COVID-19 antibody seroprevalence in Santa Clara County, California

How denialist amplification spread COVID misinformation and undermined the credibility of public health science

Denialist scientists played an outsized role in shaping public opinion and determining public health policy during the recent COVID pandemic. From early on, amplification of researchers who denied the threat of COVID shaped public opinion and undermined public health policy. The forces that amplify denialists include (1) Motivated amplifiers seeking to protect their own interests by supporting denialist scientists, (2) Conventional media outlets giving disproportionate time to denialist opinions, (3) Promoters of controversy seeking to gain traction in an 'attention economy,' and (4) Social media creating information silos in which denialists can become the dominant voice. Denialist amplification poses an existential threat to science relevant to public policy. It is incumbent on the scientific community to create a forum to accurately capture the collective perspective of the scientific community related to public health policy that is open to dissenting voices but prevents artificial amplification of denialists.

Antibody tests for identification of current and past infection with SARS-CoV-2

BACKGROUND

The diagnostic challenges associated with the COVID-19 pandemic resulted in rapid development of diagnostic test methods for detecting SARS-CoV-2 infection. Serology tests to detect the presence of antibodies to SARS-CoV-2 enable detection of past infection and may detect cases of SARS-CoV-2 infection that were missed by earlier diagnostic tests. Understanding the diagnostic accuracy of serology tests for SARS-CoV-2 infection may enable development of effective diagnostic and management pathways, inform public health management decisions and understanding of SARS-CoV-2 epidemiology.

OBJECTIVES

To assess the accuracy of antibody tests, firstly, to determine if a person presenting in the community, or in primary or secondary care has current SARS-CoV-2 infection according to time after onset of infection and, secondly, to determine if a person has previously been infected with SARS-CoV-2. Sources of heterogeneity investigated included: timing of test, test method, SARS-CoV-2 antigen used, test brand, and reference standard for non-SARS-CoV-2 cases.

SEARCH METHODS

The COVID-19 Open Access Project living evidence database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) was searched on 30 September 2020. We included additional publications from the Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-Centre) 'COVID-19: Living map of the evidence' and the Norwegian Institute of Public Health 'NIPH systematic and living map on COVID-19 evidence'. We did not apply language restrictions.

SELECTION CRITERIA

We included test accuracy studies of any design that evaluated commercially produced serology tests, targeting IgG, IgM, IgA alone, or in combination. Studies must have provided data for sensitivity, that could be allocated to a predefined time period after onset of symptoms, or after a positive RT-PCR test. Small studies with fewer than 25 SARS-CoV-2 infection cases were excluded. We included any reference standard to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction tests (RT-PCR), clinical diagnostic criteria, and pre-pandemic samples).

DATA COLLECTION AND ANALYSIS

We use standard screening procedures with three reviewers. Quality assessment (using the QUADAS-2 tool) and numeric study results were extracted independently by two people. Other study characteristics were extracted by one reviewer and checked by a second. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test and, for meta-analysis, we fitted univariate random-effects logistic regression models for sensitivity by eligible time period and for specificity by reference standard group. Heterogeneity was investigated by including indicator variables in the random-effects logistic regression models. We tabulated results by test manufacturer and summarised results for tests that were evaluated in 200 or more samples and that met a modification of UK Medicines and Healthcare products Regulatory Agency (MHRA) target performance criteria.

MAIN RESULTS

We included 178 separate studies (described in 177 study reports, with 45 as pre-prints) providing 527 test evaluations. The studies included 64,688 samples including 25,724 from people with confirmed SARS-CoV-2; most compared the accuracy of two or more assays (102/178, 57%). Participants with confirmed SARS-CoV-2 infection were most commonly hospital inpatients (78/178, 44%), and pre-pandemic samples were used by 45% (81/178) to estimate specificity. Over two-thirds of studies recruited participants based on known SARS-CoV-2 infection status (123/178, 69%). All studies were conducted prior to the introduction of SARS-CoV-2 vaccines and present data for naturally acquired antibody responses. Seventy-nine percent (141/178) of studies reported sensitivity by week after symptom onset and 66% (117/178) for convalescent phase infection. Studies evaluated enzyme-linked immunosorbent assays (ELISA) (165/527; 31%), chemiluminescent assays (CLIA) (167/527; 32%) or lateral flow assays (LFA) (188/527; 36%). Risk of bias was high because of participant selection (172, 97%); application and interpretation of the index test (35, 20%); weaknesses in the reference standard (38, 21%); and issues related to participant flow and timing (148, 82%). We judged that there were high concerns about the applicability of the evidence related to participants in 170 (96%) studies, and about the applicability of the reference standard in 162 (91%) studies. Average sensitivities for current SARS-CoV-2 infection increased by week after onset for all target antibodies. Average sensitivity for the combination of either IgG or IgM was 41.1% in week one (95% CI 38.1 to 44.2; 103 evaluations; 3881 samples, 1593 cases), 74.9% in week two (95% CI 72.4 to 77.3; 96 evaluations, 3948 samples, 2904 cases) and 88.0% by week three after onset of symptoms (95% CI 86.3 to 89.5; 103 evaluations, 2929 samples, 2571 cases). Average sensitivity during the convalescent phase of infection (up to a maximum of 100 days since onset of symptoms, where reported) was 89.8% for IgG (95% CI 88.5 to 90.9; 253 evaluations, 16,846 samples, 14,183 cases), 92.9% for IgG or IgM combined (95% CI 91.0 to 94.4; 108 evaluations, 3571 samples, 3206 cases) and 94.3% for total antibodies (95% CI 92.8 to 95.5; 58 evaluations, 7063 samples, 6652 cases). Average sensitivities for IgM alone followed a similar pattern but were of a lower test accuracy in every time slot. Average specificities were consistently high and precise, particularly for pre-pandemic samples which provide the least biased estimates of specificity (ranging from 98.6% for IgM to 99.8% for total antibodies). Subgroup analyses suggested small differences in sensitivity and specificity by test technology however heterogeneity in study results, timing of sample collection, and smaller sample numbers in some groups made comparisons difficult. For IgG, CLIAs were the most sensitive (convalescent-phase infection) and specific (pre-pandemic samples) compared to both ELISAs and LFAs (P < 0.001 for differences across test methods). The antigen(s) used (whether from the Spike-protein or nucleocapsid) appeared to have some effect on average sensitivity in the first weeks after onset but there was no clear evidence of an effect during convalescent-phase infection. Investigations of test performance by brand showed considerable variation in sensitivity between tests, and in results between studies evaluating the same test. For tests that were evaluated in 200 or more samples, the lower bound of the 95% CI for sensitivity was 90% or more for only a small number of tests (IgG, n = 5; IgG or IgM, n = 1; total antibodies, n = 4). More test brands met the MHRA minimum criteria for specificity of 98% or above (IgG, n = 16; IgG or IgM, n = 5; total antibodies, n = 7). Seven assays met the specified criteria for both sensitivity and specificity. In a low-prevalence (2%) setting, where antibody testing is used to diagnose COVID-19 in people with symptoms but who have had a negative PCR test, we would anticipate that 1 (1 to 2) case would be missed and 8 (5 to 15) would be falsely positive in 1000 people undergoing IgG or IgM testing in week three after onset of SARS-CoV-2 infection. In a seroprevalence survey, where prevalence of prior infection is 50%, we would anticipate that 51 (46 to 58) cases would be missed and 6 (5 to 7) would be falsely positive in 1000 people having IgG tests during the convalescent phase (21 to 100 days post-symptom onset or post-positive PCR) of SARS-CoV-2 infection.

AUTHORS' CONCLUSIONS

Some antibody tests could be a useful diagnostic tool for those in whom molecular- or antigen-based tests have failed to detect the SARS-CoV-2 virus, including in those with ongoing symptoms of acute infection (from week three onwards) or those presenting with post-acute sequelae of COVID-19. However, antibody tests have an increasing likelihood of detecting an immune response to infection as time since onset of infection progresses and have demonstrated adequate performance for detection of prior infection for sero-epidemiological purposes. The applicability of results for detection of vaccination-induced antibodies is uncertain.

Seroprevalence of Anti-SARS-CoV-2 Antibodies in High-Risk Occupational and Low-Risk Groups in Southwestern Iran

Background: Monitoring the spread of SARS-CoV-2 has been considered by the World Health Organization (WHO). We examined the prevalence of anti-SARS-CoV-2 immunoglobulin antibodies in southwestern Iran in spring 2020. The circulation of SARS-CoV-2 is high in the general population, especially among health care workers (HCWs) who are in close contact with patients. Objectives: The aim of this study was to determine the prevalence of anti-SARS-CoV-2 antigen in high-risk occupational and low-risk groups to investigate risk factors for serum positivity in Shiraz, southwestern Iran. Methods: A cross-sectional survey was performed on 366 participants (204 from high-risk and 162 from low-risk subjects). IgG and IgM antibodies were detected using Pishtaz Teb COVID-19 ELISA Kits to evaluate SARS-CoV-2-antigen in serum samples. After enzyme-linked immunosorbent assay (ELISA), serum prevalence, as well as IgG/IgM positive factors, was determined using logistic regression. Results: From July to September 2020 (a few months after reporting the first case of COVID-19 cases in Iran), out of 366 survived people, 72 (40.9%) were IgG positive, and 50 (27.5%) were IgM positive. The frequency of positive serology for IgG and IgM antibodies in individuals aged < 30 years was higher in the low-risk group than in the high-risk group. Multivariate logistic regression showed that headache (OR 0.312 [95% CI: 0.136 - 0.717]) and cough (OR 0.427 [95% CI: 0.182 - 1.004]) factors were associated with IgG or IgM positive serology. Conclusions: Between July and September 2020, the prevalence of anti-SARS-CoV-2 antigen was high in Shiraz. The prevalence of SARS-CoV-2 IgG/IgM antibodies in the high-risk group and their family as low risk was shown to increase viral infection due to close contact with COVID 19 patients than in the general population. Several factors were found to be related to the prevalence of anti-SARS-CoV-2 antigen that needs to be considered by policymakers to determine what to do about the SARS-CoV-2 pandemic.

