Public Health Implications of HIV Transmission Networks

描述(申请人提供)：艾滋病毒是一种快速进化的病原体，在每个感染患者中导致几乎唯一的病毒基因序列。这种快速的进化使疫苗设计和抗逆转录病毒治疗变得复杂。然而，基因序列的变化也可以用来重建病毒的传播历史。事实证明，系统发育方法对于了解艾滋病毒的起源、多样化和全球迁移是有用的。然而，分子进化分析用于公共卫生目标的潜力仍然没有得到充分的认识和开发。以前关于艾滋病毒传播网络性质的研究表明，网络中连接最紧密的部分的个人在未来传播病毒的潜力最大。方法：研究方法。在这项应用中，纽约市卫生和精神卫生部门(NYC-DOHMH)在耐药性监测期间获得的艾滋病毒序列将用于构建纽约市的艾滋病毒传播网络。通过识别病毒序列高度相似的感染者，可以识别潜在的传播伙伴并将其联系起来，以构建传播网络。针对整个网络中联系最紧密的个人的干预(抗逆转录病毒治疗、治疗性疫苗接种、暴露前预防[PrEP]等)的模拟将被执行，并与随机抗逆转录病毒干预的模拟进行比较。这些模拟的目标是确定网络知情的有针对性的干预策略 可以降低HIV感染的发生率。此外，还将在NYC-DOHMH网络上进行模拟临床预防试验，以开发网络信息指标、方法和协议，以测试临床预防试验中减少传播的情况。最后，同样的网络构建方法将应用于所有可公开获得的艾滋病毒序列，以开发一种监测工具，使其他研究人员能够迅速确定他们产生的艾滋病毒序列如何适应全球艾滋病毒传播网络。结论。这些发现将展示如何利用艾滋病毒传播网络来指导有效的治疗战略、改进临床试验设计和监测大流行的进展。

DESCRIPTION (provided by applicant): HIV is a rapidly evolving pathogen, which results in nearly unique viral genetic sequence in every infected patient. This rapid evolution complicates vaccine design and antiretroviral therapy. However, changes in the genetic sequence can also be used to reconstruct the transmission history of the virus. Phylogenetic approaches have proven useful for understanding the origins, diversification, and worldwide migration of HIV. However, the potential for molecular evolutionary analysis to be utilized for public health goals remains underappreciated and underexplored. Previous work on the nature of HIV transmission networks suggests that individuals in the most highly connected parts of the network have the greatest potential to transmit virus in the future. Methods. In this application, HIV sequences that were acquired during drug- resistance surveillance by the New York City Department of Health and Mental Hygiene (NYC-DOHMH) will be used to construct the HIV transmission network in New York City. By identifying infected individuals whose viral sequences are highly similar, potential transmission partners can be identified and linked to construct a transmission network. Simulations of intervention (antiretroviral treatment, therapeutic vaccination, pre- exposure prophylaxis [PrEP], etc), targeted at the most highly connected individuals across this network will be performed and compared to simulations of random antiretroviral intervention. The goal of these simulations is to identify network-informed targeted intervention strategies that could reduce the incidence of HIV infection. Additionally, simulated clinical preventive trials wil also be performed across the NYC-DOHMH network to develop network-informed metrics, methods, and protocols to test for reduced transmission in a clinical preventative trial. Finally, this same network construction approach will be applied to all publicly available HIV sequences to develop a surveillance tool which will allow other researchers to rapidly determine how their generated HIV sequences fit into the global HIV transmission network. Conclusions. These findings will demonstrate how HIV transmission networks can be used to guide effective treatment strategies, improve clinical trial design, and monitor the progression of the pandemic.