Computational Models Used to Assess US Tobacco Control Policies.
BACKGROUND
Simulation models can be used to evaluate existing and potential tobacco control interventions, including policies. The purpose of this systematic review was to synthesize evidence from computational models used to project population-level effects of tobacco control interventions. We provide recommendations to strengthen simulation models that evaluate tobacco control interventions.


METHODS
Studies were eligible for review if they employed a computational model to predict the expected effects of a non-clinical US-based tobacco control intervention. We searched five electronic databases on July 1, 2013 with no date restrictions and synthesized studies qualitatively.


RESULTS
Six primary non-clinical intervention types were examined across the 40 studies: taxation, youth prevention, smoke-free policies, mass media campaigns, marketing/advertising restrictions, and product regulation. Simulation models demonstrated the independent and combined effects of these interventions on decreasing projected future smoking prevalence. Taxation effects were the most robust, as studies examining other interventions exhibited substantial heterogeneity with regard to the outcomes and specific policies examined across models.


CONCLUSIONS
Models should project the impact of interventions on overall tobacco use, including nicotine delivery product use, to estimate preventable health and cost-saving outcomes. Model validation, transparency, more sophisticated models, and modeling policy interactions are also needed to inform policymakers to make decisions that will minimize harm and maximize health.


CONCLUSIONS
In this systematic review, evidence from multiple studies demonstrated the independent effect of taxation on decreasing future smoking prevalence, and models for other tobacco control interventions showed that these strategies are expected to decrease smoking, benefit population health, and are reasonable to implement from a cost perspective. Our recommendations aim to help policymakers and researchers minimize harm and maximize overall population-level health benefits by considering the real-world context in which tobacco control interventions are implemented.
The Schroeder Institute for Tobacco Research and Policy Studies at Truth Initiative, Washington, DC.
Shari P
SP
Feirman
The Schroeder Institute for Tobacco Research and Policy Studies at Truth Initiative, Washington, DC.
Allison M
AM
Glasser
The Schroeder Institute for Tobacco Research and Policy Studies at Truth Initiative, Washington, DC.
Shyanika
S
Rose
The Schroeder Institute for Tobacco Research and Policy Studies at Truth Initiative, Washington, DC.|Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.|Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC.
Ray
R
Niaura
The Schroeder Institute for Tobacco Research and Policy Studies at Truth Initiative, Washington, DC.|Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.|Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC.
David B
DB
Abrams
Department of Evaluation, Science and Research, Truth Initiative, Washington, DC.|Zanvyl Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, MD.
Lyubov
L
Teplitskaya
The Schroeder Institute for Tobacco Research and Policy Studies at Truth Initiative, Washington, DC.|Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Andrea C
AC
Villanti
D033161:Government Regulation; D006801:Humans; D008962:Models, Theoretical; D061845:Smoke-Free Policy / Q000331:legislation & jurisprudence*; D012907:Smoking / Q000331:legislation & jurisprudence*; D016540:Smoking Cessation / Q000331:legislation & jurisprudence*; D013660:Taxes; D014481:United States