Abstract
Since 2016, north-eastern Italy has faced recurring outbreaks of highly pathogenic avian influenza (HPAI) viruses in both poultry and wild bird populations, with changing dynamics and unpredictable patterns. This variability prompted us to explore which drivers might have influenced the viral lineage dispersal history and transmission using a Bayesian phylodynamic framework.
We analysed Italian HPAI H5N8 and H5N1 genomic sequences from the majority of notified infected wild birds and poultry farms, alongside environmental and ecological data, including raster layers of population density, elevation, vegetation indices, and land cover types. Continuous phylogeographic analyses using a relaxed random walk diffusion model implemented in BEAST 1.10, and the “seraphim” R package were employed to estimate viral lineage dispersal velocity and location and assess the impact of drivers.
Although no single variable was strongly linked with dispersal velocity, population diversity indices, land cover types related to agricultural areas and wetlands, elevation and proximity to waterbodies were associated with dispersal locations, with varying statistical support across epidemic waves.
Our findings highlight key factors influencing HPAI dispersal, although potential drivers not yet considered may still play a role, such as wild bird movements, migration patterns, and the potential spread of HPAI through biological carriers like insects or rodents (biotic means) or through contaminated water, soil, and surfaces (abiotic means). Our study underscores the value of integrating genetic and epidemiological data to achieve a comprehensive understanding of HPAI ecology, which is essential to refine prevention and response strategies.
We analysed Italian HPAI H5N8 and H5N1 genomic sequences from the majority of notified infected wild birds and poultry farms, alongside environmental and ecological data, including raster layers of population density, elevation, vegetation indices, and land cover types. Continuous phylogeographic analyses using a relaxed random walk diffusion model implemented in BEAST 1.10, and the “seraphim” R package were employed to estimate viral lineage dispersal velocity and location and assess the impact of drivers.
Although no single variable was strongly linked with dispersal velocity, population diversity indices, land cover types related to agricultural areas and wetlands, elevation and proximity to waterbodies were associated with dispersal locations, with varying statistical support across epidemic waves.
Our findings highlight key factors influencing HPAI dispersal, although potential drivers not yet considered may still play a role, such as wild bird movements, migration patterns, and the potential spread of HPAI through biological carriers like insects or rodents (biotic means) or through contaminated water, soil, and surfaces (abiotic means). Our study underscores the value of integrating genetic and epidemiological data to achieve a comprehensive understanding of HPAI ecology, which is essential to refine prevention and response strategies.
Co-Author(s)
Diletta Fornasiero1, Dr Alice Fusaro1, Dr Bianca Zecchin1, Dr Isabella Monne1, Dr Fabiana Gambaro2, Dr Simon Dellicour2,3, Grazia Manca1, Dr Mariette Ducatez4, Dr Paolo Mulatti1, Dr Claire Guinat4
1 Istituto Zooprofilattico Sperimentale delle Venezie, Viale dell'Università 10, 35020, Legnaro, Italy
2 Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium
3 Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
4 Interactions Hôtes-Agents Pathogènes (IHAP), UMR 1225, Université de Toulouse, INRAE, ENVT, Toulouse, France
Abstract Category
Notable outbreaks, field and molecular epidemiology, and surveillance in poultry