Swart Arno, Bekker Dick L, Maas Miriam, de Vries Ankje, Pijnacker Roan, Reusken Chantal B E M, van der Giessen Joke W B
Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
Dutch Mammal Society, Nijmegen, the Netherlands.
Infect Ecol Epidemiol. 2017 Mar 24;7(1):1287986. doi: 10.1080/20008686.2017.1287986. eCollection 2017.
This paper deals with modelling the relationship between human Puumala hantavirus (PUUV) infection, the abundance and prevalence of infection of the host (the bank vole), mast, and temperature. These data were used to build and parametrise generalised regression models, and parametrise them using datasets on these factors pertaining to the Netherlands. The performance of the models was assessed by considering their predictive power. Models including mast and monthly temperature performed well, and showed that mast intensity influences vole abundance and hence human exposure for the following year. Thus, the model can aid in forecasting of human illness cases, since (1) mast intensity influences the vole abundance and hence human exposure for the following year and (2) monitoring of mast is much more feasible than determining bank vole abundance.
本文探讨了人类普马拉汉坦病毒（PUUV）感染、宿主（棕背鼠平）感染的丰度和流行率、槲果以及温度之间关系的建模。这些数据被用于构建广义回归模型并进行参数化，使用的是与荷兰相关的这些因素的数据集。通过考虑模型的预测能力来评估其性能。包含槲果和月平均温度的模型表现良好，表明槲果强度会影响田鼠数量，进而影响次年人类的接触风险。因此，该模型有助于预测人类发病情况，原因如下：（1）槲果强度影响田鼠数量，进而影响次年人类的接触风险；（2）监测槲果比确定棕背鼠平数量更可行。
