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Historical and geographical patterns of new HPAIV emergences and association with spatial factors

Madhur Saharan Dhingra1*, Jean Artois1, Simon Dellicour1 and Marius Gilbert1*
  • 1 Free University of Brussels, Belgium

Novel highly pathogenic avian influenza (HPAI) viruses emerge by two main mechanims; conversion of a low pathogenic virus to highly pathogenic variant, and through reassortment between segments of circulating low and highly pathogenic viruses. The spatio-temporal distribution of these novel HPAI emergences has been mapped, and the species and production systems where these emergences occurred were described earlier (Dhingra et al., 2018). Even though several studies in the past have identified the risk factors associated with HPAI presence, spread and persistence at different spatial scales ( Gilbert and Pfeiffer, 2012, Dhingra et al., 2016) over the longer term, the effect of poultry intensification on novel HPAI emergence has been largely overlooked, except in a few studies (Gilbert et al., 2017). We study the global intensification of the poultry over the past decades with respect to the trajectory of intensification and the occurrence of conversion LPAI to HPAI events, with the aim to explore the association between these variables (poultry density, output/input ratio, and total stock of poultry). Generalized linear model and boosted regression trees are used to explore the the host composition over time and how it is related to the risk of emergence of HPAI through conversions. We observe that even as chicken density remains an expected contributing factor, within the high chicken density countries, the output-input ratio is the main differentiating factors associated with novel HPAI emergence. As several countries look to intensify poultry production, the nature of the poultry production systems will change too. Simultaneously, the risks of novel HPAI emergence and its impact will also shift from the backyard to the commercialised sector, and countries need to adapt and plan their surveillance for early detection and risk mitigation accordingly to minimize the losses to economic and food security.

Acknowledgements

The authors are grateful to the NIH (grant 1R01AI101028-02A1) and the Fonds National de la Recherche Scientifique (FNRS, Belgium) who funded part of this work.

References

Dhingra, M.S., Artois, J., Dellicour, S., Lemey, P., Dauphin, G., Von Dobschuetz, S., Van Boeckel, T.P., Castellan, D.M., Morzaria, S., Gilbert, M., 2018. Geographical and historical patterns in the emergences of novel highly pathogenic avian influenza (HPAI) H5 and H7 viruses in poultry. Frontiers in Veterinary Science. https://doi.org/10.3389/fvets.2018.00084 Dhingra, M.S., Artois, J., Robinson, T.P., Linard, C., Chaiban, C., Xenarios, I., Engler, R., Liechti, R., Kuznetsov, D., Xiao, X., Dobschuetz, S.V., Claes, F., Newman, S.H., Dauphin, G., Gilbert, M., 2016. Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation. eLife 5, e19571. https://doi.org/10.7554/eLife.19571 Gilbert, M., Pfeiffer, D.U., 2012. Risk factor modelling of the spatio-temporal patterns of highly pathogenic avian influenza (HPAIV) H5N1: A review. Spat. Spatio-Temporal Epidemiol. 3, 173–183. https://doi.org/10.1016/j.sste.2012.01.002 Gilbert, M., Xiao, X., Robinson, T.P., 2017. Intensifying poultry production systems and the emergence of avian influenza in China: a ‘One Health/Ecohealth’ epitome. Arch. Public Health 75. https://doi.org/10.1186/s13690-017-0218-4

Keywords: avian influenza, agricultural intensification, global change, Spatial Epidemiology, Phylogeography

Conference: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data, Davis, United States, 8 Oct - 10 Oct, 2019.

Presentation Type: Regular oral presentation

Topic: Spatial methods for environmental & exposure epidemiology and climate change

Citation: Saharan Dhingra M, Artois J, Dellicour S and Gilbert M (2019). Historical and geographical patterns of new HPAIV emergences and association with spatial factors. Front. Vet. Sci. Conference Abstract: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data. doi: 10.3389/conf.fvets.2019.05.00056

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Received: 10 Jun 2019; Published Online: 27 Sep 2019.

* Correspondence:
Ms. Madhur Saharan Dhingra, Free University of Brussels, Brussels, Brussels, 1050, Belgium, madhursd@gmail.com
Mx. Marius Gilbert, Free University of Brussels, Brussels, Brussels, 1050, Belgium, marius.gilbert@gmail.com