Risk assessment of the transmission of HPAI-H5 in wild birds in the United States based on spatio-temporal distribution and climate change

Risk assessment of the transmission of HPAI-H5 in wild birds in the United States based on spatio-temporal distribution and climate change | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Risk assessment of the transmission of HPAI-H5 in wild birds in the United States based on spatio-temporal distribution and climate change Tianmu Chen, Kang Fang, Jiahui Li, Hongfeng Zhao, Jiangshaya Bahati, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6867192/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Feb, 2026 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Wild birds play a significant role in the cross-species transmission of avian influenza. This study evaluates the transmission patterns of HPAI-H5 in wild birds from multiple aspects. Transmission capabilities of different orders were estimated through generational transmission and exponential growth models. The STL decomposition was used to analyze the seasonality and trend of its transmission. Spatial analysis revealed the spatiotemporal distribution characteristics of avian influenza in wild birds. Combined with meteorological data, machine learning models were used to analyze the impact of meteorological factors on wild bird infections. From 2022 to 2025, a total of 12,808 H5-infected wild bird samples were collected. The basic reproduction number (R 0 ) revealed the strongest transmission capacity in Strigiformes (R 0 = 3.164 (95% CI: 2.711–3.726)) and the weakest in Anseriformes (R 0 = 0.992 (95% CI: 0.990–0.994)). The number of infections in autumn and winter was twice that in spring and five times that in summer. Spatial analysis showed significant spatial autocorrelation during migratory bird seasons, with coastal areas, Central and Pacific migratory bird route areas being the main hotspots. Since 2022, the number of H5 infections in wild birds in the United States has gradually declined, but seasonality persists. H5 infections in wild birds are closely tied to migratory bird movements, with migration routes and coastal areas being key areas for prevention and control. While the transmission capacity of H5 among migratory birds is relatively weak, it is stronger in Strigiformes. Meteorological factor analysis indicated non-linear relationships in avian influenza infection. Surveillance of avian influenza in wild birds should be strengthened, and contact between wild birds and other animals should be reduced to prevent its transmission among animals. Biological sciences/Ecology/Animal migration Earth and environmental sciences/Environmental sciences/Environmental impact Earth and environmental sciences/Ecology/Animal migration Wild bird Highly pathogenic H5 Transmission risk assessment Climate change Machine learning Spatio-temporal distribution characteristics Full Text Additional Declarations There is NO Competing Interest. Supplementary Files ReportingSummary.pdf Reporting Summary nrsoftwarepolicy.pdf Software Policy checklist Cite Share Download PDF Status: Published Journal Publication published 09 Feb, 2026 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6867192","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":478501095,"identity":"7a45c1f3-1b7b-44f8-905b-7c3fbb5354a5","order_by":0,"name":"Tianmu 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