# Capturing Rural Risk Network Structures from Continuous-time Interaction Data (RISC)

> **NIH NIH P20** · UNIVERSITY OF NEBRASKA LINCOLN · 2021 · $249,477

## Abstract

PROJECT ABSTRACT
Rural drug use in the Central Plains is a large and growing public health problem. Recent substance abuse data
show that Nebraska, Iowa, and Missouri are all in the top 10 states for methamphetamine-related hospital
admissions. The high level of substance abuse is coupled with a severe lack of treatment facilities in these rural
areas, as well as restrictive syringe access laws. These conditions (high substance use, few treatment facilities,
and lack of access to clean needles) combine to create a vulnerable population, one particularly at risk for the
spread of infectious diseases, like HIV and hepatitis C virus (HCV). For example, a well-publicized HIV outbreak
in southern Indiana occurred in 2015, revealing widespread rural drug use. Outbreaks like this demonstrate that
even populations with low rates of HIV (for example) may be structurally at risk for an epidemic. Despite the
urgency of the rural drug use problem, relatively little is known about the network and behavioral risk factors of
rural drug users. Most of the data on illicit drugs come from urban settings, even while rural drug use and related
health outcomes have increased over the last few decades. The lessons learned from urban drug users are
unlikely to hold in rural areas, where conditions and experiences can be quite different; for example, rural drug
users tend to have small social circles, limited chances for social or economic mobility, high availability of drugs,
and few drug treatment venues. This project, as part of the larger Rural Drug Addiction Research Center, will fill
in crucial gaps in the knowledge of rural drug use and associated health risks while investigating the potential
efficacy of different interventions. In particular, the social network dynamics and behavioral contexts that
contribute to the risk of HCV and HIV infection will be investigated in three rural areas surrounding communities
in Nebraska, Iowa, and Missouri. Behavioral risks associated with HIV and HCV spread, as well as the structure
of the drug use network, will be measured as important risk factors for disease spread (Aim 1). Using these data,
an empirically-grounded, epidemiological simulation will be developed. The simulation approach makes it
possible to pinpoint the conditions under which an epidemic is possible and describe the possible efficacy of
different interventions in limiting a potential outbreak. Previous network models will be extended by combining
traditional survey data with innovative, continuous-time interaction data, resulting in an epidemiological
framework that measures factors like relationship timing, context, and geography (Aim 2), factors that are known
to affect disease spread but have previously been difficult to quantify. This simulation will then be used to
characterize the risk of HIV/HCV spread in this drug user population (Aim 3). Overall, the project will offer timely,
crucial information about a rural, at-risk population. The broad, long-t...

## Key facts

- **NIH application ID:** 10117091
- **Project number:** 5P20GM130461-03
- **Recipient organization:** UNIVERSITY OF NEBRASKA LINCOLN
- **Principal Investigator:** Jeffrey Smith
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $249,477
- **Award type:** 5
- **Project period:** 2019-04-05 → 2024-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10117091

## Citation

> US National Institutes of Health, RePORTER application 10117091, Capturing Rural Risk Network Structures from Continuous-time Interaction Data (RISC) (5P20GM130461-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10117091. Licensed CC0.

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