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Sci Data
. 2026 Feb 3.
doi: 10.1038/s41597-026-06701-w. Online ahead of print.
A global dataset of spatiotemporal co-occurrence patterns of avian influenza virus-associated migratory birds
Jun Ma # 1 2 , Yan-He Wang # 3 , Yun-Bo Qiu # 1 2 , Jin-Jin Chen 2 4 , Yun Han 1 2 , Yan Zhang 2 , Sheng-Hong Lin 2 , Qing-Jie Wang 1 2 , Long-Tao Chen 1 2 , Xin-Jing Zhao 2 , Sheng Zhang 1 2 , Tian Tang 2 , Yao Tian 2 , Yu-Feng Yang 2 , Qiang Xu 2 , Zi-Da Meng 2 , Chen-Long Lv 2 , Guo-Lin Wang 2 , Feng Hong 5 , Li-Qun Fang 6 7
Affiliations
Migratory birds facilitate the cross-regional spread of pathogens such as avian influenza virus (AIV). Interspecies interactions among multiple migratory bird species within shared spatiotemporal habitats can substantially enhance pathogen transmission and evolution, thereby posing potential risks to public health and livestock safety. Recent advances in tracking technologies, such as GPS, combined with publicly accessible databases like Movebank, have enabled the reconstruction of avian migratory pathways. However, existing tracking data are largely collected from individual species, remain species-specific and are insufficient for characterizing interspecies contact during migration. By integrating available tracking data from 62 migratory bird species (comprising 3,944 individual records), this study constructed a co-occurrence dataset comprising 50 migratory bird species that exhibited spatial and temporal overlap at shared locations, with a daily temporal resolution and spatial resolution aligned with first-level administrative divisions. This dataset can facilitate the identification of potential hotspots for migratory bird-associated pathogen evolution, thereby providing data-driven support for the prevention and control of emerging infectious diseases.
. 2026 Feb 3.
doi: 10.1038/s41597-026-06701-w. Online ahead of print.
A global dataset of spatiotemporal co-occurrence patterns of avian influenza virus-associated migratory birds
Jun Ma # 1 2 , Yan-He Wang # 3 , Yun-Bo Qiu # 1 2 , Jin-Jin Chen 2 4 , Yun Han 1 2 , Yan Zhang 2 , Sheng-Hong Lin 2 , Qing-Jie Wang 1 2 , Long-Tao Chen 1 2 , Xin-Jing Zhao 2 , Sheng Zhang 1 2 , Tian Tang 2 , Yao Tian 2 , Yu-Feng Yang 2 , Qiang Xu 2 , Zi-Da Meng 2 , Chen-Long Lv 2 , Guo-Lin Wang 2 , Feng Hong 5 , Li-Qun Fang 6 7
Affiliations
- PMID: 41634014
- DOI: 10.1038/s41597-026-06701-w
Migratory birds facilitate the cross-regional spread of pathogens such as avian influenza virus (AIV). Interspecies interactions among multiple migratory bird species within shared spatiotemporal habitats can substantially enhance pathogen transmission and evolution, thereby posing potential risks to public health and livestock safety. Recent advances in tracking technologies, such as GPS, combined with publicly accessible databases like Movebank, have enabled the reconstruction of avian migratory pathways. However, existing tracking data are largely collected from individual species, remain species-specific and are insufficient for characterizing interspecies contact during migration. By integrating available tracking data from 62 migratory bird species (comprising 3,944 individual records), this study constructed a co-occurrence dataset comprising 50 migratory bird species that exhibited spatial and temporal overlap at shared locations, with a daily temporal resolution and spatial resolution aligned with first-level administrative divisions. This dataset can facilitate the identification of potential hotspots for migratory bird-associated pathogen evolution, thereby providing data-driven support for the prevention and control of emerging infectious diseases.