Dubé C, Ribble C, Kelton D, McNab B
Animal Health and Production Division, Canadian Food Inspection Agency, 59 Camelot Drive, Ottawa, Ontario, K1A OY9, Canada.
Rev Sci Tech. 2011 Aug;30(2):425-36. doi: 10.20506/rst.30.2.2043.
Social networks analysis (SNA) has recently been used in veterinary epidemiology to study livestock movements. A network is obtained by considering livestock holdings as nodes in a network and movements among holdings as links among nodes. Social networks analysis enables the study of the network as a whole, exploring all the relationships among pairs of farms. Highly connected livestock holdings in the network can be identified, which can help surveillance and disease prevention activities. Observed livestock movement networks in various countries have shown an important level of contact heterogeneity and clustering (topological, not necessarily geographical or spatial) and understanding the architecture of these networks has provided a better understanding of how infections may spread. The findings of SNA studies of livestock movement should be used to build and parameterise epidemiological models of infection spread in order to improve the reliability of the outputs from these models.
社会网络分析（SNA）最近已被用于兽医流行病学中，以研究家畜流动情况。通过将家畜饲养场视为网络中的节点，并将饲养场之间的流动视为节点之间的链接，从而获得一个网络。社会网络分析能够对整个网络进行研究，探索各农场之间的所有关系。可以识别出网络中连接性高的家畜饲养场，这有助于监测和疾病预防活动。在各个国家观察到的家畜流动网络显示出重要程度的接触异质性和聚类（拓扑意义上的，不一定是地理或空间上的），而了解这些网络的架构有助于更好地理解感染可能如何传播。家畜流动的社会网络分析研究结果应用于构建感染传播的流行病学模型并为其参数化，以提高这些模型输出结果的可靠性。