Information networks for COVID-19 according to race/ethnicity

This study highlights information networks for COVID-19 according to race/ethnicity by employing social network analysis for Twitter. First, this study finds that racial/ethnic groups are differently dependent on racial/ethnic key players. Whites and Asians show the highest number of racial/ethnic key players, Hispanics have a racial/ethnic key player, and blacks have no racial/ethnic key player in the top 20. Second, racial/ethnic groups show different characteristics of information resources for COVID-19. Whites have the highest key player group in news media, politicians, and researchers, and blacks show the highest key player group in news media. Asians demonstrate the highest key player group in news media, and Hispanics exhibit institutes as the highest key player group. Lastly, there are some differences in group communications across the race/ethnicity. Whites and blacks show open communication systems, whereas Asians and Hispanics reveal closed communication systems. Therefore, governments should understand the characteristics of communications for COVID-19 according to the race/ethnicity.

Microfluidic characterisation reveals broad range of SARS-CoV-2 antibody affinity in human plasma

The clinical outcome of SARS-CoV-2 infections, which can range from asymptomatic to lethal, is crucially shaped by the concentration of antiviral antibodies and by their affinity to their targets. However, the affinity of polyclonal antibody responses in plasma is difficult to measure. Here we used microfluidic antibody affinity profiling (MAAP) to determine the aggregate affinities and concentrations of anti-SARS-CoV-2 antibodies in plasma samples of 42 seropositive individuals, 19 of which were healthy donors, 20 displayed mild symptoms, and 3 were critically ill. We found that dissociation constants, K d, of anti-receptor-binding domain antibodies spanned 2.5 orders of magnitude from sub-nanomolar to 43 nM. Using MAAP we found that antibodies of seropositive individuals induced the dissociation of pre-formed spike-ACE2 receptor complexes, which indicates that MAAP can be adapted as a complementary receptor competition assay. By comparison with cytopathic effect-based neutralisation assays, we show that MAAP can reliably predict the cellular neutralisation ability of sera, which may be an important consideration when selecting the most effective samples for therapeutic plasmapheresis and tracking the success of vaccinations.

Seropositivity of SARS-CoV-2 IgG Antibody among People in Dhaka City during the Prevaccination Period

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin G (IgG) detection can be an effective complementary tool to the reverse transcription-polymerase chain reaction (RT-PCR) test in estimating the true burden of coronavirus diseases 2019 (COVID-19) and can serve as baseline data, especially after the roll-out of vaccines against SARS-CoV-2. In this study, we aim to determine the seropositivity of SARS-CoV-2 IgG among people in Dhaka, Bangladesh. Volunteers, mostly asymptomatic people from Dhaka, were enrolled between October 2020 and February 2021. After obtaining participants' signed consents, blood samples were tested for SARS-CoV-2 IgG antibody, following the standard protocol of testing within 72 hours of collection. SARS-CoV-2 IgG was positive in 42% (101/239) of the cases. No difference was observed in terms of IgG positivity and IgG levels when stratified by age, gender, and blood group. However, RT-PCR-positive cases presented higher IgG levels compared to RT-PCR-negative/RT-PCR-not performed cases. SARS-CoV-2 IgG was found in 31% (32/102) and 28% (19/67) of RT-PCR-negative and RT-PCR-not performed cases, respectively. For RT-PCR-positive but SARS-CoV-2 IgG-negative cases (n = 13), the average time gap between the RT-PCR and SARS-CoV-2 IgG tests of six months indicates a gradual reduction of IgG. Eight cases for which samples were tested at two time points, three months apart, showed presented a decline in IgG levels with time (median IgG index of 2.55 in the first sample versus 1.22 in the second sample). Our findings reveal that several mild/asymptomatic cases that were RT-PCR-negative/not tested exist in the community, and IgG levels reduce in the human body over time.

Prevalence and Correlates of SARS CoV-2 Among a Community-Based Sample Recruited Using Randomized Venue-Based Sampling. Essex County, NJ, 2020

Disparities in morbidity and mortality related to COVID-19 based on race and ethnicity have been documented in the USA. However, it is unclear if these disparities also exist at the exposure stage. To determine this, studies are needed to document the underlying burden of disease, potential disparities through serologic surveillance. Additionally, such studies can help identify where along the disease spectrum (e.g., exposure, infection, diagnosis, treatment, death) and with regard to the structural factors that necessitate public health and/or clinical interventions. Our objectives in this study were to estimate the true burden of SARS CoV-2 in the community of Essex County, NJ, an early and hard hit area, to determine the correlates of SARS CoV-2 prevalence and to determine if COVID-19 disparities seen by race/ethnicity were also reflected in SARS CoV-2 burden. We utilized venue-based-sampling (VBS) to sample members of the community in Essex County. Participants completed a short electronic survey and provided finger stick blood samples for testing. We sampled 924 residents of Essex County, New Jersey. Testing conducted in this study identified 83 (9.0%) participants as positive for SARS-CoV-2 antibodies. Importantly, our findings suggest that the true burden of SARS-Cov-2 and the pool of persons potentially spreading the virus are slightly more than six times than that suggested by PCR testing Notably, there were no significant differences in odds of testing positive for SARS CoV-2 antibodies in terms of race/ethnicity where we compared Black and Latinx participants to other race participants. Our study suggests that disparities in COVID-19 outcomes stem from potential upstream issues such as underlying conditions, access to testing, and access to care rather than disparities in exposure to the virus.

A seroprevalence study of Covid 19 antibody after 1st wave of the pandemic in South Andaman district, India

Background

The seroepidemiological studies are essential to analyze spread of Covid 19 infection in the remote islands of Andaman and Nicobar. Hence, the present study was conducted to estimate the seroprevalence of Covid 19 antibodies in the South Andaman district.

Methods

A cross-sectional study was performed in South Andaman District after 1st wave of the Covid 19 pandemic in the island. The participants of age 18 years and above were selected by multistage cluster sampling. The blood samples were tested for IgG Covid antibodies by Erba Lisa Elisa kit. The data was analyzed by descriptive analysis and Chi Square/Fisher Exact test.

Result

The seroprevalence of Covid 19 in the S. Andaman district was found to be 39.3%. The COVID 19 antibody positivity was significantly higher in urban population (44.09%) as compared to rural population (34.27%) and in females of 41–60 years age group (45.5%) as compared to females of other age groups. The antibody positivity was similar among the population of containment and buffer zone (p-value 0.684).

Conclusion

The seropositivity in the South Andaman district was higher due to the influx of tourists on the island. The rural people in South Andaman remained less affected by the pandemic as the rural areas were far flung and thinly populated. The antibody positivity was similar in residents of containment and buffer zone because there were more social contacts and movement of the people on the island due to their extensive family linkage.

Seroprevalence of SARS-CoV-2 antibodies among healthcare workers in a teaching hospital in Eastern India

Statement of the Problem:

Healthcare workers (HCW) are the most vulnerable group for contracting SARS-CoV-2. Assessment of seroprevalence of SARS-CoV-2 antibodies among HCW, thus can provide important data on pathogen exposure, infectivity, and adherence to personal protective equipment (PPE). The present study aimed at assessing SARS-CoV-2 seroprevalence among HCW and exploring associations with demographics, category of exposure to COVID-19 patients, preventive measures taken and relation with COVID-19 symptoms.

Method of Study:

HCWs with a minimum gap 2 weeks from last duty were eligible to participate in the study. The enrolled HCW were categorized into high-risk and low-risk category based on work in COVID-19 areas. HCWs SARS-CoV-2 specific IgG and IgM antibodies were detected using rapid immunochromatography test.

Results:

Out of 821 randomly selected HCWs, either IgM or IgG antibody was detected in 32 HCWs (32/821, 3.9%). Only IgM antibodies were detected in 14 (1.7%), only IgG was detected in 9 (1.0%), and both IgM and IgG antibodies were present in 9 HCWs. Seropositivity was significantly higher in high-risk category (5.7% vs. 2.2.%), HCWs who ever had COVID-19 related symptoms in last 3 months (5.6% vs. 2.8%), and those who had earlier tested positive for SARS-CoV-2 with real-time reverse transcriptase PCR (36.6% vs. 3.5%). Seroprevalence was highest (6.9%) among housekeeping and sanitation staff.

Conclusions:

Overall, low seroprevalence of SARS-CoV-2 antibodies in our HCWs is an indicator of effective infection control practice. HCW posted in dedicated COVID ward need more stringent implementation of infection prevention measures.

A model for the spread of infectious diseases compatible with case data

For epidemics such as COVID-19, with a significant population having asymptomatic, untested infection, model predictions are often not compatible with data reported only for the cases confirmed by laboratory tests. Additionally, most compartmental models have instantaneous recovery from infection, contrary to observation. Tuning such models with observed data to obtain the unknown infection rate is an ill-posed problem. Here, we derive from the first principle an epidemiological model with delay between the newly infected (N) and recovered (R) populations. To overcome the challenge of incompatibility between model and case data, we solve for the ratios of the observed quantities and show that log(N(t)/R(t)) should follow a straight line. This simple prediction tool is accurate in hindcasts verified using data for China and Italy. In traditional epidemiology, an epidemic wanes when much of the population is infected so that 'herd immunity' is achieved. For a highly contagious and deadly disease, herd immunity is not a feasible goal without human intervention or vaccines. Even before the availability of vaccines, the epidemic was suppressed with social measures in China and South Korea with much less than 5% of the population infected. Effects of social behaviour should be and are incorporated in our model.

