West Nile Virus (WNV) is a globally important mosquito borne virus, with significant implications for human and animal health. The emergence and spread of new lineages, and increased pathogenicity, is the cause of escalating public health concern. Pinpointing the environmental conditions that favour WNV circulation and transmission to humans is challenging, due both to the complexity of its biological cycle, and the under-diagnosis and reporting of epidemiological data. Here, we used remote sensing and GIS to enable collation of multiple types of environmental data over a continental spatial scale, in order to model annual West Nile Fever (WNF) incidence across Europe and neighbouring countries. Multi-model selection and inference were used to gain a consensus from multiple linear mixed models. Climate and landscape were key predictors of WNF outbreaks (specifically, high precipitation in late winter/early spring, high summer temperatures, summer drought, occurrence of irrigated croplands and highly fragmented forests). Identification of the environmental conditions associated with WNF outbreaks is key to enabling public health bodies to properly focus surveillance and mitigation of West Nile virus impact, but more work needs to be done to enable accurate predictions of WNF risk

Rizzoli, A.; Metz, M.; Rosa', R.; Marini, G.; Chadwick, E.; Neteler, M.G. (2014). Disentangling the ecological conditions favouring West Nile virus hazard in the Old World. In: Joint Conference: National German Symposium On Zoonoses Research 2014 and 7th International Conference On Emerging Zoonoses, Berlin, October 16-17, 2014. url: http://www.zoonoses2014.com/# handle: http://hdl.handle.net/10449/24596

Disentangling the ecological conditions favouring West Nile virus hazard in the Old World

Rizzoli, Annapaola;Metz, Markus;Rosa', Roberto;Marini, Giovanni;Neteler, Markus Georg
2014-01-01

Abstract

West Nile Virus (WNV) is a globally important mosquito borne virus, with significant implications for human and animal health. The emergence and spread of new lineages, and increased pathogenicity, is the cause of escalating public health concern. Pinpointing the environmental conditions that favour WNV circulation and transmission to humans is challenging, due both to the complexity of its biological cycle, and the under-diagnosis and reporting of epidemiological data. Here, we used remote sensing and GIS to enable collation of multiple types of environmental data over a continental spatial scale, in order to model annual West Nile Fever (WNF) incidence across Europe and neighbouring countries. Multi-model selection and inference were used to gain a consensus from multiple linear mixed models. Climate and landscape were key predictors of WNF outbreaks (specifically, high precipitation in late winter/early spring, high summer temperatures, summer drought, occurrence of irrigated croplands and highly fragmented forests). Identification of the environmental conditions associated with WNF outbreaks is key to enabling public health bodies to properly focus surveillance and mitigation of West Nile virus impact, but more work needs to be done to enable accurate predictions of WNF risk
Landscape Epidemiology
Environmental determinants
Multi-model selection and inference
Temperature anomalies
Early warning systems
Remote sensing
2014
Rizzoli, A.; Metz, M.; Rosa', R.; Marini, G.; Chadwick, E.; Neteler, M.G. (2014). Disentangling the ecological conditions favouring West Nile virus hazard in the Old World. In: Joint Conference: National German Symposium On Zoonoses Research 2014 and 7th International Conference On Emerging Zoonoses, Berlin, October 16-17, 2014. url: http://www.zoonoses2014.com/# handle: http://hdl.handle.net/10449/24596
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10449/24596
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