Thakur K K, Revie C W, Hurnik D, Poljak Z, Sanchez J
Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, PEI, Canada.
Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.
Transbound Emerg Dis. 2016 Feb;63(1):e14-26. doi: 10.1111/tbed.12225. Epub 2014 Apr 17.
Direct and indirect contacts among animal holdings are important in the spread of infectious diseases. The objectives of this study were to describe networks of pig movements and the sharing of trucks used for those movements between swine farms in four Canadian regions using network analysis tools and to obtain contact parameters for infectious disease spread simulation models. Four months of swine movement data from a pilot pig traceability programme were used. Two types of networks were created using three time scales (weekly, monthly and the full study period): one-mode networks of farm-to-farm direct contact representing animal shipments and two-mode networks representing the sharing of trucks between farms. Contact patterns among farms were described by estimating a range of relevant network measures. The overall network neglecting the four regions consisted of 145 farms, which were connected by 261 distinct links. A total of 184 trucks were used to transport 2043 shipments of pigs during the study period. The median in- and out-degree for the overall one-mode network was 1 and ranged from 0 to 26 and 0 to 10, respectively. The overall one-mode network had heterogeneous degree distribution, a high clustering coefficient and shorter average path length than would be expected for randomly generated networks of similar size. On average one truck was shared by four farms in the overall network, or by three farms when considered the monthly and weekly networks. Degree distribution of the two-mode overall network demonstrated characteristics of power-law distribution. For more than 50% of shipments on any given day, the same truck was used for at least one other shipment. Findings from this study are in agreement with previous work, which suggested that swine movement networks exhibit small-world and scale-free topologies. Furthermore, trucks used for the shipment of pigs can play an important role in connecting otherwise unconnected farms and may increase the spread of disease.
养殖场之间的直接和间接接触在传染病传播中很重要。本研究的目的是使用网络分析工具描述加拿大四个地区养猪场之间的猪只移动网络以及用于这些移动的卡车共享情况，并获取传染病传播模拟模型的接触参数。使用了来自一个试点猪只可追溯计划的四个月猪只移动数据。使用三个时间尺度（每周、每月和整个研究期）创建了两种类型的网络：代表动物运输的农场到农场直接接触的单模网络，以及代表农场之间卡车共享的双模网络。通过估计一系列相关网络指标来描述农场之间的接触模式。忽略四个地区的总体网络由145个农场组成，这些农场通过261条不同的链路相连。在研究期间，总共使用了184辆卡车运输2043批猪。总体单模网络的入度和出度中位数均为1，范围分别为0至26和0至10。总体单模网络具有异质度分布、高聚类系数，并且平均路径长度比类似规模的随机生成网络预期的要短。在总体网络中，平均四个农场共享一辆卡车，在考虑每月和每周网络时，平均三个农场共享一辆卡车。双模总体网络的度分布呈现幂律分布特征。在任何给定的一天，超过50%的运输批次至少有一批使用了同一辆卡车。本研究的结果与之前的研究一致，之前的研究表明猪只移动网络呈现小世界和无标度拓扑结构。此外，用于运输猪只的卡车在连接原本不相连的农场方面可能发挥重要作用，并可能增加疾病传播。
