Global seroprevalence of SARS-CoV-2 antibodies: A systematic review and meta-analysis
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Abstract
Many studies report the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies. We aimed to synthesize seroprevalence data to better estimate the level and distribution of SARS-CoV-2 infection, identify high-risk groups, and inform public health decision making.
Methods
In this systematic review and meta-analysis, we searched publication databases, preprint servers, and grey literature sources for seroepidemiological study reports, from January 1, 2020 to December 31, 2020. We included studies that reported a sample size, study date, location, and seroprevalence estimate. We corrected estimates for imperfect test accuracy with Bayesian measurement error models, conducted meta-analysis to identify demographic differences in the prevalence of SARS-CoV-2 antibodies, and meta-regression to identify study-level factors associated with seroprevalence. We compared region-specific seroprevalence data to confirmed cumulative incidence. PROSPERO: CRD42020183634.
Results
We identified 968 seroprevalence studies including 9.3 million participants in 74 countries. There were 472 studies (49%) at low or moderate risk of bias. Seroprevalence was low in the general population (median 4.5%, IQR 2.4–8.4%); however, it varied widely in specific populations from low (0.6% perinatal) to high (59% persons in assisted living and long-term care facilities). Median seroprevalence also varied by Global Burden of Disease region, from 0.6% in Southeast Asia, East Asia and Oceania to 19.5% in Sub-Saharan Africa (p<0.001). National studies had lower seroprevalence estimates than regional and local studies (p<0.001). Compared to Caucasian persons, Black persons (prevalence ratio [RR] 3.37, 95% CI 2.64–4.29), Asian persons (RR 2.47, 95% CI 1.96–3.11), Indigenous persons (RR 5.47, 95% CI 1.01–32.6), and multi-racial persons (RR 1.89, 95% CI 1.60–2.24) were more likely to be seropositive. Seroprevalence was higher among people ages 18–64 compared to 65 and over (RR 1.27, 95% CI 1.11–1.45). Health care workers in contact with infected persons had a 2.10 times (95% CI 1.28–3.44) higher risk compared to health care workers without known contact. There was no difference in seroprevalence between sex groups. Seroprevalence estimates from national studies were a median 18.1 times (IQR 5.9–38.7) higher than the corresponding SARS-CoV-2 cumulative incidence, but there was large variation between Global Burden of Disease regions from 6.7 in South Asia to 602.5 in Sub-Saharan Africa. Notable methodological limitations of serosurveys included absent reporting of test information, no statistical correction for demographics or test sensitivity and specificity, use of non-probability sampling and use of non-representative sample frames.
Discussion
Most of the population remains susceptible to SARS-CoV-2 infection. Public health measures must be improved to protect disproportionately affected groups, including racial and ethnic minorities, until vaccine-derived herd immunity is achieved. Improvements in serosurvey design and reporting are needed for ongoing monitoring of infection prevalence and the pandemic response.
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SciScore for 10.1101/2020.11.17.20233460: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable We extracted sub-group data when they were stratified by one variable (e.g., seniors) but not two variables (e.g., female seniors). Table 2: Resources
Antibodies Sentences Resources We prioritized estimates that tested for IgG antibodies and that used traditional ELISAs, as non-IgG and anti-nucleocapsid antibodies appear to decline over time, while anti-spike IgG antibodies appear to persist for several months after infection.15–20 A modified Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Prevalence Studies was used to assess study risk … SciScore for 10.1101/2020.11.17.20233460: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable We extracted sub-group data when they were stratified by one variable (e.g., seniors) but not two variables (e.g., female seniors). Table 2: Resources
Antibodies Sentences Resources We prioritized estimates that tested for IgG antibodies and that used traditional ELISAs, as non-IgG and anti-nucleocapsid antibodies appear to decline over time, while anti-spike IgG antibodies appear to persist for several months after infection.15–20 A modified Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Prevalence Studies was used to assess study risk of bias. IgGsuggested: Noneanti-nucleocapsidsuggested: Noneanti-spike IgGsuggested: NoneSoftware and Algorithms Sentences Resources 9 We searched Medline, EMBASE, Web of Science, and Europe PMC, using a search strategy developed in consultation with a health sciences librarian. Medlinesuggested: (MEDLINE, RRID:SCR_002185)EMBASEsuggested: (EMBASE, RRID:SCR_001650)2.4 Data Analysis: Data processing and descriptive statistics were conducted in Python. p-values less than 0.05 were considered statistically significant. Pythonsuggested: (IPython, RRID:SCR_001658)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our study has limitations. Firstly, some asymptomatic individuals may not seroconvert and some individuals may have been tested prior to seroconversion, so the data in this study may underestimate the true number of SARS-CoV-2 infections.40 To ameliorate this, we prioritized estimates that tested for IgG antibodies, which show better persistence in serum compared to non-IgG and anti-nucleocapsid antibodies.15–20 Secondly, to account for measurement error in seroprevalence estimates resulting from poorly performing tests, it was necessary to use sensitivity and specificity information from multiple sources of varying quality. While we prioritized independent evaluations, these were not available for all tests. Thirdly, the residual heterogeneity in our meta-regression indicates that not all relevant explanatory variables have been accounted for. There may be other factors that confound the associations we identified in our analysis. However, a key driving factor may simply be true differences in spread of infection and impact of the pandemic. Finally, we were only able to incorporate cumulative case incidence published on national, regional, or local government dashboards. This may have systematically excluded areas too under-resourced to conduct or report mass diagnostic testing. Our systematic review is the largest synthesis of SARS-CoV-2 serosurveillance data to date. Our search was rigorous and comprehensive: we included non-English articles, government reports and unpubli...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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