Analysis of spatio-temporal patterns of African swine fever cases in Russian wild boar does not reveal an endemic situation
Analysis of spatio-temporal patterns of African swine fever cases in Russian wild boar does not reveal an endemic situation
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DOI：
10.1016/j.prevetmed.2014.08.012
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发表时间：
2014-11-15
影响因子：
2.6
通讯作者：
Thulke, H. -H.
中科院分区：
文献类型：
--
作者：
Lange, M.;Siemen, H.;Thulke, H. -H.
非洲猪瘟(ASF)是一种对家猪和野猪具有高度致死性的病毒性疾病。ASF于2007年被引入俄罗斯联邦南部，据报道现在正在野生和家养禽类种群中传播。当地野猪种群的流行情况将使牲畜种群疾病的管理大大复杂化。到目前为止，还没有可靠的方法来确定地方性疫情的特征模式，这种模式描述了同一人群中一代又一代人持续感染的情况。为了支持野生动物-家畜界面的紧急管理决策，构建了一种新的算法，以病例报告为基础检验野生动物地方病情况的假设。这里描述的方法使用观察到的诊断数据之间的空间和时间关联来区分病例发生的地方性和非地方性模式。该算法用来自流行病学模拟模型的数据进行了验证，并应用于俄罗斯南部的ASF病例数据。基于该算法和现有的诊断数据，剔除了该地区野猪ASF流行情况的零假设。(C)2014爱思唯尔B.V.保留所有权利。
African swine fever (ASF) is a highly lethal viral disease of domestic pigs and wild boar. ASF was introduced into the southern Russian Federation in 2007 and is now reported to be spreading in populations of wild and domestic suids. An endemic situation in the local wild boar population would significantly complicate management of the disease in the livestock population. To date no sound method exists for identifying the characteristic pattern of an endemic situation, which describes infection persisting from generation to generation in the same population. To support urgent management decisions at the wildlife-livestock interface, a new algorithm was constructed to test the hypothesis of an endemic disease situation in wildlife on the basis of case reports. The approach described here uses spatial and temporal associations between observed diagnostic data to discriminate between endemic and non-endemic patterns of case occurrence. The algorithm was validated with data from an epidemiological simulation model and applied to ASF case data from southern Russia. Based on the algorithm and the diagnostic data available, the null hypothesis of an endemic situation of ASF in wild boar of the region was rejected. (C) 2014 Elsevier B.V. All rights reserved.