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Preprint em Inglês | medRxiv | ID: ppmedrxiv-20164970

RESUMO

BackgroundIn 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 (HCW) in Blantyre city to estimate the cumulative incidence of SARS-CoV-2 infection in urban Malawi. MethodsFive hundred otherwise asymptomatic HCWs were recruited from Blantyre City (Malawi) from 22nd May 2020 to 19th June 2020 and serum samples were collected all participants. A commercial ELISA was used to measure SARS-CoV-2 IgG antibodies in serum. We run local negative samples (2018 - 2019) to verify the specificity of the assay. To estimate the seroprevalence of SARS CoV-2 antibodies, we adjusted the proportion of positive results based on local specificity of the assay. ResultsEighty-four participants tested positive for SARS-CoV-2 antibodies. The HCW with a positive SARS-CoV-2 antibody result came from different parts of the city. The adjusted seroprevalence of SARS-CoV-2 antibodies was 12.3% [CI 9.0-15.7]. Using age-stratified infection fatality estimates reported from elsewhere, we found that at the observed adjusted seroprevalence, the number of predicted deaths was 8 times the number of reported deaths. ConclusionThe high seroprevalence of SARS-CoV-2 antibodies among HCW 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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