Institut für Integrative Biologie, ETH Zürich, 8092 Zürich, Switzerland.
Genetics. 2011 Jul;188(3):663-72. doi: 10.1534/genetics.111.126466. Epub 2011 May 5.
In this article, I develop a methodology for inferring the transmission rate and reproductive value of an epidemic on the basis of genotype data from a sample of infected hosts. The epidemic is modeled by a birth-death process describing the transmission dynamics in combination with an infinite-allele model describing the evolution of alleles. I provide a recursive formulation for the probability of the allele frequencies in a sample of hosts and a Bayesian framework for estimating transmission rates and reproductive values on the basis of observed allele frequencies. Using the Bayesian method, I reanalyze tuberculosis data from the United States. I estimate a net transmission rate of 0.19/year [0.13, 0.24] and a reproductive value of 1.02 [1.01, 1.04]. I demonstrate that the allele frequency probability under the birth-death model does not follow the well-known Ewens' sampling formula that holds under Kingman's coalescent.
在本文中,我开发了一种基于受感染宿主样本的基因型数据推断传染病传播率和繁殖值的方法。该传染病通过一个描述传播动态的出生-死亡过程和一个描述等位基因进化的无限等位基因模型进行建模。我提供了一个样本中等位基因频率的概率的递归公式,以及一个基于观察到的等位基因频率估计传播率和繁殖值的贝叶斯框架。使用贝叶斯方法,我重新分析了来自美国的结核病数据。我估计净传播率为 0.19/年[0.13, 0.24],繁殖值为 1.02[1.01, 1.04]。我证明了在出生-死亡模型下,等位基因频率的概率不符合在 Kingman 的合并模型下成立的著名的 Ewens 抽样公式。