ABSTRACT
BackgroundCompared to the abundance of clinical and genomic information available on patients hospitalised with COVID-19 disease from high-income countries, there is a paucity of data from low-income countries. Our aim was to explore the relationship between viral lineage and patient outcome. MethodsWe enrolled a prospective observational cohort of adult patients hospitalised with PCR-confirmed COVID-19 disease between July 2020 and March 2022 from Blantyre, Malawi, covering four waves of SARS-CoV-2 infections. Clinical and diagnostic data were collected using an adapted ISARIC clinical characterization protocol for COVID-19. SARS-CoV-2 isolates were sequenced using the MinION in Blantyre. ResultsWe enrolled 314 patients, good quality sequencing data was available for 55 patients. The sequencing data showed that 8 of 11 participants recruited in wave one had B.1 infections, 6/6 in wave two had Beta, 25/26 in wave three had Delta and 11/12 in wave four had Omicron. Patients infected during the Delta and Omicron waves reported fewer underlying chronic conditions and a shorter time to presentation. Significantly fewer patients required oxygen (22.7% [17/75] vs. 58.6% [140/239], p<0.001) and steroids (38.7% [29/75] vs. 70.3% [167/239], p<0.001) in the Omicron wave compared with the other waves. Multivariable logistic-regression demonstrated a trend toward increased mortality in the Delta wave (OR 4.99 [95% CI 1.0-25.0 p=0.05) compared to the first wave of infection. ConclusionsOur data show that each wave of patients hospitalised with SARS-CoV-2 was infected with a distinct viral variant. The clinical data suggests that patients with severe COVID-19 disease were more likely to die during the Delta wave. SummaryWe used genome sequencing to identify the variants of SARS-CoV-2 causing disease in Malawi, and found that each of the four waves was caused by a distinct variant. Clinical investigation suggested that the Delta wave had the highest mortality.
ABSTRACT
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.
