Landcare Research, Wildlife Ecology and Management, Lincoln, New Zealand.
Epidemiol Infect. 2013 Jul;141(7):1509-21. doi: 10.1017/S095026881200310X. Epub 2013 Jan 23.
Surveying and declaring disease freedom in wildlife is difficult because information on population size and spatial distribution is often inadequate. We describe and demonstrate a novel spatial model of wildlife disease-surveillance data for predicting the probability of freedom of bovine tuberculosis (caused by Mycobacterium bovis) in New Zealand, in which the introduced brushtail possum (Trichosurus vulpecula) is the primary wildlife reservoir. Using parameters governing home-range size, probability of capture, probability of infection and spatial relative risks of infection we employed survey data on reservoir hosts and spillover sentinels to make inference on the probability of eradication. Our analysis revealed high sensitivity of model predictions to parameter values, which demonstrated important differences in the information contained in survey data of host-reservoir and spillover-sentinel species. The modelling can increase cost efficiency by reducing the likelihood of prematurely declaring success due to insufficient control, and avoiding unnecessary costs due to excessive control and monitoring.
野生动物疫病的调查和宣布消除较为困难,因为种群数量和空间分布的信息通常不够充分。我们描述并示范了一种新的野生动物疾病监测数据的空间模型,用于预测新西兰牛结核病(由牛分枝杆菌引起)消除的可能性,其中引入的帚尾袋貂(Trichosurus vulpecula)是主要的野生动物储存宿主。利用有关栖息地大小、捕获概率、感染概率和空间感染相对风险的参数,我们利用对储存宿主和溢出哨兵的调查数据,对消除的可能性进行推断。我们的分析表明,模型预测对参数值非常敏感,这表明宿主储存和溢出哨兵物种的调查数据中包含的信息存在重要差异。该模型可以通过降低因控制不足而过早宣布成功的可能性,以及避免因过度控制和监测而产生不必要的成本,从而提高成本效益。