Birth-death skyline plot reveals temporal changes of epidemic spread in HIV and hepatitis C virus (HCV)
Birth-death skyline plot reveals temporal changes of epidemic spread in HIV and hepatitis C virus (HCV)
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DOI：
10.1073/pnas.1207965110
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发表时间：
2013-01-02
影响因子：
11.1
通讯作者：
Drummond, Alexei J.
中科院分区：
文献类型：
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作者：
Stadler, Tanja;Kuehnert, Denise;Drummond, Alexei J.
系统发育树可用于推断生成它们的过程。在这里，我们引入了一个模型，即贝叶斯出生-死亡天际线图，它明确估计了传播率、恢复率和采样率，从而可以直接从遗传数据推断有效繁殖数。我们的方法允许这些参数随时间分段变化，并在 BEAST2 软件框架内实现。该方法是现有合并天际线图的有力替代方案，可以深入了解流行病中发病率和流行率的不同作用。我们将此方法应用于英国 HIV-1 流行病和埃及丙型肝炎病毒 (HCV) 流行病的数据。该分析揭示了有效再生数的时间变化，凸显了过去公共卫生干预措施的效果。
Phylogenetic trees can be used to infer the processes that generated them. Here, we introduce a model, the Bayesian birth-death skyline plot, which explicitly estimates the rate of transmission, recovery, and sampling and thus allows inference of the effective reproductive number directly from genetic data. Our method allows these parameters to vary through time in a piecewise fashion and is implemented within the BEAST2 software framework. The method is a powerful alternative to the existing coalescent skyline plot, providing insight into the differing roles of incidence and prevalence in an epidemic. We apply this method to data from the United Kingdom HIV-1 epidemic and Egyptian hepatitis C virus (HCV) epidemic. The analysis reveals temporal changes of the effective reproductive number that highlight the effect of past public health interventions.