STAR: Eco-Evolutionary Drivers of Viral Spillover: Integrating Long-Term Data and Scientific Collections

Many infectious diseases affecting humans are caused by viruses, which naturally circulate in wildlife before “spilling over” to people. Scientists still do not fully understand why some viruses stay confined to wildlife while others spread to humans causing outbreaks that evolve to epidemics. This lack of understanding limits our capacity to prevent future disease outbreaks. This project will uncover underlying factors that drive spillover events from wildlife to humans. Specifically, the project will examine how long-term evolutionary relationships between wildlife and their viruses and environmental conditions, influence spill over to humans. By combining large-scale global data with detailed local observations collected through the NSF National Ecological Observatory Network (NEON), this project improve the predictability of disease emergence. The project’s contributions include advancing coevolutionary theory by incorporating multi-host dynamics, producing a modeling framework applicable to other zoonotic systems. This will in turn provide broader impacts by improving the ability to predict disease spillover and inform public health strategies through better understanding of zoonotic disease transmission and viral diversity. Stakeholder training and workshops as well as development of undergraduate curricula will ensure that those insights are disseminated. This NSF STAR project seeks to advance evolutionary understanding of zoonotic spillover by integrating the evolutionary histories of orthohantaviruses and their rodent hosts using data and samples from the NEON. The project’s goal is to develop a unified eco-evolutionary framework that explains how interactions among hosts, viruses, and environmental conditions drive viral diversification, transmission, and human disease outcomes. Traditional models focus on one-host and one-pathogen analyses. This project will employ a community-level perspective that incorporates primary and secondary hosts and environmental context to explain why pathogen prevalence in wildlife often does not align with human disease incidence. The scope includes both global (macroevolutionary) and local (landscape-level) analyses, focusing on the rodent-orthohantavirus system in the US as a model for studying multi-host pathogen dynamics and spillover risk. To achieve these goals, the project will combine bioinformatics, ecological modeling, and laboratory virology. It will construct time-calibrated phylogenies for hosts and viruses using Bayesian methods and develop a generative modeling framework to quantify how phylogenetic relatedness and environmental similarity shape host-virus interactions and viral evolution. Ecological niche modeling will incorporate climate and species distribution data, while laboratory analyses of NEON rodent samples will use PCR and next-generation sequencing to identify circulating viral species. These data will be integrated with spatial and statistical analyses to examine relationships between wildlife infection patterns and human disease cases. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.