) . Interestingly, add-back pyruvate or a-KG largely rescued cancer cell survival under metabolic stress in control cells, but not in AMPKa1 or PDHA knockdown cancer cells where TCA cycle is compromised ( Figures 4D and 4E) . Remarkably, introduction of active PDHA in AMPKa1 knockdown cells enabled pyruvate or a-KG to protect cancer cells from death under metabolic stress ( Figure 4E ). Collectively, TCA maintenance ensured by AMPKmediated PDHc activation is essential for cancer cell survival under diverse stresses, thereby facilitating cancer metastasis.
Although PDHc is a crucial regulator for pyruvate metabolism and TCA cycle, how it is activated to participate in TCA cycle remains largely unclear. Earlier studies revealed that PDHA S293 phosphorylation by PDHKs serves as a negative mechanism to limit PDHc activation (Kolobova et al., 2001) . Interestingly, elevated PDHA S293 phosphorylation and enhanced interaction between PDHA and PDHK1 were observed in AMPKa1 knockdown cells ( Figures 5A and 5C ), accounting for the impairment of PDHc activity. Conversely, activation of AMPK upon either specific activator A-769662 or glucose deprivation resulted in dissociation between PDHA and PDHK1 and reduced PDHA S293 phosphorylation, which were reversed by AMPKa1 depletion or AMPK inhibitor compound C treatment ( Figures 5B, 5D , and S4A-S4D). Impaired interaction between PDHA and other PDHKs (PDHK2 and PDHK3) was also observed upon AMPK activation by glucose deprivation or overexpression of constitutively active AMPKa1 (AMPK-CA) ( Figure S4E ).
By IHC staining, comparing with corresponding primary tumor, we found elevated activity of PDHc, as indicated by lower expression of p-PDHA (S293), in metastatic tumor, correlated with enhanced activity of AMPK, as determined by p-AMPK (T172; Figure S4F ). However, both control and AMPKa1 knockdown primary 4T1 tumors displayed low AMPK and low PDHc activity. Of note, AMPKa1 knockdown in 4T1 cells, which impairs lung metastasis, remarkably reduced PDHc activity as indicated by enhanced p-PDHA level ( Figure S4F ), consistent with our in vitro results. To further support the pathophysiological link between AMPK and PDHc, we detected p-AMPK (T172) and p-PDHA (S293) in our in-house 184 breast cancer samples with different tumor stages and metastasis statuses by IHC staining. Notably, p-AMPK level was positively correlated with higher tumor stage, although p-PDHA level was negatively correlated with higher tumor stage ( Figure S4G ; Table S1 ). Moreover, the p-AMPK expression was negatively correlated with p-PDHA expression level (Figures 5E and 5F) . Importantly, high p-AMPK or low p-PDHA level predicted worse metastasis-free survival ( Figure 5G ; Tables S2 and S3), highlighting the importance of AMPK-PDHc axis in breast cancer progression and metastasis.
To gain further insight into how AMPK regulates PDHA S293 phosphorylation and PDHc activation, we determined whether AMPK can be localized in the mitochondrial matrix together with PDHc. To address this question, we performed mitochondrial isolation and mitochondrial subfractionation as previously described (Nishimura and Yano, 2014) . AMPKa could indeed localize in mitochondrial matrix with PDHA (Figures 6A and S5A-S5C). Further, AMPKa was found to interact with PDHA, but not with PDHK1 ( Figure S5D ). Moreover, active AMPKa colocalized with both PDHA and Tomm20 in mitochondria, as indicated by immunofluorescence staining (Figures 6B and S5E ). Thus, AMPK is localized in mitochondria matrix along with PDHc.
In light of these findings, we hypothesized that mitochondrialocalized AMPK could directly induce PDHA phosphorylation, thereby affecting PDHc activity. In vitro kinase assay revealed that PDHA could be readily phosphorylated by active AMPK complex in a dose-dependent manner ( Figure 6C ). AMPK complex could induce phosphorylation of Mff, a well-known AMPK substrate (Toyama et al., 2016) , but the overall phosphorylation of Mff was much lower than that of PDHA ( Figure 6C ). Additionally, g-32 P ATP incorporation kinase assays were conducted by incubating recombinant PDHA with different concentrations of active AMPK complex and g-32 P ATP to study the phosphorylation stoichiometry. The results indicate that AMPK gradually enhanced g-32 P ATP incorporation on PDHA in a time-dependent and dose-dependent manner. These results further demonstrate that AMPK serves as a direct kinase for PDHA ( Figure 6D ).
In vitro kinase assay followed by subsequent mass spectrometry analysis and combined bio-informatic phosphorylation site prediction indicated that AMPK induced PDHA phosphorylation at S295 and S314, which were highly conserved among various species ( Figures 6E, 6F , and S5F-S5H). We then developed and characterized phospho-PDHA antibodies at S295 and S314 (Figures S5I and S5J) . Using these phospho-PDHA antibodies, we validated that AMPK could specifically induce in vitro PDHA phosphorylation on S295 and S314 in a dose-dependent manner, which was abolished upon phospho-dead mutation on the corresponding site ( Figures 6G, S5K , and S5L). AMPK activation by either AMPK activator A-769662 treatment or glucose deprivation induced in vivo PDHA phosphorylation on serine 295 and 314, which was compromised upon AMPK deficiency ( Figure 6H ), indicating that AMPK activation facilitates PHDA S295 and S314 phosphorylation under physiological conditions. By performing IHC staining in lung metastatic tumor (E) The enrichment of isotope derived from 13 C3-labeled pyruvate or 13 C5-labeled glutamine in TCA intermediates and derivative (glutamate) from TCA cycle was determined by mass spectrometry analysis. Green circle: 13 C-labeled carbon atom derived from 13 C3-labeled pyruvate; yellow circle: 13 C-labeled carbon atom derived from 13 C3-labeled glutamine; blank circle: no isotope labeled carbon atom. Data are means ± SD from 3 independent experiments. *p < 0.05 and **p < 0.01. See also Figure S2 . ll Article tissues, enhanced p-AMPK level was positively correlated with elevated expression of p-PDHA (S295) and p-PDHA (S314) but inversely correlated with p-PDHA (S293) in control group, although impaired expression of p-PDHA (S295) and p-PDHA (S314) and enhanced expression of p-PDHA (S293) were observed in AMPKa1 knockdown group ( Figure S6A ).
In vivo S295 phosphorylation on PDHA was also validated by mass spectrometry analysis in cells either upon overexpression of constitutively active AMPK or glucose deprivation (Figures S6B and S6C) . Combined treatment of AMPK inhibitor compound C could abolish glucose-deprivation-induced S295 phosphorylation on PDHA ( Figure S6C ), suggesting that PDHA S295 is one of the major phosphorylation sites in vivo upon AMPK activation. Consistent with IHC staining results, S293 phosphoryla- Data are means ± SEM from 5-7 mice for metastasis assays and means ± SD from 3 independent experiments for other assays. *p < 0.05 and **p < 0.01. Scale bars indicate 500 mm. See also Figure S3 . tion and S295 phosphorylation inversely expressed ( Figures S6B and S6C ), indicative of the potential negative regulation between each other.
To investigate the role of AMPK-dependent phosphorylation on PDHA in PDHc activation, we activated AMPK by A-769662 treatment in both control and AMPKa1-deficient cells. A-769662 treatment enhanced activity of PDHc in control cells, but not in AMPKa1-deficient cells ( Figure 6I ). Moreover, we purified PDHc by pulling down PDHA and boosted PDHA phosphorylation by incubating it with active AMPK complex. Elevated PDHA phosphorylation after in vitro kinase reaction facilitated activation of PDHc (Figure 6J) . Collectively, these results indicate that PDHA phosphorylation by active AMPK enhances the enzymatic activity of PDHc. Notably, we found PDHA S295D or S314D, but not WT PDHA, PDHA S295A, or S314A, could rescue the defect of PDHc activity in AMPKa1-deficient cells ( Figure 6K ), indicative of the crucial role of AMPK-mediated PDHA S295 and S314 phosphorylation in PDHc activation.
PDHA S314 Phosphorylation Prevents It from Binding to Its Negative Regulator, and PDHA S295 Serves as an Intrinsic Catalytic Site To gain insight into how AMPK-mediated PDHA S295 and S314 phosphorylation maintains PDHc activity, we determined whether S295 and S314 phosphorylation affects PDHA-PDHKs interaction and PDHA S293 phosphorylation. Of note, PDHA S314D, but not ll Article WT PDHA or PDHA S314A, displayed impaired interaction with PDHK1 ( Figure 6L ), indicative of the suppressive role of PDHA S314 phosphorylation in PDHA and PDHK1 interaction. As a result, PDHA S293 phosphorylation was markedly reduced in PDHA S314D compared with WT PDHA and PDHA S314A (Figure 6M) . Surprisingly, both PDHA S295D and PDHA S295A displayed attenuated interaction with PDHK1 and decreased S293 phosphorylation when comparing with WT PDHA ( Figures 6L and 6M ). We rationalize that this result is likely due to the steric effect of S295 on S293, because these two sites are physically close with each other. Indeed, PDHA S295C mutant also exhibited impaired S293 phosphorylation ( Figure S6D ), suggesting that any substitution of amino acid on S295 would destroy the docking site of PDHKs, leading to reduced S293 phosphorylation. Data are means ± SEM from 5-7 mice for metastasis assays and means ± SD from 3 independent experiments for other assays. *p < 0.05 and **p < 0.01. Scale bars indicate 500 mm. See also Figure S3 .
Although both PDHA S295D and S295A mutants exhibit compromised S293 phosphorylation, only PDHA S295D, but not PDHA S295A, displays activated enzymatic activity of PDH complex, suggesting S295 phosphorylation is sufficient for determining the activity of PDHc. This result also suggests that, although loss of PDHA S293 phosphorylation elicits PDHc activation, the failure in S295 phosphorylation will drive PDHc inactivation, even when PDHA S293 phosphorylation is lost (e.g., PDHA S295A). Collectively, AMPK-mediated S314 phosphorylation, but not S295 phosphorylation, blocks the interaction of PDHA with PDHK1 and subsequent PDHA S293 phosphorylation.
We then assessed how PDHA S295 phosphorylation maintains PDHc activity. We rationalized that PDHA S295 phosphorylation may either regulate the integrity of the PDHc or serve as an intrinsic active site essential for PDHc activation. We ruled out the first possibility, as there was no difference between PDHA S295D and PDHA S295A in its interaction with other PDHc subunits ( Figure S6E ). To test the second possibility, we purified PDHc with WT PDHA, PDHA S295D, and PDHA S295A from cells and incubated them with C 14 -labeled pyruvate to determine the Please cite this article in press as: Cai et al., Phosphorylation of PDHA by AMPK Drives TCA Cycle to Promote Cancer Metastasis, Molecular Cell (2020), https://doi.org/10.1016/j.molcel.2020.09.018 amounts of C 14 -labeled pyruvate trapped in PDHc. Because the active PDHc could quickly and efficiently catalyze C 14 -labeled pyruvate, it is not expected to observe C 14 -labeled pyruvate trapped on the active PDHc. Of note, elevated C 14 -labeled pyruvate was detected in PDHc with PDHA S295A but decreased C 14 -labeled pyruvate in PDHc with S295D PDHA ( Figure 6N ). Similarly, enhanced C 14 -labeled pyruvate trapped on the PDHc was also observed in AMPK-deficient cells, which could be rescued by re-introduction of PDHA S295D, but not of PDHA S295A (Figure 6O) . Collectively, PDHA S295 phosphorylation is an intrinsic catalytic site critical for PDHc activation and pyruvate metabolism.
We determined whether PDHA S293 phosphorylation interferes with PDHA S295 phosphorylation and thus blocks intrinsic PDHc activity. Remarkably, S293 phospho-mimic mutant (PDHA S293D) abrogated PDHA S295 phosphorylation compared with the WT PDHA or S293 phospho-deficient mutant (PDHA S293A) ( Figure S7A ). Similarly, inhibition of PDHA S293 phosphorylation by DCA (dichloroacetate)-mediated PDHKs inactivation induced PDHA S295 phosphorylation ( Figure S7B ). PDHA S314A with enhanced S293 phosphorylation displayed compromised S295 phosphorylation, although PDHA S314D with impaired phosphorylation on S293 conversely exhibited increased S295 phosphorylation ( Figure S7C ). Although PDHA S314 phosphorylation is required for PDHA S295 phosphorylation, loss of PDHA S295 phosphorylation did not affect PDHA S314 phosphorylation ( Figure S7D ). Thus, PDHKs-mediated PDHA S293 phosphorylation serves as a barrier to prevent PDHA S295 phosphorylation, although AMPK-mediated PDHA S314 phosphorylation relieves the inhibitory effect of PDHA S293 phosphorylation on PDHA S295 phosphorylation, allowing for PDHc activation.
Phosphorylation of S295 and S314 by AMPK Is Essential for PDHA Function in TCA Cycle and Cancer Metastasis We investigated whether PDHA S295 and S314 phosphorylation is essential for the maintenance of TCA cycle. Only PDHA S295D or S314D, but not WT PDHA, PDHA S295A, or S314A, could rescue the defects in TCA cycle, as indicated by restored a-KG level and ATP level ( Figure 7A ), suggesting AMPK-mediated PDHA S295 and S314 phosphorylation maintains TCA cycle through activating PDHc.
To directly investigate whether PDHA S295 and S314 phosphorylation is critical for PDHA-mediated metastasis, we knocked in human WT PDHA and its mutants resistant to mouse PDHA short hairpin RNA (shRNA) to PDHA knockdown 4T1 cells and found that the introduction of PDHA S295D and S314D, but not PDHA S295A and S314A, rescued impaired lung cancer metastasis upon PDHA knockdown, albeit their expression level was still lower than endogenous mouse PDHA level ( Figure 7B ). However, WT PDHA only partially rescued impaired lung metastasis upon PDHA depletion, likely due to partial restoration of WT PDHA expression in PDHA knockdown cells ( Figure 7B ). PDHA mutants knockin did not affect primary tumor growth ( Figure S7E ). Remarkably, the impairment of tumor metastasis in AMPKa1-deficient cells was also rescued by expressing PDHA S295D or PDHA S314D, but not WT PDHA, PDHA S295A, or PDHA S314A, in both 4T1 orthotopic metastasis model and 231 tail vein injection model ( Figures 7C, 7D , and S7F), although the primary tumor was not affected by these treatment conditions ( Figure S7G ). Collectively, AMPK promotes PDHc activation, TCA cycle, and cancer cell metastasis through facilitating PDHA S295 and S314 phosphorylation.
Cancer cells are considered to bypass the TCA cycle and primarily utilize glycolysis based on the early dogma; however, emerging evidence indicates that certain cancer cells depend heavily on the TCA cycle for energy production and macromolecule synthesis (Anderson et al., 2018) . Thus, investigation of the exact function of TCA cycle and its regulation in various cellular contexts and different cancer progression stages may yield great insights into cancer metabolism and potential strategies for tackling advanced cancer. PDHc is a rate-limiting enzyme directly controlling pyruvate influx for the maintenance of TCA cycle, but its function in cancer progression is still under debate (Chen et al., 2018; Kaplon et al., 2013) . However, in our orthotopic breast cancer models, impaired PDHc activity by PDHA deficiency fails to affect primary tumor growth but dramatically impairs tumor metastasis, suggesting that PDHA is a previously unrecognized, oncogenic player that promotes tumor metastasis at least in breast cancer models. In further support of this notion, PDHc activity is significantly upregulated in our advanced breast cancer patient cohorts, and its activation correlates with poor metastasis-free survival of breast cancer patients. Thus, our study not only identifies PDHA as a biomarker for the prediction of tumor metastasis but also provides the evidence that targeting PDHc is a promising strategy for tackling breast cancer metastasis. Future study aiming to develop PDHc inhibitors, which are expected to achieve a promising efficacy for breast cancer metastasis, should be warranted.
How PDHc activity is regulated remains largely unknown. We provide a detailed model to explain how AMPK activation induced by metabolic stress inhibits PDHA S293 phosphorylation and maintains PDHc activity. AMPK triggers phosphorylation of PDHA on S314 and S295, which is required for PDHc activation. PDHA S295 phosphorylation is an intrinsic catalytic site required for PDHc activation and pyruvate metabolism, whereas PDHA S314 phosphorylation is a primed site required for subsequent PDHA S295 phosphorylation through preventing PDHA-PDHKs interaction and subsequent PDHA S293 phosphorylation, which serves as a barrier for PDHA S295 phosphorylation. The finding that AMPK-mediated PDHA S295 and S314 phosphorylation serves as a crucial step for PDHc activation provides the strategy of how PDHc can be pharmacologically targeted for the intervention of breast cancer metastasis.
(E) Immunostaining of p-AMPK (T172) and p-PDHA (S293) in breast cancer tissues with different stages were shown. (F) Scatterplot of pAMPK expression versus pPDHA expression in breast cancer tissues was shown. (G) Kaplan-Meier plots showed high expression of pAMPK and low expression of pPDHA significantly predicted metastasis-free survival. Scale bars indicate 100 mm. See also Figure S4 and Tables S1-S3. AMPK selects its substrate with the consensus motif of AMPK and prefers hydrophobic residues at À5 and +4 positions of actual phosphorylation site (Schaffer et al., 2015) . We identified PDHA S295 and S314 as two sites phosphorylated by AMPK. Consistent with optimal AMPK consensus motif, PDHA contains hydrophobic residues valine (V) and methionine (M) at +4 position for S295 and S314 sites, respectively, but histidine (H) for S295 and glutamic acid (E) for S314 at À5 position do not fit perfect AMPK consensus motif. However, there are also known AMPK substrates without this optimal consensus motif, such as H2B (Bungard et al., 2010) with arginine (R) at À5 position and PGC1a (J€ ager et al., 2007) with asparagine (N) and phenylalanine (F) at À5 position for two phosphorylation sites, respectively, indicating the complicity and flexibility of AMPK consensus motif. Moreover, basic residues at À3 position and serine (S) at À2 position are considered additional AMPK consensus motif. PDHA also contains histidine (H) at À3 position, serine (S) at À2 position for S295 and arginine (R) at À3 position, serine (S) at À2 position for S314. Using site-specific phospho-antibodies, PDHA S295 and S314 phosphorylation indeed occurs in vivo either upon A-769662 treatment or under glucose deprivation in an AMPK-dependent manner. Moreover, mass spectrometry analysis and site-specific phospho-antibodies from in vitro kinase assay reveal that AMPK phosphorylates PDHA on S295 and S314. Thus, PDHA is a bona fide substrate of AMPK.
