# Using agent-based modeling to compare strategies that can reduce rural-urban disparities in cardiovascular disease

> **NIH NIH R01** · UNIVERSITY OF GEORGIA · 2020 · $384,088

## Abstract

Project Summary
Rural-urban disparities in mortality attributable to cardiovascular disease (CVD) have widened in the United
States during the past several decades. The complex interplay of preventive health care delivery and
community-level behavioral and contextual factors contribute to the differences in cardiovascular health
between rural and urban residents. Recently, systems science and simulation modeling have played an
important role in the evaluation, selection, and implementation of evidence-based interventions. However,
existing models do not account for either the specific characteristics of populations living in rural
communities, or the health care services and other contextual factors of these communities. We propose to
use agent-based modeling -- a systems science approach that incorporates data from various sources and
simulates real-world clinical or community settings -- to help disentangle these complexities, elucidate
causal pathways, and identify potentially effective interventions in rural communities.
Our long-term goal is to find effective clinical and public health solutions to reduce rural-urban disparities in
cardiovascular health among rural communities in Georgia and New York. Taking an integrated preventive
health care and community perspective, we will accomplish our specific aims using an agent-based model
of community-based CVD prevention and test the effectiveness of the following interventions at the rural
county level. First, we will estimate the health impact of improving health care delivery and access using
home-based telemonitoring programs and expanding insurance coverage, focusing on three major CVD risk
factors: hypertension, diabetes and high cholesterol (Aim 1). Second, we will estimate the health impact of
public health interventions, including improving the food environment, community-based health promotion,
and increasing tobacco taxes for reducing four important lifestyle factors related with CVD: obesity,
unhealthy diet, physical inactivity, and smoking (Aim 2). In Aim 3, we will use the CVD Policy Model, a well-
validated US population-based CVD epidemiology simulation model and translate projected beneficial
effects on the seven risk factors and lifestyles tested in Aim 1 and 2 into downstream impact on CVD
events. This will allow us to assess the potential of these individual or combined interventions on rural-urban
disparities in the incidence and mortality of CVD and direct medical costs at the state level. The proposed
research is innovative because we develop a policy simulation model to inform decision-making for health
care and public health management of CVD in rural counties, integrating clinical with community systems to
find the most effective evidence-based intervention.

## Key facts

- **NIH application ID:** 9976596
- **Project number:** 5R01MD013886-02
- **Recipient organization:** UNIVERSITY OF GEORGIA
- **Principal Investigator:** Donglan Zhang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $384,088
- **Award type:** 5
- **Project period:** 2019-07-11 → 2023-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9976596

## Citation

> US National Institutes of Health, RePORTER application 9976596, Using agent-based modeling to compare strategies that can reduce rural-urban disparities in cardiovascular disease (5R01MD013886-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9976596. Licensed CC0.

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