# Development and validation of regional models of HIV vulnerabilities and solutions

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2022 · $572,495

## Abstract

PROJECT SUMMARY
To achieve critical health milestones (e.g., National HIV/AIDS Strategy1), the public health system needs
methods to predict HIV epidemiology within a region. An unexpected surge of new diagnoses in Miami, FL or
Austin, IN, may well be avoided if public health officials are able to forecast these changes and to intervene in
anticipation. However, modeling approaches are underutilized as mainstream tools to aid public health
decisions,2 owing to barriers including (a) unavailability of user-friendly methods that consider the
spatiotemporal relations among predictors of HIV transmission dynamics, (b) lack of inclusion of powerful big
social media data to gauge population norms and diffusion of information about HIV testing and prevention
services, (c) lack of integration of disperse yet relevant sources of data to predict HIV epidemiology, (d) lack of
visualization tools for the results of that integration, and (e) lack of models to gauge impact of new
interventions (e.g., an HIV vaccine), or changes in current interventions. In this application, we propose
methods that, if successful, will allow public health officials and the scientific community to make such refined
predictions and thereby to plan for interventions such as PrEP (PreExposure Prophylaxis). The project will rely
on existing but disperse sources of regional epidemiological, socio-structural, social media, and intervention
data to produce models and Cyber-GIS-HIV, a tool that can be used by public health officials and researchers.
The tool will analyze data and produce results in an integrated output identifying vulnerable regions, and
predicting future pockets of vulnerability and the effects of changes in intervention policy. We will integrate
epidemiological and biomedical service data recorded by health departments, data from the US Census, the
American Community Survey, the American Men Internet Survey, transmission network datasets, social media
data, and effect sizes from new interventions to derive predictions. We will also develop new methods for
social media analyses and compare spatio-temporal modeling techniques. The system will offer
recommendations about service allocation for a zip code, a county, and a region, set to introduce services
equally across areas, or to target the areas that would give the most improvement for the state as a whole. The
University of Illinois, Emory University, and the University at Albany offer the ideal social science, public health,
and computing infrastructure for this project. The team (Illinois: Albarracin, Chan, Li, Sundaram, and Wang;
Albany: Holtgrave) has developed cutting-edge big-data models to predict HIV and flu, as well as original
spatiotemporal analysis and existing state-of-the-art CyberGIS tools. Dr. Do at Emory served in the division of
HIV surveillance epidemiology at CDC for two decades and is now a faculty member. In addition, health
department personnel will be involved in designing and in testing Cyber...

## Key facts

- **NIH application ID:** 10434770
- **Project number:** 5R01AI147487-05
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** DOLORES ALBARRACIN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $572,495
- **Award type:** 5
- **Project period:** 2019-07-24 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10434770

## Citation

> US National Institutes of Health, RePORTER application 10434770, Development and validation of regional models of HIV vulnerabilities and solutions (5R01AI147487-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10434770. Licensed CC0.

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