Supplying a-KG could protect cancer cells with intact PDHc from metabolic stress, but not for cancer cells with compromised PDHc activation. Apart from its generation by TCA cycle enzyme IDH (isocitrate dehydrogenase), a-KG can be also produced through glutaminolysis (Villar et al., 2015) , which is considered as a key metabolic reprogramming for metastasis (Elia et al., 2018) . We rationalize that accumulating a-KG in disseminated cancer cells during metastasis may not only promote energy production and building blocks through TCA cycle maintenance but also orchestrate epigenetic reprogramming to empower cancer cell adaptation to hostile microenvironment through activating histone and/or DNA demethy-lases (Rinaldi et al., 2018) . a-KG also functions in regulating pro-survival signal, such as mTOR pathway (Durá n et al., 2012) , which regulates cancer cells survival under oxidative stress (Malone et al., 2017) . Thus, our study defines the critical role of AMPK-PDHc-TCA cycle-a-KG axis in cancer cell survival under diverse stresses, allowing for subsequent cancer metastasis.
In summary, our study defines the crucial role of PDHc and TCA cycle maintained by AMPK in empowering cancer cell survival in malicious environments for cancer metastasis (Figure 7E) . Moreover, we also reveal that activation of PDHc is maintained by AMPK through phosphorylating its catalytic subunit PDHA. The strategy through PDHA phosphorylation and PDHc activation by AMPK allows for breast cancer cell adaption to the hostile microenvironments for developing full-blown metastatic cancer. Our study advances our current understanding of how PDHc activity and TCA cycle are maintained and offers potential strategies to tackle cancer metastasis.
We demonstrated that AMPK induces PDHA phosphorylation in vivo under physiological conditions using multiple approaches. Importantly, we generated site-specific antibodies to validate PDHA S295 and S314 phosphorylation in cells upon AMPK activation. However, currently we are only able to detect in vivo S295 phosphorylation in cells using mass spectrometry analysis, which occurs in around 10%-20% of PDHA based on the number of S295 phosphopeptides versus total peptides (Figures S6B and S6C), although in vitro S314 phosphorylation was detected by mass spectrometry analysis ( Figure S5F ). We rationalize that this result may be due to the low abundance of PDHA protein with S314 phosphorylation in vivo condition and/or the condition for our mass spectrometry analysis that may not be fully optimized. Unfortunately, given the current situation with COVID-19, it is not possible for us to pursue further the mass spectrometry analysis. Thus, our future work will dissect how exactly the AMPK-dependent phosphorylation events regulate PDHc function.
(B) p-AMPK (T172) and PDHA co-localization was determined by immunofluorescence in cells upon A-769662 treatment. (C) Phosphorylation level on PDHA or Mff was determined by anti-phosphor-Ser/Thr antibody after in vitro kinase assay. L.E., long exposure; S.E., short exposure. (D) In vitro g-32 P ATP incorporation was determined by incubating recombinant PDHA and active AMPK complex with g-32 P ATP. (E) Phosphorylation level on PDHA was determined by anti-phosphor-Ser/Thr antibody after in vitro kinase assay (left). All the samples were subjected to SDS-PAGE, and PDHA bands were cut for mass spectrometry analysis. Phosphorylation statuses on each sample were shown (right). Relative phosphorylation intensity was indicated by the number of P. (F) Venn diagram was used to integrate phosphorylation site detected by mass spectrometry and phosphorylation site predicted by GPS 3.0 (group-based prediction system; http://gps.biocuckoo.org/). (G) S295 and S314 phosphorylation on WT PDHA and mutant PDHA after in vitro kinase assay was determined by PDHA-specific phospho-antibodies. Data are means ± SEM from 5-7 mice for metastasis assays and means ± SD from 3 independent experiments for other assays. *p < 0.05 and **p < 0.01. Scale bars indicate 500 mm. See also Figure S7 .
The authors declare no competing interests.
Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Dr. Hui-Kuan Lin ([email protected]).
The plasmids, stable cell lines and antibodies generated in this study have not been deposited to any repositories yet. These materials will be available upon request. MTA may apply.
The unprocessed data of immunoblotting have been deposited to
The animals used in this study include BALB/c (NCI BALB-cAnNCr) mice (Female, 6 weeks) for orthotopic metastasis model and nude (Crl:NU(NCr)-Foxn1 nu ) mice (Female, 6 weeks) for tail vein injection metastasis model. All the mice were purchased from Charles River Laboratories and group housed in a specific-pathogen-free facility under standard condition. All the related protocols were approved by Institutional Animal Care and Use Committee of Wake Forest School of Medicine.
Cell Culture 4T1, Hep3B, MDA-MB-231, 293T, AMPKa1 À/À a2 À/À MEFs were cultured in DMEM supplied with 10% Fetal Bovine Serum (FBS) and 1% Penicillin/Streptomycin at 37 C under 5% CO2. All the cell lines were tested to confirm no mycoplasma contamination.
All the patient tumor samples included in this study were retrieved from biobank that collected from female patients who underwent surgical resection in Chi Mei Medical Center from 1998 to 2004. The age of patients ranged from 27 to 85, with a mean of 51.5 and a medium of 50. As a rule, informed consent was obtained from all subjects and all the samples are anonymized. This study was approved by the Institutional Review Board (IRB) of the Chi Mei Medical Center (10210004).
Transfection and Viral Infection Calcium phosphate transfection method was used to transfect plasmids into 293T cells for virus package. Briefly, for lentiviral shRNA infection, 293T cells were co-transfected with pLKO.1-shRNA-puro constructs (Sigma) and packaging plasmids (pMD2G and pPAX). After 48h, virus containing supernatants were harvested to infect target cells. All stably transfected cells were selected by 3 mg/ml puromycin for 5 days. For PDHA S293A, S925D, S295A, S314D, S314A restoration in AMPK deficient cells, 293T were co-transfected with pBabe-PDHA S293A-neo or pCDH-PDHA S295D, S295A, S314D, S314A-blasticidin and package plasmids (Gag-pol/VSVG or pPAX/pMD2G). After 48h, virus containing supernatants were harvested to infect AMPK deficient cells. All stably transfected cells were selected by 1 mg/ml neomycin or 5 mg/ml blasticidin for 7 days.
RNA Isolation and q-PCR Cells were lysed by TRIZON reagent (Invitrogen) and total RNA were extracted according to the manufacture instruction. 2mg RNA was immediately processed to cDNA synthesis using PrimeScript RT Master Mix Kit (Clontech). q-PCR was performed in 20ul system containing 5ml H2O, 1ml P1 (10 mM), 1ml P2 (10 mM), 3ml diluted cDNA template and 10ml iTaq Universal SYBRÒ Green Supermix (Bio-Rad). The reaction was performed on ABI7300 Real-time PCR system. Melting curve analysis was used to guarantee the specificity of primers. b-Actin (ACTB) was used as an internal control and for normalization. DDCt method was used to indicate the relative expression level of corresponding genes. See Table S4 for a detailed primer list:
Metabolomics analysis and 13 C labeled Pyruvate/Glutamine tracing Methanol extraction was used to prepare metabolomics samples. Briefly, 2x10 6 cells were seeded on 10cm dish and refreshed with complete medium for 24h. After quickly aspirating cell culture medium, gently rinse the cells with 37 C PBS. Then immediately add 1 mL 8:2 methanol:H 2 O (À75 C, on dry ice) into the plates placed on dry ice and incubate for 30min at À75 C to quench metabolism and perform extraction. Scrape all the cells from dishes at À75 C, and transfer them into tubes. Add 0.7 mL 8:2 methanol:H 2 O (À75 C, on dry ice) to perform second extraction, scrape and transfer all the cell contents to tubes. Spin the mixture at 13,000 rpm for 5 min at 0-4 C. Remove all the soluble extract into a vial and completely dry samples using the Speedvac at 30 C. For 13 C labeled Pyruvate/Glutamine tracing assay, before extraction, the cells were treated with 13 C3 labeled Pyruvate or 13 C5 labeled Glutamine for 6h. Global metabolomics analysis was performed using Globally Optimized Targeted-MS (GOT-MS) by Northwest Metabolomics Research Center (NW-MRC) (Gu et al., 2015) .
The expression levels of a-KG, ATP and Ac-CoA level were determined by using Alpha-Ketoglutarate Colorimetric/Fluorometric Assay Kit (Biovision), ATP Determination Kit (Invitrogen) and Acetyl-Coenzyme A Assay Kit (Sigma) respectively. Briefly, 2x10 6 cells were lysed by corresponding assay buffer. Then deproteinize samples by using 10 kDa molecular weight cut off spin columns (Biovision). Perform specific reaction according to manufacture instruction and measure the absorption/luminescence/fluorescence using spectrophotometer.
Oxygen consumption rate was determined using a Seahorse Bioscience XF24 Extracellular Flux Analyzer (Seahorse Bioscience). 0.8x10 4 Hep3B and 1.5x10 4 MDA-MB-231 cells were seeded in specialized V7 Seahorse tissue culture plates for overnight. Before ll Article e4 Molecular Cell 80, 1-16.e1-e7, October 15, 2020
Please cite this article in press as: Cai et al., Phosphorylation of PDHA by AMPK Drives TCA Cycle to Promote Cancer Metastasis, Molecular Cell (2020 ), https://doi.org/10.1016 /j.molcel.2020 Lactate Level Detection Equal number of the cells was seeded in 6 well plate and refreshed with medium for 24h. Lactate level was determined by lactate test strips and Accutrend Lactate analyzer (Accutrend Lactate, Roche). Then the total cell number was counted, and the final concentration of lactate was presented as mM per 1x10 6 cells.
Activity of LDH was determined by using Lactate Dehydrogenase Activity Colorimetric Assay Kit (Biovision). 1x10 6 cells were homogenized with ice cold assay buffer and incubated on ice for 10min. Spin down at 10,000 x g for 15 min and transfer supernatant to fresh tube. Perform 100ml reaction (10ml sample, 40ml assay buffer, 50ml reaction mix) in 96 well plate. Measure absorption immediately at 450 nm in kinetic mode for 0-20 min at 37 C. According to manufacture instruction, calculate the LDH activity based on the alteration of absorption (DOD) during specific time frame (DT). Apply DOD to NADH Standard Curve to obtain B nmol of NADH generated. LDH Activity = B/(DT x 0.01) = nmol/min/ml = mU/ml Cell Survival under Metabolic or Oxidative Stress 2x10 4 cells were seeded in 24 well plate. After culturing overnight, the cells were treated with either glucose deprivation (for metabolic stress) or H 2 O 2 (for oxidative stress) with the supplement of vehicle, pyruvate (5 mM), a-KG (10 mM) for indicated 48h. Rinsing the well with PBS to remove the dead cells and stain the remaining cells with crystal violet. After dissolving in 2% SDS, absorption at 600nm was measured to calculate the relative survival rate for each group. Multiple wells were calculated, and the data were presented as means ± s.d.
Mitochondrial isolation and Mitochondrial subfractionation were performed as previously described (Nishimura and Yano, 2014) . Briefly, 1x10 8 cells were harvested after PBS wash and suspended in ice cold MTiso-buffer (3 mM HEPES (pH 7.4), 210 mM mannitol, 70 mM sucrose, 0.2 mM EGTA supplemented with protease inhibitor), then subjected to gently homogenize in a Dounce glass homogenizer using a glass ''B''-type pestle for 50-80 strokes. Pile up the homogenate on an equal volume of 340 mM sucrose and centrifuge it at 500 x g for 10min at 4 C to remove nuclei and unbroken cells as pellet. Collect the supernatant and then centrifuge it at 3,000 x g for 10min at 4 C to isolate mitochondria as pellet. To ensure the purity of the mitochondria, 10% mitochondria pellet was subjected to SDS-PAGE after boiling with SDS loading buffer. The expression levels of various sub-cellular biomarkers between whole cell lysates and intact mitochondrial lysates were determined by immunoblotting. For mitochondrial subfractionation, re-suspend the isolated mitochondria with 0.5ml of MTiso-buffer with 5 mg/ml digitonin, and mix the suspension intensely for 15min by vortex. Centrifuge the suspension at 10,000 x g for 10min at 4 C to isolate the pellet containing mitoplast (inner membrane plus matrix) and the supernatant containing solubilized outer membrane (OM) and inter-membrane space (IMS) proteins. Re-suspend the pellet (mitoplast) in 100 mL of MTiso-buffer, and perform sonication to disrupt mitoplast, and then centrifuge it at 100,000 x g for 30min at 4 C, resulting in inner membrane (IM) fraction as pellet and matrix fraction as supernatant.
Cells were transfected with Flag tagged WT or mutant PDHA. Fresh PDHc was purified through immunoprecipitation with Flag antibody and conjugated with protein A/G beads. Then the complex was directly incubated with C 14 -labeled pyruvate for 1h at room temperature. After washing with PBS for three times, pyruvate trapped in PDHc was determined by scintillation counter based on C 14 level.
In vivo Tumor Growth and Metastasis Assay 2x10 6 (1x10 4 for 4T1) cells with AMPKa1 knockdown, PDHA knockdown or AMPKa1 knockdown restored with constitutive active form of PDHA were injected into 7-week old female nude mice (n = 5-7 for each group) through tail veins. Two months later (35 days for 4T1), mice were sacrificed, and lung tissues were analyzed for the incidence of metastasis. All lung tissues were subjected to 10% formaldehyde fixation and paraffin embedding, followed by H&E (Hematoxylin and Eosin) staining, and metastatic nodules were further confirmed by microscope. For bioluminescence imaging, mice were provided with 150 mg/g D-luciferin through intraperitoneal injection. After 5 min, IVIS imaging system was used to detect bioluminescence. For spontaneous metastasis model, 1x10 4 4T1 cells were injected into the 4 th mammary fat pad of 7-week old female BALB/c mice (n = 5-7 for each group). Primary tumor was measured by Caliper for length and width every three to four days, and growth curve was documented based on the volume of tumor (V = (Length x Width x Width)/2). 35-40 days later, mice were sacrificed and lung tissues were analyzed for the incidence of metastasis. If no clear metastatic nodules were found, lung tissues were fixed with 10% formaldehyde and paraffin embedding, followed by H&E staining. ll Article e6 Molecular Cell 80, 1-16.e1-e7, October 15, 2020
Please cite this article in press as: Cai et al., Phosphorylation of PDHA by AMPK Drives TCA Cycle to Promote Cancer Metastasis, Molecular Cell (2020 ), https://doi.org/10.1016 /j.molcel.2020 QUANTIFICATION AND STATISTICAL ANALYSIS
Unless otherwise noted, all data were quantified based on 3 independent results and presented as means ± s.d. Two-tailed Student's t test was performed to calculate P value between different assay groups. For metastasis assay, the data were presented as means ± SEM from 5$7 mice and Wilcoxon rank sum test (non-parametric two sample t test) (Coffelt et al., 2015) was performed to calculate P value. For all analyses, p < 0.05 regarded as statistically significant was indicated by asterisk (*) and p < 0.01 regarded as statistically highly significant was indicated by two asterisks (**). All data were quantified based on 3 independent results and presented as means ± SD. ** represents p<0.01 by Student's t test. n.s. means no significance. Unless otherwise noted, all data were quantified based on 3 independent results and presented as means ± SD.
A B C D E F G Figure S4 : AMPK activation impairs PDHA phosphorylation on S293 through abrogating its interaction with PDHKs and activation of AMPK-PDHc axis predicts poor metastasis-free survival in breast cancer patients. (Related to Figure 5 ) (A) PDHA S293 phosphorylation was determined in cells treated with different concentration of glucose (4.5, 3, 1, 0g/L) for 4h (Left) or treated with glucose deprivation for indicated time (0, 2, 4h) (Right) by Immunoblotting. (B) Cells were treated with glucose deprivation alone or in combination with Compound C (5 μM), and phosphorylation level of PDHA on S293 was determined by immunoblotting.
(C) Control and AMPKα1 knockdown cells were treated with glucose deprivation, and phosphorylation level of PDHA on S293 was determined by Immunoblotting.
(D) 293T cells were treated with glucose deprivation alone or combined with Compound C and then subjected to IP assay with PDHA and IgG antibody. The interaction between endogenous PDHA and PDHK1 was determined by Immunoblotting.
(E) 293T cells transfected with Flag-PDHA were either treated with glucose deprivation or co-transfected with constitutively active form of AMPKα1 (AMPKα1 CA) to activate AMPK complex, and IP assay was performed with Flag antibody. The interaction between PDHA and PDHKs (PDHK1, PDHK2, PDHK3) was determined by Immunoblotting. Figure 6 ) (A) 293T cells were treated with glucose deprivation and subjected to mitochondrial isolation. AMPK level in both mitochondria and cytoplasm was determined by Immunoblotting. Cyto: cytoplasm; Mito: mitochondria. (B) Intact mitochondria were incubated with Digitonin to digest outer mitochondrial membrane for mitoplast isolation, and AMPK and PDHA level in mitoplast were determined by Immunoblotting. Tomm20 was marker for mitochondrial outer membrane.
(C) Mitochondrial isolation and sub-fractionation were performed, and various sub-cellular biomarkers between whole cell lysates and intact mitochondrial lysates were determined by Immunoblotting to ensure the purity of mitochondrial isolation (Left). AMPK and PDHA expression in mitochondrial matrix was determined by Immunoblotting (Right). Tomm20 is marker for mitochondrial outer membrane, COX4 is marker for mitochondrial inner membrane and CS is marker for mitochondrial matrix. WCL: whole cell lysis; Mito: Mitochondria.
(D) AMPKα1 interacts with PDHA but not PDHK1. 293T cells were transfected with HA-AMPK, and IP assay was performed with HA antibody. The interaction between HA-AMPK and endogenous PDHA or PDHK1 was determined by Immunoblotting.
(E) AMPK co-localizes with PDHA in mitochondria. MDA-MB-231 cells were treated with A-769662. p-AMPK (T172) and PDHA, p-AMPK (T172) and Tomm20 co-localization was performed by immunofluorescence. AMPK knockdown cells were used as a negative control to ensure the specificity of p-AMPK staining. Scale bars indicate 20 μm. (B) 293T cells were transfected with Flag-PDHA alone or co-transfected with constitutively active form of AMPKα1 (AMPKα1 CA), and then subjected to IP assay with Flag antibody. All the samples were subjected to SDS-PAGE and Flag-PDHA bands were cut for Mass Spec analysis. Raw Spectra and phospho-peptides identified on each sample by mass spectrometry analysis were shown. Relative phosphorylation intensity was indicated by the number of P on a schematic graph.
(C) 293T cells transfected with Flag-PDHA were treated with glucose deprivation alone or combined with Compound C, and then subjected to IP assay with Flag antibody. All the samples were subjected to SDS-PAGE and Flag-PDHA bands were cut for Mass Spec analysis. Raw Spectra and phospho-peptides identified on each sample by mass spectrometry analysis were shown. Relative phosphorylation intensity was indicated by the number of P on a schematic graph.
(D) Mutation on S295 abolishes PDHA phosphorylation on S293. 293T cells were transfected with Flag-PDHA WT, S295D, S295C or S295A, and IP assay was performed with Flag antibody. PDHA S293 phosphorylation was determined by Immunoblotting.
(E) PDHA S295 phosphorylation does not regulate the integrity of the PDH complex. 293T cells were transfected with Flag-PDHA WT, S295D, or S295A, and then subjected to IP assay with Flag antibody. The interaction between PDHA and other PDH complex components such as DLD, DLAT, PDHB was determined by Immunoblotting.
