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IntroductionEstimating COVID-19 cumulative incidence in Africa remains problematic due to challenges in contact tracing, routine surveillance systems and laboratory testing capacities and strategies. We undertook a meta-analysis of population-based seroprevalence studies to estimate SARS-CoV-2 seroprevalence in Africa to inform evidence-based decision making on Public Health and Social Measures (PHSM) and vaccine strategy. MethodsWe searched for seroprevalence studies conducted in Africa published 01-01-2020 to 30-12-2021 in Medline, Embase, Web of Science, and Europe PMC (preprints), grey literature, media releases and early results from WHO Unity studies. All studies were screened, extracted, assessed for risk of bias and evaluated for alignment with the WHO Unity protocol for seroepidemiological investigations. We conducted descriptive analyses of seroprevalence and meta-analysed seroprevalence differences by demographic groups, place and time. We estimated the extent of undetected infections by comparing seroprevalence and cumulative incidence of confirmed cases reported to WHO. PROSPERO: CRD42020183634. ResultsWe identified 54 full texts or early results, reporting 151 distinct seroprevalence studies in Africa Of these, 95 (63%) were low/moderate risk of bias studies. SARS-CoV-2 seroprevalence rose from 3.0% [95% CI: 1.0-9.2%] in Q2 2020 to 65.1% [95% CI: 56.3-73.0%] in Q3 2021. The ratios of seroprevalence from infection to cumulative incidence of confirmed cases was large (overall: 97:1, ranging from 10:1 to 958:1) and steady over time. Seroprevalence was highly heterogeneous both within countries - urban vs. rural (lower seroprevalence for rural geographic areas), children vs. adults (children aged 0-9 years had the lowest seroprevalence) - and between countries and African sub-regions (Middle, Western and Eastern Africa associated with higher seroprevalence). ConclusionWe report high seroprevalence in Africa suggesting greater population exposure to SARS-CoV-2 and protection against COVID-19 disease than indicated by surveillance data. As seroprevalence was heterogeneous, targeted PHSM and vaccination strategies need to be tailored to local epidemiological situations.
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BackgroundOur understanding of the global scale of SARS-CoV-2 infection remains incomplete: routine surveillance data underestimates infection and cannot infer on population immunity, there is a predominance of asymptomatic infections, and uneven access to diagnostics. We meta-analyzed SARS-CoV-2 seroprevalence studies, standardized to those described in WHOs Unity protocol for general population seroepidemiological studies, two years into the pandemic, to estimate the extent of population infection and remaining susceptibility. Methods and FindingsWe conducted a systematic review and meta-analysis, searching MEDLINE, Embase, Web of Science, preprints, and grey literature for SARS-CoV-2 seroprevalence published between 2020-01-01 and 2022-05-20. The review protocol is registered with PROSPERO, (CRD42020183634). We included general population cross-sectional and cohort studies meeting an assay quality threshold (90% sensitivity, 97% specificity; exceptions for humanitarian settings). We excluded studies with an unclear or closed population sample frame. Eligible studies - those aligned with the WHO Unity protocol - were extracted and critically appraised in duplicate, with Risk of Bias evaluated using a modified Joanna Briggs Institute checklist. We meta-analyzed seroprevalence by country and month, pooling to estimate regional and global seroprevalence over time; compared seroprevalence from infection to confirmed cases to estimate under-ascertainment; meta-analyzed differences in seroprevalence between demographic subgroups such as age and sex; and identified national factors associated with seroprevalence using meta-regression. The main limitations of our methodology include that some estimates were driven by certain countries or populations being over-represented. We identified 513 full texts reporting 965 distinct seroprevalence studies (41% LMIC) sampling 5,346,069 participants between January 2020 and April 2022, including 459 low/moderate risk of bias studies with national/sub-national scope in further analysis. By September 2021, global SARS-CoV-2 seroprevalence from infection or vaccination was 59.2%, 95% CI [56.1-62.2%]. Overall seroprevalence rose steeply in 2021 due to infection in some regions (e.g., 26.6% [24.6-28.8] to 86.7% [84.6-88.5%] in Africa in December 2021) and vaccination and infection in others (e.g., 9.6% [8.3-11.0%] to 95.9% [92.6-97.8%] in Europe high-income countries in December 2021). After the emergence of Omicron, infection-induced seroprevalence rose to 47.9% [41.0-54.9%] in EUR HIC and 33.7% [31.6-36.0%] in AMR HIC in March 2022. In 2021 Quarter Three (July to September), median seroprevalence to cumulative incidence ratios ranged from around 2:1 in the Americas and Europe HICs to over 100:1 in Africa (LMICs). Children 0-9 years and adults 60+ were at lower risk of seropositivity than adults 20-29 (p<0.0001 and p=0.005, respectively). In a multivariable model using pre-vaccination data, stringent public health and social measures were associated with lower seroprevalence (p=0.02). ConclusionsIn this study, we observed that global seroprevalence has risen considerably over time and with regional variation, however around 40 % of the global population remains susceptible to SARS-CoV-2 infection. Our estimates of infections based on seroprevalence far exceed reported COVID-19 cases. Quality and standardized seroprevalence studies are essential to inform COVID-19 response, particularly in resource-limited regions.
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BackgroundRisk of bias (RoB) assessments are a core element of evidence synthesis but can be time consuming and subjective. We aimed to develop a decision rule-based algorithm for RoB assessment of seroprevalence studies. MethodsWe developed the SeroTracker-RoB algorithm. The algorithm derives seven objective and two subjective critical appraisal items from the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence studies and implements decision rules that determine study risk of bias based on the items. Decision rules were validated using the SeroTracker seroprevalence study database, which included non-algorithmic RoB judgements from two reviewers. We quantified efficiency as the mean difference in time for the algorithmic and non-algorithmic assessments of 80 randomly selected articles, coverage as the proportion of studies where the decision rules yielded an assessment, and reliability using intraclass correlations comparing algorithmic and non-algorithmic assessments for 2,070 articles. ResultsA set of decision rules with 61 branches was developed using responses to the nine critical appraisal items. The algorithmic approach was faster than non-algorithmic assessment (mean reduction 2.32 minutes [SD 1.09] per article), classified 100% (n=2,070) of studies, and had good reliability compared to non-algorithmic assessment (ICC 0.77, 95% CI 0.74-0.80). We built the SeroTracker-RoB Excel Tool which embeds this algorithm for use by other researchers. ConclusionsThe SeroTracker-RoB decision-rule based algorithm was faster than non-algorithmic assessment with complete coverage and good reliability. This algorithm enabled rapid, transparent, and reproducible RoB evaluations of seroprevalence studies and may support evidence synthesis efforts during future disease outbreaks. This decision rule-based approach could be applied to other types of prevalence studies.
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BackgroundMany 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. MethodsIn 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. ResultsWe 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. DiscussionMost 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. FundingPublic Health Agency of Canada through the COVID-19 Immunity Task Force.
