Evidence map›Paper›PMID 35998978›Full record

SynthesisBMJ global health2022

SARS-CoV-2 infection in Africa: a systematic review and meta-analysis of standardised seroprevalence studies, from January 2020 to December 2021.

Hannah C Lewis, Harriet Ware, Mairead Whelan, Lorenzo Subissi, Zihan Li, Xiaomeng Ma, Anthony Nardone, Marta Valenciano, Brianna Cheng, Kim Noel and 14 more

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMJ global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
120citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

120 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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60 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors.

Hannah C LewisEmergency Preparedness and Response Programme, World Health Organization, Regional Office for Africa, Brazzaville, Congo lewish@who.int.ORCID 0000-0002-1925-3943
Harriet WareCentre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.ORCID 0000-0003-3869-3060
Mairead WhelanCentre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.ORCID 0000-0002-4895-9304
Lorenzo SubissiWHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland.ORCID 0000-0001-5147-575X
Zihan LiFaculty of Engineering, University of Waterloo, Waterloo, Ontario, Canada.ORCID 0000-0002-0101-977X
Xiaomeng MaInstitute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0002-4165-3062
Anthony NardoneWHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland.ORCID 0000-0003-1138-0937
Marta ValencianoWHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland.ORCID 0000-0002-2056-1062
Brianna ChengWHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland.ORCID 0000-0003-2004-2251
Kim NoelDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada.ORCID 0000-0002-8957-3459
Christian CaoCentre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.ORCID 0000-0002-0395-0381
Mercedes Yanes-LaneDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada.ORCID 0000-0003-2121-772X
Belinda L HerringEmergency Preparedness and Response Programme, World Health Organization, Regional Office for Africa, Brazzaville, Congo.ORCID 0000-0001-8284-1505
Ambrose TalisunaEmergency Preparedness and Response Programme, World Health Organization, Regional Office for Africa, Brazzaville, Congo.ORCID 0000-0001-6436-3415
Nsenga NgoyEmergency Preparedness and Response Programme, World Health Organization, Regional Office for Africa, Brazzaville, Congo.ORCID 0000-0003-1187-0362
Thierno BaldeEmergency Preparedness and Response Programme, World Health Organization, Regional Office for Africa, Brazzaville, Congo.
David CliftonInstitute of Biomedical Engineering, University of Oxford, Oxford, UK.
Maria D Van KerkhoveWHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland.ORCID 0000-0002-6135-0018
David BuckeridgeDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada.ORCID 0000-0003-1817-5047
Niklas BobrovitzTemerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0001-7883-4484
Joseph OkeibunorEmergency Preparedness and Response Programme, World Health Organization, Regional Office for Africa, Brazzaville, Congo.
Rahul K AroraCentre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.ORCID 0000-0003-3526-6338
Isabel BergeriWHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland.ORCID 0000-0002-1204-1753
UNITY Studies Collaborator Group

Funding

Medical Research Council MR/T008822/1World Health Organization 001
6 · The paper itself

Abstract

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 1 January 2020-30 December 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 seroprevalence protocol. 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 56 full texts or early results, reporting 153 distinct seroprevalence studies in Africa. Of these, 97 (63%) were low/moderate risk of bias studies. SARS-CoV-2 seroprevalence rose from 3.0% (95% CI 1.0% to 9.2%) in April-June 2020 to 65.1% (95% CI 56.3% to 73.0%) in July-September 2021. The ratios of seroprevalence from infection to cumulative incidence of confirmed cases was large (overall: 100:1, ranging from 18:1 to 954:1) and steady over time. Seroprevalence was highly heterogeneous both within countries-urban versus rural (lower seroprevalence for rural geographic areas), children versus adults (children aged 0-9 years had the lowest seroprevalence)-and between countries and African subregions.

conclusionWe report high seroprevalence in Africa suggesting greater population exposure to SARS-CoV-2 and potential protection against COVID-19 severe disease than indicated by surveillance data. As seroprevalence was heterogeneous, targeted PHSM and vaccination strategies need to be tailored to local epidemiological situations.

Indexed as

COVID-19AdultAfricaChildEuropeHumansSARS-CoV-2Seroepidemiologic StudiesCOVID-19epidemiologypublic healthserologysystematic review

Identifiers

PMID35998978
PMCPMC9402450

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.