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Recently, several studies focused on developing value-added products from marine resources, providing a large number of biomaterials that are of economic importance. Marine organisms synthesize a variety of biopolymers having interesting and unique functional, structural and biological properties with multifunctional applications in different industrial sectors. They are mainly classified into three categories: polysaccharides, proteins and nucleic acids [1] . In particular, polysaccharides-alginate, chitosan, chitin, etc.-are used for multifunctional applications owing to their biodegradability and non-toxic potential. Marine biopolymers find great potential in theranostic applications owing to their stability and biocompatibility. They can be easily surface-modified due to the presence of hydroxyl, carboxyl and amino groups, which makes them preferred candidates for drug delivery applications [2] .
It is the main structural component of crab, lobster and shrimp exoskeletons. The crustaceous shells are mainly made up of chitin (20-30%), proteins (30-40%), calcium carbonate (30-50%), lipids and astaxanthin (less than 1%). The crustacean shells present a complex hierarchical organization. In crustacean shells, chitin macromolecules are the basic units that combine together to form chitin nanofibers. They occur as highly ordered crystalline microfibrils with strong intermolecular and intramolecular hydrogen bonding. Chitin has been known to form microfibrillar arrangements (2-5 nm) and long lengths (several μm) embedded in a protein matrix, forming chitin protein fibers with diameters ranging from 50 to 300 nm ( Figure 1b) . Then, this woven network of planes, wherein chitin is embedded in proteins and calcium carbonate, forms twisted or helicoidal stacking sequences, called a Bouligand structure [4, 6] . These chitin micro fibrils can be isolated and used as relevant reinforcements or functional agents in composite materials, as is discussed all in this review article.
Three allomorphs of chitin exist, namely, α, β and γ-chitin. The crystalline structures of α-chitin and β-chitin can be elucidated from the electron diffraction patterns of highly crystalline samples. There are two antiparallel chains per unit cell in α-chitin, contrary to β-chitin, which has a parallel arrangement. In γ-chitin two chains are arranged in one direction and the other chain in the opposite direction ( Figure 2 ). α-Chitin possess strong inter and intra sheet hydrogen bonding, whereas β-chitin has weak intra-sheet hydrogen bonding [7] . [4] . (b) Representation of native chitin nanofibrils in crustacean shells [5] .
It is the main structural component of crab, lobster and shrimp exoskeletons. The crustaceous shells are mainly made up of chitin (20-30%), proteins (30-40%), calcium carbonate (30-50%), lipids and astaxanthin (less than 1%). The crustacean shells present a complex hierarchical organization. In crustacean shells, chitin macromolecules are the basic units that combine together to form chitin nanofibers. They occur as highly ordered crystalline microfibrils with strong intermolecular and intramolecular hydrogen bonding. Chitin has been known to form microfibrillar arrangements (2-5 nm) and long lengths (several µm) embedded in a protein matrix, forming chitin protein fibers with diameters ranging from 50 to 300 nm ( Figure 1b) . Then, this woven network of planes, wherein chitin is embedded in proteins and calcium carbonate, forms twisted or helicoidal stacking sequences, called a Bouligand structure [4, 6] . These chitin micro fibrils can be isolated and used as relevant reinforcements or functional agents in composite materials, as is discussed all in this review article.
Three allomorphs of chitin exist, namely, α, β and γ-chitin. The crystalline structures of α-chitin and β-chitin can be elucidated from the electron diffraction patterns of highly crystalline samples. There are two antiparallel chains per unit cell in α-chitin, contrary to β-chitin, which has a parallel arrangement. In γ-chitin two chains are arranged in one direction and the other chain in the opposite direction ( Figure 2 ). α-Chitin possess strong inter and intra sheet hydrogen bonding, whereas β-chitin has weak intra-sheet hydrogen bonding [7] .
The extraction of chitin nanofibers or nanocrystals from the complex hierarchy of crustaceans' exoskeletons involves various steps. They include the preparation of raw chitin, including chitin extraction via the demineralization and deproteinization of shrimp, crab or lobster shell wastes; and finally, the isolation of nanochitin. Substantial efforts have been made to develop chemical, mechanical and enzymatic methods to obtain purified products. Initially, the matrix components such as protein and calcium carbonate are removed by treating the crustacean's shells with NaOH and HCl aqueous solutions, respectively. In actual practice the extraction of chitin from shellfish Due to its highly ordered crystalline structure, chitin is resistant to physical and chemical agents. Chitin is insoluble in most common solvents. This insolubility seriously limits the development and application of chitin. Chitosan, a well-known derivative of chitin, is formed through the enzymatic or chemical deacetylation of chitin. Chitosan is also a copolymer of β-(1→4)-N-acetyl-d-glucosamine and β-(1→4)-d-glucosamine [9] . The degree of acetylation (DA) helps to define chitin and chitosan. DA represents the proportion of N-acetyl-D-glucosamine units with respect to the total number of units. When the degree of deacetylation (DDA) of chitin reaches about 50%, the product is named chitosan and becomes soluble in acidic aqueous solutions [10] . Due to its biocompatibility, biodegradability and bioactivity, chitosan has several applications in waste-water treatment, agriculture, cosmetics and food processing [11] .
Chitin is biodegradable, and due to its biodegradable nature, it could find immense applications in packaging and composite materials. Due to the presence of chitinases and chitinase-like proteins in the human body, chitin has been used in surgical sutures, tissue engineering and drug delivery [12] [13] [14] . Chitin and chitin derivatives can stimulate immune cells and they also show significant anticancer activity [15] [16] [17] [18] . The effect of chitin against fungal disease candidiasis has also been reported [19] . Chitin nanofibrils and nanocrystals have shown UV-protection ability, a moisturizing effect and anti-aging properties and are used in skin protective formulations [20, 21] .
In order to meet the growing demand for chitin due to its unique properties, there has been profound interest in transforming the shellfish food industry's waste (mainly crab and shrimp) into useful products. Amid the COVID-19 crisis, the global market for chitin and chitosan derivatives estimated at 106.9 thousand metric tons in the year 2020, is projected to reach a revised size of 281.7 thousand metric tons by 2027, following a report from Global Industry Analysts Inc.,USA. Japan and USA are the leading producers of chitin, followed by India, Italy and Poland [22] . About 40-55% in the case of shrimp and over 70% in the case of crabs are discarded as waste during the transformation processing. Depending on the processing method, the waste of these species contains approximately between 10% and 55% chitin on a dry weight basis.
To make it more viable for practical applications, in the last 30 years, research has been directed towards nanoscale chitin materials. Nanochitin has a larger surface area than corresponding bulk materials, which favors the filler-matrix interactions, thereby resulting in enhanced performance of the final composite material. In this context, this review complies recent advances in nanochitin isolation and its use in composite materials.
The extraction of chitin nanofibers or nanocrystals from the complex hierarchy of crustaceans' exoskeletons involves various steps. They include the preparation of raw chitin, including chitin extraction via the demineralization and deproteinization of shrimp, crab or lobster shell wastes; and finally, the isolation of nanochitin. Substantial efforts have been made to develop chemical, mechanical and enzymatic methods to obtain purified products. Initially, the matrix components such as protein and calcium carbonate are removed by treating the crustacean's shells with NaOH and HCl aqueous solutions, respectively. In actual practice the extraction of chitin from shellfish involves the step-by-step removal of two major constituents of the shell, the intimately associated proteins by deproteinization and inorganic calcium carbonate by demineralization [23] . The pigments and lipids are removed by extraction with ethanol or acetone after the demineralization process with dilute hydrochloric acid at room temperature. A wide range of chemicals have been tried as deproteinization reagents, including NaOH, Na 2 CO 3 , NaHCO 3 , KOH, K 2 CO 3 , Ca (OH) 2 , Na 2 SO 3 , NaHSO 3 , CaHSO 3 , Na 3 PO 4 and Na 2 S. NaOH is the preferred reagent on the basis of its performance and typically a 1M NaOH solution is used with variations in the temperature and duration of treatment parameters. The use of NaOH invariably results in partial deacetylation of chitin and hydrolysis of the biopolymer that lowers the molecular weight of chitin [24, 25] . Normally the residual protein content in the chitin produced from conventional commercial sources is around 1%. This yields a partially deacetylated chitin. The obtained chitin flakes or powder can be further deacetylated to chitosan or used for the isolation of nanochitin: chitin nanowhiskers (or nanocrystals) and chitin nanofibers. As already mentioned, herein, we focus on recent advances in nanochitin isolation and its use on composite materials. As example, the schematic representation of steps involved in isolation of chitin nanofibers via ultra-sonication is shown in Figure 3 .
Polymers 2020, 12, x FOR PEER REVIEW 4 of 38 involves the step-by-step removal of two major constituents of the shell, the intimately associated proteins by deproteinization and inorganic calcium carbonate by demineralization [23] . The pigments and lipids are removed by extraction with ethanol or acetone after the demineralization process with dilute hydrochloric acid at room temperature. A wide range of chemicals have been tried as deproteinization reagents, including NaOH, Na2CO3, NaHCO3, KOH, K2CO3, Ca (OH)2, Na2SO3, NaHSO3, CaHSO3, Na3PO4 and Na2S. NaOH is the preferred reagent on the basis of its performance and typically a 1M NaOH solution is used with variations in the temperature and duration of treatment parameters. The use of NaOH invariably results in partial deacetylation of chitin and hydrolysis of the biopolymer that lowers the molecular weight of chitin [24, 25] . Normally the residual protein content in the chitin produced from conventional commercial sources is around 1%. This yields a partially deacetylated chitin. The obtained chitin flakes or powder can be further deacetylated to chitosan or used for the isolation of nanochitin: chitin nanowhiskers (or nanocrystals) and chitin nanofibers. As already mentioned, herein, we focus on recent advances in nanochitin isolation and its use on composite materials. As example, the schematic representation of steps involved in isolation of chitin nanofibers via ultra-sonication is shown in Figure 3 .
Similarly to the preparation of cellulose nanowhiskers, the main process for isolation of chitin nanowhiskers from extracted chitin is also based on acid hydrolysis. Disordered and low lateral ordered regions of chitin are preferentially hydrolyzed and dissolved in the acid solution, whereas water-insoluble, highly crystalline residues that have higher resistance to acid attack remain intact [26] . Thus, following acid hydrolysis, which removes disordered and low lateral ordered crystalline defects, chitin rod-like whiskers are obtained. The swelling and hydrolysis of amorphous phases occur much faster than those of crystalline phases due to the regular tight arrangement of molecular chains in the crystalline domains. It is well established and documented that the boiling hydrochloric acid can easily dissolve the amorphous domains of chitin.
When chitin is treated with strong HCl acid, the amorphous structures will be dissolved completely, but over hydrolysis, the ether and amide linkages of chitin can be affected. Thus, it is essential to control the hydrolytic extent of chitin to obtain a good yield of chitin nanowhiskers with
Similarly to the preparation of cellulose nanowhiskers, the main process for isolation of chitin nanowhiskers from extracted chitin is also based on acid hydrolysis. Disordered and low lateral ordered regions of chitin are preferentially hydrolyzed and dissolved in the acid solution, whereas water-insoluble, highly crystalline residues that have higher resistance to acid attack remain intact [26] . Thus, following acid hydrolysis, which removes disordered and low lateral ordered crystalline defects, chitin rod-like whiskers are obtained. The swelling and hydrolysis of amorphous phases occur much faster than those of crystalline phases due to the regular tight arrangement of molecular chains in the crystalline domains. It is well established and documented that the boiling hydrochloric acid can easily dissolve the amorphous domains of chitin. When chitin is treated with strong HCl acid, the amorphous structures will be dissolved completely, but over hydrolysis, the ether and amide linkages of chitin can be affected. Thus, it is essential to control the hydrolytic extent of chitin to obtain a good yield of chitin nanowhiskers with desirable size. The overall factors affecting the yield and particle size of a chitin nanowhiskers are the (1) origin of chitin, (2) concentration of HCl and (3) hydrolytic time. Thus, different conditions have been studied taking in account the different chitin origins [27] . If the concentration of acid increases, the crystalline structures will be gradually damaged, and for concentration of 8.5 N or higher, the crystalline structures will be completely dissolved. When comparing the studies conducted by various groups on the preparation of CNW, it was observed that for 3 N HCl concentration, the hydrolytic time (from 1.5 to 6 h) did not affect the size, especially the cross-sectional width of the nanowhisker, which showed similar lateral dimensions.
Another significant method used for chitin nanowhiskers' isolation is the called TEMPO: mediated oxidation (2, 2, 6, 6-tetramethylpiperidine-1-oxyl radical mediated oxidation). The oxidation of purified chitin takes place in the presence of compounds such as NaBr and NaClO with a pH of 10. After oxidation reactions, the major products remaining will be water-soluble polyuronic acid and water insoluble particles. Reaction rates of these two products can be controlled by the amount of NaClO in the system. The water-insoluble particles are the whiskers, which will undergo further ultra-sonication treatment. By this process, very narrow particles (width < 10 nm) can be obtained with a good yield rate of approximately 90% [27, 28] .
Based on these approaches, whiskers have recently been prepared from chitins of different sources, such as crab shells, shrimp shells, lobster shells and squid pens [29] [30] [31] [32] [33] [34] [35] [36] .
Lu et al. [36] , reported for the first time a route for preparing suspensions of chitin crystallite particles in 1993. In this method, purified chitin was first treated within a 2.5 N hydrochloric acid solution under reflux for 1 h; the excess acid was decanted and then distilled water was added to obtain the suspension. They found that acid-hydrolyzed chitin spontaneously dispersed into rod-like particles that could be concentrated to a liquid crystalline phase and self-assemble to a cholesteric liquid crystalline phase above a certain concentration. Dufresne and co-workers have successfully isolated the crystalline regions of chitin whiskers from the crab shells and squid pens by hydrochloric acid hydrolysis [29, 30] . The crystallites obtained were rod-like particles with an average size of 200 ± 20 nm in length and 8 ± 1 nm in width. Because of the nanoscale size, the acicular crystals can be called nanocrystals or whiskers. Morin and Dufresne [37] also prepared nanochitin whiskers from Riftia (marine invertebrates). The diameter of those whiskers was 18 nm and lengths were around 120 nm. In another study, Gopalan and Dufresne extracted nanochitin whiskers from crab shell. They successfully extracted 100-600 nm in length and 4-40 nm in width nanocrystals form 500-1000 µm chitin microcrystals [29] .
Rujiravanit and co-workers reported the preparation of chitin whiskers by acid hydrolysis of shrimp shells [38] . The nanochitin whiskers consisted of slender rods with sharp points that had a broad distribution in terms of size. The length of the chitin fragments ranged from 150 to 800 nm; the width ranged from 5 to 70 nm. More than 75% of the whiskers, however, had a length below 420 nm. Lu and co-workers prepared nanochitin whiskers from crab shell. They were spindle shaped with broad distribution in length (L), ranging from 100 to 650 nm, and diameter (D), ranging from 10 to 80 nm. The averages of length and diameter were estimated to be 500 and 10 nm, respectively. Revol et al. and Li et al. reported an approach toward the preparation of a suspension of chitin crystallites through acid hydrolysis [39, 40] . The obtained crystallites in a colloidal state were rod like particles with average size of 200 ± 20 nm in length and 8 ± 1 nm in width. Salaberria et al. extracted chitin from yellow lobster wastes followed by the isolation of nanocrystals by acid hydrolysis [41] . The ensuing chitin nanocrystals presented a random rod-like morphology with average diameter of 60 nm and length of 300 nm.
Since chitin occurs in nature in the form of nanofibrillar networks, it is possible to obtain chitin nanofibers from prawn, crab, shrimp and lobster shells and squid pen chitin by mechanical and physical processing. Those kinds of processes favor transverse cleavage along the longitudinal axis of the chitin microfibrillar structure by high shear, resulting in the isolation of long nanochitin fibers. Blender grinding; high-pressure homogenizing; and combinations of those and other techniques with ultrasonic treatments have been used [42] [43] [44] [45] . Typically, nanofibers have a great aspect ratio; a high surface to volume ratio; and contrarily to chitin nanocrystals, which present mainly crystal domains, chitin nanofibers present amorphous and crystal regions. Chitin nanofibers are very long fibers with a diameter ranging from 10 to 20 nm, giving a high aspect ratio of approximately 100 [45] . Moreover, nanofibers generally possess unique mechanical, optical and other characteristics, which allow them to be used in different fields.
Grinder equipment has been used to disintegrate the aggregated chitin nanofibers, and in this process, an aqueous suspension of chitin usually 1 wt % of concentration will be passed through the specially designed grinding stones. After the grinding process, the slurry will be formed into gel, which is well dispersed into water [43] . This method of manufacturing is applicable for many varieties of prawns, such as Penaeus monodon (black tiger prawn), Marsupenaeus japonicas (Japanese tiger prawn), and Pandalus eous Makarov (Alaskan pink shrimp). These shrimp are commonly used in the food industry and widely cultured around the globe [46] . Salaberria et al. used a dynamic high-pressure homogenization to obtain chitin nanofibers from yellow lobster [44] . This homogenization technique is based on the passage of a chitin suspension (1 wt % in water) at a very high pressure through a homogenizing valve. This passage is able to downsize chitin into chitin nanofibers. With this approach, the authors obtained chitin nanofibers with diameters below 100 nm and several micrometers in length.
A number of studies have been reported in the literature about the chemical structure of chitin by using infrared spectra. [31, 47, 48] Usually, the C=O stretching region of the amide moiety is found between 1600 and 1500 cm −1 ; the sharp band at 1378 cm −1 is assigned to CH 3 symmetrical deformation. The band at 1656 cm −1 is commonly assigned to stretching of the C=O group hydrogen bonded to N-H of the neighboring intra-sheet chain. The band at 1621 cm −1 may indicate a specific hydrogen bond of C=O with the hydroxymethyl group of the next chitin residue of the same chain. This is reinforced by the presence of only one band in this region for N-acetyl d-glucosamine [24] . In α-chitin, the amide I band is split at 1660 and 1620 cm −1 and the amide II band is at 1556 cm −1 . The amide I absorption band is a single peak at 1650 cm −1 for β-chitin, whereas the amide I bands for γ-chitin are at 1660 cm −1 and 1620 cm −1 .
In X-ray diffraction measurement, the sample is bombarded with X-rays and the diffraction pattern produced is recorded. In general, broad, diffuse and less intense peaks are observed for chitosan, and for chitin well-resolved and intense peaks are observed, showing the more crystalline nature of chitin compared to chitosan. Figure 4A shows the XRD spectra of chitin flakes, chitin nanofibrils and chitosan NPs and chitosan [49] . and 1620 cm .