Cohort profile: a national, community-based prospective cohort study of SARS-CoV-2 pandemic outcomes in the USA-the CHASING COVID Cohort study

PURPOSE

The Communities, Households and SARS-CoV-2 Epidemiology (CHASING) COVID Cohort Study is a community-based prospective cohort study launched during the upswing of the USA COVID-19 epidemic. The objectives of the cohort study are to: (1) estimate and evaluate determinants of the incidence of SARS-CoV-2 infection, disease and deaths; (2) assess the impact of the pandemic on psychosocial and economic outcomes and (3) assess the uptake of pandemic mitigation strategies.

PARTICIPANTS

We began enrolling participants from 28 March 2020 using internet-based strategies. Adults≥18 years residing anywhere in the USA or US territories were eligible. 6740 people are enrolled in the cohort, including participants from all 50 US states, the District of Columbia, Puerto Rico and Guam. Participants are contacted regularly to complete study assessments, including interviews and dried blood spot specimen collection for serologic testing.

FINDINGS TO DATE

Participants are geographically and sociodemographically diverse and include essential workers (19%). 84.2% remain engaged in cohort follow-up activities after enrolment. Data have been used to assess SARS-CoV-2 cumulative incidence, seroincidence and related risk factors at different phases of the US pandemic; the role of household crowding and the presence of children in the household as potential risk factors for severe COVID-19 early in the US pandemic; to describe the prevalence of anxiety symptoms and its relationship to COVID-19 outcomes and other potential stressors; to identify preferences for SARS-CoV-2 diagnostic testing when community transmission is on the rise via a discrete choice experiment and to assess vaccine hesitancy over time and its relationship to vaccine uptake.

FUTURE PLANS

The CHASING COVID Cohort Study has outlined a research agenda that involves ongoing monitoring of the incidence and determinants of SARS-CoV-2 outcomes, mental health outcomes and economic outcomes. Additional priorities include assessing the incidence, prevalence and correlates of long-haul COVID-19.

Assessing the consequences of quarantines during a pandemic

This paper analyzes the epidemiological and economic effects of quarantines. We use a basic epidemiological model, a SEIR-model, that is calibrated to roughly resemble the COVID-19 pandemic, and we assume that individuals that become infected or are isolated on average lose a share of their productivity. An early quarantine postpones but does not alter the course of the pandemic at a cost that increases in the duration and the extent of the quarantine. For quarantines at later stages of the pandemic there is a trade-off between lowering the peak level of infectious people on the one hand and minimizing fatalities and economic losses on the other hand. A longer quarantine dampens the peak level of infectious people and also reduces the total number of infected persons but increases economic losses. Both the peak level of infectious individuals and the total share of the population that will have been infected are U-shaped in relation to the share of the population in quarantine, while economic costs increase in this share. In particular, a quarantine covering a moderate share of the population leads to a lower peak, fewer deaths and lower economic costs, but it implies that the peak of the pandemic occurs earlier.

Low Seroprevalence of SARS-CoV-2 in Rhode Island blood donors during may 2020 as determined using multiple serological assay formats

BACKGROUND

Epidemic projections and public health policies addressing Coronavirus disease (COVID)-19 have been implemented without data reporting on the seroconversion of the population since scalable antibody testing has only recently become available.

METHODS

We measured the percentage of severe acute respiratory syndrome- Coronavirus-2 (SARS-CoV-2) seropositive individuals from 2008 blood donors drawn in the state of Rhode Island (RI). We utilized multiple antibody testing platforms, including lateral flow immunoassays (LFAs), enzyme-linked immunosorbent assays (ELISAs) and high throughput serological assays (HTSAs). To estimate seroprevalence, we utilized the Bayesian statistical method to adjust for sensitivity and specificity of the commercial tests used.

RESULTS

We report than an estimated seropositive rate of RI blood donors of approximately 0.6% existed in April-May of 2020. Daily new case rates peaked in RI in late April 2020. We found HTSAs and LFAs were positively correlated with ELISA assays to detect antibodies specific to SARS-CoV-2 in blood donors.

CONCLUSIONS

These data imply that seroconversion, and thus infection, is likely not widespread within this population. We conclude that IgG LFAs and HTSAs are suitable to conduct seroprevalence assays in random populations. More studies will be needed using validated serological tests to improve the precision and report the kinetic progression of seroprevalence estimates.

Low Seroprevalence of SARS-CoV-2 in Rhode Island blood donors during may 2020 as determined using multiple serological assay formats

BACKGROUND

Epidemic projections and public health policies addressing Coronavirus disease (COVID)-19 have been implemented without data reporting on the seroconversion of the population since scalable antibody testing has only recently become available.

METHODS

We measured the percentage of severe acute respiratory syndrome- Coronavirus-2 (SARS-CoV-2) seropositive individuals from 2008 blood donors drawn in the state of Rhode Island (RI). We utilized multiple antibody testing platforms, including lateral flow immunoassays (LFAs), enzyme-linked immunosorbent assays (ELISAs) and high throughput serological assays (HTSAs). To estimate seroprevalence, we utilized the Bayesian statistical method to adjust for sensitivity and specificity of the commercial tests used.

RESULTS

We report than an estimated seropositive rate of RI blood donors of approximately 0.6% existed in April-May of 2020. Daily new case rates peaked in RI in late April 2020. We found HTSAs and LFAs were positively correlated with ELISA assays to detect antibodies specific to SARS-CoV-2 in blood donors.

CONCLUSIONS

These data imply that seroconversion, and thus infection, is likely not widespread within this population. We conclude that IgG LFAs and HTSAs are suitable to conduct seroprevalence assays in random populations. More studies will be needed using validated serological tests to improve the precision and report the kinetic progression of seroprevalence estimates.

COVID-19: clinical presentation and detection methods

The unending outburst of COVID-19 has reinforced the necessity of SARS-CoV-2 identification approaches for the prevention of infection transmission and the proper care of severe and critical patients. As there is no cure, a prompt and reliable diagnosis of SARS-CoV2 is vital to counter the spread and to provide adequate care and treatment for the infection. Currently, RT-PCR is a gold standard detection method for the qualitative and quantitative detection of viral nucleic acids. Besides, enzyme-linked immunosorbent assay is also a primarily used method for qualitative estimation of viral load. However, almost all the detection methods have their pros and cons in terms of specificity, accuracy, sensitivity, cost, time consumption, the need for sophisticated laboratories, and the requirement of skilled technical experts to carry out the detection tests. Thus, it is suggested to integrate different techniques to enhance the detection efficiency and accurateness for SARS-CoV2. This review focuses on preliminary, pre-confirmatory, and confirmatory methods of detection such as imaging techniques (chest-X-ray and chest- computed tomography), nucleic acid detection methods, serological assay methods, and viral culture and identification methods that are currently being employed to detect the presence of SARS-CoV-2 infection along with recent detection method and applicability for COVID-19.

Risk of infection and transmission of SARS-CoV-2 among children and adolescents in households, communities and educational settings: A systematic review and meta-analysis

BACKGROUND

There is uncertainty with respect to SARS-CoV-2 transmission in children (0-19 years) with controversy on effectiveness of school-closures in controlling the pandemic. It is of equal importance to evaluate the risk of transmission in children who are often asymptomatic or mildly symptomatic carriers that may incidentally transmit SARS-CoV-2 in different settings. We conducted this review to assess transmission and risks for SARS-CoV-2 in children (by age-groups or grades) in community and educational-settings compared to adults.

METHODS

Data for the review were retrieved from PubMed, EMBASE, Cochrane Library, WHO COVID-19 Database, China National Knowledge Infrastructure (CNKI) Database, WanFang Database, Latin American and Caribbean Health Sciences Literature (LILACS), Google Scholar, and preprints from medRixv and bioRixv) covering a timeline from December 1, 2019 to April 1, 2021. Population-screening, contact-tracing and cohort studies reporting prevalence and transmission of SARS-CoV-2 in children were included. Data were extracted according to PRISMA guidelines. Meta-analyses were performed using Review Manager 5.3.

RESULTS

Ninety studies were included. Compared to adults, children showed comparable national (risk ratio (RR) = 0.87, 95% confidence interval (CI) = 0.71-1.060 and subnational (RR = 0.81, 95% CI = 0.66-1.01) prevalence in population-screening studies, and lower odds of infection in community/household contact-tracing studies (odds ratio (OR) = 0.62, 95% CI = 0.46-0.84). On disaggregation, adolescents observed comparable risk (OR = 1.22, 95% CI = 0.74-2.04) with adults. In educational-settings, children attending daycare/preschools (OR = 0.53, 95% CI = 0.38-0.72) were observed to be at lower-risk when compared to adults, with odds of infection among primary (OR = 0.85, 95% CI = 0.55-1.31) and high-schoolers (OR = 1.30, 95% CI = 0.71-2.38) comparable to adults. Overall, children and adolescents had lower odds of infection in educational-settings compared to community and household clusters.

CONCLUSIONS

Children (<10 years) showed lower susceptibility to COVID-19 compared to adults, whereas adolescents in communities and high-schoolers had comparable risk. Risks of infection among children in educational-settings was lower than in communities. Evidence from school-based studies demonstrate it is largely safe for children (<10 years) to be at schools, however older children (10-19 years) might facilitate transmission. Despite this evidence, studies focusing on the effectiveness of mitigation measures in educational settings are urgently needed to support both public health and educational policy-making for school reopening.

