RESEARCH SPOTLIGHT: Predicting the Spread of Highly Pathogenic Avian Influenza Virus Using Animal Movement Data
A recent study published in the journal Transboundary and Emerging Diseases uses GPS tracking data from wild waterfowl to predict the location and timing of the highly pathogenic avian influenza virus (HPAIv) spread across North America in 2022.
Status of HPAIv
Understanding the timing and distribution of virus spread is critical for global commercial and wildlife biosecurity management. The current global HPAIv panzootic poses a serious threat to animals and public health, having affected approximately 600 bird and mammal species globally and over 83 million birds across North America as of December 2023. Of particular concern is the transmission of the virus to mammals, including the recent discovery of infections in dairy cattle in the U.S. and the detection of HPAIv in milk, posing a significant human health concern.
While previous studies linked bird migrations to avian flu outbreaks at poultry farms, only one earlier study by USGS authors predicted the virus could spread to cattle. It found wild waterfowl moving between natural wetlands and cattle facilities, likely attracted to supplemental water and food sources when natural resources dwindled along the Pacific Flyway.
Predictive Models & Key Findings
The study combined extensive, long-term GPS tracking data from 16 species of wild waterfowl across North America with on-ground, county-level HPAIv surveillance data to understand the overlap of waterfowl and HPAIv detections. The researchers were also able to predict future outbreaks in counties and provincial areas through bird movements using a novel empirical SI (Susceptible-Infected) model, similar to the SIR (Susceptible-Infected-Recovered) model used to model COVID disease dynamics, via exposed migratory waterfowl.
The SI model projected exposure of up to 100% of birds via ‘outbreak’ exposure in counties with HPAIv occurrence during spring migration, except for Pacific flyway birds, which were predicted to experience widespread arrival of HPAIv via ‘birdbird’ exposure (up to 100%) during fall migration. The SI model accurately predicted HPAIv arrival in all flyways by migratory waterfowl, raptors, and ‘other’ birds but was a lagging indicator for commercial facilities, Pelicans, and resident waterfowl/captive species in the Pacific flyway.
Management Implications
- Accurately predicting the location and timing of animal-borne disease spread, can prevent further outbreaks in animals, including humans, by strategically prioritizing risk management, monitoring and biosecurity in vulnerable areas.
- Tracking pathways of disease introduction or exposure provides a better opportunity to enhance early detection and rapid response for managing HPAIv and disease risk.
- Combining animal movement studies and disease surveillance in predictive models may be the most powerful tool to presage disease spread and get ahead of outbreaks
Looking Forward
The study suggests that current tracking efforts are not sufficient to effectively predict disease spread, as evidenced by the lack of consistency with the established understanding of HPAIv dynamics, particularly in Pelicans. The development of a proactive, consistent, and taxonomically diverse telemetry-based wildlife monitoring program could enhance surveillance and risk management of zoonotic viruses that threaten wildlife and human health. A system called AIMS for Wildlife has been described by USGS scientists and makes large-scale animal movement data streams combined with environmental and other data available in near real-time to wildlife managers to promote true adaptive management.
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