In X-ray diffraction measurement, the sample is bombarded with X-rays and the diffraction pattern produced is recorded. In general, broad, diffuse and less intense peaks are observed for chitosan, and for chitin well-resolved and intense peaks are observed, showing the more crystalline nature of chitin compared to chitosan. Figure 4A shows the XRD spectra of chitin flakes, chitin nanofibrils and chitosan NPs and chitosan [49] . In the case of chitin and nanochitin, four major diffraction peaks located around 9.5 • , 19.5 • , 20.9 • and 23.4 corresponding to the 0 2 0, 1 1 0, 1 2 0, 1 3 0 crystal planes could be observed. However, for chitosan the two main diffraction peaks are located at 10 • -11 • and at 20 • -21 • . The peak shows broad diffraction peaks, indicating an amorphous polymer structure compared to chitin. This change is explained as the distortion of macromolecular configuration induced by strong deacetylation conditions. As previously discussed, depending on its origin, chitin can occur in three crystalline forms, α, β and γ-forms. Compared to α-chitin, β-chitin exhibits a broad diffuse scattering and less intense peaks. This is due to the differences in the crystallographic arrangements of these two polymorphs [51] . Kaya et al. analyzed the diffraction patterns in chitin. Six crystalline reflection peaks were obtained at 2-theta range ( Figure 4B ). I 020 crystalline reflection values were at 9.46, 8.59 • and 9.35 • for α, β and γ-chitin, respectively [50] . The crystalline index (CrI) value of γ-chitin was 68.6 • and was between that of α and β-chitin.
Following acid hydrolysis that removes disordered and low lateral ordered crystalline defects, chitin rod-like whiskers are obtained [52] . The principle toward preparation of polysaccharide nanocrystals is on the basis of the different hydrolytic kinetics between amorphous and crystalline domains [53] . That is to say, both the amorphous and the crystalline phases of polysaccharides can be hydrolyzed during treatment with strong acid aqueous solutions. Unlike tunicin whiskers, which can only be prepared by hydrolysis in strong sulfuric acid solutions, CNWs can be prepared by hydrolysis in HCl solutions. In general, the obtained rod-like whiskers showed similar size in width in the range of 10−50 nm, irrespective of the chitin's origins and hydrolytic time. However, the lengths of the whiskers greatly vary in the range of 150−2200 nm for different origins of chitin, which may be ascribed to the different original sizes of the chitin particles and the diffusion-controlled nature of the acid hydrolysis. Typical morphologies and sizes (average length and width) of dilute CHW suspension observed by TEM and AFM are displayed in Figure 5a ,b [29, 36] . The suspension contains chitin fragments consisting of both individual microcrystals and associated or collapsed microcrystals. More recently, individual chitin nanowhiskers have been prepared from partially deacetylated α-chitin by fibril surface cationization. When CNWs with degrees of N-acetylation (DA) from 0.74 to 0.70 were mechanically disintegrated in aqueous solutions from pH 3 to 4, individualized nanowhiskers of average width and length 6.2 ± 1.1 and 250 ± 140 nm were successfully prepared, as reported by Fan et al. [54] The driving force for individualization of CNWs is the same as that in the TEMPO-mediated oxidation method, that is, surface charge-induced electrical repulsion. The differences in the two methods are that TEMPO-mediated oxidation endows CNW surfaces with anionic charges versus cationic charges for the latter. The TEM image and sizes of the individual CNWs are shown in Figure 4c ,d; some long individual fibrils, with widths similar to those of the whiskers, but lengths of >500 nm, were observed, which have not been reported in previous CNWs prepared by the conventional method.
The morphology of α-chitin nanofibers isolated by dynamic, high-pressure homogenization is quite different from α-chitin isolated by acid hydrolysis and TEMPO. It consists of long chitin nanofibers presenting lengths of several micrometers (from 3 to 10 μm) and widths between 80 and 100 nm and a high aspect ratio (greater than 60) [44] .
Numerous polymer composites have been produced from a variety of natural materials extracted from waste and biomass sources, and a plethora of processing techniques have also been studied. Production of novel polymer materials from nanochitin through physical methods relying extensively on green technology was found to be sustainable.
They are characterized by their excellent mechanical properties and reinforcing capability, abundance in availability, low weight and biodegradability. However, just as for any nanoparticle, The suspension contains chitin fragments consisting of both individual microcrystals and associated or collapsed microcrystals. More recently, individual chitin nanowhiskers have been prepared from partially deacetylated α-chitin by fibril surface cationization. When CNWs with degrees of N-acetylation (DA) from 0.74 to 0.70 were mechanically disintegrated in aqueous solutions from pH 3 to 4, individualized nanowhiskers of average width and length 6.2 ± 1.1 and 250 ± 140 nm were successfully prepared, as reported by Fan et al. [54] The driving force for individualization of CNWs is the same as that in the TEMPO-mediated oxidation method, that is, surface charge-induced electrical repulsion. The differences in the two methods are that TEMPO-mediated oxidation endows CNW surfaces with anionic charges versus cationic charges for the latter. The TEM image and sizes of the individual CNWs are shown in Figure 4c ,d; some long individual fibrils, with widths similar to those of the whiskers, but lengths of >500 nm, were observed, which have not been reported in previous CNWs prepared by the conventional method.
The morphology of α-chitin nanofibers isolated by dynamic, high-pressure homogenization is quite different from α-chitin isolated by acid hydrolysis and TEMPO. It consists of long chitin nanofibers presenting lengths of several micrometers (from 3 to 10 µm) and widths between 80 and 100 nm and a high aspect ratio (greater than 60) [44] .
Numerous polymer composites have been produced from a variety of natural materials extracted from waste and biomass sources, and a plethora of processing techniques have also been studied. Production of novel polymer materials from nanochitin through physical methods relying extensively on green technology was found to be sustainable. They are characterized by their excellent mechanical properties and reinforcing capability, abundance in availability, low weight and biodegradability. However, just as for any nanoparticle, the main challenge is related to their homogeneous dispersion within a polymeric matrix. Chitin nanocrystals have a reactive surface covered with hydroxyl groups, opening up the possibility of extensive chemical modification. Using surfactants or by chemical grafting/modifications, these nanocrystals can be dispersed in non-aqueous media. This strategy not only decreases the surface energy and polar character of the polysaccharide nanoparticles, but improves their adhesion property with a non-polar polymeric matrix, which imposes serious constraints when the mechanical performance of the composite is considered. The reinforcement effect shown by nanocrystals is generally due to the formation of a percolating network of hydrogen bond.
Different processing techniques exist for nanochitin-reinforced polymer nanocomposites wherein chitin nanocrystal fillers are blended with polymeric matrices, such as poly (methyl methacrylate), epoxy, polystyrene, polyaniline, polysulfone, polycarbonate and thermoplastic polyurethane [55] . Polymer based blends show incompatibility due to repulsion between polar nanochitin functional groups and hydrophobic polymeric matrices. Studies were done on the addition of chitin nanocrystals as a compatibilizer in a blend system. Additionally, nanochitin has been blended with hydrophilic and bio-based polymeric matrices, namely, chitosan, starch, PLA, cellulose nanocrystals [33, 41, [56] [57] [58] [59] . There are many potential applications for polymer/nanochitin in membrane technology, dye removal, packaging materials, drug delivery, tissue engineering and biochemical relevance. Among the processing techniques for the development of nanochitin-reinforced polymer nanocomposites, freeze-drying, solvent casting, extrusion and electrospinning are described below.
The freeze-drying approach, which allows producing aerogels having high porosity and internal surface area and low heat conductivity, is a widely accepted technique. The dispersion of nanoparticles in the nanocomposite suspension depends on the processing technique and conditions. Nanocellulose-nanochitin biohybrid aerogels (BHA) were produced by Zhang et al. by freeze drying hydrogels (BHH) [60] . The aerogels were found to exhibit adsorption potential for Arsenite and methylene blue ( Figure 6 ).
Polymers 2020, 12, x FOR PEER REVIEW 9 of 38 the main challenge is related to their homogeneous dispersion within a polymeric matrix. Chitin nanocrystals have a reactive surface covered with hydroxyl groups, opening up the possibility of extensive chemical modification. Using surfactants or by chemical grafting/modifications, these nanocrystals can be dispersed in non-aqueous media. This strategy not only decreases the surface energy and polar character of the polysaccharide nanoparticles, but improves their adhesion property with a non-polar polymeric matrix, which imposes serious constraints when the mechanical performance of the composite is considered. The reinforcement effect shown by nanocrystals is generally due to the formation of a percolating network of hydrogen bond. Different processing techniques exist for nanochitin-reinforced polymer nanocomposites wherein chitin nanocrystal fillers are blended with polymeric matrices, such as poly (methyl methacrylate), epoxy, polystyrene, polyaniline, polysulfone, polycarbonate and thermoplastic polyurethane [55] . Polymer based blends show incompatibility due to repulsion between polar nanochitin functional groups and hydrophobic polymeric matrices. Studies were done on the addition of chitin nanocrystals as a compatibilizer in a blend system. Additionally, nanochitin has been blended with hydrophilic and bio-based polymeric matrices, namely, chitosan, starch, PLA, cellulose nanocrystals [33, 41, [56] [57] [58] [59] . There are many potential applications for polymer/nanochitin in membrane technology, dye removal, packaging materials, drug delivery, tissue engineering and biochemical relevance. Among the processing techniques for the development of nanochitinreinforced polymer nanocomposites, freeze-drying, solvent casting, extrusion and electrospinning are described below.
The freeze-drying approach, which allows producing aerogels having high porosity and internal surface area and low heat conductivity, is a widely accepted technique. The dispersion of nanoparticles in the nanocomposite suspension depends on the processing technique and conditions. Nanocellulose-nanochitin biohybrid aerogels (BHA) were produced by Zhang et al. by freeze drying hydrogels (BHH) [60] . The aerogels were found to exhibit adsorption potential for Arsenite and methylene blue ( Figure 6 ). The mechanism behind the self-assembly of nanocellulose and nanochitin was found to be electrostatic interaction. Aerogels were produced from surface-modified chitin nanowhiskers and carbon nanotubes (CNTs). The resulting aerogels had decreased storage and loss modulus with the addition of CNT, which could be related to the change in morphology upon the incorporation of CNT [61] . Zubillaga et al. designed and made genipin-chitosan cross-linked matrices impregnated with chitin nanoforms by freeze-drying method. The potential of the obtained 3D porous scaffolds as primary support and guidance for stem cells in tissue engineering and regenerative medicine were assessed. In vitro cell biocompatibility studies showed that both L-929 and human adipose stem cells were viable in contact with the extractive media of these biomaterials; and cells were able to adhere The mechanism behind the self-assembly of nanocellulose and nanochitin was found to be electrostatic interaction. Aerogels were produced from surface-modified chitin nanowhiskers and carbon nanotubes (CNTs). The resulting aerogels had decreased storage and loss modulus with the addition of CNT, which could be related to the change in morphology upon the incorporation of CNT [61] . Zubillaga et al. designed and made genipin-chitosan cross-linked matrices impregnated with chitin nanoforms by freeze-drying method. The potential of the obtained 3D porous scaffolds as primary support and guidance for stem cells in tissue engineering and regenerative medicine were assessed. In vitro cell biocompatibility studies showed that both L-929 and human adipose stem cells were viable in contact with the extractive media of these biomaterials; and cells were able to adhere and proliferate on the 3D porous scaffolds. Moreover, the addition of chitin nanoforms improved cell adhesion at low chitin nanoform ratios [56] . More recently, the same authors assessed the adipose-derived mesenchymal stem cell chondrospheroids cultured in hypoxia in the same 3D porous scaffolds as a platform for cartilage tissue engineering [33] .
Casting/solvent evaporation is another method of producing nanocomposites, wherein the polymer is first dissolved in an appropriate solvent (e.g., organic, aqueous) and chitin nanoparticles are blended into the polymer solution using different mixing techniques, namely, Ultra-Turrax, stirring and ultra-sound, to obtain homogenous dispersion. Afterwards, the suspension is cast in a mold, and finally the solvent is evaporated to get a solid nanocomposite film. Several investigations mentioned the use of water-soluble, water-dispersible polymers such as chitosan and starch [41, 62] . Carboxylated styrene-butadiene rubber (xSBR) composites were prepared with chitin nanocrystals using the solvent casting method [63] . The chitin nanocrystals proved to improve the mechanical properties of the composite in terms of elastic modulus, tensile strength and strain at break of xSBR, as seen from the stress-strain graph given in Figure 7 . and proliferate on the 3D porous scaffolds. Moreover, the addition of chitin nanoforms improved cell adhesion at low chitin nanoform ratios [56] . More recently, the same authors assessed the adiposederived mesenchymal stem cell chondrospheroids cultured in hypoxia in the same 3D porous scaffolds as a platform for cartilage tissue engineering [33] .
Casting/solvent evaporation is another method of producing nanocomposites, wherein the polymer is first dissolved in an appropriate solvent (e.g., organic, aqueous) and chitin nanoparticles are blended into the polymer solution using different mixing techniques, namely, Ultra-Turrax, stirring and ultra-sound, to obtain homogenous dispersion. Afterwards, the suspension is cast in a mold, and finally the solvent is evaporated to get a solid nanocomposite film. Several investigations mentioned the use of water-soluble, water-dispersible polymers such as chitosan and starch [41, 62] . Carboxylated styrene-butadiene rubber (xSBR) composites were prepared with chitin nanocrystals using the solvent casting method [63] . The chitin nanocrystals proved to improve the mechanical properties of the composite in terms of elastic modulus, tensile strength and strain at break of xSBR, as seen from the stress-strain graph given in Figure 7 . This study shows that uniform distribution of nanofillers in a polymer matrix could drastically influence the overall properties of a composite.
The preparation of nanocomposites by melt extrusion is carried out by pumping the suspension of nanocrystals into the polymer melt during the extrusion process [64] . Chitin nano-size fillers were incorporated in thermoplastic starch matrix via melt-mixing [59] . The thermoplastic starch-based nano-bio composites prepared with chitin nanofibers showed better thermal and mechanical properties and storage moduli than those prepared with chitin nanocrystals.
Polypropylene (PP)/chitin nanowhisker composites showed increase in tensile properties, which is common with addition of nanofillers [65] . The compatibilizer used was maleated PP. There was no significant change in rheological properties. Moreover, the properties decreased with nanofillers' incorporation as the material became rigid. This can be explained by the fact that at low filler addition, the mobility of the matrix is restrained, and at higher addition, loading agglomeration occurs, resulting in stress-concentration sites. The case was different with polylactide (PLA) and chitin nanocomposites prepared by melt blending [66] . Due to the hydrophobic nature of PLA, the nanocomposites were also modified with compatibilizing agent maleic anhydride. Here, contrary to This study shows that uniform distribution of nanofillers in a polymer matrix could drastically influence the overall properties of a composite.
The preparation of nanocomposites by melt extrusion is carried out by pumping the suspension of nanocrystals into the polymer melt during the extrusion process [64] . Chitin nano-size fillers were incorporated in thermoplastic starch matrix via melt-mixing [59] . The thermoplastic starch-based nano-bio composites prepared with chitin nanofibers showed better thermal and mechanical properties and storage moduli than those prepared with chitin nanocrystals.
Polypropylene (PP)/chitin nanowhisker composites showed increase in tensile properties, which is common with addition of nanofillers [65] . The compatibilizer used was maleated PP. There was no significant change in rheological properties. Moreover, the properties decreased with nanofillers' incorporation as the material became rigid. This can be explained by the fact that at low filler addition, the mobility of the matrix is restrained, and at higher addition, loading agglomeration occurs, resulting in stress-concentration sites. The case was different with polylactide (PLA) and chitin nanocomposites prepared by melt blending [66] . Due to the hydrophobic nature of PLA, the nanocomposites were also modified with compatibilizing agent maleic anhydride. Here, contrary to the above work, the tensile strengths of both nanocomposite and modified nanocomposites decreased with the addition of chitin due to hydrolysis of PLA during composite preparation. Rheology studies showed that addition of chitin decreases the elastic storage modulus.
Electrospinning is a method used to prepare nanofibers with diameters up to 100 nm through the action of electrostatic forces. Here electrical charge is used to draw a positively charged polymer solution from an orifice to a collector [67] . The process is simple and does not require the use of high temperatures or chemical treatments to produce nanofibers from solution.
Junkasem et al. reported the fabrication of polyvinyl alcohol (PVA)/chitin nanowhisker nanocomposites using electrospinning with water as the solvent. The electrospun composite membranes exhibited bead formation, while neat PVA showed smooth morphology. The Young's modulus of the nanocomposite also increased 4-8 times when compared to the pristine PVA [68] . Polyvinylidene fluoride (PVDF)/CNW membranes were fabricated by our group by employing a DMF:acetone solvent mixture. The membranes had good mechanical strength; moreover, due to hydrophilicity of the membranes water could pass through by diffusion retaining oil droplets on the surface, demonstrating its potential for oil-water separation [69] . Previously, we had reported similar membranes fabricated by electrospinning a 15% solution of PVDF with 1% CNW in dimethyl acetamide (DMAc); 88.9% removal of the dye indigo carmine could be achieved with neat PVDF showing only 22.3% removal alone, the governing mechanism being hydrogen bonding and the electrostatic force of attraction. The main highlight of this work was the reusability of the membranes for three cycles [24] .
For studying the properties of nanostructured materials at the nanometer scale, investigation of nanostructures is required. Transmission electron microscopy (TEM) is one of the best techniques used for the characterization of nanomaterials and nanocomposites. It gives a precise idea of nanoparticle size; grain size; size distribution; homogeneity; lattice type; crystal structure; dispersion; and also the chemical and physical properties of phases such as number, morphology and structure of each phase. It provides structural and chemical information over a range of length scales down to the level of atomic dimensions. TEM is an unavoidable tool for understanding the properties of nanostructured materials.
Anwer et al. in their work on biodegradable bionanocomposites evaluated the effect of CNWs as reinforcing agents in epoxy. They studied the morphological properties of DGEBA epoxy. The TEM images could confirm the presence of CNW clusters within the epoxy matrix [70] (Figure 8 ).
of each phase. It provides structural and chemical information over a range of length scales down to the level of atomic dimensions. TEM is an unavoidable tool for understanding the properties of nanostructured materials.
Anwer et al. in their work on biodegradable bionanocomposites evaluated the effect of CNWs as reinforcing agents in epoxy. They studied the morphological properties of DGEBA epoxy. The TEM images could confirm the presence of CNW clusters within the epoxy matrix [70] (Figure 8 ). In a study reported by Alomnso et al., the chitin-silica nanocomposites and mesoporous materials were prepared by sol-gel processes through a colloid-based approach using elongated chitin nanorods [71] . They could observe a spheroid shape of spray-dried chitin-silica particles from the TEM analysis. The result suggests that the chitin nano rods were coated by siloxane oligomers and formed hybrid rods ( Figure 9 ). The TEM image showed silica rods of 2-3 nm wide, and the imprint of the chitin monocrystals (marked in the image). In a study reported by Alomnso et al., the chitin-silica nanocomposites and mesoporous materials were prepared by sol-gel processes through a colloid-based approach using elongated chitin nanorods [71] . They could observe a spheroid shape of spray-dried chitin-silica particles from the TEM analysis. The result suggests that the chitin nano rods were coated by siloxane oligomers and formed hybrid rods ( Figure 9 ). The TEM image showed silica rods of 2-3 nm wide, and the imprint of the chitin monocrystals (marked in the image). . TEM analysis of spray-dried microparticles obtained with high initial chitin volume fractions [71] . The sample is formed by entangled rods of silica (white dashed rectangles) separated by voids (10-100 nm). These rods come from the initial chitin nanorods represented by the rectangles (23 × 260 nm 2 ). Inside the silica rods, the imprint of the chitin monocrystals (2-3 nm wide) can be distinguished (black arrows in the zoomed area)
The use of different characterization techniques is important to understand the basic physical and chemical properties of polymer nanocomposites. For several applications, it facilitates the study of emerging materials by giving information on intrinsic properties. Various techniques have been used extensively in polymer nanocomposite research. Structural and morphological characterization by scanning electron microscopy (SEM) uses a focused beam of electrons which provides images of Figure 9 . TEM analysis of spray-dried microparticles obtained with high initial chitin volume fractions [71] . The sample is formed by entangled rods of silica (white dashed rectangles) separated by voids (10-100 nm). These rods come from the initial chitin nanorods represented by the rectangles (23 × 260 nm 2 ). Inside the silica rods, the imprint of the chitin monocrystals (2-3 nm wide) can be distinguished (black arrows in the zoomed area).
