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Abstract
This dissertation presents three analyses that leverage genomic data from human, animal, and wastewater surveillance to study the evolution, epidemiology, and ecology of circulating and emerging viruses with significant public health implications. We focus on epidemics and epizootics, with SARS-CoV-2 and raccoon rabies virus (RRV) as case studies. Each manuscript uses viral sequence data from clinical specimens to reconstruct viral evolutionary history in a Bayesian phylogenetic framework. We incorporate host and location data into evolutionary models via phylogenetic discrete trait analyses, allowing the analysis of viral spread among hosts and geographic areas, in addition to drivers of spatial diffusion. To address gaps in clinical surveillance, we incorporate wastewater data, which has re-emerged as a critical tool during the COVID-19 pandemic for population-wide monitoring. This dissertation develops analytical pipelines that integrate genomic, epidemiological, and ecological data—including host, location, landscape features, wastewater-derived genomes, case counts, and student movement—to study epidemic dynamics and inform public health decision-making. Chapter 2 examines the role of rivers as natural barriers for RRV gene flow and spatial diffusion in Connecticut, which can inform rabies control efforts such as oral rabies vaccine distribution. We also characterize spillover events, cross-border incursions, long distance translocation events, and key sources and sinks in eastern North America to identify high-priority areas for enhanced surveillance. Chapter 3 investigates the transmission dynamics of the SARS-CoV-2 Delta variant in Georgia, identifying geographic sources and sinks of transmission to guide resource allocation and prepare for future epidemics for at-risk populations. We also characterize the number and timing of introduction events, subsequent local circulation, and detection lags to inform outbreak investigation and response, including targeted contact tracing and testing.
Chapter 4 evaluates the strengths and limitations of wastewater data in monitoring the emergence and dynamics of SARS-CoV-2 variants (Alpha, Delta, and Omicron) in Clarke County, Georgia. By incorporating wastewater data into spatial transmission models, we highlighted the role of student movement events in viral expansion, increased transmission, and case surges. Together, these studies demonstrate the power of integrating genomic, epidemiological, and ecological data to advance viral surveillance, improve epidemic response, and support public health action.