Mathematical Modeling in Tobacco Control Research: Initial Results From a Systematic Review

The US Food and Drug Administration has expressed interest in using mathematical models to evaluate potential tobacco policies. The goal of this systematic review was to synthesize data from tobacco control studies that employ mathematical models.

We searched five electronic databases on July 1, 2013 to identify published studies that used a mathematical model to project a tobacco-related outcome and developed a data extraction form based on the ISPOR-SMDM Modeling Good Research Practices. We developed an organizational framework to categorize these studies and identify models employed across multiple papers. We synthesized results qualitatively, providing a descriptive synthesis of included studies.

The 263 studies in this review were heterogeneous with regard to their methodologies and aims. We used the organizational framework to categorize each study according to its objective and map the objective to a model outcome. We identified two types of study objectives (trend and policy/intervention) and three types of model outcomes (change in tobacco use behavior, change in tobacco-related morbidity or mortality, and economic impact). Eighteen models were used across 118 studies.

This paper extends conventional systematic review methods to characterize a body of literature on mathematical modeling in tobacco control. The findings of this synthesis can inform the development of new models and the improvement of existing models, strengthening the ability of researchers to accurately project future tobacco-related trends and evaluate potential tobacco control policies and interventions. These findings can also help decision-makers to identify and become oriented with models relevant to their work.