SARS-CoV-2 infection in Africa : a systematic review and meta-analysis of standardised seroprevalence studies, from January 2020 to December 2021
© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ..
INTRODUCTION: Estimating 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.
METHODS: We 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.
RESULTS: We 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.
CONCLUSION: We 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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:7 |
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| Enthalten in: |
BMJ global health - 7(2022), 8 vom: 19. Aug. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Lewis, Hannah C [VerfasserIn] |
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| Links: |
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| Themen: |
COVID-19 |
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| Anmerkungen: |
Date Completed 25.08.2022 Date Revised 16.02.2024 published: Print Citation Status MEDLINE |
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| doi: |
10.1136/bmjgh-2022-008793 |
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| Förderinstitution / Projekttitel: |
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| 245 | 1 | 0 | |a SARS-CoV-2 infection in Africa |b a systematic review and meta-analysis of standardised seroprevalence studies, from January 2020 to December 2021 |
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| 500 | |a Date Revised 16.02.2024 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. | ||
| 520 | |a INTRODUCTION: Estimating 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 | ||
| 520 | |a METHODS: We 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 | ||
| 520 | |a PROSPERO: CRD42020183634 | ||
| 520 | |a RESULTS: We 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 | ||
| 520 | |a CONCLUSION: We 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Meta-Analysis | |
| 650 | 4 | |a Systematic Review | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a epidemiology | |
| 650 | 4 | |a public health | |
| 650 | 4 | |a serology | |
| 650 | 4 | |a systematic review | |
| 700 | 1 | |a Ware, Harriet |e verfasserin |4 aut | |
| 700 | 1 | |a Whelan, Mairead |e verfasserin |4 aut | |
| 700 | 1 | |a Subissi, Lorenzo |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Zihan |e verfasserin |4 aut | |
| 700 | 1 | |a Ma, Xiaomeng |e verfasserin |4 aut | |
| 700 | 1 | |a Nardone, Anthony |e verfasserin |4 aut | |
| 700 | 1 | |a Valenciano, Marta |e verfasserin |4 aut | |
| 700 | 1 | |a Cheng, Brianna |e verfasserin |4 aut | |
| 700 | 1 | |a Noel, Kim |e verfasserin |4 aut | |
| 700 | 1 | |a Cao, Christian |e verfasserin |4 aut | |
| 700 | 1 | |a Yanes-Lane, Mercedes |e verfasserin |4 aut | |
| 700 | 1 | |a Herring, Belinda L |e verfasserin |4 aut | |
| 700 | 1 | |a Talisuna, Ambrose |e verfasserin |4 aut | |
| 700 | 1 | |a Ngoy, Nsenga |e verfasserin |4 aut | |
| 700 | 1 | |a Balde, Thierno |e verfasserin |4 aut | |
| 700 | 1 | |a Clifton, David |e verfasserin |4 aut | |
| 700 | 1 | |a Van Kerkhove, Maria D |e verfasserin |4 aut | |
| 700 | 1 | |a Buckeridge, David |e verfasserin |4 aut | |
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| 700 | 1 | |a Okeibunor, Joseph |e verfasserin |4 aut | |
| 700 | 1 | |a Arora, Rahul K |e verfasserin |4 aut | |
| 700 | 1 | |a Bergeri, Isabel |e verfasserin |4 aut | |
| 700 | 0 | |a UNITY Studies Collaborator Group |e verfasserin |4 aut | |
| 700 | 1 | |a Adamou, Rafiou |e investigator |4 oth | |
| 700 | 1 | |a Adegnika, Ayola A |e investigator |4 oth | |
| 700 | 1 | |a Assoumou, Samira Z |e investigator |4 oth | |
| 700 | 1 | |a Audu, Rosemary A |e investigator |4 oth | |
| 700 | 1 | |a Barnor, Jacob S |e investigator |4 oth | |
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| 700 | 1 | |a Cheng, Matthew P |e investigator |4 oth | |
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| 700 | 1 | |a Cohen, Cheryl |e investigator |4 oth | |
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| 700 | 1 | |a Deveaux, Gabriel |e investigator |4 oth | |
| 700 | 1 | |a Diop, Boly |e investigator |4 oth | |
| 700 | 1 | |a Divala, Titus H |e investigator |4 oth | |
| 700 | 1 | |a Dokubo, Emily K |e investigator |4 oth | |
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| 700 | 1 | |a Gottberg, Anne von |e investigator |4 oth | |
| 700 | 1 | |a Harris, Tiffany G |e investigator |4 oth | |
| 700 | 1 | |a Ilincic, Natasha |e investigator |4 oth | |
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