# Are Ending the HIV Epidemic goals attainable across race/ethnic groups, risk groups, and settings?

> **NIH NIH R01** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2024 · $820,845

## Abstract

Project Abstract
In collaboration with the Shelby County Health Department, which has jurisdiction over Memphis as well as
rural northwest Mississippi and Arkansas, we propose to inform policy decisions towards improving HIV
outcomes for population-level and subgroup-specific HIV goals in three diverse settings that together typify
high incidence locations in the U.S. HIV epidemic (New York City, Memphis, and northwest Mississippi).
We will use mathematical modeling to simulate alternative ways to distribute resources across interventions,
settings, and target populations to reduce HIV incidence and improve overall health. Our analyses will be
distinguished by incorporating screening and responding to CASM conditions (Conditions of Alcohol,
Substance and Mood), measures of inequality-aversion (i.e., willingness to trade-off some aggregate benefit in
order to distribute it more equally) towards vulnerable subgroups, and the promising new modalities of long-
acting-injectable PrEP and ART. Our partners at the Shelby County Health Department and their larger group
of stakeholders will provide context on local HIV infection patterns and feasibility and acceptability constraints
to inform modeling analyses.

## Key facts

- **NIH application ID:** 11009175
- **Project number:** 1R01AA031644-01A1
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Ronald Scott Braithwaite
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $820,845
- **Award type:** 1
- **Project period:** 2024-09-15 → 2029-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11009175

## Citation

> US National Institutes of Health, RePORTER application 11009175, Are Ending the HIV Epidemic goals attainable across race/ethnic groups, risk groups, and settings? (1R01AA031644-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11009175. Licensed CC0.

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