Mitigating Risk: Predicting H5N1 Avian Influenza Spread with an Empirical Model of Bird Movement

Abstract

Understanding timing and distribution of virus spread is critical to global commercial and wildlife biosecurity management. A highly pathogenic avian influenza virus (HPAIv) global panzootic, affecting ~600 bird and mammal species globally and over 83 million birds across North America (December 2023), poses a serious global threat to animals and public health. We combined a large, long-term waterfowl GPS tracking dataset (16 species) with on-ground disease surveillance data (county-level HPAIv detections) to create a novel empirical model that evaluated spatiotemporal exposure and predicted future spread and potential arrival of HPAIv via GPS tracked migratory waterfowl through 2022. Our model was effective for wild waterfowl, but predictions lagged HPAIv detections in poultry facilities and among some highly impacted nonmigratory species. Our results offer critical advance warning for applied biosecurity management and planning and demonstrate the importance and utility of extensive multispecies tracking to highlight potential high-risk disease spread locations and more effectively manage outbreaks.