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Wild waterbirds, and especially wild waterfowl, are considered to be a reservoir for avian influenza viruses, with transmission likely occurring at the agricultural-wildlife interface. In the past few decades, avian influenza has repeatedly emerged in China along the East Asian-Australasian Flyway (EAAF), where extensive habitat conversion has occurred. Rapid environmental changes in the EAAF, especially distributional changes in rice paddy agriculture, have the potential to affect both the movements of wild migratory birds and the likelihood of spillover at the agricultural-wildlife interface. To begin to understand the potential implications such changes may have on waterfowl and disease transmission risk, we created dynamic Brownian Bridge Movement Models (dBBMM) based on waterfowl telemetry data. We used these dBBMM models to create hypothetical scenarios that would predict likely changes in waterfowl distribution relative to recent changes in rice distribution quantified through remote sensing. Our models examined a range of responses in which increased availability of rice paddies would drive increased use by waterfowl and decreased availability would result in decreased use, predicted from empirical data. Results from our scenarios suggested that in southeast China, relatively small decreases in rice agriculture could lead to dramatic loss of stopover habitat, and in northeast China, increases in rice paddies should provide new areas that can be used by waterfowl. Finally, we explored the implications of how such scenarios of changing waterfowl distribution may affect the potential for avian influenza transmission. Our results provide advance understanding of changing disease transmission threats by incorporating real-world data that predicts differences in habitat utilization by migratory birds over time.
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Landscape changes elevate the risk of avian influenza virus diversification and emergence in the East Asian–Australasian Flyway
Highly pathogenic avian influenza viruses (HPAIV) persistently threaten wild waterfowl, domestic poultry, and public health. The East Asian–Australasian Flyway plays a crucial role in HPAIV dynamics due to its large populations of migratory waterfowl and poultry. Over recent decades, this flyway has undergone substantial landscape changes, including both losses and gains of waterfowl habitats. These changes can affect waterfowl distributions, increase contact with poultry, and consequently alter ecological conditions that favor avian influenza virus (AIV) evolution. However, limited research has assessed these likely impacts. Here, we integrated empirical data and an individual-based model to simulate AIV transmission in migratory waterfowl and domestic poultry, including wild-to-poultry spillover and reassortment dynamics in poultry, across landscapes representing the years 2000 and 2015. We used the reassortment incidence as a proxy for ecological and transmission conditions that support viral diversification and the emergence of novel subtypes. Our simulations show that landscape change reshaped the waterfowl distribution, facilitated bird aggregation at improved habitats, increased coinfection, and raised reassortment rate by 1,593%, indicating a substantially higher potential for viral diversification and emergence. Model-generated risk maps show expanded and increased reassortment risk in southeastern China, the Yellow River Basin, and northeastern China. These findings suggest the importance of landscape change as a driver of potential AIV diversification and subtype emergence. This underscores the need for interdisciplinary approaches that integrate landscape dynamics, host movement, and viral evolution to better assess and mitigate future risk.
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- Award ID(s):
- 2200310
- PAR ID:
- 10661939
- Publisher / Repository:
- PNAS
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 122
- Issue:
- 34
- ISSN:
- 0027-8424
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1073/pnas.2503427122