Seroprevalence of SARS-CoV-2 antibody among individuals aged above 15 years and residing in congregate settings in Dire Dawa city administration, Ethiopia

BACKGROUND

Determining the extent of seropositivity of SARS-CoV-2 antibody has the potential to guide prevention and control efforts. We aimed to determine the seroprevalence of SARS-CoV-2 antibody among individuals aged above15 years and residing in the congregate settings of Dire Dawa city administration, Ethiopia.

METHOD

We analyzed COVID-19 seroprevalence data on 684 individuals from a community based cross-sectional survey conducted among individuals aged above 15 years and residing in congregate settings in Dire Dawa from June 15 to July 30, 2020. Data were collected using interview and blood sample collection. Participants were asked about demographic characteristics, COVID-19 symptoms, and their practice of preventive measures. Seroprevalence was determined using SARS-CoV-2 IgG test. Bivariate and multivariate multilevel mixed effects logistic regression model was fitted and statistical significance was set at p value < 0.05.

RESULT

The estimated SARS-CoV-2 seroprevalence was 3.2% (95 % CI 2.0-4.8) in the study region with no differences by age and sex but considerable differences were observed by self-reported practice of COVID-19 preventive measures. The cluster effect is not significant (P = 0.396) which has suggested no evidence of heterogeneity in SARS-CoV-2 seroprevalence among the clusters. The odds of SARS-CoV-2 antibody seroprevalence were higher for individuals who were employed and work by moving from home to work area (AOR; 9.73 95% CI 2.51, 37.68), reported of not wearing facemasks when leaving home (AOR; 6.4 95% CI 2.30, 17.66) and did not practice physical distancing measures (AOR; 10 95% CI 3.01, 33.20) compared to their counterparts, respectively. Our estimated seroprevalence of SARS-CoV-2 among participants who reported not to have practiced social distancing measures was 12.8 (95% CI, 7.0, 19) and 1.5 (95% CI, 0.5, 2.5) among those who reported of practicing them. More than 80% of study participants reported of implementing infection prevention measures (face masks and physical distancing recommendations).

CONCLUSION

The detected SARS-CoV-2 seroprevalence among the study participants was low at the time of the survey indicating higher proportion of population yet to be infected. COVID-19 preventive measures were associated with reduced seroprevalence and should be promoted to avoid transmission to the uninfected majority.

Nationwide seroprevalence of antibodies against SARS-CoV-2 in Israel

The first local spread of COVID-19 in Israel was detected in March 2020. Due to the diversity in clinical presentations of COVID-19, diagnosis by RT-PCR alone might miss patients with mild or no symptoms. Serology testing may better evaluate the actual magnitude of the spread of infection in the population. This is the first nationwide seroprevalence study conducted in Israel. It is one of the most widespread to be conducted thus far, and the largest per-country population size. The survey was conducted between June 28 and September 14, 2020 and included 54,357 patients who arrived at the Health Maintenance Organizations to undergo a blood test for any reason. A patient was considered seropositive after two consecutive positive results with two different kits (Abbott and DiaSorin).The overall seroprevalence was 3.8% (95%CI 3.7-4.0), males higher than females [4.9% (95%CI 4.6-5.2) vs. 3.1% (95%CI 2.9-3.3) respectively]. Adolescents had the highest prevalence [7.8% (95%CI 7.0-8.6)] compared to other age groups. Participants who had undergone RT-PCR testing had a tenfold higher risk to be seropositive. The prevalence-to-incidence ratio was 4.5-15.7. Serology testing is an important complimentary tool for assessing the actual magnitude of infection and thus essential for implementing policy measures to control the pandemic. A positive serology test result was recently accepted in Israel as being sufficient to define recovery, with possible far-reaching consequences, such as the deploying of employees to ensure the maintenance of a functional economy.

Overcoming the discourse of science mistrust: how science education can be used to develop competent consumers and communicators of science information

Science educators can provide learning experiences that challenge notions of mistrust in science, and provide students with the science skills necessary to obtain, evaluate, and communicate credible scientific information. As the COVID-19 pandemic persists, the American public continues to be inundated with messages reinforcing the importance of social distancing, hand-washing and the effectiveness of masks to slow the spread of the coronavirus. While most citizens diligently responded to these recommendations with compliance, there remained subcultures of the American public determined to resist these recommendations and engage in a discourse rooted in a mistrust of science. This discourse of science mistrust was perpetuated through the use of social media, as well as the modeling behaviors of government leaders, particularly as social media posts and news coverage were primary methods of social interaction during mandated stay-at-home orders. The discourse of science mistrust perpetuated during the COVID-19 pandemic reveals that a concerted effort is required by all science educators to aid with overcoming this discourse. Overcoming science mistrust begins in the science classroom by implementing pedagogical opportunities for science students to obtain, evaluate, and communicate scientific information. Allowing students to obtain and evaluate information are a critical skill to develop in the science classroom as science educators aim to produce competent consumers of scientific information. Furthermore, science students ought to also have experience with the skills associated with communicating scientific information. Communicating scientific information is a critical skill for science students to develop as it is through the effective communication of credible scientific information that the discourse of science mistrust can be overcome. Providing these learning opportunities to science students empower students to effectively evaluate social media and news coverage associated with the COVID-19 pandemic, and promote a future, wherein citizens are able to read, interpret, and critically consume scientific information to overcome discourses of science mistrust.

Serological surveys to inform SARS-CoV-2 epidemic curve: a cross-sectional study from Odisha, India

This was a population based cross-sectional study carried out to estimate and compare the seroprevalence, hidden prevalence and determine the demographic risk factors associated with SARS-CoV-2 infection among adults in the three largest cities of Odisha, India, and ascertain the association with the progression of the epidemic. The survey carried out in August 2020 in the three largest cities of the state of Odisha, India. Blood samples were collected from the residents using random sampling methods and tested for anti- SARS CoV-2 antibodies using an automated CLIA platform. A total of 4146 participants from the 3 cities of Bhubaneswar (BBS), Berhampur (BAM) and Rourkela (RKL) participated. The female to male participation ratio was 5.9:10 across the three cities. The gender weighted seroprevalence across the three cities was 20.78% (95% CI 19.56–22.05%). While females reported a higher seroprevalence (22.8%) as compared to males (18.8%), there was no significant difference in seroprevalence across age groups. A majority of the seropositive participants were asymptomatic (90.49%). The case to infection ratio on the date of serosurvey was 1:6.6 in BBS, 1:61 in BAM and 1:29.8 in RKL. The study found a high seroprevalence against COVID-19 in urban Odisha as well as high numbers of asymptomatic infections. The epidemic curves had a correlation with the seroprevalence.

Repeated Leftover Serosurvey of SARS-CoV-2 IgG Antibodies in Greece, May to August 2020

A serosurvey of IgG antibodies against SARS-CoV-2 was conducted in Greece between May and August 2020. It was designed as a cross-sectional survey and was repeated at monthly intervals. The leftover sampling methodology was used and a geographically stratified sampling plan was applied. Of 20,110 serum samples collected, 89 (0.44%) were found to be positive for anti-SARS-CoV-2 antibodies, with higher seroprevalence (0.35%) observed in May 2020. The highest seroprevalence was primarily observed in the "30-49" year age group. Females presented higher seroprevalence compared to males in May 2020 (females: 0.58% VS males: 0.10%). This difference reversed during the study period and males presented a higher proportion in August 2020 (females: 0.12% VS males: 0.58%). Differences in the rate of seropositivity between urban areas and the rest of the country were also observed during the study period. The four-month infection fatality rate (IFR) was estimated to be 0.47%, while the respective case fatality rate (CFR) was at 1.89%. Our findings confirm low seroprevalence of COVID-19 in Greece during the study period. The young adults are presented as the most affected age group. The loss of the cumulative effect of seropositivity in a proportion of previous SARS-CoV-2 infections was indicated.

Incorporating false negative tests in epidemiological models for SARS-CoV-2 transmission and reconciling with seroprevalence estimates

Susceptible-Exposed-Infected-Removed (SEIR)-type epidemiologic models, modeling unascertained infections latently, can predict unreported cases and deaths assuming perfect testing. We apply a method we developed to account for the high false negative rates of diagnostic RT-PCR tests for detecting an active SARS-CoV-2 infection in a classic SEIR model. The number of unascertained cases and false negatives being unobservable in a real study, population-based serosurveys can help validate model projections. Applying our method to training data from Delhi, India, during March 15-June 30, 2020, we estimate the underreporting factor for cases at 34-53 (deaths: 8-13) on July 10, 2020, largely consistent with the findings of the first round of serosurveys for Delhi (done during June 27-July 10, 2020) with an estimated 22.86% IgG antibody prevalence, yielding estimated underreporting factors of 30-42 for cases. Together, these imply approximately 96-98% cases in Delhi remained unreported (July 10, 2020). Updated calculations using training data during March 15-December 31, 2020 yield estimated underreporting factor for cases at 13-22 (deaths: 3-7) on January 23, 2021, which are again consistent with the latest (fifth) round of serosurveys for Delhi (done during January 15-23, 2021) with an estimated 56.13% IgG antibody prevalence, yielding an estimated range for the underreporting factor for cases at 17-21. Together, these updated estimates imply approximately 92-96% cases in Delhi remained unreported (January 23, 2021). Such model-based estimates, updated with latest data, provide a viable alternative to repeated resource-intensive serosurveys for tracking unreported cases and deaths and gauging the true extent of the pandemic.

