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

  1. Hannah C Lewis
  2. Harriet Ware
  3. Mairead Whelan
  4. Lorenzo Subissi
  5. Zihan Li
  6. Xiaomeng Ma
  7. Anthony Nardone
  8. Marta Valenciano
  9. Brianna Cheng
  10. Kim Noel
  11. Christian Cao
  12. Mercedes Yanes-Lane
  13. Belinda L Herring
  14. Ambrose Talisuna
  15. Nsenga Ngoy
  16. Thierno Balde
  17. David Clifton
  18. Maria D Van Kerkhove
  19. David Buckeridge
  20. Niklas Bobrovitz
  21. Joseph Okeibunor
  22. Rahul K Arora
  23. Isabel Bergeri

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Abstract

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.

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  1. Version published to 10.1136/bmjgh-2022-008793
  2. ScreenIT

    SciScore for 10.1101/2022.02.14.22270934: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    Where there were multiple estimates per study unrelated to time, estimates were prioritised based on adjustment, antibody isotypes, test type, and antibody targets (full details: Supplement S3.1).
    test type
    suggested: None
    Software and Algorithms
    SentencesResources
    We searched MEDLINE, Embase, Web of Science, and Europe PMC for published articles, preprints, grey literature, and media reports.
    MEDLINE
    suggested: (MEDLINE, RRID:SCR_002185)
    Embase
    suggested: (EMBASE, RRID:SCR_001650)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strengths and limitations: Previous assessments of COVID-19 seroprevalence studies highlight methodological heterogeneity as a key barrier to synthesising data.[33–35] The distinctive dataset described here is standardised, representative and granular, enabling unique insights into seroprevalence in Africa. Recently, in part via WHO’s UNITY Studies Initiative, more seroprevalence data has become available, disaggregated by demographic groups (age, sex), place (e.g. sub-region, country) and time (quarterly periods). In line with the equity principles of the UNITY Studies Initiative, our dataset 0 included a broad range of studies in low-income countries (62%, n=95), lower-middle-income countries (LMIC) (22%, n=33) and vulnerable HRP countries (41%, n=62). Around one quarter of studies were conducted at the national level, which is unique to this analysis. UNITY study collaborators shared timely evidence, facilitating geographic coverage and reducing publication bias. Additionally, standardised epidemiological and serological methods (including the supply of a well-performing assay to LMIC) enabled through the UNITY Studies Initiative means that the estimates included in our meta-analysis are robust and comparable. Finally, recognizing that assay performance is a key determinant of seroprevalence, we linked our data to independent test kit evaluations[27,28] of serological assay performance to correct seroprevalence estimates in a sensitivity analysis, helping ensure the robust...

    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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

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  3. Version published to 10.1101/2022.02.14.22270934v1 on medRxiv