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

Area of Science:

• Veterinary Science
• Epidemiology
• Wildlife Ecology

Background:

• Global biosecurity management requires understanding virus spread timing and distribution.
• Highly pathogenic avian influenza virus (HPAIv) poses a significant threat to animal and public health, impacting numerous species worldwide.

Purpose of the Study:

• To develop an empirical model evaluating spatiotemporal exposure and predicting HPAIv spread via migratory waterfowl.
• To provide advance warning for biosecurity management and planning.

Main Methods:

• Combined a large, long-term waterfowl GPS tracking dataset (16 species) with on-ground disease surveillance data (county-level HPAIv detections).
• Developed a novel empirical model to evaluate spatiotemporal exposure and predict HPAIv spread.

Main Results:

• The model effectively predicted HPAIv spread in wild waterfowl.
• Model predictions lagged HPAIv detections in poultry facilities and some nonmigratory species.

Conclusions:

• Extensive multispecies tracking is crucial for identifying high-risk disease spread locations.
• The developed model offers critical advance warning for applied biosecurity management and outbreak control.