Malesios C, Demiris N, Kostoulas P, Dadousis K, Koutroumanidis T, Abas Z
Department of Rural Development,Democritus University of Thrace,Orestiada,Greece.
Department of Statistics,Athens University of Economics and Business,Athens,Greece.
Epidemiol Infect. 2016 Sep;144(12):2485-93. doi: 10.1017/S095026881600087X. Epub 2016 May 6.
We present and analyse data collected during a severe epidemic of foot-and-mouth disease (FMD) that occurred between July and September 2000 in a region of northeastern Greece with strategic importance since it represents the southeastern border of Europe and Asia. We implement generic Bayesian methodology, which offers flexibility in the ability to fit several realistically complex models that simultaneously capture the presence of 'excess' zeros, the spatio-temporal dependence of the cases, assesses the impact of environmental noise and controls for multicollinearity issues. Our findings suggest that the epidemic was mostly driven by the size and the animal type of each farm as well as the distance between farms while environmental and other endemic factors were not important during this outbreak. Analyses of this kind may prove useful to informing decisions related to optimal control measures for potential future FMD outbreaks as well as other acute epidemics such as FMD.
我们展示并分析了2000年7月至9月间在希腊东北部一个具有战略重要性的地区发生的口蹄疫严重疫情期间收集的数据,该地区具有重要战略意义,因为它是欧洲和亚洲的东南边界。我们采用通用贝叶斯方法,该方法在拟合多个现实复杂模型方面具有灵活性,这些模型能够同时捕捉“过多”零值的存在、病例的时空依赖性、评估环境噪声的影响并控制多重共线性问题。我们的研究结果表明,疫情主要由每个农场的规模、动物类型以及农场之间的距离驱动,而环境和其他地方因素在此次疫情期间并不重要。此类分析可能有助于为未来潜在口蹄疫疫情以及其他急性疫情(如口蹄疫)的最佳控制措施相关决策提供信息。