On Ambiguity Reduction and the Role of Decision Analysis during the Pandemic

The COVID-19 pandemic has created a multitude of decision problems for a variety of fields. Questions from the seriousness and breadth of the problem to the effectiveness of proposed mitigation measures have been raised. We assert that the decision sciences have a crucial role to play here, as the questions requiring answers involve complex decision making under both uncertainty and ambiguity. The collection, processing, and analysis of data is critical in providing a useful response-especially as information of fundamental importance to such decision making (base rates and transmission rates) is lacking. We propose that scarce testing resources should be diverted away from confirmatory analysis of symptomatic people, as laboratory diagnosis appears to have little decision value in treatment choice over clinical diagnosis in patients presenting with symptoms. In contrast, the exploratory use of testing resources to reduce ambiguity in estimates of the base rate of infection appears to have significant value and great practical import for public policy purposes. As these stances may be at odds with triage practices among medical practitioners, they highlight the important role the decision analyst can play in responding to the challenges of the COVID-19 pandemic.

Understanding the Challenges and Uncertainties of Seroprevalence Studies for SARS-CoV-2

SARS-CoV-2 continues to widely circulate in populations globally. Underdetection is acknowledged and is problematic when attempting to capture the true prevalence. Seroprevalence studies, where blood samples from a population sample are tested for SARS-CoV-2 antibodies that react to the SARS-CoV-2 virus, are a common method for estimating the proportion of people previously infected with the virus in a given population. However, obtaining reliable estimates from seroprevalence studies is challenging for a number of reasons, and the uncertainty in the results is often overlooked by scientists, policy makers, and the media. This paper reviews the methodological issues that arise in designing these studies, and the main sources of uncertainty that affect the results. We discuss the choice of study population, recruitment of subjects, uncertainty surrounding the accuracy of antibody tests, and the relationship between antibodies and infection over time. Understanding these issues can help the reader to interpret and critically evaluate the results of seroprevalence studies.

Nationwide seroprevalence of antibodies to SARS-CoV-2 in asymptomatic population in South Korea: a cross-sectional study

OBJECTIVE

Asymptomatic active infection might be an important contributor to the COVID-19 outbreak. Serological tests can assess the extent of exposure and herd immunity to COVID-19 in general populations. This study aimed to estimate the nationwide seroprevalence of SARS-CoV-2 antibodies according to age, sex and clinical status in South Korea.

DESIGN, SETTING AND PARTICIPANTS

This cross-sectional study randomly selected health examinees who underwent health check-up at 16 health promotion centres in 13 Korean cities across the country between late September and early December 2020. Residual serum samples were obtained from 4085 subjects (2014 men and 2071 women). Antibodies to SARS-CoV-2 were measured by electrochemiluminescence immunoassay using Elecsys Anti-SARS-CoV-2 (Roche Elecsys, Mannheim, Germany).

PRIMARY AND SECONDARY OUTCOME MEASURES

Fisher's exact test was used to compare the seroprevalence according to sex, age group and region. The relative risks of being seropositive according to the characteristics of the study subjects were analysed using logistic regression analysis.

RESULTS

The overall seroprevalence of anti-SARS-CoV-2 was 0.39% (95% CI=0.20% to 0.58%): 0.30% (95% CI=0.06% to 0.54%) for men and 0.48% (95% CI=0.18% to 0.78%) for women. The rate of anti-SARS-CoV-2 positivity varied significantly between different regions of Korea (p=0.003), but not with age group, sex, or the statuses of obesity, diabetes, hypertension or smoking.

CONCLUSIONS

Most of the Korean population is still immunologically vulnerable to SARS-CoV-2, but the seroprevalence has increased relative to that found in studies performed prior to September 2020 in Korea.

The experience of the health care workers of a severely hit SARS-CoV-2 referral Hospital in Italy: incidence, clinical course and modifiable risk factors for COVID-19 infection

BACKGROUND

During the COVID-19 pandemic, the health care workers (HCWs) at the frontline have been largely exposed to infected patients, running a high risk of being infected by the SARS-CoV-2 virus.Since limiting transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in health care setting is crucial to avoid the community spread of SARS-CoV-2, we want to share our experience as an early hit hospital where standard infection control practices have been conscientiously applied and effective. We believe that our example, as first and hardest hit country, might be a warning and aid not only for those who have been hit later, but also for a second fearful wave of contagion. In addition, we want to offer an insight on modifiable risk factors for HWs-related infection.

METHODS

Demographic, lifestyle, work-related and comorbidities data of 1447 HCWs, which underwent a nasopharyngeal swab for SARS-CoV-2, were retrospectively collected. For the 164 HCWs positive for SARS-CoV-2, data about safety in the workplace, symptoms and clinical course of COVID-19 were also collected. Cumulative incidence of SARS-CoV-2 infection was estimated. Risk factors for SARS-CoV-2 infection were assessed using a multivariable Poisson regression.

RESULTS

The cumulative incidence of SARS-CoV-2 infection among the screened HCWs was 11.33% (9.72-13.21). Working in a COVID-19 ward, being a former smoker (versus being a person who never smoked) and BMI was positively associated with SARS-CoV-2 infection, whereas being a current smoker was negatively associated with this variable.

CONCLUSIONS

Assuming an equal accessibility and proper use of personal protective equipment of all the HCWs of our Hospital, the great and more prolonged contact with COVID-19 patients remains the crucial risk factor for SARS-CoV-2. Therefore, increased and particular care needs to be focused specifically on the most exposed HCWs groups, which should be safeguarded. Furthermore, in order to limit the risk of asymptomatic spread of SARS-CoV-2 infection, the HCWs mild symptoms of COVID-19 should be considered when evaluating the potential benefits of universal staff testing.

Intra-Household and Close-Contact SARS-CoV-2 Transmission Among Children - a Systematic Review

Introduction: The outbreak of the novel coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to a range of emergency measures worldwide. Early in the pandemic, children were suspected to act as drivers of the COVID-19 spread in the population, which was based on experiences with influenza virus and other respiratory pathogens. Consequently, closures of schools and kindergartens were implemented in many countries around the world, alongside with other non-pharmaceutical interventions for transmission control. Given the grave and multifaceted consequences of contact restriction measures for children, it is crucial to better understand the effect size of these incisive actions for the COVID-19 pandemic. Therefore, we systematically review the current evidence on transmission of SARS-CoV-2 to and by children. Data Sources: PubMed and preprints uploaded on medRxiv. Study Selection: Original research articles, case reports, brief communications, and commentaries were included into the analysis. Each title or abstract was independently reviewed to identify relevant articles. Studies in other languages than English were not included. Data Extraction: Two reviewers independently reviewed the selected studies. Extracted data included citation of each study, type of healthcare setting, location of the study, characteristics of patient population, and reported outcomes. Results: Data on transmission of SARS-CoV-2 on or by children is scarce. Several studies show a lower seropositivity of children compared to adults, suggesting a lower susceptibility of especially younger children. Most insight currently comes from household studies suggesting, that children are predominantly infected by their household contacts. The contagiousness however, seems to be comparable between children and adults, based on our meta-analysis of included studies. Conclusions: Larger and systematic studies are urgently needed to better understand the age dependent patterns of SARS-CoV-2 transmission and thereby design more effective non-pharmaceutical interventions to reduce disease transmission.

Initial determination of COVID-19 seroprevalence among outpatients and healthcare workers in Minnesota using a novel SARS-CoV-2 total antibody ELISA

OBJECTIVES

To avoid the significant risks posed by the use of COVID-19 serology tests with supply chain constraints or poor performance characteristics, we developed an in-house SARS-CoV-2 total antibody test. Our test was compared with three commercial methods, and was used to determine COVID-19 seroprevalence among healthcare workers and outpatients in Minnesota.

METHODS

Seventy-nine plasma and serum samples from 50 patients 4-69 days after symptom onset who tested positive by a SARS-CoV-2 PCR method using a nasopharyngeal (NP) swab were used to evaluate our test's clinical performance. Seropositive samples were analyzed for IgG titers in a follow-up assay. Thirty plasma and serum from 12 patients who tested negative by a SARS-CoV-2 PCR method using a nasopharyngeal (NP) swab and 210 negative pre-pandemic serum samples were also analyzed. Among samples from patients > 14 days after symptom onset, the assay had 100% clinical sensitivity and 100% clinical specificity, 100% positive predictive value and 100% negative predictive value. Analytical specificity was 99.8%, indicating minimal cross-reactivity. A screening study was conducted to ascertain COVID-19 seroprevalence among healthcare workers and outpatients in Minnesota.

RESULTS

Analysis of serum collected between April 13 and May 21, 2020 indicated a COVID-19 seroprevalence of 2.96% among 1,282 healthcare workers and 4.46% among 2,379 outpatients.

CONCLUSIONS

Our in-house SARS-CoV-2 total antibody test can be used to conduct reliable epidemiological studies to inform public health decisions during the COVID-19 pandemic.

