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.
This research project will (i) use evolutionary principles to guide HIV treatment and clinical trial design and (ii) develop web-based computer software to assist researchers in monitoring the progression of the HIV pandemic. This work will improve the efficacy of treatment, the scope of clinical trials, and HIV surveillance efforts.