The SimSmoke Tobacco Control Policy Simulation Model (Georgetown University) is a compartmental macro model that estimates the effect of tobacco control policies on smoking prevalence and smoking-attributable deaths. The original US SimSmoke model begins with a population in the baseline year 1993 (1,2), but a more recent version starts with the baseline data year 1965 (3). The population is distinguished by age and gender and evolves over time through birth and death rates. The 1965 population is further divided into never, current, and former smokers (distinguished by years since quit) using National Health Interview Survey (NHIS) smoking prevalence estimates, obtained as part of the CISNET smoking base case. Smoking is defined as having smoked more than 100 cigarettes over one’s lifetime and currently smoking on some or all days. Individuals evolve into and out of smoking through initiation, cessation, and relapse following a discrete first-order Markov process. Initiation and cessation estimates are obtained from the NHIS, and relapse is based on previous studies.
SimSmoke models the effects of multiple tobacco control policies, including cigarette taxes, smoke-free air laws, media campaigns, cessation treatment policies, health warnings, advertising restrictions, and youth access. To determine the relationship between policies and smoking rates, each of the policies relies on information from the literature as well as the advice of an expert panel. Policy effects depend on the level of the policy, with the initial effect on cessation occurring directly through a percentage reduction in prevalence in the first year when the policy was enacted, and subsequently applied to the initiation rate and to the first-year cessation rate in future years. When more than one policy is implemented, the percentage reductions are multiplied, implying that in the absence of synergies between policies, the effect of an additional policy is reduced proportional to the effect of any other policy.
SimSmoke (4-6) was extended using 2003 data from the Tobacco Use Supplement of the Current Population Survey to distinguish the effect of cessation treatment policies on quit attempts (QA), treatment use (TxUse, including pharmacotherapy and behavioral therapy), and treatment effectiveness (TxEFF). The model considers: (i) expanded cessation treatment reimbursement; (ii) telephone quit lines; (iii) brief provider interventions; (iv) Internet-based cessation programs; and (v) systems integration that includes tailoring of treatment, stepped care approaches, and continuity of care strategies. The model shows the synergies between cessation treatment policies that tend to promote quit success and other policies that tend to promote quit attempts. In distinguishing treatment use and effectiveness by types of treatment, the model is well suited to cost effectiveness analysis and to better understanding factors that inhibit quitting by different socioeconomic groups.
Actual policies are programmed into the US SimSmoke model for the tracking period, 1965 through 2014, which affect smoking rates over time. The model has been validated over the 50-year period 1965-2014 using the NHIS data, broken down by age and gender. The validated model shows the effect on smoking rates and smoking attributable deaths of policies implemented between 1965 and 2012, as well as the potential effect of future policies, thereby providing a justification for policies. Because the model shows how the effect of particular policies depends on the way in which they are implemented and the other policies in effect, the model has also been used for planning purposes. For example, the model has been used to evaluate the Healthy People 2010 goals (1) and in an Institute of Medicine report on minimum purchase age policies to reduce tobacco use (7).
References
- Levy DT, Nikolayev L, Mumford E, Compton C. The Healthy People 2010 smoking prevalence and tobacco control objectives: results from the SimSmoke tobacco control policy simulation model (United States). Cancer Causes Control. 2005;16(4):359-371.
- Levy DT, Nikolayev L, Mumford E. Recent trends in smoking and the role of public policies: results from the SimSmoke tobacco control policy simulation model. Addiction. 2005;100(10):1526-1536.
- Levy DT, Meza R, Zhang Y, Holford T. Gauging the Effect of U.S. Tobacco Control Policies from 1965 Through 2014 Using SimSmoke, Am J Prev Med. 2016;50(4):535-42.
- Levy DT, Graham AL, Mabry PL, Abrams DB, Orleans CT. Modeling the impact of smoking-cessation
treatment policies on quit rates. Am J Prev Med. Mar 2010;38(3 Suppl):S364-372.
- Levy DT, Mabry PL, Graham AL, Orleans CT, Abrams DB. Reaching Healthy People 2010 by 2013: A SimSmoke simulation. Am J Prev Med. Mar 2010;38(3 Suppl):S373-381.
- Levy DT, Mabry PL, Graham AL, Orleans CT, Abrams DB. Exploring scenarios to dramatically reduce smoking prevalence: a simulation model of the three-part cessation process. Am J Public Health. Jul 2010;100(7):1253-1259.
- Levy D. The Role of Public Policies in Reducing Smoking Prevalence: Results from the SimSmoke Tobacco Policy Simulation Model. In: Bonnie RJ, Stratton K, Wallace RB, eds. Ending the Tobacco Problem: A Blueprint for the Nation. Washington, DC: The National Academies Press; 2007.
