# Computational approaches to understand the impact of social determinants of health on HIV care continuums

> **NIH NIH R21** · UNIVERSITY OF CHICAGO · 2022 · $205,000

## Abstract

PROJECT SUMMARY/ABSTRACT
Background: Black men who have sex with men (MSM) are disproportionately affected by HIV and other
socio-structural factors that contribute to inequities along the HIV prevention and care continuum. Evidence
suggests that factors such as housing instability, criminal justice involvement, and unemployment may pose
significant barriers to engagement in HIV prevention and care for Black MSM. To date however, existing
interventions have been ineffective at addressing these barriers for Black MSM. Because such interventions
are resource intensive and logistically challenging, particularly for vulnerable communities who are often highly
mobile and less likely to engage in research in traditional settings, guidance is needed at the intervention
development stage to determine the most impactful and efficient intervention strategies. Agent-based models
(ABMs) provide an opportunity to virtually evaluate candidate interventions to facilitate more efficient and timely
intervention development. Because they allow for the conduct of counterfactual experiments, ABMs can also
facilitate identification of effects that would be difficult to isolate using traditional approaches and provide
valuable insights to guide implementation of HIV prevention interventions. Objective: Building on an existing
modeling platform, this proposal will utilize multiple existing data sources to characterize relationships among
socio-structural stressors, psychosocial mediators, and HIV prevention and care continuum outcomes among
Black MSM and combine methods from implementation science and agent-based modeling to understand the
potential impact of structural interventions for reducing HIV transmission. Methods: We will utilize local
empirical data to create a realistic synthetic population within an existing agent-based model and apply
statistical and computational methods to better understand how socio-structural factors impact engagement in
HIV prevention and care continuums. We will then conduct a series of experiments to evaluate how socio-
structural factors impact the uptake of existing biomedical interventions and compare outcomes under
scenarios with different combinations of interventions Significance: A better understanding of where and how
to focus intervention efforts offers potential to improve outcomes along the care continuum by addressing
socio-structural barriers to HIV prevention and care engagement for Black MSM. Once developed, our
approach can be adapted to other geographic areas to reflect prevention priorities for local health departments
and can serve as an example application of ABM methods within implementation science to advance HIV
prevention science.

## Key facts

- **NIH application ID:** 10447767
- **Project number:** 5R21MH128116-02
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Anna Hotton
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $205,000
- **Award type:** 5
- **Project period:** 2021-07-08 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10447767

## Citation

> US National Institutes of Health, RePORTER application 10447767, Computational approaches to understand the impact of social determinants of health on HIV care continuums (5R21MH128116-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10447767. Licensed CC0.

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