Cited by 110COVID-19 epidemiological studiesSARS-CoV-2 and COVID-19 ResearchSARS-CoV-2 detection and testing

High SARS-CoV-2 seroprevalence in health care workers but relatively low numbers of deaths in urban Malawi

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Chibwana, Marah G., Jere, Khuzwayo C., Kamng'ona, Raphael, Mandolo, Jonathan, Katunga-Phiri, Vincent, Tembo, Dumizulu, Mitole, Ndaona, Musasa, Samantha +15 more·2020·Wellcome Open Research

Published version of a preprint

Abstract

Background : In low-income countries, like Malawi, important public health measures including social distancing or a lockdown have been challenging to implement owing to socioeconomic constraints, leading to predictions that the COVID-19 pandemic would progress rapidly. However, due to limited capacity to test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, there are no reliable estimates of the true burden of infection and death. We, therefore, conducted a SARS-CoV-2 serosurvey amongst health care workers (HCWs) in Blantyre city to estimate the cumulative incidence of SARS-CoV-2 infection in urban Malawi. Methods : We recruited 500 otherwise asymptomatic HCWs from Blantyre City (Malawi) from 22 nd May 2020 to 19 th June 2020 and serum samples were collected from all participants. A commercial ELISA was used to measure SARS-CoV-2 IgG antibodies in serum. Results : A total of 84 participants tested positive for SARS-CoV-2 antibodies. The HCWs with positive SARS-CoV-2 antibody results came from different parts of the city. The adjusted seroprevalence of SARS-CoV-2 antibodies was 12.3% [CI 8.2 - 16.5]. Using age-stratified infection fatality estimates reported from elsewhere, we found that at the observed adjusted seroprevalence, the number of predicted deaths was eight times the number of reported deaths. Conclusions : The high seroprevalence of SARS-CoV-2 antibodies among HCWs and the discrepancy in the predicted versus reported deaths suggests that there was early exposure but slow progression of COVID-19 epidemic in urban Malawi. This highlights the urgent need for development of locally parameterised mathematical models to more accurately predict the trajectory of the epidemic in sub-Saharan Africa for better evidence-based policy decisions and public health response planning.

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Authors
Chibwana, M. G., Jere, K. C., Kamng'ona, R., Mandolo, J., Katunga-Phiri, V., Tembo, D., Mitole, N., Musasa, S., Sichone, S., Lakudzala, A., Sibale, L., Matambo, P., Kadwala, I., Byrne, R. L., Mbewe, A., Henrion, M. Y. R., Morton, B., Phiri, C., Mallewa, J., Mwandumba, H. C., Adams, E. R., Gordon, S. B., & Jambo, K. C.
Affiliations
  • Malawi-Liverpool-Wellcome Trust Clinical Research Programme (MW)
  • University of Liverpool (GB)
  • University of Malawi (MW)
  • Liverpool School of Tropical Medicine (GB)
  • Ministry of Health (MW)
Corresponding author
Gordon, Stephen B.
Venue
Wellcome Open Research
Published
2020-08-25
Volume
5
Pages
199
ISSN
2398-502X (ISSN-L)
OpenAlex
W3046449642
Cited by
110
References
15
Citations by year
2026: 3 · 2025: 2 · 2024: 13 · 2023: 9 · 2022: 24 · 2021: 44 · 2020: 15
FWCI
3.63
Type
journal article
Language
en
Open access
Locations
  • Wellcome Open Research (publishedVersion, cc-by)
  • medRxiv (acceptedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • LSTM Online Archive (Liverpool School of Tropical Medicine) (acceptedVersion)
  • PubMed Central (submittedVersion, cc-by-nc-nd)
  • Figshare (submittedVersion, cc-by)
  • Figshare (cc-by)
Funders
  • Medical Research Council (MR/T008822/1)
  • National Institutes of Health (U01AI131348)
  • National Institute for Health Research (3477609, 200907)
  • Wellcome Trust (201945, 220764, 206545, 211433)
Topics
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 detection and testing
Keywords
SARS-CoV-2, COVID-19 pandemic, seroprevalence, healthcare workers, IgG, underreporting of deaths, epidemic trajectory, epidemic modeling, Blantyre, sub-Saharan Africa

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