Transboundary Spread and Ecological Drivers of HPAI H5N1 Clade 2.3.4.4b During the 2022–2023 Outbreak in Chile: An Integrated Genomic and Spatial Epidemiology Framework
TL;DR
Combining genomic and ecological data provides an integrated framework for risk‐based surveillance and early warning, enabling the identification of high‐risk host groups, environments, and transboundary corridors critical for anticipating and mitigating the regional spread of emerging avian influenza viruses.
Abstract
The 2022–2023 outbreak of highly pathogenic avian influenza (HPAI) H5N1 in Chile caused extensive mortality in wild birds, domestic poultry, and marine mammals, highlighting the rapid transboundary spread of this emerging pathogen in South America. However, the evolutionary and ecological processes shaping viral dissemination within Chile have remained insufficiently characterized. Here, we integrated whole‐genome sequencing, Bayesian phylogeographic analyses, and ecological modeling to reconstruct introduction routes, diversification patterns, and environmental drivers of H5N1 circulation in Chile. All analyzed genomes belonged to clade 2.3.4.4b, genotype B3.2. Phylogenetic analyses revealed multiple Chilean subclusters, including a lineage characterized by PB2 F323L and D740N substitutions and a single virus carrying the previously mammalian‐associated PB2 D701N mutation. Phylogeographic inference identified strongly supported viral movements across South America, with Argentina acting as a major regional connector. Key diffusion pathways linked Peru to Chile and revealed extensive connectivity among Argentina, Chile, Brazil, Uruguay, and the Falkland Islands, delineating three interacting transboundary transfer systems along the Pacific Coast, the Southern Cone, and the Southwest Atlantic. Within Chile, viral population structure reflected ecological segregation. Northern lineages were predominantly associated with coastal and raptor species, whereas southern lineages were mainly linked to freshwater birds. Ecological modeling showed that H5N1 detection probability in wild birds increased with temperature and relative humidity and decreased with human population density, with freshwater species exhibiting the highest infection probability. Together, these results demonstrate how integrating genomic and ecological data provides an integrated framework for risk‐based surveillance and early warning, enabling the identification of high‐risk host groups, environments, and transboundary corridors critical for anticipating and mitigating the regional spread of emerging avian influenza viruses.