Location: Geospatial and Environmental Epidemiology Research Unit
Project Number: 6064-32000-001-012-A
Project Type: Cooperative Agreement
Start Date: Jul 1, 2026
End Date: Jun 30, 2030
Objective:
Conduct research to apply advanced computation, epidemiological, and environmental modeling approaches towards development of disease transmission and forecasting models for poultry, cervids, and catfish. Specific research objectives include:
1. Develop and refine models that predict how highly pathogenic avian influenza (HPAI) can spread to poultry farms.
o Completing a system dynamics model informed by industry input to estimate infection risk for commercial egg layer operations.
o Expanding studies of how multiple wildlife and insect species interact near poultry facilities and may contribute to disease movement.
o Improving and validating computational fluid dynamics (CFD) models to better predict how airborne particles move in and around poultry houses, with emphasis on HPAI transport.
o Advancing models that assess how aerosolized HPAI may travel in air plumes.
o Creating next generation modeling tools that help producers rapidly detect, respond to, and reduce HPAI risk.
2. Improve spatial prediction tools for chronic wasting disease (CWD) by refining risk maps for priority states and evaluating how different management actions may change disease transmission.
3. Build high resolution models of disease transmission risks associated with vectors in catfish aquaculture systems.
4. Develop flexible, rapid response disease transmission models for other producer identified priority diseases to support GEERU’s broader mission.
Approach:
Development of disease-transmission models at local, state, and regional scales will be advanced using a combination of computational, geospatial, and epidemiological methods. This work will employ system-dynamics modeling as the central framework for describing transmission pathways and associated risks, supported by environmental data and information on vector activity. In parallel, new efforts will focus on integrating weather, wildlife, and other real-time data streams to increase the accuracy and applicability of these models across broader geographic regions.