The construction and analysis of epidemic trees with reference to the 2001 UK foot-and-mouth outbreak
The construction and analysis of epidemic trees with reference to the 2001 UK foot-and-mouth outbreak
复制标题
DOI：
10.1098/rspb.2002.2191
复制
发表时间：
2003-01-22
影响因子：
4.7
通讯作者：
Woolhouse, MEJ
中科院分区：
文献类型：
--
作者：
Haydon, DT;Chase-Topping, M;Woolhouse, MEJ
传染病传播的病例-再生产比率是了解流行病动态和评价控制措施对感染传播的影响的一个极为重要的概念。可靠的估计这一比例是流行病学的核心问题，最常见的是通过拟合动态模型的数据和估计参数的组合，相当于病例繁殖率。在这里，我们开发了一种新的无参数的方法，允许直接估计的历史，从详细观察一个特定的流行病恢复的传播事件。从这些重建的“流行病树”，可以直接估计病例再现率。我们开发了一个自举算法，产生百分位数的间隔，这些估计表明，该程序是精确的和强大的历史重建中可能的不确定性。通过确定和“修剪”这些树木的枝条，可以估计这些替代措施的可能功效，因为这些树木的发生本来可以通过实施更严格的控制措施来防止。检查这些树的分支结构作为每个病例与其感染源的距离的函数，揭示了关于长距离传播事件与流行规模之间关系的有用见解。我们证明了这些方法的实用性，将它们应用于2001年在英国爆发的口蹄疫的数据。
The case-reproduction ratio for the spread of an infectious disease is a critically important concept for understanding dynamics of epidemics and for evaluating impact of control measures on spread of infection. Reliable estimation of this ratio is a problem central to epidemiology and is most often accomplished by fitting dynamic models to data and estimating combinations of parameters that equate to the case-reproduction ratio. Here, we develop a novel parameter-free method that permits direct estimation of the history of transmission events recoverable from detailed observation of a particular epidemic. From these reconstructed 'epidemic trees', case-reproduction ratios can be estimated directly. We develop a bootstrap algorithm that generates percentile intervals for these estimates that shows the procedure to be both precise and robust to possible uncertainties in the historical reconstruction. Identifying and 'pruning' branches from these trees whose occurrence might have been prevented by implementation of more stringent control measures permits estimation of the possible efficacy of these alternative measures. Examination of the cladistic structure of these trees as a function of the distance of each case from its infection source reveals useful insights about the relationship between long-distance transmission events and epidemic size. We demonstrate the utility of these methods by applying them to data from the 2001 foot-and-mouth disease outbreak in the UK.