Synchrony of Bird Migration with Global Dispersal of Avian Influenza Reveals Exposed Bird Orders

Since 2014, highly pathogenic avian influenza viruses (HPAIVs) subtype H5, especially clade 2.3.4.4, have caused widespread outbreaks in domestic poultry and wild birds, with occasional spillover to humans. Unlike previous clades, clade 2.3.4.4 exhibits more persistent spillovers to poultry and higher mortality in diverse wild bird species. While human-to-human transmission hasn't been observed, zoonotic jumps pose a significant public health threat. The global spread of HPAIVs is attributed to the live poultry trade and wild bird migration. Clade 2.3.2.1, endemic in Asia, spread across Eurasia and Africa, demonstrating a link between long-distance viral dispersal and wild bird migration. Clade 2.3.4.4's global dispersal provides further evidence of migratory birds' crucial role. This clade showed lower pathogenicity but higher transmissibility in some species, potentially facilitating intercontinental spread. Previous phylogenomic work supported the introduction of clade 2.3.4.4 into Europe and North America via long-distance migration. Challenges in studying HPAIV dispersal include insufficient bird movement data and a lack of HPAIV prevalence data. Existing studies are often limited by regional scope or taxonomic focus, highlighting the need for a global-scale approach integrating bird behavior, life history, and viral genomics. This research addresses how seasonal bird migration facilitates viral dispersal and identifies bird orders exposed to HPAIV H5 at various geographical locations. The study uses site-scaled phylogeographic analyses of HPAIV H5 clades 2.3.4.4 and 2.3.2.1 HA genes, along with species distribution models based on bird tracking data and environmental factors, to examine this.

The literature extensively documents the role of migratory birds in the global spread of avian influenza viruses. Studies have shown correlations between viral dispersal patterns and migratory routes of various bird species. However, a comprehensive understanding of the interplay between migratory patterns, virus evolution, and host susceptibility across different bird orders remains limited. Previous research has focused primarily on Anseriformes, while the roles of other bird orders in avian influenza dynamics are less understood. Studies analyzing the contribution of the live poultry trade to the spread of the virus have also been conducted, but they often lack the detailed spatial resolution needed to fully characterize its impact. Additionally, while the importance of bird migration has been emphasized, the precise mechanisms by which migration facilitates viral spread and the specific species and regions most critical for transmission remain active areas of investigation.

This study employed a combination of phylogenetic and ecological approaches to investigate the relationship between bird migration and the global dispersal of HPAIV H5. First, time-scaled maximum clade credibility (MCC) trees were constructed for HPAIV H5 clades 2.3.4.4 and 2.3.2.1 using hemagglutinin (HA) gene sequences obtained from GISAID. Discrete trait phylogeography was performed to infer virus lineage movements between aggregated regions. Generalized linear models (GLMs) with Bayesian model selection were used to quantify the contributions of seasonal bird migration and yearly poultry population size to inter-regional HPAIV H5 dispersal. To model monthly geographical distributions of bird orders, species distribution models (SDMs) were built based on environmental factors and bird tracking data from Movebank. The risk of bird exposure to HPAIV H5 was evaluated by analyzing the statistical association between local bird distributions and virus lineage migration routes, using block bootstrapping to assess statistical significance of correlations between bird migration patterns and viral dispersal timing. The analysis included the construction of a bird migration network summarizing migration data from Movebank, integrating this network into the viral phylogeographic reconstruction to directly assess the contribution of bird migration to HPAIV dispersal. Time-resolved phylogenies were estimated using the Markov chain Monte Carlo (MCMC) approach in BEAST v1.10.4 with various models. Finally, the synchrony of bird migration and virus lineage movements was analyzed by correlating monthly time series of virus lineage movement frequency and bird order distribution probability using Pearson’s correlation and block bootstrapping.

The study found strong evidence linking seasonal bird migration to the global dispersal of HPAIV H5 clade 2.3.4.4. Phylogeographic analyses showed that inter-regional viral introductions occurred more frequently after 2018, suggesting increased dispersal between regions. GLM analyses demonstrated that seasonal bird migration was a significantly better predictor of HPAIV H5 dispersal than poultry population size or live poultry trade. The analysis of virus lineage movements revealed a synchrony between the seasonality of bird migration and virus dispersal, with northward movements coinciding with spring migration and southward movements with autumn migration. The study identified specific bird orders significantly correlated with virus lineage movement along various routes. For example, the southern migration of Ciconiiformes from Europe synchronized with more frequent viral dispersal from Europe to Africa, and the northern migration of Pelicaniformes from Japan/Korea synchronized with more frequent viral dispersal from Japan/Korea to Russia. Before 2018, Anseriformes and Accipitriformes were identified as exposed bird orders in Asia. The study highlighted the potential exposure risks of various bird orders, including relatively under-studied groups like Passeriformes, emphasizing the need for broader consideration of avian hosts in avian influenza research. The temporal patterns of virus dispersal also varied among clades, with clade 2.3.4.4 showing a stronger seasonal bias than clade 2.3.2.1. The observed differences may suggest that clade 2.3.4.4 is more endemic in wild birds than clade 2.3.2.1.

This study provides robust evidence supporting the crucial role of wild bird migration in the global dissemination of HPAIV H5, particularly clade 2.3.4.4. By directly integrating bird migration network data into the phylogeographic analysis, the study goes beyond previous correlative studies, providing stronger support for the causal link between bird movement and virus spread. The identification of specific bird orders associated with virus dispersal highlights the importance of considering a broader range of avian hosts in future avian influenza research. The findings emphasize the need for more comprehensive surveillance efforts, particularly targeting under-studied bird orders and regions with limited sampling. The seasonal patterns observed in virus dispersal underscore the importance of incorporating temporal dynamics into epidemiological models. The difference in seasonal patterns between clades 2.3.4.4 and 2.3.2.1 suggests potential variations in the ecological niches and transmission dynamics of different HPAIV H5 clades. This study provides a framework for integrating bird movement ecology and virological data to understand avian influenza epidemiology, which may prove valuable for predicting future outbreaks and developing targeted intervention strategies.

This study provides a robust framework for integrating avian ecology and viral genomics to understand avian influenza epidemiology. It strongly supports the role of migratory birds in disseminating HPAIV H5, identifies key bird orders exposed to the virus, and highlights the importance of considering temporal and spatial dynamics. The findings underscore the need for improved global surveillance of avian influenza in wild birds, particularly focusing on under-studied bird orders and geographic areas. Future studies should incorporate more detailed bird movement data at the species level and integrate additional viral genes to refine understanding of HPAIV evolution and transmission.

The study's conclusions are subject to several limitations. The availability of bird tracking data is limited by both species and geographical coverage, impacting the accuracy of species distribution models and the representation of avian migration networks. Virus genomic data also exhibit geographical biases, potentially affecting the inference of virus lineage movements. The analysis did not explicitly account for time lags between bird movements and viral dispersal, which may influence correlation estimates. Further research is needed to fully address these limitations and enhance the accuracy of the model. Future studies should include a larger, more comprehensive dataset of bird tracking information and viral genome sequences from diverse geographic locations.