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首页> 外文期刊>Transboundary and emerging diseases >Comparing network analysis measures to determine potential epidemic size of highly contagious exotic diseases in fragmented monthly networks of dairy cattle movements in Ontario, Canada
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Comparing network analysis measures to determine potential epidemic size of highly contagious exotic diseases in fragmented monthly networks of dairy cattle movements in Ontario, Canada

机译：比较网络分析方法以确定加拿大安大略省奶牛运动零散的每月网络中高度传染性外来疾病的潜在流行病规模

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Adult milking cow movements occurring in monthly periods in 2004-2006 were analysed to compare three network analysis measures to determine the lower and upper bounds of potential maximal epidemic size in an unrestrained epidemic: the out-degree, the infection chain or output domain of a farm, and the size of the strong and weak components. The directed networks generated by the movements of adult milking cows were highly fragmented. When all the farms that were not involved in shipments were included in the analysis, the risk of infection transmission through movements of adult cows was very low. To determine the size of an epidemic when an infected farm shipped cows in such a fragmented network, farm out-degree and infection chain provided similar and more reasonable estimates of potential maximal epidemic size than the size of the strong and weak components. Component analysis always provided estimates that were two to three times larger than the out-degree of infection chain approaches. For example, the upper bound was estimated to be 12-13 farms using out-degree and 16-17 farms using the infection chain, the components approach showed a range of 39-51 potentially exposed farms. Strong components provided an inflated measure of the lower bound of potential maximal epidemic size at first diagnosis because the time sequence of shipments was not considered. Weak components provided an inflated measure of the upper bound because both the time sequence and directionality of shipments between farms were ignored. Farm degree and infection chain measures should now be tested to determine their usefulness for estimating maximum epidemic size in large connected networks.
机译：对2004-2006年每月发生的成年挤奶牛运动进行了分析，以比较三种网络分析方法，以确定无限制流行中潜在最大流行病规模的上限和下限：门诊感染的程度，感染链或输出域场，以及强项和弱项的大小。成年奶牛运动产生的定向网络高度分散。当所有不涉及运输的农场都包括在分析中时，通过成年母牛的运动传播感染的风险非常低。为了确定当受感染的农场以这种分散的网络运送奶牛时的流行病规模，农场的疫情程度和感染链比潜在的最大流行病规模提供了比强壮和弱势组件的规模相似且更合理的估计。成分分析始终提供的估计值比感染链方法的超出程度大2至3倍。例如，估计上限为使用外部学位的12-13个农场和使用感染链的16-17个农场，分量法显示了39-51个潜在暴露的农场。由于没有考虑运输的时间顺序，因此强大的组件在首次诊断时就提供了潜在最大流行病规模下限的膨胀度量。弱组件提供了上限的过高度量，因为忽略了农场之间运输的时间顺序和方向性。现在应测试农场程度和感染链措施，以确定其在估算大型连接网络中最大流行规模时的有用性。

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