Avian influenza H5N1 subtype has caused a global public health concern due to its high pathogenicity in poultry and high case fatality rates in humans. The recently emerged H7N9 is a growing pandemic risk due to its sustained high rates of human infections, and recently acquired high pathogenicity in poultry. Here, we used Bayesian phylogeography on 265 H5N1 and 371 H7N9 haemagglutinin sequences isolated from humans, animals and the environment, to identify and compare migration patterns and factors predictive of H5N1 and H7N9 diffusion rates in China. H7N9 diffusion dynamics and predictor contributions differ from H5N1. Key determinants of spatial diffusion included: proximity between locations (for H5N1 and H7N9), and lower rural population densities (H5N1 only). For H7N9, additional predictors included low avian influenza vaccination rates, low percentage of nature reserves and high humidity levels. For both H5N1 and H7N9, we found viral migration rates from Guangdong to Guangxi and Guangdong to Hunan were highly supported transmission routes (Bayes Factor > 30). We show fundamental differences in wide-scale transmission dynamics between H5N1 and H7N9. Importantly, this indicates that avian influenza initiatives designed to control H5N1 may not be sufficient for controlling the H7N9 epidemic. We suggest control and prevention activities to specifically target poultry transportation networks between Central, Pan-Pearl River Delta and South-West regions.
Highly pathogenic avian influenza (HPAI) viruses of the H5N1 subtype are a major concern to human and animal health in Indonesia. This study aimed to characterize transmission dynamics of H5N1 over time using novel Bayesian phylogeography methods to identify factors which have influenced the spread of H5N1 in Indonesia. We used publicly available hemagglutinin sequence data sampled between 2003 and 2016 to model ancestral state reconstruction of HPAI H5N1 evolution. We found strong support for H5N1 transmission routes between provinces in Java Island and inter-island transmissions, such as between Nusa Tenggara and Kalimantan Islands, not previously described. The spread is consistent with wild bird flyways and poultry trading routes. H5N1 migration was associated with the regions of high chicken densities and low human development indices. These results can be used to inform more targeted planning of H5N1 control and prevention activities in Indonesia.
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