Pathogen Transmission Dynamics among Wildlife and Human Settlements in Rural Western Uganda

Emerging diseases are a growing global problem, and wildlife pathogens are the principal source of disease. Human encroachment and climate change are increasing interactions between wildlife and human communities, leading to greater zoonotic and epizootic spillover. The genetic similarity of humans and non-human primates (NHPs) provides an opportunity for viruses to impact both human and animal populations, especially in areas where contact is continuing to increase. Notable knowledge gaps persist concerning the dynamics and likely routes of viral transmission within such heterogeneous natural environments. Here, we examine a model pathogen, adenovirus (AdV), common to humans, NHPs, and many other hosts and sources, to determine and model transmission routes in an interconnected biodiversity hotspot in East Africa. We will apply next-generation DNA sequencing, combined with demographic data and advanced phylogenetic analysis techniques, to identify likely transmission pathways and to model host factors and interactions affecting viral transmission. Our four main objectives are to: 1) Obtain fine-grained, longitudinal surveillance data on AdV from wild NHPs, domestic animals, flies, ticks, dung beetles, water, and soil in a natural, heterogeneous spi llover hotspot; 2) Apply advanced phylogenetic and bioinformatics tools to next-generation sequencing (NGS) data for the presence, abundance, variation and routes of transmission of AdV within and among hosts and environs; 3) Identify source factors impacting viral transmissi on, e.g., host or source type, proximity, density, other viruses and pathogens, host evolutionary relationships; 4) Develop prediction models of how factors (e.g., host species,, phylogeny, proximity, source) influence viral transmission routes, with the ultimate aim to inform mitigation efforts regarding disease transmission for the benefit of human and animal health. By focusing on a common, prevalent virus like AdV, we can identify, quantify, model, and ultimately predict key aspects of viral transmission and the factors affecting spillover in complex natural environments, which will be applicable for understanding and preventing disease transmission more broadly. In addition, this research builds capacity and supports broader African and U.S. genomic and biostatistics training. The knowledge gained will be instrumental for policy decision-making to prevent and mitigate zoonotic and anthroponotic disease outbreaks and improving quality of life with conservation and oublic health benefits. RELEVANCE (See Instructions): Results from our surveillance sampling, AdV phylodynamics, advanced computational tools and predictive transmission Is will provide knowledge of disease transmission in a spillover hotspot. Our protocol will demonstrate how tools and predictive models will provide knowledge of disease transmission pathways in complex environments. The proposed work will enable future research targeting dangerous but rarepathogens, such as single-stranded RNA viruses of zoonotic origin (e.g., Ebola). Transmission d ynamics of viral pathogens will inform proactive health and conservation policies to i reduce cross-species disease transmission at a time of increasing climate change and human-wildlife ntc, r-~r+innc