# MODELING COMBINATION BIOMEDICAL SUBSTANCE USE INTERVENTIONS TO INFORM A GETTING TO ZERO IMPLEMENTATION FOR BLACK MEN WHO HAVE SEX WITH MEN

> **NIH NIH R03** · BROWN UNIVERSITY · 2020 · $41,990

## Abstract

Project Summary/Abstract
Getting to Zero (GTZ) and other HIV elimination initiatives have gained momentum in the United States
following the UNAIDS strategic plan GTZ in 2010. These initiatives have typically focused on HIV elimination
within local jurisdictions and been driven by a plateauing domestic HIV incidence combined with growing use of
biomedical prevention modalities such as antiretroviral treatment (ART) initiation for treatment-as-prevention,
and pre-exposure prophylaxis (PrEP). While overall HIV incidence in Illinois (and across the U.S.) has
plateaued over the past decade, these declines have not been experienced equally by sub-populations.
Younger (18-34 years) Black gay, bisexual and other MSM (YBMSM) have experienced relatively stable
incidence rates. These observations support development of interventions designed to reduce HIV incidence
among YBMSM. The scale-up of ART and PrEP among BMSM is constrained in part because of the many
barriers that prevent their wider use among YBMSM. Addiction, mental health conditions, criminal justice
involvement, and unemployment upon release from custody are some of the barriers that disproportionately
impact YBMSM. Substance use is one such barrier, and it has been associated with suboptimal ART
adherence and missed PrEP doses among MSM. Substance use interventions have been found to reduce
behaviors that elevate risk for HIV acquisition, engagement in the continuums of ART care, and PrEP
retention. Combination biomedical substance use interventions may therefore provide a pathway to decrease
HIV incidence that may be more implementable than the current scenarios considered. It is difficult, however,
to design evidence-based interventions that will optimally implement GTZ goals. Computational models can
provide an in-silico laboratory to examine how the impact of such combination interventions can be maximized.
Rigorous examination of how the impact of such combination interventions can be optimized should be used to
inform best practices prior to intervention roll-out. Agent-based network models (ABNMs) provide a
computationally rigorous, yet flexible, platform that allow for inclusion of a variety of micro-level individual
behaviors, meso-level network factors, and their feedbacks with macro-level population structures, which allow
for rigorous examination of processes and their parameterization at multiple scales. ABNMs can therefore
promote development of multilevel interventions prior to their roll-out. In the proposed study, we will: (1)
develop a comprehensive suite of parameters that describe the impact of stimulant use on ART and PrEP care
continuums among YBMSM in Illinois; (2) recalibrate an existing ABNM of HIV transmission among YBMSM
using the parameters collected above to develop modules that account for the impact of stimulant use on
engagement in the ART and PrEP continuums; (3) estimate the potential efficacy of combination biomedical
substance use interventions.

## Key facts

- **NIH application ID:** 10333380
- **Project number:** 7R03DA049662-03
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Aditya Subhash Khanna
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $41,990
- **Award type:** 7
- **Project period:** 2021-01-26 → 2021-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10333380

## Citation

> US National Institutes of Health, RePORTER application 10333380, MODELING COMBINATION BIOMEDICAL SUBSTANCE USE INTERVENTIONS TO INFORM A GETTING TO ZERO IMPLEMENTATION FOR BLACK MEN WHO HAVE SEX WITH MEN (7R03DA049662-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10333380. Licensed CC0.

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