The use of different characterization techniques is important to understand the basic physical and chemical properties of polymer nanocomposites. For several applications, it facilitates the study of emerging materials by giving information on intrinsic properties. Various techniques have been used extensively in polymer nanocomposite research. Structural and morphological characterization by scanning electron microscopy (SEM) uses a focused beam of electrons which provides images of the surface associated with a sample. It can be used to observe the fracture surfaces of polymer nanocomposites and to see the dispersion of nanoparticles in polymers across the failed surface. SEM is supportive in clarifying the presence of pores, impurities and morphological changes. SEM could also be supportive in explaining the dispersion of nanofiller materials.
For instance, in a study reported by Qin et al. PVDF-CNW membranes were prepared with 18 wt % PVDF and 0-10 wt % of CNW. They observed that the average surface pore size of composite membranes was comparatively smaller than that of neat PVDF membrane, with the pores becoming more uniform with further addition chitin nanowhiskers. This explains the uniform dispersion of chitin nanowhiskers on PVDF matrix, as seen from Figure 10 The effect of increasing chitin nanowhisker content leading to the formation of an interconnected structure in membrane could be explained using the SEM. This morphological development was due to the tendency of chitin nanowhiskers to adsorb water, resulting in a liquid-liquid phase separation. The adhesion between different materials and the propagation of applied stress in a composite system can be explained with the support of SEM images.
In a work by Mathew et al. the fracture surfaces of the uncross-linked and cross-linked chitosan/chitin crystal nanocomposites did not show any large agglomerates, indicating good adhesion between the matrix and the reinforcement, and the fracture propagated through the matrix rather than through the chitosan-chitin interface [73] (Figure 11 ). The effect of increasing chitin nanowhisker content leading to the formation of an interconnected structure in membrane could be explained using the SEM. This morphological development was due to the tendency of chitin nanowhiskers to adsorb water, resulting in a liquid-liquid phase separation. The adhesion between different materials and the propagation of applied stress in a composite system can be explained with the support of SEM images.
In a work by Mathew et al. the fracture surfaces of the uncross-linked and cross-linked chitosan/chitin crystal nanocomposites did not show any large agglomerates, indicating good adhesion between the matrix and the reinforcement, and the fracture propagated through the matrix rather than through the chitosan-chitin interface [73] (Figure 11 ).
The adhesion between different materials and the propagation of applied stress in a composite system can be explained with the support of SEM images.
In a work by Mathew et al. the fracture surfaces of the uncross-linked and cross-linked chitosan/chitin crystal nanocomposites did not show any large agglomerates, indicating good adhesion between the matrix and the reinforcement, and the fracture propagated through the matrix rather than through the chitosan-chitin interface [73] (Figure 11 ). Porous foams were fabricated with PVA and chitin nanowhiskers using the freeze-drying technique [74] . PVA concentration was kept constant as 0.8 wt % and CNW concentrations were varied from 0.4-1.2 wt %. The changes in morphology with varying concentrations of CNW were analyzed by SEM, as shown in Figure 12 . Porous foams were fabricated with PVA and chitin nanowhiskers using the freeze-drying technique [74] . PVA concentration was kept constant as 0.8 wt % and CNW concentrations were varied from 0.4-1.2 wt %. The changes in morphology with varying concentrations of CNW were analyzed by SEM, as shown in Figure 12 . At 0.4 wt % CNW, several structural deformities could be seen with crack formation (Figure 12a ). At 0.8 wt % of CNW, highly ordered lamellar structures with no evident defects were seen, as shown in Figure 12b . At higher concentrations, aggregations were seen (Figure 12c ).
To understand the mechanical properties, it is important to have a thorough knowledge of the At 0.4 wt % CNW, several structural deformities could be seen with crack formation (Figure 12a ). At 0.8 wt % of CNW, highly ordered lamellar structures with no evident defects were seen, as shown in Figure 12b . At higher concentrations, aggregations were seen (Figure 12c ).
To understand the mechanical properties, it is important to have a thorough knowledge of the chemistry and morphology of the polymer matrix and how it correlates with the surface chemistry, the size and the shape of a nanoscale filler. The chemistry of the nanoscale filler influences enthalpic interactions with the polymer chain, and specific interactions, such as covalent bonds. The effects of the mechanical properties of the filler on the overall mechanical properties of the nanocomposites have been explored by several research groups. They reported that for any nanofiller the mechanical properties depend on parameters including nanofiller size and shape, interfacial region, processing conditions, method of manufacture, etc. The interactions between the polymer matrix and nanofiller and filler-filler interactions influence the mechanical behavior of the polysaccharide, nanocrystal-reinforced nanocomposites. The adhesion of polysaccharide nanoparticles with a non-polar polymeric matrix is reported to cause a negative effect on the mechanical performances of the nanocomposite because of the formation of a percolating network through hydrogen bonding forces.
A biodegradable porous scaffold of thermoset elastomer was fabricated by Tian et al., for which chitin-nanocrystal-supported emulsion-freeze-casting was utilized [75] . The mass percentages of chitin nanocrystals were controlled at 15%, 20%, 25%, 30%, 35% and 40%. The nanocomposite exhibited good elastic resilience and improved mechanical properties with increasing chitin nanocrystal content. In another report by Mushi et al., chitin nanofibers and chitosan-based biocomposite films of high toughness was prepared and characterized [76] . This biopolymer nanocomposite containing chitin nanofiber networks in chitosan matrix had the highest toughness at 8 vol. % chitin content, and at very high chitin content the nanocomposites showed tensile strength of 140 MPa, and strain to failure 11%. Nie et al. produced epoxidized natural rubber (ENR)/chitin nanocrystals composites without using conventional crosslinking agents. They explained that chitin nanocrystals reacted with the epoxy group of ENR and formed hydrogen bonds resulting in the formation of supramolecular network. This structure could effectively enhance the mechanical properties along with superior self-healing capacity [77] .
The effect of chitin nanocrystals on the formation of shish-kebab crystals in bimodal polyethylene (BPE) injection bars was evaluated by Bie et al. [78] . They reported that the addition of chitin nanocrystals (0-0.5 wt % chitin nanocrystals) enhanced the ultimate tensile strength and Young's modulus of the injection bars. Compared to BPE, the tensile modulus of composites with 0.3 wt % cellulose nanocrystals increased by 11.6%. The ability of chitin nanowhiskers to effectively act as a reinforcing filler was showed by Peng et al. using poly(vinyl alcohol) (PVA) and chitin nanowhiskers. PVA/CNW hydrogels for drug delivery applications were proposed with bovine serum albumin (BSA) as the model drug and glutaraldehyde as the crosslinker [79] . The mechanical properties were analyzed, and neat PVA displayed poor mechanical properties and was very fragile compared to PVA/CNWs hydrogel (Figure 13a-f) .
However, the hydrogel comprised of PVA/CNWs was strong enough and the stress at fracture increased from 1.55 to 26.59 MPa with an increase in the ratio of CNWs to PVA content (0% to 40%). The drug release profile showed a release of more than 50% of drug within 60 h (Figure 13g ). wt % cellulose nanocrystals increased by 11.6%. The ability of chitin nanowhiskers to effectively act as a reinforcing filler was showed by Peng et al. using poly(vinyl alcohol) (PVA) and chitin nanowhiskers. PVA/CNW hydrogels for drug delivery applications were proposed with bovine serum albumin (BSA) as the model drug and glutaraldehyde as the crosslinker [79] . The mechanical properties were analyzed, and neat PVA displayed poor mechanical properties and was very fragile compared to PVA/CNWs hydrogel (Figure 13a-f) . However, the hydrogel comprised of PVA/CNWs was strong enough and the stress at fracture increased from 1.55 to 26.59 MPa with an increase in the ratio of CNWs to PVA content (0% to 40%). The drug release profile showed a release of more than 50% of drug within 60 h (Figure 13g ).
The thermal properties of composites comprising of nanochitin have been analyzed by numerous researchers with the aid of thermo gravimetric analysis (TGA) and differential scanning calorimetry (DSC) [80] [81] [82] usually under a nitrogen atmosphere [80, [83] [84] [85] [86] .
The thermal stability of carboxymethylcellulose (CMC)-based films containing chitin nanocrystals and grapefruit seed extract (GSE) was investigated by Oun et al. using thermogravimetric analysis under nitrogen flow; all films showed two stages of thermal degradation [84] . The preliminary phase was detected around 80-130 °C with weight loss extending from 4.9% to 7.9%, which was associated with the elimination of free water below 110 °C and bound water. The chief thermal degradation was observed at 200-400 °C, which was connected with the thermal degradation of carbohydrate polymers and the volatilization of glycerol. All films revealed analogous thermal degradation parameters of the initial decomposition temperature (Tonset) in the range of 200-210 °C, the mid-point of the degradation (T0.5) of 270-275 °C and the end of degradation temperature (Tend) of 321-333 °C. The final residue remaining after thermal degradation at 600 °C of the neat CMC film was 21.7%, but improved to about 30% thanks to the incorporation of nanocrystals and GSE.
The thermal properties of biodegradable poly (butylene adipate-co-terephthalate) (PBAT) composites reinforced with bio-based nanochitin were investigated by Meng et al. using TGA and
The thermal properties of composites comprising of nanochitin have been analyzed by numerous researchers with the aid of thermo gravimetric analysis (TGA) and differential scanning calorimetry (DSC) [80] [81] [82] usually under a nitrogen atmosphere [80, [83] [84] [85] [86] .
The thermal stability of carboxymethylcellulose (CMC)-based films containing chitin nanocrystals and grapefruit seed extract (GSE) was investigated by Oun et al. using thermogravimetric analysis under nitrogen flow; all films showed two stages of thermal degradation [84] . The preliminary phase was detected around 80-130 • C with weight loss extending from 4.9% to 7.9%, which was associated with the elimination of free water below 110 • C and bound water. The chief thermal degradation was observed at 200-400 • C, which was connected with the thermal degradation of carbohydrate polymers and the volatilization of glycerol. All films revealed analogous thermal degradation parameters of the initial decomposition temperature (T onset ) in the range of 200-210 • C, the mid-point of the degradation (T 0.5 ) of 270-275 • C and the end of degradation temperature (T end ) of 321-333 • C. The final residue remaining after thermal degradation at 600 • C of the neat CMC film was 21.7%, but improved to about 30% thanks to the incorporation of nanocrystals and GSE.
The thermal properties of biodegradable poly (butylene adipate-co-terephthalate) (PBAT) composites reinforced with bio-based nanochitin were investigated by Meng et al. using TGA and DSC under a nitrogen atmosphere [80] . TGA curves and derivative thermal and PBAT/nanochitin composites are shown in Figure 14a ,b, respectively. DSC under a nitrogen atmosphere [80] . TGA curves and derivative thermal and PBAT/nanochitin composites are shown in Figure 14a ,b, respectively. The TGA curve for the nanochitin powder exhibited two discrete mass losses. The primary one happened below 100 °C and matches with the loss of physically absorbed water. The second and grander mass loss befell in the 280-400 °C range and could be ascribed to the carbonization of the polysaccharide structure. In contrast, the thermal degradation of pristine PBAT and the PBAT/nanochitin composites occurred in a one-step process at temperatures between 300 and 400 °C. The TGA curve for the nanochitin powder exhibited two discrete mass losses. The primary one happened below 100 • C and matches with the loss of physically absorbed water. The second and grander mass loss befell in the 280-400 • C range and could be ascribed to the carbonization of the polysaccharide structure. In contrast, the thermal degradation of pristine PBAT and the PBAT/nanochitin composites occurred in a one-step process at temperatures between 300 and 400 • C. The thermal stability of the PBAT/chitin composites was similar to pristine PBAT when the chitin content was lower than 4%. Char yields of the composites increased with chitin content, as expected since the chitin acted as an additional carbon source for char formation. Furthermore, the nanochitin delayed heat transmission along the PBAT matrix, consequently varying the carbonization kinetics of PBAT. DSC was used to examine the effect of nanochitin powder addition on the crystallization and melting behavior of PBAT. DSC cooling curves and second heating curves for pristine PBAT and the various PBAT/nanochitin composites are shown in Figure 15a ,b, respectively. The TGA curve for the nanochitin powder exhibited two discrete mass losses. The primary one happened below 100 °C and matches with the loss of physically absorbed water. The second and grander mass loss befell in the 280-400 °C range and could be ascribed to the carbonization of the polysaccharide structure. In contrast, the thermal degradation of pristine PBAT and the PBAT/nanochitin composites occurred in a one-step process at temperatures between 300 and 400 °C. The thermal stability of the PBAT/chitin composites was similar to pristine PBAT when the chitin content was lower than 4%. Char yields of the composites increased with chitin content, as expected since the chitin acted as an additional carbon source for char formation. Furthermore, the nanochitin delayed heat transmission along the PBAT matrix, consequently varying the carbonization kinetics of PBAT. DSC was used to examine the effect of nanochitin powder addition on the crystallization and melting behavior of PBAT. DSC cooling curves and second heating curves for pristine PBAT and the various PBAT/nanochitin composites are shown in Figure 15a ,b, respectively. The addition of a small amount of nanochitin (0.5 wt %) had quite a dramatic effect of the melting and recrystallization of PBAT. The values of T m , ∆H m , T c , ∆H c and χ c for chitin-0.5 were all higher than the corresponding values for pristine PBAT. The data strongly recommend that integration of nanochitin at 0.5 wt % had a varied nucleation result, helping the establishment of crystallites in the PBAT matrix during cooling from the melt. The researchers concluded that the thermal properties of the composites were largely reliant on the concentration (0.5 wt % being optimal) and dispersion of nanochitin [80] . Coltelli et al., during their investigation on the thermal properties of poly (lactic acid) (PLA)-based composites comprising chitin nanofibrils using DSC under a nitrogen atmosphere, resolved that the concurrent existence of CNFs and triethyl citrate (TEC) in the studies composition range did not incite substantial deviations, apart from the apparent decline of the glass transition temperature owing to the plasticizing effect of TEC [81] . The inclinations of glass transition temperature (T g ) and crystallinity (X c ) as functions of CNF concentration (represented as CN in figure) are depicted in Figure 16a ,b.
The T g values were practically unchanged, but higher for the first heating than for the second. The crystallinity X c was almost constant as a function of CNF concentration in the second heating, displaying an insignificant consequence of CNFs on controlled crystallization. On the contrary, the crystallinity was pointedly amplified when the concentration of CNF was 5 and 12 wt %. As a consequence of CNF addition to the samples, the thermal properties exhibited few specific variations, only being responsible for a slight nucleating effect. This restructuring is apparent above 5 wt % of CNFs. In a study conducted by Xu et al., the compositions, thermal stabilities and decomposition kinetics of TEMPO-oxidized cellulose nanofiber (TOCNF), partially deacetylated α-chitin nanofiber (α-DECHN) and TOCNF/multi-wall carbon nanotube (MWCNT)/α-DECHN composite wires were analyzed by TGA [85] . As shown in the above Figure 17 , the preliminary phase of the thermal decomposition of TOCNF/MWCNT/α-DECHN composite wire is consistent with that of TOCNFs.
PBAT matrix during cooling from the melt. The researchers concluded that the thermal properties of the composites were largely reliant on the concentration (0.5 wt % being optimal) and dispersion of nanochitin [80] . Coltelli et al., during their investigation on the thermal properties of poly (lactic acid) (PLA)-based composites comprising chitin nanofibrils using DSC under a nitrogen atmosphere, resolved that the concurrent existence of CNFs and triethyl citrate (TEC) in the studies composition range did not incite substantial deviations, apart from the apparent decline of the glass transition temperature owing to the plasticizing effect of TEC [81] . The inclinations of glass transition temperature (Tg) and crystallinity (Xc) as functions of CNF concentration (represented as CN in figure) are depicted in Figure 16a , b. The Tg values were practically unchanged, but higher for the first heating than for the second. The crystallinity Xc was almost constant as a function of CNF concentration in the second heating, displaying an insignificant consequence of CNFs on controlled crystallization. On the contrary, the crystallinity was pointedly amplified when the concentration of CNF was 5 and 12 wt %. As a consequence of CNF addition to the samples, the thermal properties exhibited few specific variations, only being responsible for a slight nucleating effect. This restructuring is apparent above 5 wt % of CNFs. In a study conducted by Xu et al., the compositions, thermal stabilities and decomposition kinetics of TEMPO-oxidized cellulose nanofiber (TOCNF), partially deacetylated α-chitin nanofiber (α-DECHN) and TOCNF/multi-wall carbon nanotube (MWCNT)/α-DECHN composite wires were analyzed by TGA [85] . As shown in the above Figure 17 , the preliminary phase of the thermal decomposition of TOCNF/MWCNT/α-DECHN composite wire is consistent with that of TOCNFs. As the temperature rises, the difference between the weight loss percentages of TOCNF/MWCNT/α-DECHN composite wire and α-DECHNs is steadily diminished. This observation specifies that in the composite wire, TOCNF decomposes at a lower temperature than α-DECHNs.
While learning the role of corn oil on gelatin-based nanocomposite membranes comprising nanochitin, differential scanning calorimetery (DSC) under nitrogen atmosphere was adopted by Sahraee et al. to inspect the thermal properties of emulsion nanocomposite films [82] . Incorporation of CNF to gelatin film increased Tm and ∆Hm of nanocomposite films which can be justified considering good compatibility and filling property of nanoparticles with gelatin. The melting point of nanocomposite gelatin films containing CNF (~102 °C) was found to be higher than that of net gelatin films (~83 °C). Another reason proposed for the fortifying effect of CNF was that it could increase the overall crystallinity of polymer, leading to higher transition temperature and enthalpy. Li et al. [83] researched chitin nanowhisker/metal ion (Zn 2+ ) dual reinforcements in synthetic polyacrylamide (PAAm) network-based nanocomposite hydrogels; the thermal properties of the samples were measured using TGA under a nitrogen atmosphere. They observed that the nanocomposite hydrogels of PAAm/CNWs and PAAm/CNW/Zn 2+ followed a degradation trend similar to that of the PAAm hydrogel, but the nanocomposite hydrogels showed higher residual weight in the thermograms. Additionally, the increase of the residual weight was observed in the PAAm/CNWs/Zn 2+ hydrogel in comparison with the PAAm/CNWs hydrogel. These findings indicated that the presence of strong non-covalent interactions of CNWs with PAAm and Zn 2+ As the temperature rises, the difference between the weight loss percentages of TOCNF/MWCNT/ α-DECHN composite wire and α-DECHNs is steadily diminished. This observation specifies that in the composite wire, TOCNF decomposes at a lower temperature than α-DECHNs.
