Since the arrival of porcine epidemic diarrhea virus (PEDV) in the United States in 2013, elimination and control programmes have had partial success. The dynamics of its spread are hard to quantify, though previous work has shown that local transmission and the transfer of pigs within production systems are most associated with the spread of PEDV. Our work relies on the history of PEDV infections in a region of the southeastern United States. This infection data is complemented by farm-level features and extensive industry data on the movement of both pigs and vehicles. We implement a discrete-time survival model and evaluate different approaches to modelling the local-transmission and network effects. We find strong evidence in that the local-transmission and pig-movement effects are associated with the spread of PEDV, even while controlling for seasonality, farm-level features and the possible spread of disease by vehicles. Our fully Bayesian model permits full uncertainty quantification of these effects. Our farm-level out-of-sample predictions have a receiver-operating characteristic area under the curve (AUC) of 0.779 and a precision-recall AUC of 0.097. The quantification of these effects in a comprehensive model allows stakeholders to make more informed decisions about disease prevention efforts.

中文翻译：

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猪流行性腹泻病毒的离散时间生存模型

自2013年猪流行性腹泻病毒（PEDV）抵达美国以来，消除和控制计划已取得部分成功。尽管之前的研究表明，本地传播和生产系统内生猪的转移与 PEDV 的传播密切相关，但其传播动态很难量化。我们的工作依赖于美国东南部地区的 PEDV 感染历史。这些感染数据得到了农场层面的特征以及有关生猪和车辆移动的广泛行业数据的补充。我们实现了离散时间生存模型，并评估了模拟本地传输和网络效应的不同方法。我们发现强有力的证据表明，即使在控制季节性、农场水平特征和车辆可能传播疾病的情况下，本地传播和生猪流动效应与 PEDV 的传播有关。我们的完全贝叶斯模型允许对这些影响进行完全不确定性量化。我们的农场级样本外预测的接收者操作特征曲线下面积 (AUC) 为 0.779，精确召回 AUC 为 0.097。在综合模型中量化这些影响使利益相关者能够就疾病预防工作做出更明智的决策。