# Building an innovative Ethno-Geographic Information System (EGIS) to address opioid overdose disparities in Inland So Ca

> **NIH NIH R21** · UNIVERSITY OF CALIFORNIA RIVERSIDE · 2022 · $189,271

## Abstract

PROJECT SUMMARY
 In the United States, drug overdose is the leading cause of injury-related death. Nationally, narratives of
opioid overdose as a predominantly White suburban crisis tell only a partial story, overshadowing the
importance of local geosocial contexts in producing overdose disparities in marginalized and underserved
communities. As one example, Riverside County is California’s third-largest in population, representing a
socioeconomically, racially, and geographically diverse region characterized by widespread health disparities
and a shortage of healthcare providers. Overdose rates have been rising for more than a decade; nearly half of
all overdoses are among non-White populations, and deaths have increased among Blacks by 30%, Native
Americans by 47%, and Latinos by 52%, while 5-year average overdose rates are highest in several
predominantly minority and rural communities beyond the county’s urban hub, the City of Riverside. We
consider Riverside County as a “risk environment,” defined as the social and physical spaces where contextual
factors interact to cluster harms among disadvantaged populations. However, the spatial characteristics of
overdose risk environments are not well characterized because current spatial models lack ethnographic
granularity on how structural factors shape lived experiences of opioid use. Thus, we ask: how do we better
characterize opioid overdose disparities to enhance our response across diverse social geographies?
 The overall goal of this project is to develop an innovative Ethno-Geographic Information System
(EGIS) that combines ethnography with spatial analytics to characterize opioid overdose and guide research
and resource allocation to reduce overdose disparities in underserved communities. The specific aims of the
project are to: 1) Develop spatially-explicit models relating epidemiologic indicators of opioid overdose (i.e.,
overdose mortality, EMS calls) to spatial contextual variables hypothesized to influence the risk of overdose.
These models will combine to create a “risk surface” map of Riverside County and identify which aspects of
spatial context are associated with opioid overdose disparities through the use of formal spatial analytical
methods. 2) Examine the structural, social, and spatial contexts of overdose among a diverse sample of people
who use opioids via ethnographic methods (observations, in-depth interviews, and ethnographic mapping).
This work will build upon, contextualize, and reconsider the risk surface map developed in Aim 1 using on-the-
ground data to explain observed opioid overdose disparities. 3) Integrate the geospatial and ethnographic data
from Aims 1 and 2 to develop an Ethno-Geographic Information System (EGIS) that characterizes opioid
overdose disparities to guide resource allocation and future research efforts focused on reducing disparities.
Our research will provide an innovative new method, EGIS, to serve as a foundation for developing and testing
co...

## Key facts

- **NIH application ID:** 10447815
- **Project number:** 5R21DA054611-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA RIVERSIDE
- **Principal Investigator:** Jennifer Leigh Syvertsen
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $189,271
- **Award type:** 5
- **Project period:** 2021-07-15 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10447815

## Citation

> US National Institutes of Health, RePORTER application 10447815, Building an innovative Ethno-Geographic Information System (EGIS) to address opioid overdose disparities in Inland So Ca (5R21DA054611-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10447815. Licensed CC0.

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