While learning the role of corn oil on gelatin-based nanocomposite membranes comprising nanochitin, differential scanning calorimetery (DSC) under nitrogen atmosphere was adopted by Sahraee et al. to inspect the thermal properties of emulsion nanocomposite films [82] . Incorporation of CNF to gelatin film increased T m and ∆H m of nanocomposite films which can be justified considering good compatibility and filling property of nanoparticles with gelatin. The melting point of nanocomposite gelatin films containing CNF (~102 • C) was found to be higher than that of net gelatin films (~83 • C). Another reason proposed for the fortifying effect of CNF was that it could increase the overall crystallinity of polymer, leading to higher transition temperature and enthalpy. Li et al. [83] researched chitin nanowhisker/metal ion (Zn 2+ ) dual reinforcements in synthetic polyacrylamide (PAAm) network-based nanocomposite hydrogels; the thermal properties of the samples were measured using TGA under a nitrogen atmosphere. They observed that the nanocomposite hydrogels of PAAm/CNWs and PAAm/CNW/Zn 2+ followed a degradation trend similar to that of the PAAm hydrogel, but the nanocomposite hydrogels showed higher residual weight in the thermograms. Additionally, the increase of the residual weight was observed in the PAAm/CNWs/Zn 2+ hydrogel in comparison with the PAAm/CNWs hydrogel. These findings indicated that the presence of strong non-covalent interactions of CNWs with PAAm and Zn 2+ enhanced the thermal stability of resultant nanocomposites.
Rheology is an active and noteworthy method with which to comprehend the microstructures of biopolymers and their dispersions in solution or under fluid state, as impacted by the processing approaches; and afterward, to launch the optimum techniques and settings to understand the intricate melting and flow behaviors (e.g., viscoelastic properties), and to accomplish certain properties for the ultimate products. Rheology, as a complementary technique, offers evidence about the connections among fillers and how these can be altered with polymers. Mostly, rheological properties, viz., viscosity and yield stress, and the surface forces verified via examination procedures such as AFM, are nicely associated [87] . Studies have proven that interfacial, rather than bulk rheological factors can be made use of in envisaging the outcomes of the e-spinning procedure [88] . The bulk parameters are calculated by polymer content and directly influence jet instigation, whereas the interfacial parameters govern the durability of the jet and fiber construction [89] . Rheological properties of substantial importance are the linear viscoelastic moduli, G (storage modulus) and G (loss modulus), the shear-rate-dependent viscosity and the yield stress. The linear viscoelastic moduli are reliant on the unperturbed (quiescent) microstructure, although the nonlinear rheological properties such as the viscosity and yield stress necessitate definite attention to flow effects on the microstructure [87] .
Oscillatory analyses are generally attained with the help of controlled stress rheometers by means of only as much compression as required to offer highest contact area and least slip. Amplitude sweeps are initially completed so as to determine the linear viscoelastic range (LVR). Storage (G ) and loss (G") shear moduli along with strain are recorded as afunctions of stress, at a fixed frequency (usually of 1 Hz). The constant strain value, at which the subsequent frequency sweeps are carried out to acquire the mechanical spectra, is then selected from the originally determined LVR for individual samples. Each mechanical spectrum is then documented at this constant strain value in the LVR. G and G , along with the tangent of the phase angle (tan δ = G"/G ) and complex viscosity (η *), are recorded as functions of increasing angular frequency (ω; rad s −1 ), after attaining steady-state for each point. On the whole, G exhibits a tendency to remain independent of frequency, and stays superior to G in all the cases where the elastic component of the material is superior to the viscous component, archetypal of a gel-like character. The complex viscosity of the mixtures diminishes just about linearly with the augmentation of the frequency displaying shear thinning behavior, possibly owing to the structure of the hybrid polymer network [90] .
Li et al. while studying the role of chitin nanowhisker and metal ion (Zn 2+ ) dual reinforcements in synthetic polyacrylamide network-based nanocomposite hydrogels observed that as the CNW dosage in the blend was increased from 0.1% to 0.5%, the compression strength of the nanocomposites with constant Zn 2+ concentration reached 6.95 ± 0.20 MPa, up from 1.95 ± 0.14 MPa [83] . The compression strength of the nanocomposites declined slightly when the CNWs' concentration surpassed 0.5%, and the PAAm-CNW-0.5-Zn 2+ hydrogel exhibited brilliant compression performance. They also assessed that for all hydrogels, the G values are always much larger than the corresponding G values over the whole frequency range, indicating dominant elastic solid-like behavior. Among them, the PAAm-CNW-0.5-Zn 2+ hydrogel had pronouncedly high storage/loss moduli due to the strong hydrogen-bonding and metal-coordination interactions within the network.
Bionanocomposite films based on konjac glucomannan (KGM), chitosan (CS) and TEMPO-oxidized chitin nanocrystals (CNCs) were fabricated by Sun et al.; they characterized the film forming solutions (FFSs) for their rheological properties since they play a huge role in determining the uniformity of the liquid coating layer, the mechanical properties and the spreadability [86] . The viscosity of all FFSs diminished as the shear rate increased, as shown in Figure 18 , indicating the existence of the pseudoplastic properties or the shear thinning area of these FFS. (In the figure CNCs are represented as ChNCs).
compression performance. They also assessed that for all hydrogels, the G′ values are always much larger than the corresponding G′′ values over the whole frequency range, indicating dominant elastic solid-like behavior. Among them, the PAAm-CNW-0.5-Zn 2+ hydrogel had pronouncedly high storage/loss moduli due to the strong hydrogen-bonding and metal-coordination interactions within the network.
Bionanocomposite films based on konjac glucomannan (KGM), chitosan (CS) and TEMPOoxidized chitin nanocrystals (CNCs) were fabricated by Sun et al.; they characterized the film forming solutions (FFSs) for their rheological properties since they play a huge role in determining the uniformity of the liquid coating layer, the mechanical properties and the spreadability [86] . The viscosity of all FFSs diminished as the shear rate increased, as shown in Figure 18 , indicating the existence of the pseudoplastic properties or the shear thinning area of these FFS. (In the figure CNCs are represented as ChNCs). The incorporation of TEMPO-CNCs seemed to make the FSS microstructure better, thereby augmenting the mechanical properties of the resultant bionanocomposite films by establishing new chemical bonds and a vastly entangled network among KGM, CS and TEMPO-CNCs. The outcomes showed that the TEMPO-CNCs could improve the rheological properties of the FFS, and the integration of 3% (w/w) TEMPO-CNCs was proven to be the optimal concentration. Chitin whiskers are suitable to be incorporated as nanofillers in reinforcing polymer nanocomposites due to their high The incorporation of TEMPO-CNCs seemed to make the FSS microstructure better, thereby augmenting the mechanical properties of the resultant bionanocomposite films by establishing new chemical bonds and a vastly entangled network among KGM, CS and TEMPO-CNCs. The outcomes showed that the TEMPO-CNCs could improve the rheological properties of the FFS, and the integration of 3% (w/w) TEMPO-CNCs was proven to be the optimal concentration. Chitin whiskers are suitable to be incorporated as nanofillers in reinforcing polymer nanocomposites due to their high modulus values. Grafted samples present a significant increase in viscosity at high concentration values, without formation of the desired chiral nematic phase [87] . The role of varying nanochitin concentrations (0.25-1.0%, w/v) on the rheological properties, structure, compression behavior, pH and NaCl sensitivity of the gelatin hydrogels were methodically inspected by Li et al. by means of dynamic rheological experiments and compression assessments [91] . Dynamic rheological measurements of the nanocomposite hydrogels were carried out as functions of frequency sweeps, temperature sweeps and time sweeps, thereby proving that gelatin composite hydrogels showed excellent stability under conditions of increased acidity and high ionic strength with the incorporation of nanochitin whiskers (CHW). It was thus concluded that gelatin is capable of forming strong hydrogels with nanochitin in a saline environment.
Zhou et al. prepared mixed Pickering emulsions by blending anionic nanocellulose-stabilized lipid droplets with cationic nanochitin-stabilized lipid droplets, whose rheological properties were characterized by dynamic shear rheometry [92] (Figure 20 ). They successfully proved that pickering emulsions with different rheological characteristics could be prepared by blending positive and negative droplets together in different ratios. While learning the effects of chitin nanocrystals in supple packing layers, Zhong et al. described that the TEMPO oxidised chitin nanocrystals (TOCNs) transformed the flow behavior of the water-based acrylic resin (AR) [93] . As displayed in Figure 21a , both the bare AR formulation and the AR formulation with low TOCN content (1 wt %) revealed almost Newtonian behavior, where the viscosity stayed practically unaffected with changing shear rates. They successfully proved that pickering emulsions with different rheological characteristics could be prepared by blending positive and negative droplets together in different ratios. While learning the effects of chitin nanocrystals in supple packing layers, Zhong et al. described that the TEMPO oxidised chitin nanocrystals (TOCNs) transformed the flow behavior of the water-based acrylic resin (AR) [93] . As displayed in Figure 21a , both the bare AR formulation and the AR formulation with low TOCN content (1 wt %) revealed almost Newtonian behavior, where the viscosity stayed practically unaffected with changing shear rates. A more rigid network structure formed at the higher TOCN content (3 or 5 wt %) led to a distinctive shear thinning flow behavior; with higher shear rate, the viscosity declined since the network was disturbed. Figure 21b shows that the AR viscosity increased linearly at medium or high constant shear levels with a higher TOCN concentration; the effect of the material at the higher constant shear rate was decreased. The dynamic viscoelastic nature of the water-based AR was also reformed with the integration of TOCNs. Figure 21c shows the storage modulus G′ and loss modulus G′′ of the AR/TOCNs3 and AR/TOCNs5 formulations. The AR/TOCNs5 formulation exhibited solidlike (elastic) behavior at low angular frequencies as evidenced by the G′ > G′′. It also had a higher storage modulus along with the whole angular frequency range because of its higher TOCN content. The outcome shows that the TOCNs have the capability for modifying the rheological and mechanical properties of water-based coating arrangements. Chitin hybrid biodegradable materials reinforced with graphene oxide nanosheets (nGO) were prepared and characterized by Gonzalez et al. [90] , where nGO acted as a filler, inducing structural rearrangements in chitin with the occurrence of new hydrogen bonds among the chains. Results proved that rheological behavior of the material became more solid-like with increasing nGO content. A physical composite nanochitin/microemulsion hydrogel was explored by Wang et al. for an extended release of hydrophobic compounds (drugs) under in vitro physiological surroundings, whereby it was made known that the composite hydrogels displayed slightly inferior values of storage modulus and loss modulus when compared to pure nanochitin hydrogels [94] . However, the G′ values of all the composite hydrogels were roughly around 1000 Pa. Chemical crosslinking studies of glutaraldehyde (Glu) with nanochitin were carried out by Liu et al., which proved that G′ values for nanochitin (x)/Glu (0.4) hydrogels were at least an order of magnitude higher than for the sturdiest chitin-derived hydrogels published hitherto [95] . A more rigid network structure formed at the higher TOCN content (3 or 5 wt %) led to a distinctive shear thinning flow behavior; with higher shear rate, the viscosity declined since the network was disturbed. Figure 21b shows that the AR viscosity increased linearly at medium or high constant shear levels with a higher TOCN concentration; the effect of the material at the higher constant shear rate was decreased. The dynamic viscoelastic nature of the water-based AR was also reformed with the integration of TOCNs. Figure 21c shows the storage modulus G and loss modulus G of the AR/TOCNs3 and AR/TOCNs5 formulations. The AR/TOCNs5 formulation exhibited solid-like (elastic) behavior at low angular frequencies as evidenced by the G > G . It also had a higher storage modulus along with the whole angular frequency range because of its higher TOCN content. The outcome shows that the TOCNs have the capability for modifying the rheological and mechanical properties of water-based coating arrangements. Chitin hybrid biodegradable materials reinforced with graphene oxide nanosheets (nGO) were prepared and characterized by Gonzalez et al. [90] , where nGO acted as a filler, inducing structural rearrangements in chitin with the occurrence of new hydrogen bonds among the chains. Results proved that rheological behavior of the material became more solid-like with increasing nGO content. A physical composite nanochitin/microemulsion hydrogel was explored by Wang et al. for an extended release of hydrophobic compounds (drugs) under in vitro physiological surroundings, whereby it was made known that the composite hydrogels displayed slightly inferior values of storage modulus and loss modulus when compared to pure nanochitin hydrogels [94] . However, the G values of all the composite hydrogels were roughly around 1000 Pa. Chemical crosslinking studies of glutaraldehyde (Glu) with nanochitin were carried out by Liu et al., which proved that G values for nanochitin (x)/Glu (0.4) hydrogels were at least an order of magnitude higher than for the sturdiest chitin-derived hydrogels published hitherto [95] .
Evaluation of barrier properties for composites is important due to the role of water in the production of microbial and the degradation results [57] . A coating or a film is very often needed in product packaging to minimize or prevent the transfer of moisture between the product and the surrounding environment. Water vapor permeability is the most imperative and extensive properties of bio-based polymer films, due to the direct influence on the deteriorating reactions in packaged food products. The qualities of the membrane will usually be strengthened by using appropriate additives [96] . In bio-polymer films, a broad variety of nanofillers have been applied to enhance the thermal and mechanical properties, as discussed before, and also water vapor barrier properties. Sustainable membrane structures dependent on nanomaterials produced from polysaccharides have drawn great deal of interest in recent times [93] . Chitin nanomaterials, together with cellulose nanomaterials, have garnered attention as products for safe gas barriers. Chitin is used as an origin of nanoparticles like those used in barrier films as one of the most important nanofiller reinforcements [97, 98] . Nonetheless, the effects of crystallinity, charges and measurements of chitin nanomaterials on the efficiency of their oxygen barriers are poorly explored [99] . Nanoparticles, nanofibers and nanocomposites produced using chitin reflect new families of polymer carriers and matrices capable of improving film/composite mechanical and barrier properties [100] . The intent of a barrier layer or film in a packaging product is to decelerate or essentially eliminate the advance of oxygen, water vapor or other molecules, thereby increasing the shelf life, protection and likely also the taste of goods-especially in the case of foods. The nanomaterials can be predicted to swell with rising relative humidity owing to the ample quantity of water-loving hydroxyl groups found on all polysaccharides. It is therefore widely established that the capacity of polysaccharide-based films to withstand water vapor would decrease sharply with rising relative humidity. Many considerations such as the chemical makeup of sources, the introduction of plasticisers and the crystallinity of the polymer material often influence the water barrier role of polysaccharide membranes and coatings [98] .
Permeability of gases through a substrate is described as the measurement of the transmission of permeate (gas and vapor) across a resistant medium. The predominant mode of gas distribution in a film without any flaws such as pinholes or cracks is the solubilization of gas molecules on a film surface (Henry's law) accompanied by the diffusion across the mass (Fick's law), and lastly desorption of gas particles from the opposing surface. There have been clear associations between the capacity of a film to inhibit the flow of oxygen gas and its ability to obstruct the passage of non-polar organic compounds in either the gaseous or the liquid state. The very same hydrogen bonds that bind the barrier film components together are often heavily affected by the influence of moisture or humidity [98] . Since film water vapor permeability (WVP) is based on the solubility and dissemination of particles throughout the film, nanoparticles may reduce this permeability by growing cross-linkage across polymer chains and loading the membrane porosity. Since nanoparticles can boost the cross-linking and cohesion of intermolecular interactions, they strengthen the oxygen barrier properties of the membranes [101] .
The study discussed by Hubbe et al. demonstrates the role of chitin nanoparticles on barrier film efficiency, and that these environmentally friendly components are often chosen in the resulting films where one of the objectives is to induce antimicrobial effects [98] . The latest studies have revealed that nanochitin can strengthen the barriers of gelatin films to water vapor by loading properties and causing a circuitous course across water molecules [97, 101, 102] . Chitin nanoparticles extracted from different sources, irrespective of their types and modifications, have been proven to improve water, gas and light barrier properties of composite films [57, 84, 86, 93, 97, 99, 103] . The barrier efficiencies of recorded nano-chitin-reinforced films were assessed using different protocols. Among the different metrics addressed, it seems that the most demanding requirements include avoiding the permeation of both water vapor and oxygen, and also to continue to resist this permeation even as the film is subjected to a broad spectrum of moisture. The membranes must therefore be adequately crucial to prevent the simple passage of oxygen, water vapor, aromas or bacteria into or out of the food packet [98] .
It has been reviewed that PLA-based nanostructured composites, comprising nano-fillers (such as phillosilicates, cellulose or chitin nanofibrils) can be capable of expanding the barrier properties of biodegradable composites without altering their optical properties (transparency). The attained Ag-non-woven tissue made of chitin nanofibers (CNF) and chitosan (CS) displayed the ability to diminish the burden bacteria of infested skin, and to augment the reparative capacity of the skin, presenting boosted antibacterial activity in conjunction with wound healing efficacy [100] . It has also been stated that particle concentrations influence the degree of coalescence during emulsification of solid-stabilized emulsions; actually, the coalescence can be decreased by rising the number of chitin nanoparticles in emulsions, which permits the establishment of links of accumulated units in the continuous phase [103] . Films fabricated by Ge et al. exhibited gradually decreased WVP values from 7.8 × 10 −4 to 6.7 × 10 −4 g day −1 m −1 atm −1 , perhaps due to the intramolecular and intermolecular connections among black rice bran anthocyanins (BACNs), oxidized chitin nanocrystals (O-CNCs) and gelatin, which condensed the breach in the film [97] . In addition, the massive aromatic and pyrylium rings in the skeleton of anthocyanins could impede the internal networks of BACNs-Ch films and lessen their water vapor affinity. Even though nanochitin could decline WVPs of gelatin membranes, they still had high affinity to water vapor due to the hydrophilic character of gelatin and nanochitin.
