Spatiotemporal Analysis of COVID-19 Risk in Malawi: The Impact of Age, Poverty, Population Density, and Environmental Factors

BackgroundUnderstanding the spatiotemporal variation of COVID-19 transmission and its determinants is crucial for gaining deeper insights into the dynamics of disease spread. Regional and temporal differences in demographics, socioeconomic conditions, and environmental factors shaped the trajectory of the COVID-19 pandemic, underscoring the importance of advanced spatio-temporal modelling. This research aims to construct a spatiotemporal model to examine the relationship between age groups, poverty, population density, precipitation, and COVID-19 risk, as well as to pinpoint high-risk areas. MethodsHere we present a spatiotemporal statistical analysis using COVID-19 case data from Malawi recorded from 2 April 2020 to 27 March 2022. Bayesian spatiotemporal models were fitted, with weekly confirmed cases as the response variable and demographic, socioeconomic, and environmental factors as predictors. ResultsThe findings reveal that spatial and temporal factors, along with age, population density, and poverty, significantly affect observed COVID-19 incidence in Malawi, whereas precipitation does not. The greatest risk was observed during colder months (June-July), Decembers festive season, and January. Urban centres and lake-shore districts were disproportionately impacted, with individuals aged 40 - 49 at particularly high risk. ConclusionsThese results emphasise the need to prioritise vaccinations for working-age populations in urban and tourist areas during high-risk periods. Moreover, ensuring adherence to public health guidelines and enhancing healthcare services in these districts is critical. Key MessagesO_LIThe age group 40-49 faced a significantly higher risk of COVID-19 compared to all other age groups. C_LIO_LICOVID-19 risk is generally low across Malawi during the study period, with Blantyre being a notable exception. C_LIO_LIPositive associations were identified between COVID-19 risk and factors such as age, poverty levels, and population density. C_LIO_LIBoth spatial and temporal dynamics were found to have substantial impacts on COVID-19 transmission risk. C_LI