A literature review of 2019 novel coronavirus (SARS-CoV2) infection in neonates and children

At the time of writing, there are already millions of documented infections worldwide by the novel coronavirus 2019 (2019-nCoV or severe acute respiratory syndrome coronavirus 2 (SARS-CoV2)), with hundreds of thousands of deaths. The great majority of fatal events have been recorded in adults older than 70 years; of them, a large proportion had comorbidities. Since data regarding the epidemiologic and clinical characteristics in neonates and children developing coronavirus disease 2019 (COVID-19) are scarce and originate mainly from one country (China), we reviewed all the current literature from 1 December 2019 to 7 May 2020 to provide useful information about SARS-CoV2 viral biology, epidemiology, diagnosis, clinical features, treatment, prevention, and hospital organization for clinicians dealing with this selected population. IMPACT: Children usually develop a mild form of COVID-19, rarely requiring high-intensity medical treatment in pediatric intensive care unit. Vertical transmission is unlikely, but not completely excluded. Children with confirmed or suspected COVID-19 must be isolated and healthcare workers should wear appropriate protective equipment. Some clinical features (higher incidence of fever, vomiting and diarrhea, and a longer incubation period) are more common in children than in adults, as well as some radiologic aspects (more patchy shadow opacities on CT scan images than ground-glass opacities). Supportive and symptomatic treatments (oxygen therapy and antibiotics for preventing/treating bacterial coinfections) are recommended in these patients.

SARS-CoV-2 Viral and Serological Testing When College Campuses Reopen: Some Practical Considerations

The coronavirus disease 2019 (COVID-19) pandemic prompted universities across the United States to close campuses in Spring 2020. Universities are deliberating whether, when, and how they should resume in-person instruction in Fall 2020. In this essay, we discuss some practical considerations for the use of 2 potentially useful control strategies based on testing: (1) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse transcriptase-polymerase chain reaction (RT-PCR) testing followed by case-patient isolation and quarantine of close contacts, and (2) serological testing followed by an "immune shield" approach, that is, low social distancing requirements for seropositive persons. The isolation of case-patients and quarantine of close contacts may be especially challenging, and perhaps prohibitively difficult, on many university campuses. The "immune shield" strategy might be hobbled by a low positive predictive value of the tests used in populations with low seroprevalence. Both strategies carry logistical, ethical, and financial implications. The main nonpharmaceutical interventions will remain methods based on social distancing (eg, capping class size) and personal protective behaviors (eg, universal facemask wearing in public space) until vaccines become available, or unless the issues discussed herein can be resolved in such a way that using mass testing as main control strategies becomes viable.

Exploring COVID-19 Daily Records of Diagnosed Cases and Fatalities Based on Simple Nonparametric Methods

Containment strategies to combat epidemics such as SARS-CoV-2/COVID-19 require the availability of epidemiological parameters, e.g., the effective reproduction number. Parametric models such as the commonly used susceptible-infected-removed (SIR) compartment models fitted to observed incidence time series have limitations due to the time-dependency of the parameters. Furthermore, fatalities are delayed with respect to the counts of new cases, and the reproduction cycle leads to periodic patterns in incidence time series. Therefore, based on comprehensible nonparametric methods including time-delay correlation analyses, estimates of crucial parameters that characterise the COVID-19 pandemic with a focus on the German epidemic are presented using publicly available time-series data on prevalence and fatalities. The estimates for Germany are compared with the results for seven other countries (France, Italy, the United States of America, the United Kingdom, Spain, Switzerland, and Brazil). The duration from diagnosis to death resulting from delay-time correlations turns out to be 13 days with high accuracy for Germany and Switzerland. For the other countries, the time-to-death durations have wider confidence intervals. With respect to the German data, the two time series of new cases and fatalities exhibit a strong coherence. Based on the time lag between diagnoses and deaths, properly delayed asymptotic as well as instantaneous fatality-case ratios are calculated. The temporal median of the instantaneous fatality-case ratio with time lag of 13 days between cases and deaths for Germany turns out to be 0.02. Time courses of asymptotic fatality-case ratios are presented for other countries, which substantially differ during the first half of the pandemic but converge to a narrow range with standard deviation 0.0057 and mean 0.024. Similar results are obtained from comparing time courses of instantaneous fatality-case ratios with optimal delay for the 8 exemplarily chosen countries. The basic reproduction number, R0, for Germany is estimated to be between 2.4 and 3.4 depending on the generation time, which is estimated based on a delay autocorrelation analysis. Resonances at about 4 days and 7 days are observed, partially attributable to weekly periodicity of sampling. The instantaneous (time-dependent) reproduction number is estimated from the incident (counts of new) cases, thus allowing us to infer the temporal behaviour of the reproduction number during the epidemic course. The time course of the reproduction number turns out to be consistent with the time-dependent per capita growth.

Human mobility and poverty as key drivers of COVID-19 transmission and control

BACKGROUND

Applying heavy nationwide restrictions is a powerful method to curtail COVID-19 transmission but poses a significant humanitarian and economic crisis. Thus, it is essential to improve our understanding of COVID-19 transmission, and develop more focused and effective strategies. As human mobility drives transmission, data from cellphone devices can be utilized to achieve these goals.

METHODS

We analyzed aggregated and anonymized mobility data from the cell phone devices of> 3 million users between February 1, 2020, to May 16, 2020 - in which several movement restrictions were applied and lifted in Israel. We integrated these mobility patterns into age-, risk- and region-structured transmission model. Calibrated to coronavirus incidence in 250 regions covering Israel, we evaluated the efficacy and effectiveness in decreasing morbidity and mortality of applying localized and temporal lockdowns (stay-at-home order).

RESULTS

Poorer regions exhibited lower and slower compliance with the restrictions. Our transmission model further indicated that individuals from impoverished areas were associated with high transmission rates. Considering a horizon of 1-3 years, we found that to reduce COVID-19 mortality, school closure has an adverse effect, while interventions focusing on the elderly are the most efficient. We also found that applying localized and temporal lockdowns during regional outbreaks reduces the overall mortality and morbidity compared to nationwide lockdowns. These trends were consistent across vast ranges of epidemiological parameters, and potential seasonal forcing.

CONCLUSIONS

More resources should be devoted to helping impoverished regions. Utilizing cellphone data despite being anonymized and aggregated can help policymakers worldwide identify hotspots and apply designated strategies against future COVID-19 outbreaks.

Proteomics Analysis of Serum from COVID-19 Patients

Coronavirus disease 2019 (COVID-19) is a worldwide pandemic. To understand the changes in plasma proteomics upon SARS-CoV-2 infection, we analyzed the protein profiles of plasma samples from 10 COVID-19 patients and 10 healthy volunteers by using the DIA quantitative proteomics technology. We compared and identified differential proteins whose abundance changed upon SARS-CoV-2 infection. Bioinformatic analyses were then conducted for these identified differential proteins. The GO/KEEG database was used for functional annotation and enrichment analysis. The interaction relationship of differential proteins was evaluated with the STRING database, and Cytoscape software was used to conduct network analysis of the obtained data. A total of 323 proteins were detected in all samples. Difference between patients and healthy donors was found in 44 plasma proteins, among which 36 proteins were up-regulated and 8 proteins were down-regulated. GO functional annotation showed that these proteins mostly composed of cellular anatomical entities and proteins involved in biological regulation, cellular processes, transport, and other processes. KEEG functional annotation further showed that these proteins were mainly involved in complement system activation and infectious disease processes. Importantly, a KEEG pathway (natural killer cell-mediated cytotoxicity) was enriched, with three important activators of this pathway, ICAM1/2 and IgG, being up-regulated. Protein-protein interaction (PPI) statistics indicated that, among these 44 proteins, 6 were the most significantly up-regulated (DBH, SHGB, TF, ICAM2, THBS1, and C1RL) while 2 were the most significantly down-regulated (APCS and ORM1). Results from this study showed that a few proteins associated with immune activation were up-regulated in patient plasma. In addition, this study established a method for extraction and quantitative determination of plasma components in convalescent plasma from COVID-19 patients.

Designing and Interpreting Coronavirus Disease 2019 (COVID-19) Diagnostics: Mathematics, Visual Logistics, and Low Prevalence

CONTEXT.—

Coronavirus infectious disease-19 (COVID-19) diagnostics require understanding of how predictive values depend on sensitivity, specificity, and especially, low prevalence. Clear expectations, high sensitivity and specificity, and manufacturer disclosure will facilitate excellence of tests.

OBJECTIVES.—

To derive mathematical equations for designing and interpreting COVID-19 tests, assess US Food and Drug Administration (FDA) Emergency Use Authorization and Health Canada minimum requirements, establish sensitivity and specificity tiers, and enhance clinical performance in low prevalence settings.

DESIGN.—

PubMed and other sources generated articles on COVID-19 testing and prevalence. EndNote X9.1 consolidated references. Mathematica and open access software helped prove equations, perform recursive calculations, graph multivariate relationships, and visualize patterns, including a new relationship, predictive value geometric mean-squared.

RESULTS.—

Derived equations were used to illustrate shortcomings of COVID-19 diagnostics in low prevalence. Visual logistics helped establish sensitivity/specificity tiers. FDA/Canada's 90% sensitivity, 95% specificity minimum requirements generate excessive false positives at low prevalence. False positives exceed true positives at prevalence lower than 5.3%, or if sensitivity is improved to 100% and specificity to 98%, at prevalence lower than 2%. Recursive testing improves predictive value. Three tiers emerged from these results. With 100% sensitivity, physicians can select desired predictive values, then input local prevalence, to determine suitable specificity.

CONCLUSIONS.—

Understanding low prevalence impact will help health care providers meet COVID-19 needs for effective testing. Laypersons should receive clinical performance disclosure when submitting specimens. Home testing needs to meet the same high standards as other tests. In the long run, it will be more cost-effective to improve COVID-19 point-of-care tests rather than repeat testing multiple times.

Serosurveillance of Health Care Workers in a COVID Hospital: Immune Response, and Its Longevity

Objective: We aimed to study the seroprevalence of coronavirus disease 2019 (COVID-19) and sustainability of the immune response in health care workers (HCWs). A cross-sectional study was conducted between October 7 and November 30, 2020, in a multi-specialty hospital in Eastern India designated as COVID hospital during this pandemic. Study participants included 2,110 HCWs, including those who have recovered from COVID infection.

