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Identifying the Environmental Conditions Favouring West Nile Virus Outbreaks in Europe

机译:确定有利于在欧洲爆发西尼罗河病毒的环境条件

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摘要

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.
机译:西尼罗河病毒(WNV)是一种全球重要的蚊媒病毒,对人类和动物健康具有重要意义。新血统的出现和传播,以及致病性的增强,是引起公众对健康日益关注的原因。由于其生物周期的复杂性以及流行病学数据的不足诊断和报告,查明有利于WNV传播和传播给人类的环境条件具有挑战性。在这里,我们使用遥感和GIS来对大陆空间尺度上的多种类型的环境数据进行整理,以模拟整个欧洲和邻国的西尼罗河热(WNF)年发病率。多模型选择和推论被用来从多个线性混合模型中获得共识。气候和景观是WNF爆发的主要预测因子(特别是冬末/初春高降雨,夏季高温,夏季干旱,农田灌溉和森林高度分散)。识别与WNF爆发有关的环境条件是使公共卫生机构能够正确地集中监视和缓解西尼罗河病毒影响的关键,但是需要做更多的工作才能准确预测WNF风险。

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