出生-死亡天际线图揭示了 HIV 和丙型肝炎病毒 (HCV) 流行传播的时间变化。
Birth-death skyline plot reveals temporal changes of epidemic spread in HIV and hepatitis C virus (HCV).
机构信息
Department of Environmental Systems Science, Eidgenössische Technische Hochschule Zürich, 8092 Zürich, Switzerland.
出版信息
Proc Natl Acad Sci U S A. 2013 Jan 2;110(1):228-33. doi: 10.1073/pnas.1207965110. Epub 2012 Dec 17.
Abstract
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.
摘要
系统发育树可用于推断产生它们的过程。在这里，我们引入了一个模型，即贝叶斯出生-死亡天空图模型，该模型明确估计了传播、恢复和抽样的速率，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以分段的方式随时间变化，并在 BEAST2 软件框架内实现。该方法是现有合并天空图的有力替代方法，它深入了解了传染病中发病率和患病率的不同作用。我们将该方法应用于英国 HIV-1 流行和埃及丙型肝炎病毒（HCV）流行的数据。分析结果揭示了有效繁殖数的时间变化，突出了过去公共卫生干预措施的影响。
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