Molecular Epidemiology for HIV Prevention for Drug Users and Other Risk Groups

本项目的目标是整合来自本地研究、临床和公众的受试者数据 正在筛查和治疗艾滋病毒感染者的卫生实体。数据从这些 将以去识别的方式获取源，进行解析，然后组织成一个HIPAA 包含社会人口统计学、地理和系统发育信息的合规数据库 对于每一个主题。该数据库将被设置为真实的实时更新新的艾滋病毒感染 在我们的集水区被发现。此外，我们将使用病毒序列数据绘制 我们本地流行病的系统发育网络结构。我们将利用一个背景， 全国范围内的序列获得艾滋病毒序列库，以改善我们的信号 系统发育结构，并使用贝叶斯最大似然分析来建立这些 网络以强大的方式，利用我们机构的生物信息学专业知识， 加州大学圣地亚哥分校。我们还将以真实的时间更新此网络结构 随着新感染的发现，最后，我们将使用这种构建的监视 系统来绘制新的社会人口，地理和系统发育位置， 确定急性和早期艾滋病毒感染，并利用这些信息指导社区 具体的预防资源（即针具交换、教育资源等）， 防止艾滋病毒传播集群发展或扩大的最终目标。

The goal of this project is to integrate subject data from local research, clinical and public health entities that are screening for and treating HIV infected individual. Data from these sources will be obtained in a de‐identified manner, parsed and then organized into a HIPAA compliant database containing socio‐demographic, geographic and phylogenetic information for each subject. The database will be set up to update itself in real‐time as new HIV infections are identified in our catchment area. In addition, we will use the viral sequence data to map out the phylogenetic network structure of our local epidemic. We will utilize a background of nationwide sequences obtained HIV sequence repositories to improve the signal in our phylogenetic structures, and use Bayesian maximum likelihood analysis to build these networks in a robust manner, leveraging the bioinformatics expertise at our institution, the University of California, San Diego. We will also update this network structure in a real‐time fashion as new infections are identified. Finally we will use this constructed surveillance system to map the socio‐demographic, geographic and phylogenetic locations of newly identified acute and early HIV infections, and use this information to direct community specific prevention resources (i.e. needle exchange, education resources etc…) with the ultimate goal of preventing HIV transmission clusters from developing or expanding.