CHROME: Continuum of HIV Response through Observational Molecular Epidemiology - PROJECT SUMMARY/ABSTRACT Introduction. In the United States, the decline in HIV incidence over the preceding decades had stalled. In New York City, over 129,000 people are currently living with HIV/AIDS, around 1.4% of the population. Paramount to bringing about the end of the HIV epidemic, is ensuring that these individuals are engaged with medical care leading to antiretroviral therapy that suppresses the replication of HIV. This outcome not only improves the lives of people living with HIV but also precludes the possibility of onward sexual transmission. Success along the HIV care continuum—from diagnosis, to linkage to care, to antiretroviral therapy, to viral suppression—is facilitated by name-based HIV surveillance by public health departments. Ensuring success along the care continuum, including re-engagement with care, falls to local public health surveillance and prevention personnel. This public health surveillance approach, known as data-to-care, also includes the analysis of HIV genetic sequences produced for drug-resistance screening (i.e., molecular epidemiology), which can be used to characterize clusters of HIV transmission. Across the United States, these transmission clusters are used to prioritize public health services to reduce HIV incidence and facilitate engagement in care. These clusters can be useful in understanding trends in diagnosis rates as well as progression through the care continuum. However, nearly half of people with a recent HIV diagnosis lack a reported HIV genetic sequence. Methods. Here, we propose a retrospective study designed to evaluate the impact of these public health activities currently implemented in NYC. First, we will determine whether people without a reported HIV sequence—who are overlooked in molecular HIV surveillance activities—have faster or slower progression through the care continuum including re-engagement with care, compared with people who have a reported HIV sequence. Second, we will determine whether shared membership in molecular transmission clusters can be used to predict the success of re- engagement with care services resulting viral suppression. Third, we will develop a novel phylodynamic framework that permits the analysis of longitudinally-sampled data (e.g., HIV viral load and CD4+ count) in a viral phylogenetic trees to determine the relationship between viral suppression/re-engagement with care services and incident transmission in HIV transmission clusters. Conclusions. This study will provide a comprehensive picture of how HIV molecular epidemiology informed public health action can lead to success along the HIV care continuum improve and how this success can accelerate the decline of the HIV epidemic in the United States.