Salaberria et al. reported the modification of chitin nanocrystals via acylation using anhydride acetic and dodecanoyl chloride acid to improve their compatibility with PLA [57] . A minor diminution in the water vapor transmission rate (WVTR) (Figure 22 ), could be observed which is directly connected with the integration of hydrophobic clusters on the exterior of the chitin nanocrystals (CNCs). It has been reviewed that PLA-based nanostructured composites, comprising nano-fillers (such as phillosilicates, cellulose or chitin nanofibrils) can be capable of expanding the barrier properties of biodegradable composites without altering their optical properties (transparency). The attained Agnon-woven tissue made of chitin nanofibers (CNF) and chitosan (CS) displayed the ability to diminish the burden bacteria of infested skin, and to augment the reparative capacity of the skin, presenting boosted antibacterial activity in conjunction with wound healing efficacy [100] . It has also been stated that particle concentrations influence the degree of coalescence during emulsification of solidstabilized emulsions; actually, the coalescence can be decreased by rising the number of chitin nanoparticles in emulsions, which permits the establishment of links of accumulated units in the continuous phase [103] . Films fabricated by Ge et al. exhibited gradually decreased WVP values from 7.8 × 10 −4 to 6.7 × 10 −4 g day −1 m −1 atm −1 , perhaps due to the intramolecular and intermolecular connections among black rice bran anthocyanins (BACNs), oxidized chitin nanocrystals (O-CNCs) and gelatin, which condensed the breach in the film [97] . In addition, the massive aromatic and pyrylium rings in the skeleton of anthocyanins could impede the internal networks of BACNs-Ch films and lessen their water vapor affinity. Even though nanochitin could decline WVPs of gelatin membranes, they still had high affinity to water vapor due to the hydrophilic character of gelatin and nanochitin.
Salaberria et al. reported the modification of chitin nanocrystals via acylation using anhydride acetic and dodecanoyl chloride acid to improve their compatibility with PLA [57] . A minor diminution in the water vapor transmission rate (WVTR) (Figure 22 ), could be observed which is directly connected with the integration of hydrophobic clusters on the exterior of the chitin nanocrystals (CNCs). Both types of modified CNC appeared to be efficient components, i.e., they amended the hydrophobic nature of the PLA nanocomposite membranes to a small extent. However, the decline in the WVTR was more obvious for the PLA-based nanocomposites manufactured with nanochitin modified with fatty aliphatic chains (C12) rather than with acetic anhydride (C2) [57] . Reports have shown that in the case of carrageenan/chitin nanofibrils composites, moisture content of films pronouncedly diminished after combining with nanochitin [104] . The WVP of maize starch nanocomposite films declined with chitin nanowhisker (CNW) content increasing from 0 to 2%. Both types of modified CNC appeared to be efficient components, i.e., they amended the hydrophobic nature of the PLA nanocomposite membranes to a small extent. However, the decline in the WVTR was more obvious for the PLA-based nanocomposites manufactured with nanochitin modified with fatty aliphatic chains (C 12 ) rather than with acetic anhydride (C 2 ) [57] . Reports have shown that in the case of carrageenan/chitin nanofibrils composites, moisture content of films pronouncedly diminished after combining with nanochitin [104] . The WVP of maize starch nanocomposite films declined with chitin nanowhisker (CNW) content increasing from 0 to 2%. Concerning starch/chitin nanocrystals (CNC) nanocomposite membranes, when 5 and 10 wt % of nanochitin were added, WVTR values were lowered. Along with the clustering nature of chitin, another reason for the meagre water vapor barrier property is the occurrence of high residual NH 2 groups, which causes high attraction for water OH groups at the surfaces of the chitin nano-objects [96] .
Studies by Sahraee et al. have revealed that nanochitin assimilation in gelatin films significantly reduced their water vapor and oxygen permeability values, thereby helping them to preserve the peroxide value of cakes at lesser levels than other associated polymers [101] . At the same time, it has been recommended that applying gelatin emulsion film as the second layer could be pertinent. In another parallel research, Zhong et al. observed that TEMPO oxidised chitin nanocrystals (TOCNs) as a dispersed phase in the acrylic resin matrix did not augment the oxygen barrier property of the subsequent composites, but the neat continuous TOCN coating layer upgraded the oxygen barrier property of the laminates [93] (Figure 23 ). Concerning starch/chitin nanocrystals (CNC) nanocomposite membranes, when 5 and 10 wt % of nanochitin were added, WVTR values were lowered. Along with the clustering nature of chitin, another reason for the meagre water vapor barrier property is the occurrence of high residual NH2 groups, which causes high attraction for water OH groups at the surfaces of the chitin nano-objects [96] .
Studies by Sahraee et al. have revealed that nanochitin assimilation in gelatin films significantly reduced their water vapor and oxygen permeability values, thereby helping them to preserve the peroxide value of cakes at lesser levels than other associated polymers [101] . At the same time, it has been recommended that applying gelatin emulsion film as the second layer could be pertinent. In another parallel research, Zhong et al. observed that TEMPO oxidised chitin nanocrystals (TOCNs) as a dispersed phase in the acrylic resin matrix did not augment the oxygen barrier property of the subsequent composites, but the neat continuous TOCN coating layer upgraded the oxygen barrier property of the laminates [93] (Figure 23 ). They have also proposed the use of a multilayer structure for grander oxygen barrier properties. Other studies have specified that nanochitin are capable barrier materials; even trace amounts or a thin layer added to different substrates could result in outstanding barrier properties [105] [106] [107] . Figure 24 illustrates the barrier properties of gelatin/oxidized chitin nanocrystal nanocomposite films reliant on black rice bran anthocyanin (BACN) content. They have also proposed the use of a multilayer structure for grander oxygen barrier properties. Other studies have specified that nanochitin are capable barrier materials; even trace amounts or a thin layer added to different substrates could result in outstanding barrier properties [105] [106] [107] . Figure 24 illustrates the barrier properties of gelatin/oxidized chitin nanocrystal nanocomposite films reliant on black rice bran anthocyanin (BACN) content.
With the rise of BACNs, the oxygen permeability (OP) exhibited an alterable waning from 2.035 cm 3 m −2 d −1 atm −1 to 1.323 cm 3 m −2 d −1 atm −1 . Perhaps the hydrogen bond relations between BACNs and matrix controlled or protracted the penetrating path of oxygen. It was proposed the BACNs incorporation could pointedly boost the oxygen barrier. Remarkably, the OP of BACNs-Ch100 group was better than that of BACNs-Ch80 group, maybe due to the aggregation of anthocyanins and uneven distribution of matrix [97] . The drop in oxygen transmission rate (OTR) of PVA by various chitin nanomaterials were investigated by Tran et al. [99] . The virgin PVA film exhibited an OTR of 55.35 ± 9.22 mL/m 2 ·day, which was inadequate for usage in most food-packaging applications. The incorporation of chitin nanomaterials enhanced the oxygen barrier properties of the PVA membrane, thus aiding it to achieve values comparable to that of ethylene vinyl alcohol (EVOH) (<5 mL/m 2 ·day), an exemplary oxygen-barrier polymeric film. Conversely, graphene oxide, less considered in the food application arena than chitin has capable characteristics in the fabrication of food wraps owing to its oxygen barrier nature. Furthermore, the chemical groups in GO sheets unlocks the application fields for chitin, a low reactive polysaccharide [90] .
Polymers 2020, 12, x FOR PEER REVIEW 26 of 38 Figure 24 . Water vapor permeability and oxygen permeability of BACNs-Ch films [97] .
With the rise of BACNs, the oxygen permeability (OP) exhibited an alterable waning from 2.035 cm 3 m −2 d −1 atm −1 to 1.323 cm 3 m −2 d −1 atm −1 . Perhaps the hydrogen bond relations between BACNs and matrix controlled or protracted the penetrating path of oxygen. It was proposed the BACNs incorporation could pointedly boost the oxygen barrier. Remarkably, the OP of BACNs-Ch100 group was better than that of BACNs-Ch80 group, maybe due to the aggregation of anthocyanins and uneven distribution of matrix [97] . The drop in oxygen transmission rate (OTR) of PVA by various chitin nanomaterials were investigated by Tran et al. [99] . The virgin PVA film exhibited an OTR of 55.35 ± 9.22 mL/m 2 ·day, which was inadequate for usage in most food-packaging applications. The incorporation of chitin nanomaterials enhanced the oxygen barrier properties of the PVA membrane, thus aiding it to achieve values comparable to that of ethylene vinyl alcohol (EVOH) (<5 mL/m 2 ·day), an exemplary oxygen-barrier polymeric film. Conversely, graphene oxide, less considered in the food application arena than chitin has capable characteristics in the fabrication of food wraps owing to its oxygen barrier nature. Furthermore, the chemical groups in GO sheets unlocks the application fields for chitin, a low reactive polysaccharide [90] .
Studies revealed that the use of nanochitin in versatile polypropylene films, either as an additive in the framework or as a continuous layer in a laminate, would not affect the initial packaging's optical clarity; this was an added advantage as transparency is a desirable feature in modern food packaging. Shankar et al. studied the apparent color and clarity of carrageenan/chitin nanofibril films defined by the Hunter Lab-values and the percent visible light transmittance (660 nm), respectively. It could be seen that lightness (L-value) and transmittance of the composite films reduced linearly, while greenness (a-value), yellowness (b-value), and total color difference (ΔE) of the composite films improved monotonously with upsurge in the concentration of chitin nanofibrils [104] . Figure 25 demonstrates the light transmission spectra for the gelatin/black rice bran anthocyanins (BACNs)/oxidized chitin nanocrystals (O-CNCs) films developed by Ge et al. [97] .
Studies revealed that the use of nanochitin in versatile polypropylene films, either as an additive in the framework or as a continuous layer in a laminate, would not affect the initial packaging's optical clarity; this was an added advantage as transparency is a desirable feature in modern food packaging. Shankar et al. studied the apparent color and clarity of carrageenan/chitin nanofibril films defined by the Hunter Lab-values and the percent visible light transmittance (660 nm), respectively. It could be seen that lightness (L-value) and transmittance of the composite films reduced linearly, while greenness (a-value), yellowness (b-value), and total color difference (∆E) of the composite films improved monotonously with upsurge in the concentration of chitin nanofibrils [104] . Figure 25 demonstrates the light transmission spectra for the gelatin/black rice bran anthocyanins (BACNs)/oxidized chitin nanocrystals (O-CNCs) films developed by Ge et al. [97] . The light transmittance rate at 560 nm declined from 91.45% to 31.27% as the BACN contents were augmented from 0 mg to 100 mg, which was attributed to the merging effect of BACNs on the well-organized construction of O-CNCs and gelatin. The subsequent figures verified that the films comprising of BACNs could defend ultraviolet light and diminish the food decay instigated by The light transmittance rate at 560 nm declined from 91.45% to 31.27% as the BACN contents were augmented from 0 mg to 100 mg, which was attributed to the merging effect of BACNs on the well-organized construction of O-CNCs and gelatin. The subsequent figures verified that the films comprising of BACNs could defend ultraviolet light and diminish the food decay instigated by ultraviolet light and explicit range of visible light (200-400 nm).
New areas in the use of chitin have evolved across a variety of purposes including nanocomposite materials, electrical and electronic devices, cosmetics, agriculture, packaging, environmental and biomedical applications. Nanochitin serves as a possible nanofiller to be used as chitin nanocrystals, oxidized-chitin nanocrystals, nanofibrils, partly deacetylated chitin nanofibers, etc. to stabilize biopolymer-based composites [84] . The use of polymers and nanochitin to produce bio nanocomposites offers a good opportunity to prepare bio plastic materials with enhanced functional and structural properties. Agricultural scientists have analyzed nanochitin for their effects on crop growth enhancement, metabolism of carbon or nitrogen, stress tolerance, and elicitation of plant disease response [108] [109] [110] . Effects of nanochitin on improving grain yields and winter wheat quality were recorded by Xue et al. where they showed that 0.006 g kg -1 of nanochitin in soil could pointedly boost the yield by 23% for multi-spike wheat (MSW) and 33.4% for large spike wheat (LSW), with substantial rises of net photosynthesis rate, stomatal conductance, intercellular CO 2 concentrations, and transpiration rate in flag leaf at the grain filling stage [111] . Cheng et al., while studying the motivating effect of chitin nanoparticles on the metabolism of carbon and nitrogen, and the enhancement of grain yield and crude protein in winter wheat, suggested that nanochitin encouraged nitrogen metabolism more than carbon metabolism and increased crude protein concentration in grain by 13.26% and grain yield by 27.56% [112] . When applied at an optimal rate, cationic nanochitin whisker could inhibit root rot tobacco and wheat diseases, promote photosynthesis, and enhance the grain yield of winter wheat by promoting net photosynthesis rate, stomatal conductivity, intercellular CO 2 concentrations, and grain-filling transpiration rate in flag leaf. Grain protein, iron, and zinc in wheat also increased substantially when treated with nanochitin. Liang et al. researched nanochitin whisker's antifungal activity against crown rot wheat diseases and proved to have important inhibitory effects on mycelial growth and conidial production [113] . This suggested that nanochitin has good antifungal activity against soil-borne wheat pathogens and decreases the use of chemical fungicide in wheat planting. The impact of nanochitin suspensions on tobacco seed germination, seedling proliferation and symbiotic interaction with fungicides were investigated by Zhou et al. in indoor and field trials, while evaluating the bioactivity of nanochitin on tobacco [114] . Researchers found that 0.004% (w/v) of nanochitin enhanced tobacco seed germination and considerably reduced the mean time for germination; 0.005% (w/v) of nanochitin increased tobacco stem length, stem girth, leaf number and leaf area, and 0.001% (w/v) of nanochitin had simulatory effects on tobacco root rot inhibition when mixed with metalaxyl mancozeb and thiophanate methyl fungicides. This suggests that suspensions of nanochitin have a huge potential to safeguard tobacco from root rot diseases and to minimize the need for toxic fungicides in tobacco fields. Farmers have made significant use of nanochitin and its derivatives as biopesticides, biofertilizers and as agricultural film in seed and fruit coating among the vast array of alternative products for agricultural purposes identified so far.
Chitin nanofibrils (CNFs), consisting of colloidal nano-rods, institute the crystalline fraction of chitin isolated from marine food waste; they have been documented to exhibit anti-microbial properties and promote regeneration of cells. Chitin nanowhiskers also fall in the category of cost-effective fillers that can impart antibacterial activity for applications involving wound healing and food packaging. The antibacterial activity of chitin nano whiskers was explored Jiang et al., where lysozyme was adsorbed onto the surface of nanowhiskers which exhibited enhanced antibacterial activity when compared to lysozyme alone [115] . Chitin nanowhiskers extracted from crab shells were also used to prepare composite films in combination with maize starch. The films showed excellent antibacterial effect against gram positive bacteria but not against gram negative E. coli. The films also showed improved mechanical strength than neat starch films.
Nanochitin has been extensively studied in multifarious biomedical applications involving tissue engineering, drug delivery, wound healing etc. Torres-Rendon et al. manufactured bioactive gyroid scaffolds developed by sacrificial templating of nanocellulose and nanochitin hydrogels as edifying models for biomimetic tissue engineering, based on prior findings that human fibroblast adhesion to low deacetylation chitin is weak whereas human fibroblast and keratinocyte adhesion to highly deacetylated chitin is high [116] . Wang et al. effectively produced a physical composite nanochitin/microemulsion hydrogel for extended release under in vitro physiological conditions of hydrophobic compounds (drugs) [94] . They demonstrated that the composite hydrogel successfully embedded Nile Red in phosphate-buffered saline with an extended release time of 60 h (PBS pH 7.4, equivalent to biological conditions). The wound healing abilities of superficially deacetylated nanofibrils of chitin (SDACNFs) have been tested by Izumi et al.; they showed that SDACNFs successfully mediated re-epithelium, and fibroblast and collagen tissue proliferation [117] . Nano chitin was also used as an alternate natural nanomaterial in a study performed by Tang et al. to blend with cellulose fibers to make high-strength paper which improved the colorimetric output of glucose bioassays [118] .
Chitin nanofibers and surface deacetylated chitin nanofibers have been reported as potential functional foods for patients having obesity [119] . The beneficial role of deacylated chitin nanofibers (DEChNs) in reducing hypercholesterolemia was investigated in mice by dividing them into five groups [120] . The blank group comprised mice fed with a normal diet and saline solution; the control group included mice fed a high fat diet and dilute acetic acid solution; and remaining three groups of mice were treated with different doses of DEChNs. The histopathology studies of liver revealed that the control group showed a large number of fat vacuoles ( Figure 26 ). The blank group was diploid for vacuole formation, and that was the case for the mice treated with DEChNs too. The study clearly showed that the chitin nanofibers could effectively control lipid accumulation and could prevent fatty liver formation. Chitin nanofibrils have been majorly applied as nanofillers in the reinforcement of both natural and synthetic composites due to their size, mechanical strength and relevant biological properties. The various applications of chitin-based composites have been listed in Table 1 . Chitin nanofibrils have been majorly applied as nanofillers in the reinforcement of both natural and synthetic composites due to their size, mechanical strength and relevant biological properties. The various applications of chitin-based composites have been listed in Table 1 . Biomimetic scaffolds for bone tissue engineering [116] Sahraee et al. fabricated films for cake packaging based on bovine gelatin-nanochitin-nano ZnO [101] ; such films are suitable for packing of sponge cakes that do not involve preservatives because this packaging can avoid fungal growth for longer periods of time and could preserve the chemical and organoleptic consistency of cakes even more. Nano chitin composites are also employed for managing the freshness of food products, especially sea foods. Although Wu et al. effectively prepared intelligent chitosan-based films containing black rice bran anthocyanins for tracking seafood and animal-based protein contamination, they noted that the introduction of oxidized chitin nanocrystals improved the film's mechanical and barrier properties [121] . Analogous research was recorded by Ge et al. in which gelatin/oxidized chitin nanocrystal composite films comprising black rice bran anthocyanins were used for related applications for freshness monitoring [97] . Such films were pH-sensitive and displayed impressive improvements in color in different buffer solutions that could be used by noticeable color changes to track the freshness of shrimp.
Nano scale chitin and its derivatives also play extensive roles in environmental applications. Dye adsorption sectors and water treatment sectors have made use of the superior absorption capacities of chitin nanoparticles. One of the many such studies include the report by Gopi et al. where the researchers produced and examined shrimp shell chitin nano whiskers (CNW) for improved crystal violet adsorption [125] . A series of adsorbent materials such as chitin-Fe 3 O 4 , cellulose, and cellulose-Fe 3 O 4 , along with CNW, have been used to compare the results and to better explain adsorption phenomena. When compared to various sorbent materials, the newly synthesized chitin nanowhiskers exhibited augmented efficiency of removal (79.13%) and adsorption potential (39.56 mg g −1 ). The results showed that CNW could be a viable candidate for the elimination of crystal violet from polluted water. As a strong-efficiency adsorbent for water treatment, biohybrid hydrogel and aerogel from self-assembled nanocellulose and nanochitin were manufactured by Zhang et al. [60] . Biohybrid aerogels (BHA) demonstrated super-high adsorption potential of 217 mg·g −1 for As(III) under neutral pH conditions and 531 mg·g -1 for Methylene Blue (MB) under an alkaline aqueous atmosphere with accelerated kinetics of adsorption, in striking contrast to traditional biobased adsorption. In fact, the BHA is renewable, which still demonstrated a strong 505 mg·g -1 MB adsorption efficiency even after five consecutive cycles of adsorption-desorption. In parallel reported literature, Wu and colleagues developed biodegradable chitosan hydrogel beads containing nanochitin for the rapid and effective elimination of Cu(II) and magnetic chitosan microfibers comprising of nanochitin via continuous injection gelation method for removal of Ni(II) ions from aqueous solutions [126, 127] . The Fe 3 O 4 encapsulated polystyrene (FP) microparticles (as a magnetic separation material) and nanochitin (n-CT, as an advantageous natural metal-cation adsorbent) were integrated in situ into poly(vinyl alcohol)-enhanced chitosan hybrids (PVA/CTS) to form environmental-friendly nanocomposite hydrogels (FPCC) with magnetic segregation capability. Relative to the pure PVA/CTS hydrogels with a Cu (II) adsorption value of 38.7 mg/g, the FPCC hybridized hydrogels provided around 1.7-fold Cu (II) adsorption efficiency. Within 10 h, the FPCC magnetic microfibers (adsorbent dosage: 1 g, pH: 4.1, and temperature: 293 K) could adsorb 99.7% Ni (II), after which the hybridized microfibers were shown to be readily isolated from the aqueous solution by a magnetic separation process. The manufacture of nanochitin/manganese oxide-biodegradable composite adsorbent for heavy metal ions was also documented by Krivoshapkin et al. where it was found that the use of organomineral composite sorbents adopted the Ni 2+ > Cu 2+ > Sr 2+ pattern for removal of heavy metal ions, with a sorption efficiency of 114.0 ± 1.1 mg/g for Ni 2+ [122] . The harvested biodegradable sorbents were aimed at addressing ecological problems correlated with radioactive metallic ions polluting natural water.
