Reconstructing HIV Epidemics from HIV Phylogenetics

描述（由申请人提供）：艾滋病毒继续在世界范围内感染人群，强调需要能够准确描述传播模式的流行病学工具。因此，我们将开发的方法将对艾滋病毒疫苗产生具体影响；进化;流行病学参数：感染在不同人群中的传播；干预;更广泛地说，是关于传染病的基础科学。总体目标是了解病毒进化与其流行病学历史之间的关系，并创建能够进行可靠接触者追踪和评估流行动态变化的流行病学工具。我们最近的研究表明，在种群水平上，流行率与病毒进化率呈负相关。因此，拟议研究背后的具体假设是，流行病在人群中传播的速度与病毒在该人群中进化的速度之间存在关系。我们已经观察到，在传播史和病毒系统发育之间存在差异，并且由于流行病的推断是基于系统发育，因此了解这种推断的局限性变得很重要。基于此，本建议的具体目标是：1。创建一个模型，准确地描述传播历史和病毒系统发育之间的联系。初步结果表明，在病毒系统发育中存在与传播事件有关的“隐藏谱系”，这可能会误导传播事件的重建。我们将特别研究供体中有效种群大小的影响，传播的瓶颈，以及传播和采样过程中不完整的谱系分类。我们的目标是估计重建的人际传播的有意义的置信水平，使我们能够在专门为流行病学跟踪设计的统计框架中探索替代假设。2. 确定流行率与病毒进化率之间的关联机制。我们将破译流行率和病毒进化率之间的联系。目前，我们有四种可能导致观察到的流行病与进化速度之间相关性的解释（宿主免疫选择、病毒产生时间效应、传播过程中的选择和重组效应）。我们将使用不同的基因序列数据、密码子位置以及氨基酸特征来区分这些假设的解释。我们将使用大型数据集来开发包括这四种假设解释的流行病学模型，以调查它们对人口水平的影响，并模拟社会网络、流行病和系统地理动态。

DESCRIPTION (provided by applicant): HIV continues to infect human populations worldwide, emphasizing the need for epidemiological tools that can accurately describe transmission patterns. Thus, the methods we will develop will have specific impact on HIV vaccines; evolution; epidemiological parameters: spread of infection in different groups; intervention; and more generally on the fundamental science of infectious diseases. The overall goal is to understand the relationship between virus evolution and its epidemiological history, and to create epidemiological tools that can make reliable contact tracings and assess changes in epidemic dynamics. We have recently shown that the epidemic rate is inversely correlated to the virus evolutionary rate on the population level. Thus, the specific hypothesis behind the proposed research is that there is a relationship between the speed at which an epidemic moves through a human population and the rate at which the virus evolves in that population. We have observed that there are discrepancies between transmission histories and viral phylogenies, and because the inferences of epidemics are based on phylogenetics, it becomes important to understand the limitations in such inferences. Based on this the specific aims of this proposal are to: 1. Create a model that accurately describes the connection between transmission history and viral phylogeny. Preliminary results suggest that there are "hidden lineages" in viral phylogenies that are involved in transmission events, potentially misleading reconstruction of transmission events. We will especially investigate the effects of the effective population size in the donor, the bottleneck at transmission, and incomplete lineage sorting during transmission and sampling. We aim to estimate meaningful confidence levels on reconstructed person-to-person transmissions enabling us to explore alternative hypotheses in a statistical framework specifically designed for epidemiological tracking. 2. Identify the mechanism that correlates epidemic rate and virus evolutionary rate. We will decipher the connection between epidemic rate and viral evolutionary rate. Currently, we have four alternative explanations that may cause the observed correlation between epidemic and evolutionary rate (host immune selection, viral generation time effects, selection during transmission, and recombination effects). We will use different gene sequence data, codon positions as well as amino acid signatures to discriminate between these hypothetical explanations. We will use large datasets to develop epidemiological models that include these four hypothetical explanations to investigate their effects on the population level, and also model social networks and epidemic and phylogeographic dynamics. PUBLIC HEALTH RELEVANCE: The mathematical methods developed in this project aim to give better inferences of the spread of pathogens, here mainly HIV. At the contact tracing level we will estimate meaningful confidence levels on reconstructed person-to-person transmissions enabling us to explore alternative hypotheses in a statistical framework specifically designed for epidemiological tracking. At the epidemic level we will develop methods that can follow and signal when important changes in spread patterns occur, including the origin of the infection.