Predicting risk of zoonotic diseases, i.e., diseases shared by humans and animals, is often complicated by the population ecology of wildlife host(s). We here demonstrate how ecological knowledge of a disease system can be used for early prediction of human risk using Puumala hantavirus (PUUV) in bank voles (Myodes glareolus), which causes Nephropathia epidemica (NE) in humans, as a model system. Bank vole populations at northern latitudes exhibit multiannual fluctuations in density and spatial distribution, a phenomenon that has been studied extensively. Nevertheless, existing studies predict NE incidence only a few months before an outbreak. We used a time series on cyclic bank vole population density (1972–2013), their PUUV infection rates (1979–1986; 2003–2013), and NE incidence in Sweden (1990–2013). Depending on the relationship between vole density and infection prevalence (proportion of infected animals), either overall density of bank voles or the density of infected bank voles may be used to predict seasonal NE incidence. The density and spatial distribution of voles at density minima of a population cycle contribute to the early warning of NE risk later at its cyclic peak. When bank voles remain relatively widespread in the landscape during cyclic minima, PUUV can spread from a high baseline during a cycle, culminating in high prevalence in bank voles and potentially high NE risk during peak densities.

中文翻译：

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银行田鼠的种群动态预测人类Puumala汉坦病毒的风险。

野生动物宿主的种群生态学常常使人畜共患疾病（即人畜共患疾病）的风险预测变得复杂。我们在这里展示了如何利用疾病的生态学知识来利用银行田鼠（Myodes glareolus）中的Puumala汉坦病毒（PUUV）对人类风险进行早期预测，这会导致肾病的流行（NE）作为模型系统。北部纬度的河田鼠种群密度和空间分布出现多年波动，这一现象已得到广泛研究。尽管如此，现有研究预测爆发前仅几个月就出现了NE。我们使用了关于周期性银行田鼠种群密度（1972-2013年），其PUUV感染率（1979-1986年； 2003-2013年）和瑞典NE发病率（1990-2013年）的时间序列。根据田鼠密度与感染率（感染动物的比例）之间的关系，可以使用河岸田鼠的整体密度或河岸田鼠的感染密度来预测季节性NE发生率。种群周期最小密度处的田鼠密度和空间分布有助于在后期周期性高峰时对NE风险进行预警。