IFM Theory and Modelling, Linköping University, 581 83 Linköping, Sweden.
Prev Vet Med. 2010 Jun 1;95(1-2):23-31. doi: 10.1016/j.prevetmed.2010.03.002. Epub 2010 Mar 30.
Animal movement poses a great risk for disease transmission between holdings. Heterogeneous contact patterns are known to influence the dynamics of disease transmission and should be included in modeling. Using pig movement data from Sweden as an example, we present a method for quantification of between holding contact probabilities based on different production types. The data contained seven production types: Sow pool center, Sow pool satellite, Farrow-to-finish, Nucleus herd, Piglet producer, Multiplying herd and Fattening herd. The method also estimates how much different production types will determine the contact pattern of holdings that have more than one type. The method is based on Bayesian analysis and uses data from central databases of animal movement. Holdings with different production types are estimated to vary in the frequency of contacts as well as in what type of holding they have contact with, and the direction of the contacts. Movements from Multiplying herds to Sow pool centers, Nucleus herds to other Nucleus herds, Sow pool centers to Sow pool satellites, Sow pool satellites to Sow pool centers and Nucleus herds to Multiplying herds were estimated to be most common relative to the abundance of the production types. We show with a simulation study that these contact patterns may also be expected to result in substantial differences in disease transmission via animal movements, depending on the index holding. Simulating transmission for a 1 year period showed that the median number of infected holdings was 1 (i.e. only the index holding infected) if the infection started at a Fattening herd and 2161 if the infection started on a Nucleus herd. We conclude that it is valuable to include production types in models of disease transmission and the method presented in this paper may be used for such models when appropriate data is available. We also argue that keeping records of production types is of great value since it may be helpful in risk assessments.
动物的移动会给养殖场之间的疾病传播带来很大的风险。不同的接触模式会影响疾病传播的动态,因此应该在模型中加以考虑。本文以瑞典的猪只移动数据为例,提出了一种基于不同生产类型量化养殖场间接触概率的方法。该数据包含七种生产类型:母猪核心群中心、母猪核心群卫星、育肥场、核心群、仔猪生产场、扩繁群和育肥场。该方法还估计了不同生产类型将如何决定具有多种生产类型的养殖场的接触模式。该方法基于贝叶斯分析,使用来自动物移动的中央数据库的数据。具有不同生产类型的养殖场在接触频率以及与哪种类型的养殖场接触以及接触的方向上都有所不同。从扩繁群到母猪核心群中心、核心群到其他核心群、母猪核心群中心到母猪核心群卫星、母猪核心群卫星到母猪核心群中心和核心群到扩繁群的移动被估计为相对于生产类型的丰度最为常见。我们通过模拟研究表明,这些接触模式也可能导致通过动物移动传播疾病的显著差异,这取决于索引养殖场。模拟 1 年的传播表明,如果感染从育肥场开始,则只有索引养殖场感染,感染的养殖场数量中位数为 1;如果感染从核心群开始,则感染的养殖场数量中位数为 2161。我们得出的结论是,在疾病传播模型中纳入生产类型是很有价值的,并且当有适当的数据时,本文提出的方法可以用于此类模型。我们还认为,记录生产类型具有很大的价值,因为它有助于风险评估。