Department of Biology, The Pennsylvania State University, University Park, Pennsylvania, United States of America.
Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.
PLoS Comput Biol. 2022 Aug 19;18(8):e1010354. doi: 10.1371/journal.pcbi.1010354. eCollection 2022 Aug.
The structure of contact networks affects the likelihood of disease spread at the population scale and the risk of infection at any given node. Though this has been well characterized for both theoretical and empirical networks for the spread of epidemics on completely susceptible networks, the long-term impact of network structure on risk of infection with an endemic pathogen, where nodes can be infected more than once, has been less well characterized. Here, we analyze detailed records of the transportation of cattle among farms in Turkey to characterize the global and local attributes of the directed-weighted shipments network between 2007-2012. We then study the correlations between network properties and the likelihood of infection with, or exposure to, foot-and-mouth disease (FMD) over the same time period using recorded outbreaks. The shipments network shows a complex combination of features (local and global) that have not been previously reported in other networks of shipments; i.e. small-worldness, scale-freeness, modular structure, among others. We find that nodes that were either infected or at high risk of infection with FMD (within one link from an infected farm) had disproportionately higher degree, were more central (eigenvector centrality and coreness), and were more likely to be net recipients of shipments compared to those that were always more than 2 links away from an infected farm. High in-degree (i.e. many shipments received) was the best univariate predictor of infection. Low in-coreness (i.e. peripheral nodes) was the best univariate predictor of nodes always more than 2 links away from an infected farm. These results are robust across the three different serotypes of FMD observed in Turkey and during periods of low-endemic prevalence and high-prevalence outbreaks.
接触网络的结构会影响疾病在人群中的传播概率和任意给定节点的感染风险。尽管在完全易感网络上，理论和经验网络对传染病的传播都已经得到了很好的描述，但网络结构对地方流行病原体感染风险的长期影响却描述得较少。在这里，我们分析了土耳其农场之间牛群运输的详细记录，以描述 2007-2012 年之间定向加权运输网络的全局和局部属性。然后，我们使用记录的疫情研究同一时期网络属性与口蹄疫（FMD）感染或暴露的相关性。运输网络显示出复杂的特征组合（局部和全局），这些特征在其他运输网络中尚未报道过；即小世界性、无标度性、模块化结构等。我们发现，那些感染或高风险感染 FMD 的节点（距离感染农场一个链接内）的度、中心性（特征向量中心性和核心度）都不成比例地更高，并且与始终距离感染农场两个以上链接的节点相比，更有可能成为运输的净接收者。高输入度（即接收了许多运输）是感染的最佳单变量预测指标。低核心度（即外围节点）是始终距离感染农场两个以上链接的节点的最佳单变量预测指标。这些结果在土耳其观察到的三种不同血清型的 FMD 和低地方流行率和高流行率疫情期间都是稳健的。
