Malesios C, Demiris N, Abas Z, Dadousis K, Koutroumanidis T
Department of Agricultural Development, Democritus University of Thrace, Pantazidou 193, Orestiada, Greece.
Department of Statistics, Athens University of Economics and Business, 76, Patission Str., Athens, Greece.
Spat Spatiotemporal Epidemiol. 2014 Oct;11:1-10. doi: 10.1016/j.sste.2014.07.003. Epub 2014 Jul 21.
Sheep pox is a highly transmissible disease which can cause serious loss of livestock and can therefore have major economic impact. We present data from sheep pox epidemics which occurred between 1994 and 1998. The data include weekly records of infected farms as well as a number of covariates. We implement Bayesian stochastic regression models which, in addition to various explanatory variables like seasonal and environmental/meteorological factors, also contain serial correlation structure based on variants of the Ornstein-Uhlenbeck process. We take a predictive view in model selection by utilizing deviance-based measures. The results indicate that seasonality and the number of infected farms are important predictors for sheep pox incidence.
绵羊痘是一种高度传染性疾病，可导致牲畜严重损失，因此会产生重大经济影响。我们展示了1994年至1998年间发生的绵羊痘疫情数据。这些数据包括受感染农场的每周记录以及一些协变量。我们实施贝叶斯随机回归模型，该模型除了包含季节和环境/气象因素等各种解释变量外，还基于奥恩斯坦-乌伦贝克过程的变体包含序列相关结构。我们通过利用基于偏差的度量在模型选择中采取预测性观点。结果表明，季节性和受感染农场的数量是绵羊痘发病率的重要预测因素。
