Publication Date
1-1-2024
Document Type
Article
Publication Title
Transboundary and Emerging Diseases
Volume
2024
DOI
10.1155/2024/5525298
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.
Funding Number
2200310
Funding Sponsor
Arctic Goose Joint Venture
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Department
Moss Landing Marine Laboratories
Recommended Citation
Fiona McDuie, Cory T. Overton, Austen A. Lorenz, Elliott L. Matchett, Andrea L. Mott, Desmond A. MacKell, Joshua T. Ackerman, Susan E.W. De La Cruz, Vijay P. Patil, Diann J. Prosser, John Y. Takekawa, Dennis L. Orthmeyer, Maurice E. Pitesky, Samuel L. Díaz-Muñoz, Brock M. Riggs, Joseph Gendreau, Eric T. Reed, Mark J. Petrie, and Chris K. Williams. "Mitigating Risk: Predicting H5N1 Avian Influenza Spread with an Empirical Model of Bird Movement" Transboundary and Emerging Diseases (2024). https://doi.org/10.1155/2024/5525298
