# Project 3: Tobacco Town Policy Modeling

> **NIH NIH P01** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2022 · $446,809

## Abstract

Project 3 Tobacco Town: Project Summary/Abstract
Tobacco use continues to be the greatest cause of preventable death and disease in the US,
and socioeconomic disparities persist in many communities and populations. New and
innovative tobacco control interventions focused on the retail environment are gaining ground,
and aim to reduce the pervasiveness of tobacco products and eliminate disparities, chiefly
through one of three mechanisms: place (e.g., lowering tobacco retailer density), price (e.g.,
curbing discounts), or product availability (e.g., limiting flavored tobacco products). However, the
evidence supporting the effectiveness of these strategies is just emerging. Developing a strong
evidence base for retail tobacco control is a priority for practitioners. While prospective
experimental studies to assess these interventions are difficult, if not impossible, to conduct,
computational modeling is poised to help fill the evidence gap. The goal of the proposed study is
to develop a computational agent-based model to examine and compare the potential impact of
various retail tobacco control strategies across different community contexts. The study has
three primary aims. 1) Develop Tobacco Town, an agent-based model that represents
community environments with individual current and potential tobacco users. The model will
incorporate realistic geographic and commercial spaces, individual tobacco use behaviors (e.g.,
initiation, cessation, purchase), and retailer practices (e.g., pricing and product availability). 2)
Use the model as a simulated laboratory to implement innovative strategies to better understand
how each might impact smoking-related behaviors. We will also consider the strategies in terms
of vulnerable populations, specifically racial/ethnic and sexual minorities and low-income
residents. 3) Tailor Tobacco Town to represent diverse neighborhoods in 10-12 large urban-
suburban areas in the US to examine potential context-specific effects of different interventions.
While helping to build the evidence base for innovative tobacco control strategies, the Tobacco
Town model will also enhance the relevance of this evidence through simulating various
interventions in different contexts. Finally, the model and its results will advance the use of
computational approaches to tobacco control and reducing tobacco use, and public health more
broadly.

## Key facts

- **NIH application ID:** 10471900
- **Project number:** 5P01CA225597-05
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** KURT M. RIBISL
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $446,809
- **Award type:** 5
- **Project period:** 2018-09-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10471900

## Citation

> US National Institutes of Health, RePORTER application 10471900, Project 3: Tobacco Town Policy Modeling (5P01CA225597-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10471900. Licensed CC0.

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