Epidemiological and phylogenetic analyses of public SARS-CoV-2 data from Malawi

Abstract The novel Coronavirus SARS-CoV-2 was first identified in a person in Wuhan city, China in December 2019, and had spread to all continents in less than three months. While there were many similarities between the resulting COVID-19 pandemic in different regions and countries, there were also important differences, motivating systematic quantitative analysis of available data for as diverse a set of geographical locations as possible to drive generation of insights relevant for response to COVID-19 and other respiratory viral and pandemic threats. Malawi had its first COVID-19 case on 2 April 2020 and, like many countries in the Global South, had access to orders of magnitude less data than countries in the Global North to inform its response. Here, we present modelling analyses of SARS-CoV-2 epidemiology and phylogenetics in Malawi from 2 April 2020 to 19 October 2022. We carried out this analysis using open-source software tools and open data on cases, deaths, geography, demographics, and viral genomics. In particular, we used R to visualise the raw data and results, alongside Generalised Additive Models (GAMs), which were fit to case and mortality data to describe the incidence trends, growth rate and doubling time of SARS-CoV-2. IQTree, TreeTime and interactive Tree of Life were used to perform the phylogenetic analysis. This analysis reveals five major waves of COVID-19 in Malawi, associated with different lineages: (1) Early variants; (2) Beta; (3) Delta; (4) Omicron BA.1; (5) Other Omicron. Some sequences associated with the Alpha variant were present but these did not appear to drive a major wave as they did in some other countries. 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 cases and deaths were highly geographically heterogeneous. We argue that such analyses could have been and could in future be carried out in real time in Malawi and other countries in the Global South with similar computational and data resources. Author summary Malawi detected its first infection with SARS-CoV-2 at the start of April 2020, and like many other countries in the Global South did not have comparable volumes of data to Global North countries to inform its response to the COVID-19 pandemic. Here, we present quantitative analyses of the epidemiology and phylogenetics of SARS-CoV-2 in Malawi using open software and data that can be straightforwardly deployed in other countries and for other pathogens, under similar data availability. We observed five major COVID waves over a period from April 2020 to October 2022, each associated with different variants of SARS-CoV-2, as well as significant geographical heterogeneity. Waves were typically associated with early doubling times of between 7 and 4 days, with the second major wave driven by the Beta variant rather than the Alpha and Gamma variants observed in some other countries. Pylogenetic analysis revealed a temporal tree structure consistent with both major variant structure identified elsewhere, and known epidemiology of major variants. Competing Interest Statement The authors have declared no competing interest. Funding Statement MKA was supported by the Schlumberger Foundation Faculty for the Future. KL was supported by the Royal Society and the Wellcome Trust (107652/Z/15/Z) and the Li Ka Shing Foundation. OJ was supported by the Wellcome Trust (228264/Z/23/Z). KL, IH and TH were supported by the Wellcome Trust (227438/Z/23/Z). RC, IH and TH were supported by the UKRI Impact Acceleration Account (IAA 386). Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study used openly available data accessed from: https://gisaid.org/ https://ourworldindata.org/ I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability The manuscript presents secondary analysis of public data. We are not the data guardians for this, so provide sources in the manuscript to allow other researcher to obtain the data from its owners.