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bioRxiv · 10.64898/2026.05.30.728949

Data gaps of international databases on HPAI H5 in wildlife in the Americas: implications for surveillance, research, and conservation

Abstract

Global efforts to prevent and mitigate the impacts of high pathogenicity avian influenza (HPAI) H5 on domestic animals, humans, and wildlife rely on timely and transparent information that is both accurate and interpretable across countries and sectors. International epidemiological and genomic databases, such as the World Animal Health Information System (WAHIS), the Global Animal Disease Information System (EMPRES-i+), the Global Initiative on Sharing All Influenza Data (GISAID), and the National Center for Technological Bioinformation Virus Portal (NCBI) provide essential information for surveillance, research, and decision-making. To evaluate how well these resources capture recent wildlife impacts, we consolidated information from these databases and complementary public sources including government reports, scientific literature, and news articles, on wildlife mortality associated with HPAI H5 in the Americas from November 2021 to July 2024. The consolidated dataset comprised 615,883 wild birds (287 spp.) and 63,409 wild mammals (39 spp.). In comparison, WAHIS represented 16,902 wild birds (261 spp.) and 6,323 wild mammals (31 spp.) while EMPRES-i+ captured a substantially smaller portion of affected host diversity for both wild birds (105 spp.) and wild mammals (27 spp.). Genomic databases (GISAID and NCBI) represented 7,027 whole genome equivalents of H5 viruses from wild birds (175 spp.) and 371 from wild mammals (26 spp.). These discrepancies indicate that international databases, while essential, provide an incomplete picture of HPAI impacts on wildlife, with significant geographic and taxonomic asymmetries attributable to differences in surveillance capacity, reporting practices, sequencing effort, and data-sharing pathways. Studies and management strategies relying on these resources without complementary validation may therefore mistake data gaps for real-world epidemiological patterns. Strengthening data reporting standards, improving validation procedures, and integrating international databases with national reports, scientific publications, and other sources will enhance the reliability of epidemiological analyses and support more effective One Health surveillance, risk assessment, and conservation action. Author summaryHigh pathogenicity avian influenza (HPAI) H5 viruses, often called bird flu viruses, can cause severe disease in birds and mammals, including humans. Because of their relevance for human health, livestock production, and wildlife conservation, international databases were established to share information on when and where these viruses are detected, which species are affected, and what virus strains are found. These databases are essential tools for governments, scientists, and conservation practitioners working to track outbreaks, understand how these viruses spread and evolve, and guide surveillance and response. In this study, we compiled and compared information on recent HPAI H5 events in wildlife in the Americas available in international databases with information from other public sources, including reports from governments, scientific literature, and news articles. We found important discrepancies in how countries and species affected were represented across sources. As a result, international databases might not fully capture the actual distribution or conservation impact of HPAI H5 on wildlife. Our findings also show why decision-makers and scientists should interpret database-derived patterns carefully. We provide recommendations to improve international databases to address these gaps and better inform One Health risk assessment and wildlife conservation actions.

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BibTeXRIS

Vanstreels, R. E. T., Uhart, M. M.. 2026-06-01. Data gaps of international databases on HPAI H5 in wildlife in the Americas: implications for surveillance, research, and conservation. https://doi.org/10.64898/2026.05.30.728949

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