Journal Article
Published 2025
Epidemiological and phylogenetic analyses of public SARS-CoV-2 data from Malawi
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Dr. Atupele Ngina Mulaga
Co-author
Mathematical Sciences
11 total publications
Atupele N. Mulaga’s expertise is in Applied Statistics. She is currently a lecturer and researcher in Statistics at the Malawi University of Business and Applied Sciences, Department of Mathematical Sciences. She received a Consortium for Advanced Re...
UN Sustainable Development Goals
Global Impact
Research Fields & Tags
Primary Author
Dr Mwandida Afuleni
Co-Authors
Roberto Cahuantz, Katrina A. Lythgoe, Ian Hall, Dr. Atupele Ngina Mulaga, Olatunji Johnson, Thomas House
Abstract
The COVID-19 pandemic has had varying impacts across different regions, necessitating
localised data-driven responses. SARS-CoV-2 was first identified in a person in Wuhan,
China, in December 2019 and spread globally within three months. While there were similarities in the pandemic’s impact across regions, key differences motivated systematic
quantitative analysis of diverse geographical data to inform responses. Malawi reported
its first COVID-19 case on 2 April 2020 but had significantly less data than Global North
countries to inform its response. Here, we present a modelling analysis of SARS-CoV-2
epidemiology and phylogenetics in Malawi between 2 April 2020 and 19 October 2022.
We carried out this analysis using open-source tools and open data on confirmed cases,
deaths, geography, demographics, and viral genomics. R was used for data visualisation,
while Generalised Additive Models (GAMs) estimated incidence trends, growth rates,
and doubling times. Phylogenetic analysis was conducted using IQ-TREE, TreeTime,
and interactive tree of life. This analysis identifies five major COVID-19 waves in Malawi,
driven by different lineages: (1) Early variants, (2) Beta, (3) Delta, (4) Omicron BA.1,
and (5) Other Omicron. While the Alpha variant was present, it did not cause a major
wave, likely due to competition from the more infectious Delta variant, since Alpha circulated in Malawi when Beta was phasing out and Delta emerging. Case Fatality Ratios
were higher for Delta, and lower for Omicron, than for earlier lineages. Phylogeny reveals
separation of the tree into major lineages as would be expected, and early emergence
of Omicron, as is consistent with proximity to the likely origin of this variant. Both variant prevalence and overall rates of confirmed cases and confirmed deaths were highly
geographically heterogeneous. We suggest that real-time analyses should be considered in Malawi and other countries, where similar computational and data resources are
available
localised data-driven responses. SARS-CoV-2 was first identified in a person in Wuhan,
China, in December 2019 and spread globally within three months. While there were similarities in the pandemic’s impact across regions, key differences motivated systematic
quantitative analysis of diverse geographical data to inform responses. Malawi reported
its first COVID-19 case on 2 April 2020 but had significantly less data than Global North
countries to inform its response. Here, we present a modelling analysis of SARS-CoV-2
epidemiology and phylogenetics in Malawi between 2 April 2020 and 19 October 2022.
We carried out this analysis using open-source tools and open data on confirmed cases,
deaths, geography, demographics, and viral genomics. R was used for data visualisation,
while Generalised Additive Models (GAMs) estimated incidence trends, growth rates,
and doubling times. Phylogenetic analysis was conducted using IQ-TREE, TreeTime,
and interactive tree of life. This analysis identifies five major COVID-19 waves in Malawi,
driven by different lineages: (1) Early variants, (2) Beta, (3) Delta, (4) Omicron BA.1,
and (5) Other Omicron. While the Alpha variant was present, it did not cause a major
wave, likely due to competition from the more infectious Delta variant, since Alpha circulated in Malawi when Beta was phasing out and Delta emerging. Case Fatality Ratios
were higher for Delta, and lower for Omicron, than for earlier lineages. Phylogeny reveals
separation of the tree into major lineages as would be expected, and early emergence
of Omicron, as is consistent with proximity to the likely origin of this variant. Both variant prevalence and overall rates of confirmed cases and confirmed deaths were highly
geographically heterogeneous. We suggest that real-time analyses should be considered in Malawi and other countries, where similar computational and data resources are
available
Year of Publication
2025
External Digital Object URL
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Journal Name
PLoS Global Public Health
Volume
5
Issue
3
Page Numbers
1-16
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