Viral sequence data coupled with phylodynamic models have become instrumental in investigating the outbreaks of human and animal diseases, and the incorporation of the hypothesized drivers of pathogen spread can enhance the interpretation from phylodynamic inference. Integrating animal movement data with phylodynamics allows us to quantify the extent to which the spatial diffusion of a pathogen is influenced by animal movements and contrast the relative importance of different types of movements in shaping pathogen distribution. We combine animal movement, spatial, and environmental data in a Bayesian phylodynamic framework to explain the spatial diffusion and evolutionary trends of a rapidly spreading sub-lineage (denoted L1A) of porcine reproductive and respiratory syndrome virus (PRRSV) Type 2 from 2014 to 2017. PRRSV is the most important endemic pathogen affecting pigs in the USA, and this particular virulent sub-lineage emerged in 2014 and continues to be the dominant lineage in the US swine industry to date. Data included 984 open reading frame 5 (ORF5) PRRSV L1A sequences obtained from two production systems in a swine-dense production region (∼85,000 mi2) in the USA between 2014 and 2017. The study area was divided into sectors for which model covariates were summarized, and animal movement data between each sector were summarized by age class (wean: 3–4 weeks; feeder: 8–25 weeks; breeding: ≥21 weeks). We implemented a discrete-space phylogeographic generalized linear model using Bayesian evolutionary analysis by sampling trees (BEAST) to infer factors associated with variability in between-sector diffusion rates of PRRSV L1A. We found that between-sector spread was enhanced by the movement of feeder pigs, spatial adjacency of sectors, and farm density in the destination sector. The PRRSV L1A strain was introduced in the study area in early 2013, and genetic diversity and effective population size peaked in 2015 before fluctuating seasonally (peaking during the summer months). Our study underscores the importance of animal movements and shows, for the first time, that the movement of feeder pigs (8–25 weeks old) shaped the spatial patterns of PRRSV spread much more strongly than the movements of other age classes of pigs. The inclusion of movement data into phylodynamic models as done in this analysis may enhance our ability to identify crucial pathways of disease spread that can be targeted to mitigate the spatial spread of infectious human and animal pathogens.

中文翻译：

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将动物运动与系统地理学相结合，模拟 PRRSV 在美国的传播

病毒序列数据与系统动力学模型相结合已成为调查人类和动物疾病爆发的工具，并且结合假设的病原体传播驱动因素可以增强对系统动力学推断的解释。将动物运动数据与系统动力学相结合，使我们能够量化病原体的空间扩散受动物运动影响的程度，并对比不同类型运动在塑造病原体分布中的相对重要性。我们在贝叶斯系统动力学框架中结合动物运动、空间和环境数据来解释 2014 年至 2017 年猪繁殖与呼吸综合征病毒 (PRRSV) 2 型快速传播的亚谱系（表示为 L1A）的空间扩散和进化趋势. PRRSV 是影响美国猪的最重要的地方性病原体，这种特殊的剧毒亚系于 2014 年出现，并且至今仍是美国养猪业的主要谱系。数据包括 984 个开放阅读框 5 (ORF5) PRRSV L1A 序列，这些序列在 2014 年至 2017 年期间从美国猪密集生产区（约 85,000 平方英里）的两个生产系统中获得。研究区域被划分为模型协变量为总结，每个部门之间的动物运动数据按年龄等级总结（断奶：3-4 周；饲养：8-25 周；育种：≥21 周）。我们使用贝叶斯进化分析通过采样树 (BEAST) 实施了一个离散空间系统地理广义线性模型，以推断与 PRRSV L1A 的部门间扩散率变化相关的因素。我们发现，饲养猪的移动、部门的空间相邻性和目的地部门的农场密度增强了部门间的传播。PRRSV L1A毒株于2013年初引入研究区，遗传多样性和有效种群规模在2015年达到顶峰，然后出现季节性波动（夏季达到顶峰）。我们的研究强调了动物运动的重要性，并首次表明，饲养猪（8-25 周龄）的运动对 PRRSV 传播的空间模式的影响远大于其他年龄组猪的运动。如本分析中所做的那样，将运动数据纳入系统动力学模型可能会增强我们识别疾病传播关键途径的能力，这些途径可以针对减轻传染性人类和动物病原体的空间传播。