Method: HCWs were required to complete a questionnaire and give written consent to participate in the study. Their venous blood sample was collected for serum analysis of IgG antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by chemiluminescent immunoassay.

Results: Positive IgG antibodies were seen in 924 participants with a point prevalence of 43.79%. Slightly higher reactivity was seen in males. History of COVID-19 infection was noted in 10.9%, with the highest antibody response in 81% cases. A maximum of 87.9% reactivity was seen in the first two months, and a significant fall was noted in the fourth month, with reactivity seen in only 50% of the study participants.

Conclusion: SARS-CoV-2 infection is associated with a variable immune response in the infected population. The declining trend of the antibodies correlates with short-lived protective immunity and the possibility of re-infection. Further studies are needed to explore the probable reasons for varied seroprevalence.

Serological Evaluation of Human Antibodies of the Immunoglobulin Class A and G Against SARS-CoV-2 in Serum Collected in Newfoundland and Labrador

The ability to detect antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently under investigation with various performance characteristics and indications for use. In this article, we analyzed the ability of the Abbott SARS-CoV-2 immunoglobulin class G (IgG), EuroImmun SARS-CoV-2 enzyme-linked immunosorbent assay (ELISA) IgG, and EuroImmun SARS-CoV-2 ELISA immunoglobulin class A (IgA) kits to detect evidence of previous infection with SARS-CoV-2. We tested 49 known coronavirus disease-19 (COVID-19) patients and 111 prepandemic stored serology specimens. This resulted in a sensitivity of 95.9%, 100.0%, and 91.3% and a specificity of 98.2%, 98.2%, and 90.8% respectively, using manufacturer recommended cutoffs after inconclusive results (one for EuroImmun IgG and five for EuroImmun IgA) being excluded in the final statistical analyses. Cross-reactivity of hepatitis C virus seropositive specimens was observed resulting in false positives (p < 0.05). If a two-tiered algorithmic approach was applied, that is, testing with Abbott SARS-CoV-2 assay followed by EuroImmun SARS-CoV-2 IgG, 100% specificity and sensitivity could be obtained after six inconclusive results were excluded from data set before statistical analyses. Performance characteristics presented demonstrate the superior performance of IgG class antibodies for investigating previous infections. In addition, utilizing a second antibody test for supplementary testing may significantly enhance performance, particularly in lower prevalence settings.

Second waves, social distancing, and the spread of COVID-19 across the USA

We recently described a dynamic causal model of a COVID-19 outbreak within a single region. Here, we combine several instantiations of this (epidemic) model to create a (pandemic) model of viral spread among regions. Our focus is on a second wave of new cases that may result from loss of immunity-and the exchange of people between regions-and how mortality rates can be ameliorated under different strategic responses. In particular, we consider hard or soft social distancing strategies predicated on national (Federal) or regional (State) estimates of the prevalence of infection in the population. The modelling is demonstrated using timeseries of new cases and deaths from the United States to estimate the parameters of a factorial (compartmental) epidemiological model of each State and, crucially, coupling between States. Using Bayesian model reduction, we identify the effective connectivity between States that best explains the initial phases of the outbreak in the United States. Using the ensuing posterior parameter estimates, we then evaluate the likely outcomes of different policies in terms of mortality, working days lost due to lockdown and demands upon critical care. The provisional results of this modelling suggest that social distancing and loss of immunity are the two key factors that underwrite a return to endemic equilibrium.

Community Transmission of SARS-CoV-2 by Surfaces: Risks and Risk Reduction Strategies

SARS-CoV-2, the virus responsible for the COVID-19 pandemic, is perceived to be primarily transmitted via person-to-person contact through droplets produced while talking, coughing, and sneezing. Transmission may also occur through other routes, including contaminated surfaces; nevertheless, the role that surfaces have on the spread of the disease remains contested. Here, we use the Quantitative Microbial Risk Assessment framework to examine the risks of community transmission of SARS-CoV-2 through surfaces and to evaluate the effectiveness of hand and surface disinfection as potential interventions. Using conservative assumptions on input parameters of the model (e.g., dose-response relationship, ratio of genome copies to infective virus), the average of the median risks for single hand-to-surface contact followed by hand-to-face contact range from 1.6 × 10-4 to 5.6 × 10-9 for modeled prevalence rates of 0.2%-5%. For observed prevalence rates (0.2%, 1%), this corresponds to a low risk of infection (<10-6). Hand disinfection substantially reduces risks of transmission independently of the disease's prevalence and contact frequency. In contrast, the effectiveness of surface disinfection is highly dependent on the prevalence and the frequency of contacts. The work supports the current perception that contaminated surfaces are not a primary mode of transmission of SARS-CoV-2 and affirms the benefits of making hand disinfectants widely available.

Predictive values, uncertainty, and interpretation of serology tests for the novel coronavirus

Antibodies testing in the coronavirus era is frequently promoted, but the underlying statistics behind their validation has come under more scrutiny in recent weeks. We provide calculations, interpretations, and plots of positive and negative predictive values under a variety of scenarios. Prevalence, sensitivity, and specificity are estimated within ranges of values from researchers and antibodies manufacturers. Illustrative examples are highlighted, and interactive plots are provided in the Supplementary Information. Implications are discussed for society overall and across diverse locations with different levels of disease burden. Specifically, the proportion of positive serology tests that are false can differ drastically from up to 3%-88% for people from different places with different proportions of infected people in the populations while the false negative rate is typically under 10%.

A model of COVID-19 propagation based on a gamma subordinated negative binomial branching process

We build a parsimonious Crump-Mode-Jagers continuous time branching process of COVID-19 propagation based on a negative binomial process subordinated by a gamma subordinator. By focusing on the stochastic nature of the process in small populations, our model provides decision making insight into mitigation strategies as an outbreak begins. Our model accommodates contact tracing and isolation, allowing for comparisons between different types of intervention. We emphasize a physical interpretation of the disease propagation throughout which affords analytical results for comparison to simulations. Our model provides a basis for decision makers to understand the likely trade-offs and consequences between alternative outbreak mitigation strategies particularly in office environments and confined work-spaces. Combining the asymptotic limit of our model with Bayesian hierarchical techniques, we provide US county level inferences for the reproduction number from cumulative case count data over July and August of this year.

Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys

Establishing how many people have been infected by SARS-CoV-2 remains an urgent priority for controlling the COVID-19 pandemic. Serological tests that identify past infection can be used to estimate cumulative incidence, but the relative accuracy and robustness of various sampling strategies have been unclear. We developed a flexible framework that integrates uncertainty from test characteristics, sample size, and heterogeneity in seroprevalence across subpopulations to compare estimates from sampling schemes. Using the same framework and making the assumption that seropositivity indicates immune protection, we propagated estimates and uncertainty through dynamical models to assess uncertainty in the epidemiological parameters needed to evaluate public health interventions and found that sampling schemes informed by demographics and contact networks outperform uniform sampling. The framework can be adapted to optimize serosurvey design given test characteristics and capacity, population demography, sampling strategy, and modeling approach, and can be tailored to support decision-making around introducing or removing interventions.

SARS-COV-2 ANTIBODY PREVALENCE AMONG HEALTHCARE WORKERS AND FIRST RESPONDERS, FLORIDA, MAY-JUNE 2020

BACKGROUND

The SARS-CoV-2 virus responsible for severe respiratory infection associated with coronavirus disease 2019 (COVID-19) was first confirmed in Florida on March 1, 2020. Responding to the pandemic, multi-agency collaborative partnerships put in place actions integrating point-of-care antibody testing at established large-scale COVID-19 testing sites where the baseline seropositivity of COVID-19 in health care workers and first responders in Florida at the start of the pandemic was established.

PURPOSE

Determine the seropositivity of healthcare workers and first responders at five drive thru testing sites using a rapid SARS-CoV-2 antibody test in Florida from May 6 through June 3, 2020.

METHODS

The first drive-thru SARS-CoV-2 antibody test site was opened at Miami Hard Rock Stadium, May 6, 2020. Testing expanded to three additional sites on May 9, 2020: Jacksonville, Orlando, and Palm Beach. The fifth and final site, Miami Beach, began testing on May 21, 2020. Healthcare workers and first responder's self-seeking SARS-CoV-2 testing were designated for antibody testing and completed a laboratory collection form onsite for the point-of-care test. All testing was performed on whole blood specimens (obtained by venipuncture) using the Cellex Inc. qSARS-CoV-2 IgG/IgM Rapid Test. Seropositivity was assessed by univariate analysis and by logistic regression including the covariates age, sex, race/ethnicity, and testing location.

RESULTS AND DISCUSSION

As of June 3, 2020, of 5,779 healthcare workers and first responders tested, 4.1% were seropositive (range 2.6-8.2%). SARS-COV-2 antibody tests had higher odds of being positive for persons testing at the Miami Hard Rock Stadium (aOR 2.24 [95% C.I. 1.48-3.39]), persons of Haitian/Creole ethnicity (aOR 3.28 [95% C.I. 1.23-8.72]), Hispanic/Latino(a) ethnicity (aOR 2.17 [95% C.I. 1.50-3.13], and Black non-Hispanic persons (aOR 1.63 [95% C.I. 1.08-2.46]). SARS-COV-2 antibody prevalence among first responders and healthcare workers in five sites in Florida varied by race and ethnicity and by testing location.

Unraveling the flaws of estimates of the infection fatality rate for COVID-19

The infection fatality rate (IFR) of COVID-19 is of importance for policymaking. We show that there are significant flaws in many studies estimating the IFR and used as references by public health authorities.