Yet another field that nanochitin finds application includes electrical and electronic devices. For example, biobased cryogel membranes were implemented as electrolyte holders in dye solar cells (DSC) [128] , thus facilitating carrier transport during service. It was also observed that the system performance and stability were also improved with the help of chitin nano fibers. Conductive biomass-based composite wires with cross-linking anionic nanocellulose and cationic nanochitin as scaffolds were developed by Xu et al., who efficiently designed a collection of conductive composite wires by coupling dispersions of multi-wall carbon nanotubes (MWCNTs) and TEMPO-oxidized cellulose nanofibers (TOCNFs) with specific MWCNT compositions into a dispersion of partly deacetylated α-chitin nanofibers (α-DECHNs) proceeded with a drying procedure [85] . When the content of MWCNTs exceeded 14 wt %, the designed composite wire could illuminate LED at 5 V voltage, demonstrating the enormous latency of this product based on biomass in conductive material deployment.
Management of crustacean shell waste has become a huge problem in the sea food industries. The effective processing of shell waste from marine organisms is being exploited for extracting chitin and its derivatives. In contrast to synthetic polymers, natural polymers such as chitin are good raw materials for producing inexpensive, rapidly degradable bioplastics. Despite the described advantages, the utilization of biopolymers has been limited due to concerns regarding their poor mechanical and barrier properties, which can be improved by adding bio-based reinforcing agents (fillers), forming composites. Nanochitin have shown considerable advantages in various sectors, such as biomedicine, the food industry and agriculture, due to its unique properties. Future research should focus on finding greener solutions for cost effective processing of nanochitin. Use of eco-friendly solvents or recycling of the reagents can minimize the toxicity due to hazardous effluents. A combination of enzymatic and chemical techniques for the isolation of chitin can also be considered. However, a fundamental understanding of structure-function relationship is essential for the development of multifunctional composites that could probably overcome the current constraints.
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The first two COVID-19 cases were confirmed in Italy in January 2020 and, by the end of February, the virus had spread over northern regions of the country. During March, the toll of new cases and deaths kept surging, rapidly overtaking the numbers registered in China and making Italy the hardest-hit country in Europe and one of the epicentres of the global pandemic.
In Lombardy, the heart of the outbreak, COVID-19 was not yet labelled a pandemic, but the healthcare system had already started groaning under the strain of the invisible enemy. In the struggle to cope with the expanding threat, war-like measures were adopted by the Government, but Italy was insufficiently prepared to face this unprecedented challenge and, on the brink of collapse, weaknesses were unveiled.
As Italian citizens, and doctors, we wondered whether there was anything to be done differently, anything we could do to be more prepared to tackle the virus and allow our healthcare system to respond adequately to the crisis. We, therefore, hypothesized that digital epidemiology could provide valuable insights into the spread of the viral infection and hints useful to predict the COVID-19 outbreak in Italy.
Google Trends is a public, open-access tool (https ://trend s.googl e.com/trend s/), used to monitor patterns and volumes of queries in a selected geographical area over a specified period. Absolute search volumes are not provided, but a value of 100 is assigned to the peak interest of the time range and relative search popularity in the other time points is proportionally conveyed in a data series over a 0-100 normalized scale.
Since temporal correlation between Google Trends and outbreaks of diseases different from COVID-19 has been suggested [1, 2] , we imagined that a spike in searches of early symptoms characterizing the prodromal stage of the disease, as cough and fever, could precede admissions to intensive care units (ICUs) and deaths from COVID-19. Case data started to be recorded on February 24 and are provided daily by the Civil Protection Department, accessible on the Italian Government's website https ://www.salut e.gov.it.
We analysed official data on increase in ICU admissions and new deaths collected until April 6. A Google Trends' search was performed in Italian language using the key terms "tosse" and "febbre", respectively, meaning "cough" and "fever" in English translation, over the period between February 24 and April 6, 2020. We thus plotted the size of daily increase in ICU admissions against the synchronous proportion of interest toward "tosse" and "febbre" (Fig. 1a, b) . Then, the same approach was applied to the data on new deaths (Fig. 1c, d) .
Visual inspection suggested a temporal correlation, with a lag period between trends in search volumes and ICU admissions or deaths, respectively, of about 1 and 2 weeks. Hence, we repeated the Google Trends' search anticipating the search period by 1 and 2 weeks, then plotting the increase in ICU admissions against Google Trends for "tosse" and "febbre" 1 week earlier (Fig. 1e, f) , and the number of new deaths against the search volumes for "tosse" and "febbre" 2 weeks earlier (Fig. 1g, h) .
We subsequently analysed the findings through linear regression ( Fig. 2a-d) . The strength of the relationship was expressed by a coefficient of determination (R 2 ) of 0.580 and 0.576, respectively, between the increase in ICU admissions and Google Trends for "tosse" or "febbre" 1 week earlier. Furthermore, the R 2 was, respectively, 0.507 and 0.624 between new deaths and searches for "tosse" or between February 24 and April 6, 2020, plotted against Google Trends' search volumes of the Italian words "Tosse" and "Febbre", corresponding to "cough" and "fever" in English translation. a Google Trends for "Tosse" synchronous to the increase in ICU admissions. b Google Trends for "Febbre" synchronous to the increase in ICU admissions. c Google Trends for "Tosse" synchro-nous to new deaths. d Google Trends for "Febbre" synchronous to new deaths. e Google Trends for "Tosse" 1 week earlier than ICU admissions. f Google Trends for "Febbre" 1 week earlier than ICU admissions. g Google Trends for "Tosse" 2 weeks earlier than new deaths. h Google Trends for "Febbre" 2 weeks earlier than new deaths. "febbre" 2 weeks earlier. All P values were statistically significant < 0.001.
In few days, COVID-19 stretched the Italian healthcare system beyond the limits, overloading hospitals in the northern part of the country with a quickly escalating number of critically ill patients needing ICU beds and respiratory support. As the virus piled pressure on the system, the Government responded investing resources and rushing to increase the capacity of ICUs, but in the early stages SARS-CoV-2 was spreading faster than our ability to fight it.
Could we brace for impact? Could we predict the outbreak? Observing Google Trends, we noted a correlation between the dynamics of key searches for symptoms referable to SARS-CoV-2 infection, the increase in ICU admissions and new deaths. Indeed, Google searches for cough and fever preceded by 1 week, the need for critical care in Italy and by 2 weeks deaths from COVID-19. Recent research attempted to explore the relationship between Google Trends and COVID-19 and to evaluate the possibility of predicting new cases from internet searches [3, 4] . However, at least in Italy, the search of keywords as "coronavirus" or "pneumonia" during the COVID-19 crisis was broadly unspecific and mostly attributable to informative purposes, showing a linear increase temporally corresponding to the interest toward the pandemic from mass media and public opinion. Therefore, we postulated that simple terms referring to key early COVID-19 symptoms-e.g. "fever" and "cough"-or even more specific such as "loss of smell" or "loss of taste" could be more explanatory of the viral outbreak's evolution.
To strengthen our results, we assessed whether a correlation between search volumes for commonly occurring symptoms not directly related to SARS-CoV-2 infection [5] and ICU admissions existed or not. For this analysis, we selected the same period of ICU admissions from February 24 to April 6 and we searched Google trends 1 week before using the Italian words "mal di schiena", "tachicardia", "prurito", "diarrea", corresponding to "back pain", "tachycardia", "itching" and "diarrhea" in English translation. In linear regression analysis, we found an extremely weak positive correlation between searches for "diarrea" (R 2 0.122, p = 0.023) and increase in ICU admissions, no correlation
Google Trends search volumes of the Italian words "Tosse" and "Febbre", corresponding to "cough" and "fever" in English translation, and increase in ICU admissions and new deaths from COVID-19 between February 24 and April 6, 2020. a Google Trends for "Tosse" 1 week earlier and increase in ICU admissions. b Google Trends for "Febbre" 1 week earlier and increase in ICU admissions. c Google Trends for "Tosse" 2 weeks earlier and new deaths. d Google Trends for "Febbre" 2 weeks earlier and new deaths. for "mal di schiena" (R 2 0.012, p = 0.496) and negative correlations for "prurito" (R 2 0.119, p = 0.025) and tachycardia (R 2 0.273, p < 0.001). No temporal trends could, therefore, be identified between search volumes of terms not closely referable to COVID-19 and increase in ICU admissions (Fig. 3a-d) , confirming that symptoms suggestive of viral respiratory infection, such as "fever" and "cough", could more reliably predict the increase in ICU beds demand.
However, being aware that "fever" and "cough" cannot be considered specific of COVID-19 infection and that a surge in interest is expected during seasonal flu outbreaks, we compared Google Trends volumes for "fever" and "cough" between winter 2018-2019 and winter 2019-2020. In particular, official Italian data (https ://www.epice ntro.iss.it/influ enza/bilan cio-2018_2019) reported that, in 2018-2019, seasonal flu peaked between late January and early February 2019. We thus plotted Google Trends of key terms "fever" and "cough" from December 2018 to April 2019 against search volumes during the same months of the 2019-2020 season, outlining how the interest toward "fever" and "cough" was considerably higher during the COVID-19 pandemic compared to the peak of previous year flu outbreak ( Fig. 4a, b) . Interestingly, a surge in Google Trends for "fever" and "cough" could also be observed around the end of January 2020, corresponding to the increase of seasonal flu. However, Google Trends volumes for "fever" and "cough" in 2020 seasonal flu period were, respectively, less than 50% and 65% of those referable to the COVID-19 pandemic (Fig. 4a, b) . This observation suggests how COVID-19 might have a substantial impact on the occurrence of respiratory symptoms in the general population, thus corroborating the theory of a role for Google Trends in monitoring the dynamics of future COVID-19 evolution.
Our idea is indeed that the interpretation of Google Trends data could have been useful to warn the healthcare system concerning what we were about to experience 1 week ahead. This time we were close to breaking point, but second waves of COVID-19 are expected [6] and monitoring Google Trends might help us to anticipate them. One week might be enough to strengthen and re-organize the healthcare system and activate critical care facilities. Next time, 1 week in advance could be crucial to react faster and be more aggressive in the effort to prevent and contain the pandemic, hoping treatments will be available to fight COVID-19 [7, 8] . Fig. 3 Increase in ICU admissions COVID-19 between February 24 and April 6, 2020, plotted against Google Trends' search volumes of the Italian words "Mal di schiena", "Tachicardia", "Prurito" and "Diarrea", corresponding to "back pain", "tachicardia", "itching" "diarrhea" in English translation. a Google Trends for "Mal di schiena" 1 week earlier than ICU admissions. b Google Trends for "Tachicardia" 1 week earlier than ICU admissions. c Google Trends for "Prurito" 1 week earlier than ICU admissions. Google Trends for "Diarrea" 1 week earlier than ICU admissions.
Intrigued by the potential of Google Trends data, we used intuitive statistics to explore their possible value in the management of COVID-19 outbreak. Big data analytics is beyond our competence, but integrating information of top online health search requests from different countries, languages and time periods, might in our opinion shed light on the dynamics of COVID-19 global spread.
In conclusion, although appropriate use and reliability of the tool have not been thoroughly defined and data should be calibrated for future use, tracking public health information from online search engines, which is called "infodemiology" and "infoveillance" [9] , might have a role in the prediction of future COVID-19 waves, complementarily to traditional public health surveillance systems.
Funding None.
Conflict of interest The authors declare they have no conflict of interest.
No human participant or animal was involved in the present research.
The authors used open-access data and information available on official websites of the Italian government. Only aggregate, anonymous data were used for the purpose of the present research. Therefore, informed consent was not required.
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The COVID-19 pandemic has proven to be a tensile stress test for Singapore, as the collective consciousness of the Severe Acute Respiratory Syndrome (SARS) still lingers. On the psychological front, healthcare worker (HCW) survivors still recall the emotional stress owing to the fear of an unknown disease, public stigma, and the grim realities of mortality (Kwek et al.,2004; Maunder et al.,2003) . Notably, caring for fellow HCWs as patients was a unique yet challenging emotional experience (Maunder et al.,2003) . These challenges underscore the need to provide psychological support to frontline HCWs. However, this provision is not without its challenges due to the lack of shared experiences from lay mental health providers, and the competing demands between patient care and staff support (Duan and Zhu, 2020) .
Learning from the experience of SARS, COVID-19 pandemic preparedness now extends beyond medical and systemic aspects of care. It recognizes the psychological support of HCWs as an essential strategy in ensuring a robust workforce with a sustained ability to provide safe care (Kang et al.,2020) . Therefore, psychiatrists play a crucial role in education and advocacy during a pandemic, considering the multifarious psychological implications of COVID-19 (Tandon, 2020) .
A Psychological Preparedness Toolkit for HCWs was designed for Singapore's National Centre for Infectious Diseases to prepare HCWs who were about to be deployed to crucial COVID-19 care areas. Its objective was to provide realistic depictions of frontline work, which would be unfamiliar to HCWs from different care settings and levels of experience. This toolkit preceded hospital-wide psychological support measures, such as the nomination of welfare officers and psychological first aid training. The toolkit content comprised four main categories: (i) expected emotional responses, (ii) changes in the work environment, (iii) support measures, and (iv) anticipated effects on mental health.
The paradigm shift defining COVID-19 apart from the era of SARS lies in the ease and speed in how information is obtained, consumed, and disseminated with technology and social media. As such, the toolkit avoided replication of existing content such as stress management strategies that were readily available from reputable sources.
With the rapid sharing of information across various digital media, those receiving information from various sources may doubt about the credibility of hearsay (Vosoughi et al.,2018) . The toolkit provided a reliable source of advice and practical coping strategies from the pioneer cohort of HCWs who served in COVID-19 care areas. An illustrative and informative example is the commonly-encountered discomfort of Personal Protective Equipment (PPE) and HCWs learning to reduce mask abrasions with emollients.
The ethno-geographic diversity of Singapore's healthcare workforce and its implications were illustrated by the Malaysian border lockdown enforced within 48 hours of its announcement (The Star, 2020). Given that HCWs form a significant part of the 300,000 people crossing the Malaysia-Singapore border daily (The Straits Times 2016), those who chose to continue working in Singapore were stranded, and accommodation and alternative work arrangements became issues that required immediate attention. The toolkit acknowledged these challenges that occurred outside of healthcare and provided tips on using social media and telecommunications to foster connectivity with the workers' families.
The toolkit included the Burnout Measure (short version) (Malach-Pines, 2005), a widely used self-reported appraisal of burnout because of its intuitive questions and ease of use, to encourage periodic mental health check-ins. The hospital's employee assistance program helplines were appended to nudge distressed persons to seek help.
Inclusion of principles of organization theory in the context of COVID-19 management aided supervisors in the evaluation of employee behaviors, and in identifying risk factors for burnout and disengagement. Specific sources of stress, namely biosecurity measures, loss of autonomy, and perceived lack of control, guided the identification of pain points that may affect employee well-being.
Storytelling is recognized as a powerful educational strategy in health professions education and is often employed as a means of information sharing, engagement, and promotion of citizen participation (Haigh and Hardy, 2011) . Personally-narrated stories of frontline HCWs were weaved into the toolkit to highlight essential learning points. The creation of relatable and easily identifiable content overcomes issues with cognitive overload and information fatigue.
[ Table 1 ]
The psychological preparedness toolkit is an emergency educational tool borne out of exigent circumstances. Given the needs of the day, the toolkit was designed as an informative just-in-time strategy, focusing on needs-related training, easy accessibility, and highly-identifiable content. Timely and effective psychological preparedness interventions are necessary to ensure the sustainability of a resilient workforce that should not only be able to mount a sprint response, but also possess the tenacity to run a long-drawn marathon of a global pandemic.
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Mar 27]. Available from: https://www.straitstimes.com/asia/se-asia/nearly-300000-peoplewalk-between-malaysia-singapore-daily-malaysian-immigration-dept
Quote Acknowledging anxiety and affirming acclimatisation "People will start off feeling anxious because they are afraid of getting infected, and struggle working in a new environment. But I notice that by the 3rd shift, most people are settled in and become fairly comfortable."
Accepting change and a dynamic environment "Because workflows are always changing, I fear making mistakes and worry what I do will be unsafe."
Anticipating discomfort "Be prepared to get really warm in the PPE! I wore the PPE for three hours and I was soaked in sweat right down to my undergarments. But everyone understands it's for our own protection."
Building trust in protective measures "PPE is armour you can trust in. I have been in direct contact with five desaturating COVID-19 patients while wearing PPE. And although I fell sick, I tested COVID-19 negative three times. So wear that armour with pride." Addressing presenteeism and civic responsibility Nobody is indispensable and your team has your back. So if you are sick or running a fever, please do not come to work. I was on 14 days of hospitalisation leave because of an unrelenting fever which fortunately turned out to be strep[tococcus] throat. But the ward team continued in my absence -it was business as usual."
Active ownership of emotional wellbeing "Little pockets of time you can find during lull periods or when commuting to work, can be used to be with your thoughts. And if you can afford some time to free write, that might be even better. Be mindful of your thoughts and see what is frustrating you so that you can sit with those feelings then let them pass." Benevolent care and meaning-making in difficult circumstances "People don't always remember what you said or what you did, but how you made them feel. One of the desaturating COVID-19 patients was very anxious and kept moving whilst I was taking bloods. It was frustrating, but I tried my best to be professional. I saw her in clinic yesterday, and she remembered my voice. She said she was thankful for my gentle insistence on trying again… that I was patient although she had been emotional. So yes, that was humbling." Addressing the effects of stigma against HCWs My healthcare assistant was told by her landlord to pack up and leave on a Friday afternoon, after he found out that she worked in our hospital. I frantically tried to find accommodation. I felt outraged. How can she be penalised for her duty? Fortunately a fellow colleague welcome her to her home that very weekend."
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