Understanding the role that feral swine populations and their habitat play in ASF virus epidemiology has been limited, resulting in a lack of known effective ASF response measures in this north…

Understanding the role that feral swine populations and their habitat play in ASF virus epidemiology has been limited, resulting in a lack of known effective ASF response measures in this north american feral swine population. The risk of an ASF incursion in feral swine becoming endemic, as IT has in several other countries, is a very real threat to the US feral and domestic swine herd. To rapidly and efficiently address a potential ASF incursion in feral swine, their movements and population dynamics must be more thoroughly investigated and understood. Current prevention, detection, and response planning for an asfv incursion, at a state and national level, have been limited based on knowledge gaps in feral swine population dynamics, specifically population distribution, density, and connectivity of subpopulations. These data sets are necessary to develop models that forecast disease spread and assess public policies and guide disease control efforts. These datasets will come from source populations of feral swine in two river basins, the yadkin-PEE DEE and the cape fear, where a combination of growing feral swine populations, ongoing evidence of disease in feral populations, and the high density of commercial swine facilities further amplify the threat that feral swine pose to the state economy, as well as and the national pork industry. This project will determine population density metrics and movement parameters of feral swine through camera trapping with appropriate analytical algorithms. This information will be combined with GPS and GIS monitoring of collared feral swine to produce population connectivity metrics. The overall model, report, and resources will be shared with animal health officials in both our state and neighboring states, tennessee and south carolina, to enhance regionwide response planning, develop models that forecast disease spread and prepare for the arrival of large-scale diseases like ASF in a harmonized way.