An accurate estimate of the burden and characterization of the transmission dynamics of influenza type A virus is one of the most important health issues globally. Influenza A viruses (IAVs) present as highly evolving pathogens giving rise to highly pathogenic and zoonotic strains, which have greatly affected both poultry and human health.  Modern advancements in sequencing platforms have enabled deep sequencing of influenza viral genomes on which phylogenetic-based and mathematical modelling techniques have been applied to understand the viral evolution and phylodynamics. Mathematical models have also been utilised to predict environmental factors driving viral spread within and across hosts species.

However, these methods have been successfully utilized mostly in resource-rich countries where enough influenza data have been obtained. The scarcity in long-term viral epidemiological and sequence data collected across Africa has limited the number of studies on influenza transmission in African populations. The only few existing studies are sparsely spread across the continent. These bottlenecks have blurred our knowledge about the scope of influenza burden, transmission patterns and risk factors associated with its spread across Africa.

This project aims to; adopt and apply bioinformatics, phylogenetic and computational analysis tools on publicly available African human and avian influenza sequence datasets (n=1,367, collected between 1994-2018) to characterise viral transmission patterns and estimate epidemic parameters across Africa. The project will also utilise locally stored Ugandan human influenza samples (n=200, collected between 2010-2018) to generate new viral sequences which will be availed in online databases for future studies.

The project results will update our knowledge about the burden, patterns of transmission and risk factors associated with influenza epidemics and pandemics on both the Ugandan and African scale. This knowledge is crucial for the establishment of effective intervention strategies and pandemic management.