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      Global seroprevalence of SARS-CoV-2 antibodies: A systematic review and meta-analysis

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          Abstract

          Background

          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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          Most cited references48

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          Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement

          David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses
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            Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19): A Review

            The coronavirus disease 2019 (COVID-19) pandemic, due to the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a worldwide sudden and substantial increase in hospitalizations for pneumonia with multiorgan disease. This review discusses current evidence regarding the pathophysiology, transmission, diagnosis, and management of COVID-19.
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              How to perform a meta-analysis with R: a practical tutorial

              Meta-analysis is of fundamental importance to obtain an unbiased assessment of the available evidence. In general, the use of meta-analysis has been increasing over the last three decades with mental health as a major research topic. It is then essential to well understand its methodology and interpret its results. In this publication, we describe how to perform a meta-analysis with the freely available statistical software environment R, using a working example taken from the field of mental health. R package meta is used to conduct standard meta-analysis. Sensitivity analyses for missing binary outcome data and potential selection bias are conducted with R package metasens. All essential R commands are provided and clearly described to conduct and report analyses. The working example considers a binary outcome: we show how to conduct a fixed effect and random effects meta-analysis and subgroup analysis, produce a forest and funnel plot and to test and adjust for funnel plot asymmetry. All these steps work similar for other outcome types. R represents a powerful and flexible tool to conduct meta-analyses. This publication gives a brief glimpse into the topic and provides directions to more advanced meta-analysis methods available in R.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: ValidationRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: SoftwareRole: VisualizationRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: SoftwareRole: VisualizationRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: SoftwareRole: VisualizationRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                23 June 2021
                2021
                23 June 2021
                : 16
                : 6
                : e0252617
                Affiliations
                [1 ] Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
                [2 ] Department of Critical Care Medicine, University of Calgary, Calgary, Alberta, Canada
                [3 ] Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
                [4 ] Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
                [5 ] Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
                [6 ] Department of Social Policy and Intervention, University of Oxford, Oxford, United Kingdom
                [7 ] COVID-19 Immunity Task Force, McGill University, Montreal, Quebec, Canada
                [8 ] School of Population and Global Health, McGill University, Montreal, Quebec, Canada
                [9 ] Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada
                [10 ] Faculty of Engineering, University of Waterloo, Waterloo, Ontario, Canada
                [11 ] JD MacLean Centre for Tropical Diseases, McGill University, Montreal, Quebec, Canada
                [12 ] Divisions of Infectious Diseases and Medical Microbiology, McGill University Health Centre, Montreal, Quebec, Canada
                [13 ] Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
                [14 ] Division of Pediatric Infectious Diseases, Department of Pediatrics, McGill University Health Centre, Montreal, Quebec, Canada
                Centers for Disease Control and Prevention, UNITED STATES
                Author notes

                Competing Interests: MPC reports personal fees from Gen1E Lifesciences (as a member of the scientific advisory board) and personal fees from nplex biosciences (as a member of the scientific advisory board), both outside the submitted work. JP reports grants and personal fees from Seegene and AbbVie, grants from MedImmune and Sanofi Pasteur, outside the submitted work. RKA, NB, and TY report grants from the World Health Organization and the Canadian Medical Association for SARS-CoV-2 serosurveillance, both outside the submitted work. DAC reports personal fees from Biobeats ( https://www.bio-beat.com/), and Sensyne Health during the conduct of the study. There are no patents, products in development or marketed products associated with this research to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                ‡ NB and RKA contributed equally to this work and served as co-first authors. JP and MPC also contributed equally to this work and served as co-senior authors.

                Author information
                https://orcid.org/0000-0001-7883-4484
                https://orcid.org/0000-0003-3526-6338
                https://orcid.org/0000-0002-0395-0381
                https://orcid.org/0000-0003-2724-8797
                https://orcid.org/0000-0003-4232-871X
                Article
                PONE-D-20-40466
                10.1371/journal.pone.0252617
                8221784
                34161316
                4864d989-c792-43ac-98a3-edfe5cfcfbe8
                © 2021 Bobrovitz et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 24 December 2020
                : 18 May 2021
                Page count
                Figures: 3, Tables: 6, Pages: 21
                Funding
                Funded by: Public Health Agency of Canada via the COVID-19 Immunity Task Force
                This research was funded by the Public Health Agency of Canada through Canada’s COVID-19 Immunity Task Force ( https://www.covid19immunitytaskforce.ca/). DAC reports personal fees from Oxford University Innovation, Biobeats ( https://www.bio-beat.com/), and Sensyne Health. MPC reports grants from McGill Interdisciplinary Initiative in Infection and Immunity and grants from Canadian Institutes of Health Research during the conduct of the study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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                All files are available from the SeroTracker database ( https://serotracker.com/). Data are from the 'Data' page of the site. The authors did not receive special access privileges to the data that others would not have.
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