# Towards prevention of HIV among vulnerable and stigmatized populations using geospatial data

> **NIH NIH K01** · DREXEL UNIVERSITY · 2020 · $118,767

## Abstract

HIV remains a global public health priority and occurs disproportionality among minority and stigmatized
populations such as men who have sex with men (MSM). The occurrence of HIV is not random in the population,
rather it exhibits patterns by individual and contextual factors. Is it the contextual factors, such as the
neighborhood where one lives, socializes, or engages in sex, that is the focus of the proposed research. This
proposed program of training and research examines the geospatial features of HIV using epidemiological data and
analyses. The overarching goal is to improve the epidemiology of studying HIV by incorporating geospatial
measures into HIV risk models through three areas. First, opportunities exist to tailor and refine existing HIV
surveillance programs towards the most vulnerable groups using contextual determinants of risk. A second
opportunity is to improve the validity of geospatial analyses through more accurate measurement and correct
quantification of the spatial unit. A final opportunity is to improve risk quantification and reduce biased inference
by applying spatial features of disease distribution to studying HIV risk. Taken together, attention to these three
insights can improve HIV surveillance and epidemiology to guide prevention services.
This project utilizes Philadelphia Department of Public Health’s AIDS Activities Coordinating Office surveillance
data of people living with HIV/AIDS in Philadelphia in conjunction with data obtained via systematic review.
Research questions to be answered include the optimal placement of HIV screening services in Philadelphia, the
most appropriate choice of contextual unit to analyze spatial data (e.g., neighborhood, ZIP code, census tract), and
the impact of sexual networks based upon geographic location of partner selection. Analyses will include advanced
geospatial methods, hierarchical regression modeling, and agent-based simulation models. Follow-up work will
include joint systems dynamic and agent-based models with a focus on health disparities in HIV.
The proposed research will be complemented by experiential and didactic training in (1) geographic information
systems and spatial analysis of epidemiologic data, (2) systems science and health disparities, and (3)
epidemiological surveillance systems with a focus on HIV surveillance. This research and training will enable a
program of independent research on the contextual factors relating neighborhood and HIV transmission and
infection among vulnerable and stigmatized populations.

## Key facts

- **NIH application ID:** 10006327
- **Project number:** 5K01AI143356-02
- **Recipient organization:** DREXEL UNIVERSITY
- **Principal Investigator:** Neal D Goldstein
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $118,767
- **Award type:** 5
- **Project period:** 2019-09-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10006327

## Citation

> US National Institutes of Health, RePORTER application 10006327, Towards prevention of HIV among vulnerable and stigmatized populations using geospatial data (5K01AI143356-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10006327. Licensed CC0.

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