# Using agent-based modeling to estimate the effectiveness of the Miami Getting to Zero HIV campaign

> **NIH NIH K01** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2022 · $44,862

## Abstract

Project Summary/Abstract
Agent-based modeling has provided epidemiologists with an advanced tool to estimate critical epidemiologic
outcomes among large, diverse populations. The proposed research will build on a well-established model
platform, the HIV-Calibrated Dynamic Model (HIV-CDM), to construct a model of the HIV epidemic in Miami,
which experiences among the highest rates of new HIV infection in the country.
In response to the growing HIV epidemic in Miami, local policymakers, clinicians, and researchers have formed
a “Getting to Zero” Task Force that seeks to eliminate all new HIV infections in the Miami metropolitan area.
The campaign is founded on the principle of combination prevention, which enlists the concurrent use of many
evidence-based prevention strategies, such as treatment as prevention, pre-exposure prophylaxis (PrEP), and
frequent/targeted HIV testing. Presently it is unknown what effect this campaign will have on incident HIV
infections in Miami. This proposal seeks to use agent-based modeling to estimate the long-term impact of the
combination prevention program outlined in the Getting to Zero campaign adopted in 2017. Along with
estimating specific epidemic outcomes (e.g., HIV incidence, HIV prevalence, time to epidemic elimination), this
approach may also assess the relative contribution of each component to the success of the program. Such
estimates will be crucial in maximizing the goals of the campaign, as well as assist with the implementation of
similar HIV elimination programs.
This proposal will: (1) expand the HIV-CDM model, to simulate the demographics and HIV risk behavior of the
diverse metropolitan Miami population; (2) estimate the success and limitations of the Getting to Zero
campaign using the HIV-CDM model; and (3) perform primary and secondary analyses within subgroups of the
Miami population to better understand current research gaps, and those identified in the first two aims. Each
component of the research plan will be supported and aligned with specific training components designed to
provide the candidate with the necessary professional development and mentorship to execute the research
aims, and begin an independent research career.
The results obtained from this work may directly impact the assessment of the Miami Getting to Zero campaign
and inform all future HIV elimination campaigns in the U.S. and globally. Additionally, the training program will
provide exceptional methodological and practical experience leading to an independent and influential scientific
career. Supporting this work will be a mentorship team of academic and community leaders in HIV elimination,
epidemiology and modeling methodology. This mentorship will build on the methodological and substantive
experience I have demonstrated while leading numerous studies on epidemic modeling and HIV epidemiology.

## Key facts

- **NIH application ID:** 10694567
- **Project number:** 7K01AI138863-06
- **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** Daniel Escudero
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $44,862
- **Award type:** 7
- **Project period:** 2018-02-22 → 2025-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10694567

## Citation

> US National Institutes of Health, RePORTER application 10694567, Using agent-based modeling to estimate the effectiveness of the Miami Getting to Zero HIV campaign (7K01AI138863-06). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10694567. Licensed CC0.

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