Rautureau S, Dufour B, Durand B
Epidemiology unit EPI, French agency for food, environmental and occupational health safety (ANSES), Maisons-Alfort Cedex, France. Epidemiology unit EPIMAI, Alfort National Veterinary School (ENVA), Maisons-Alfort Cedex, France.
Epidemiology unit EPI, French agency for food, environmental and occupational health safety (ANSES), Maisons-Alfort Cedex, France Epidemiology unit EPIMAI, Alfort National Veterinary School (ENVA), Maisons-Alfort Cedex, France.
Transbound Emerg Dis. 2011 Apr;58(2):110-20. doi: 10.1111/j.1865-1682.2010.01187.x. Epub 2010 Dec 15.
Besides farming, trade of livestock is a major component of agricultural economy. However, the networks generated by live animal movements are the major support for the propagation of infectious agents between farms, and their structure strongly affects how fast a disease may spread. Structural characteristics may thus be indicators of network vulnerability to the spread of infectious disease. The method proposed here is based upon the analysis of specific subnetworks: the giant strongly connected components (GSCs). Their existence, size and geographic extent are used to assess network vulnerability. Their disappearance when targeted nodes are removed allows studying how network vulnerability may be controlled under emergency conditions. The method was applied to the cattle trade network in France, 2005. Giant strongly connected components were present and widely spread all over the country in yearly, monthly and weekly networks. Among several tested approaches, the most efficient way to make GSCs disappear was based on the ranking of nodes by decreasing betweenness centrality (the proportion of shortest paths between nodes on which a specific node lies). Giant strongly connected components disappearance was obtained after removal of <1% of network nodes. Under emergency conditions, suspending animal trade activities in a small subset of holdings may thus allow to control the spread of an infectious disease through the animal trade network. Nodes representing markets and dealers were widely affected by these simulated control measures. This confirms their importance as 'hubs' for infectious diseases spread. Besides emergency conditions, specific sensitization and preventive measures should be dedicated to this population.
除了农业生产,牲畜贸易是农业经济的一个主要组成部分。然而,活体动物流动所形成的网络是传染病在养殖场之间传播的主要载体,其结构强烈影响疾病传播的速度。因此,结构特征可能是网络对传染病传播脆弱性的指标。这里提出的方法基于对特定子网的分析:巨型强连通分量(GSCs)。它们的存在、规模和地理范围用于评估网络脆弱性。当目标节点被移除时它们的消失使得能够研究在紧急情况下网络脆弱性如何得到控制。该方法应用于2005年法国的牛贸易网络。在年度、月度和周度网络中,巨型强连通分量都存在且广泛分布于全国。在几种经过测试的方法中,使巨型强连通分量消失的最有效方法是基于节点的中介中心性(特定节点位于其上的节点之间最短路径的比例)降序排列来对节点进行排序。在移除不到1%的网络节点后,巨型强连通分量消失。因此,在紧急情况下,暂停一小部分养殖场的动物贸易活动可能有助于控制传染病通过动物贸易网络的传播。代表市场和经销商的节点受到这些模拟控制措施的广泛影响。这证实了它们作为传染病传播“枢纽”的重要性。除紧急情况外,应针对这一群体采取特定宣传和预防措施。