Uncovering epidemiological dynamics in heterogeneous host populations using phylogenetic methods
Uncovering epidemiological dynamics in heterogeneous host populations using phylogenetic methods
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DOI：
10.1098/rstb.2012.0198
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发表时间：
2013-03-19
影响因子：
6.3
通讯作者：
Bonhoeffer, Sebastian
中科院分区：
文献类型：
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作者：
Stadler, Tanja;Bonhoeffer, Sebastian
宿主种群结构对流行病学动态有重大影响。然而，特别是在性传播疾病方面，很难获得关于人口接触结构的定量数据。在这里，我们介绍了一种新的方法，量化主机人口结构的基础上系统发育树，这是从病原体的遗传序列数据。我们的方法是基于一个最大似然框架，并使用多类型的分支过程中，每个主机被分配到一个类型（亚群）。在模拟研究中，我们表明，我们的方法产生准确的参数估计的系统发育树中，每个提示被分配到一个类型，以及系统发育树中的提示的类型是未知的。我们将该方法应用于拉脱维亚HIV-1数据集，量化静脉吸毒者流行病对异性恋流行病（已知尖端状态）的影响，并确定男性与男性发生性关系流行病（未知尖端状态）中的超级传播者动态。
Host population structure has a major influence on epidemiological dynamics. However, in particular for sexually transmitted diseases, quantitative data on population contact structure are hard to obtain. Here, we introduce a new method that quantifies host population structure based on phylogenetic trees, which are obtained from pathogen genetic sequence data. Our method is based on a maximum-likelihood framework and uses a multi-type branching process, under which each host is assigned to a type (subpopulation). In a simulation study, we show that our method produces accurate parameter estimates for phylogenetic trees in which each tip is assigned to a type, as well for phylogenetic trees in which the type of the tip is unknown. We apply the method to a Latvian HIV-1 dataset, quantifying the impact of the intravenous drug user epidemic on the heterosexual epidemic (known tip states), and identifying super-spreader dynamics within the men-having-sex-with-men epidemic (unknown tip states).