Phylodynamic analysis of the highly pathogenic avian influenza H5N8 epidemic in France, 2016-2017

TRANSBOUNDARY AND EMERGING DISEASES(2022)

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Abstract
In 2016-2017, France experienced a devastating epidemic of highly pathogenic avian influenza (HPAI) H5N8, with more than 400 outbreaks reported in poultry farms. We analyzed the spatiotemporal dynamics of the epidemic using a structured-coalescent-based phylodynamic approach that combined viral genomic data (n = 196; one viral genome per farm) and epidemiological data. In the process, we estimated viral migration rates between departements (French administrative regions) and the temporal dynamics of the effective viral population size (Ne) in each departement. Viral migration rates quantify viral spread between departements and Ne is a population genetic measure of the epidemic size and, in turn, is indicative of the within-departement transmission intensity. We extended the phylodynamic analysis with a generalized linear model to assess the impact of multiple factors-including large-scale preventive culling and live-duck movement bans-on viral migration rates and Ne. We showed that the large-scale culling of ducks that was initiated on 4 January 2017 significantly reduced the viral spread between departements. No relationship was found between the viral spread and duck movements between departements. The within-departement transmission intensity was found to be weakly associated with the intensity of duck movements within departements. Together, these results indicated that the virus spread in short distances, either between adjacent departements or within departements. Results also suggested that the restrictions on duck transport within departements might not have stopped the viral spread completely. Overall, we demonstrated the usefulness of phylodynamics in characterizing the dynamics of a HPAI epidemic and assessing control measures. This method can be adapted to investigate other epidemics of fast-evolving livestock pathogens.
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Key words
emerging infectious diseases, modelling infectious disease dynamics, outbreak analytics, reconstruction of viral transmission, virus evolution, virus molecular epidemiology
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