Second waves, social distancing, and the spread of COVID-19 across the USA

We recently described a dynamic causal model of a COVID-19 outbreak within a single region. Here, we combine several instantiations of this (epidemic) model to create a (pandemic) model of viral spread among regions. Our focus is on a second wave of new cases that may result from loss of immunity-and the exchange of people between regions-and how mortality rates can be ameliorated under different strategic responses. In particular, we consider hard or soft social distancing strategies predicated on national (Federal) or regional (State) estimates of the prevalence of infection in the population. The modelling is demonstrated using timeseries of new cases and deaths from the United States to estimate the parameters of a factorial (compartmental) epidemiological model of each State and, crucially, coupling between States. Using Bayesian model reduction, we identify the effective connectivity between States that best explains the initial phases of the outbreak in the United States. Using the ensuing posterior parameter estimates, we then evaluate the likely outcomes of different policies in terms of mortality, working days lost due to lockdown and demands upon critical care. The provisional results of this modelling suggest that social distancing and loss of immunity are the two key factors that underwrite a return to endemic equilibrium.

Estimated seroprevalence of SARS-CoV-2 antibodies among adults in Orange County, California

Clinic-based estimates of SARS-CoV-2 may considerably underestimate the total number of infections. Access to testing in the US has been heterogeneous and symptoms vary widely in infected persons. Public health surveillance efforts and metrics are therefore hampered by underreporting. We set out to provide a minimally biased estimate of SARS-CoV-2 seroprevalence among adults for a large and diverse county (Orange County, CA, population 3.2 million). We implemented a surveillance study that minimizes response bias by recruiting adults to answer a survey without knowledge of later being offered SARS-CoV-2 test. Several methodologies were used to retrieve a population-representative sample. Participants (n = 2979) visited one of 11 drive-thru test sites from July 10th to August 16th, 2020 (or received an in-home visit) to provide a finger pin-prick sample. We applied a robust SARS-CoV-2 Antigen Microarray technology, which has superior measurement validity relative to FDA-approved tests. Participants include a broad age, gender, racial/ethnic, and income representation. Adjusted seroprevalence of SARS-CoV-2 infection was 11.5% (95% CI: 10.5-12.4%). Formal bias analyses produced similar results. Prevalence was elevated among Hispanics (vs. other non-Hispanic: prevalence ratio [PR] = 1.47, 95% CI 1.22-1.78) and household income < $50,000 (vs. > $100,000: PR = 1.42, 95% CI: 1.14 to 1.79). Results from a diverse population using a highly specific and sensitive microarray indicate a SARS-CoV-2 seroprevalence of ~ 12 percent. This population-based seroprevalence is seven-fold greater than that using official County statistics. In this region, SARS-CoV-2 also disproportionately affects Hispanic and low-income adults.

Seroprevalence of SARS-CoV-2 Antibodies in Children and Adults in St. Louis, Missouri, USA

Reported coronavirus disease 2019 (COVID-19) case counts likely underestimate the true prevalence because mild or asymptomatic cases often go untested. Here, we use a sero-survey to estimate the seroprevalence of IgG antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the St. Louis, MO, metropolitan area in a symptom-independent manner. Five hundred three adult and 555 pediatric serum/plasma samples were collected from patients presenting to Barnes-Jewish Hospital or St. Louis Children's Hospital between 14 April 2020 and 12 May 2020. We developed protocols for in-house enzyme-linked immunosorbent assays (ELISAs) using spike and nucleoprotein and used the assays to estimate a seroprevalence rate based on our samples. Overall IgG seropositivity was estimated to be 1.71% (95% credible interval [CI], 0.04% to 3.38%) in pediatric samples and 3.11% (95% CI, 0.92% to 5.32%) in adult samples. Seropositivity was significantly lower in children under 5 years of age than in adults, but rates between adults and children aged 5 or older were similar. Of the 176 samples tested from children under 4 years of age, none were positive.IMPORTANCE This study determined the percentages of both children and adult samples from the greater St. Louis metropolitan area who had antibodies to SARS-CoV-2 in late April to early May 2020. Approximately 1.7 to 3.1% of the tested individuals had antibodies, indicating that they had previously been infected by SARS-CoV-2. These results demonstrate that the extent of infection was about 10 times greater than the number of confirmed cases at that time. Furthermore, it demonstrated that by 5 years of age, children were infected to an extent similar to that of adults.

Bayesian estimation of SARS-CoV-2 prevalence in Indiana by random testing

From 25 to 29 April 2020, the state of Indiana undertook testing of 3,658 randomly chosen state residents for the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, the agent causing COVID-19 disease. This was the first statewide randomized study of COVID-19 testing in the United States. Both PCR and serological tests were administered to all study participants. This paper describes statistical methods used to address nonresponse among various demographic groups and to adjust for testing errors to reduce bias in the estimates of the overall disease prevalence in Indiana. These adjustments were implemented through Bayesian methods, which incorporated all available information on disease prevalence and test performance, along with external data obtained from census of the Indiana statewide population. Both adjustments appeared to have significant impact on the unadjusted estimates, mainly due to upweighting data in study participants of non-White races and Hispanic ethnicity and anticipated false-positive and false-negative test results among both the PCR and antibody tests utilized in the study.

Assessment of Seroprevalence of SARS-CoV-2 and Risk Factors Associated With COVID-19 Infection Among Outpatients in Virginia

Importance

Data from seroepidemiologic surveys measuring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure in diverse communities and ascertaining risk factors associated with infection are important to guide future prevention strategies.

Objective

To assess the prevalence of previous SARS-CoV-2 infection across Virginia and the risk factors associated with infection after the first wave of coronavirus disease 2019 (COVID-19) infections in the US.

Design, Setting, and Participants

In this statewide cross-sectional surveillance study, 4675 adult outpatients presenting for health care not associated with COVID-19 in Virginia between June 1 and August 14, 2020, were recruited to participate in a questionnaire and receive venipuncture to assess SARS-CoV-2 serology. Eligibility was stratified to meet age, race, and ethnicity quotas that matched regional demographic profiles.

Main Outcomes and Measures

The main outcome was SARS-CoV-2 seropositivity, as measured by the Abbott SARS-CoV-2 immunoglobulin G assay.

Results

Among 4675 adult outpatients (mean [SD] age, 48.8 [16.9] years; 3119 women [66.7%]; 3098 White [66.3%] and 4279 non-Hispanic [91.5%] individuals) presenting for non-COVID-19-associated health care across Virginia, the weighted seroprevalence was 2.4% (95% CI, 1.8%-3.1%) and ranged from 0% to 20% by zip code. Seroprevalence was notably higher among participants who were Hispanic (10.2%; 95% CI, 6.1%-14.3%), residing in the northern region (4.4%; 95% CI, 2.8%-6.1%), aged 40 to 49 years (4.4%; 95% CI, 1.8%-7.1%), and uninsured (5.9%; 95% CI, 1.5%-10.3%). Higher seroprevalence was associated with Hispanic ethnicity (adjusted odds ratio [aOR], 3.56; 95% CI, 1.76-7.21), residence in a multifamily unit (aOR, 2.55; 95% CI, 1.25-5.22), and contact with an individual with confirmed COVID-19 infection (aOR, 4.33; 95% CI, 1.77-10.58). The sensitivity of serology results was 94% (95% CI, 70%-100%) among those who reported receiving a previous polymerase chain reaction test for COVID-19 infection. Among 101 participants with seropositive results, 67 individuals (66.3%) were estimated to have asymptomatic infection. These data suggested a total estimated COVID-19 burden that was 2.8-fold higher than that ascertained by PCR-positive case counts.

Conclusions and Relevance

This large statewide serologic study estimated that 2.4% of adults in Virginia had exposure to SARS-CoV-2, which was 2.8-fold higher than confirmed case counts. Hispanic ethnicity, residence in a multifamily unit, and contact with an individual with confirmed COVID-19 infection were significant risk factors associated with exposure. Most infections were asymptomatic. As of August 2020, the population in Virginia remained largely immunologically naive to the virus.

Rapid review of COVID-19 epidemic estimation studies for Iran

BACKGROUND

To inform researchers about the methodology and results of epidemic estimation studies performed for COVID-19 epidemic in Iran, we aimed to perform a rapid review.

METHODS

We searched for and included published articles, preprint manuscripts and reports that estimated numbers of cumulative or daily deaths or cases of COVID-19 in Iran. We found 131 studies and included 29 of them.

RESULTS

The included studies provided outputs for a total of 84 study-model/scenario combinations. Sixteen studies used 3-4 compartmental disease models. At the end of month two of the epidemic (2020-04-19), the lowest (and highest) values of predictions were 1,777 (388,951) for cumulative deaths, 20,588 (2,310,161) for cumulative cases, and at the end of month four (2020-06-20), were 3,590 (1,819,392) for cumulative deaths, and 144,305 (4,266,964) for cumulative cases. Highest estimates of cumulative deaths (and cases) for latest date available in 2020 were 418,834 on 2020-12-19 (and 41,475,792 on 2020-12-31). Model estimates predict an ominous course of epidemic progress in Iran. Increase in percent population using masks from the current situation to 95% might prevent 26,790 additional deaths (95% confidence interval 19,925-35,208) by the end of year 2020.

CONCLUSIONS

Meticulousness and degree of details reported for disease modeling and statistical methods used in the included studies varied widely. Greater heterogeneity was observed regarding the results of predicted outcomes. Consideration of minimum and preferred reporting items in epidemic estimation studies might better inform future revisions of the available models and new models to be developed. Not accounting for under-reporting drives the models' results misleading.