Inferring HIV transmission networks from time-resolved viral phylogenies for epidemiological modelling

在英国，艾滋病毒的流行正在增长，无论是在异性恋者中，这是一种相对较新的流行病，还是在男同性恋者中，新的感染病例以前已经稳定下来。该提案旨在制定方法，以查明大多数新感染发生在什么环境中。我们将使用病毒序列的匿名数据来发现HIV传播是随着时间的推移而稳定发生，还是通过网络突然发生。早期的研究表明网络很重要，所以我们需要能够识别关键的设置。我们将使用一个计算机程序来描述（模拟）我们所理解的流行病，包括酒吧，健身房和互联网等人们可以遇到性伴侣的场所。该模型将允许来自病毒序列数据的信息帮助我们预测哪些将是最有效的链接，以减少新的感染。

The HIV epidemic in the UK is growing, both among heterosexuals, which is a relatively new epidemic, and again among gay men, where new infections had previously stabilised. This proposal is intended to develop methods for finding out in what settings most new infections occur. We will use anonymised data on viral sequences to discover whether HIV transmission occurs steadily over time, or whether it occurs in bursts, through networks. Early studies suggest networks are important, so we need to be able to identify the key settings. We will do this by using a computer program which describes ( models ) the epidemic as far as we understand it, including settings such as bars, gyms and the internet, where people can meet sexual partners. The model will allow information from the viral sequence data to help us to predict which will be the most effective links to target to reduce new infections.