RECONCILE HEALTH DISPARITIES. DIGNIFY HUMAN LIFE.

HiFi Lab develops and tests culturally-responsible intervention strategies that can be integrated and targeted to address determinants of HIV infection among African and African diaspora communities. Our research projects employ a range of research traditions, designs and methods including randomized controlled trials, structural equation modeling, ethnography and systematic reviews.

The HIV Prevention Trials Network, HPTN

Large-scale study in selected Ending the Epidemic (EHE) initiative communities with a focus on improving HIV outcomes for Black men who have sex with men (MSM) in the U.S. South. The project, HPTN 096: Building Equity Through Advocacy, is being led by three co-chairs, Dr. LaRon Nelson from Yale University, Dr. Robert Remien from Columbia University, and Dr. Chris Beyrer from Johns Hopkins University, along with a multidisciplinary team which includes researchers from U.S. universities, the Centers for Disease Control and Prevention (CDC), the Health Services Research Administration (HRSA), the National Institutes of Health (NIH), Fred Hutchinson Cancer Research Center, FHI 360 and several community partners. We are conducting HPTN 096 in collaborative partnership with EHE Planning Committees, health departments, community stakeholders and health service facilities. We believe that by working together to improve outcomes among Black MSM, we will increase our chances of success in achieving the goals of EHE.

This study is a community-randomized, controlled, hybrid type III implementation effectiveness study. The study will deliver an integrated strategy that includes a combination of four community-, organizational-, and interpersonal-level components designed to impact individual-level outcomes. A cross-sectional assessment will be conducted at baseline and at the end of the 3-year implementation period. Study endpoints will be assessed using study-collected data, routinely collected HIV surveillance data and commercially available prescription data.

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