The Kentucky SimSmoke tobacco policy simulation model: reaching Healthy People 2010 goals through policy change

The Kentucky SimSmoke Tobacco Control Policy Model of Smokeless Tobacco and Cigarette Use

BACKGROUND

Smokeless tobacco (SLT) prevalence was decreasing in Kentucky before 2007, but has since increased. This study examines the impact of policies on cigarette and SLT use by applying the SimSmoke tobacco control policy simulation model.

METHODS

Using data from the large-scale Tobacco Use Supplement of the Current Population Survey (TUS-CPS) and information on state-specific tobacco policies, Kentucky SimSmoke is updated and extended to incorporate exclusive SLT and dual cigarette and SLT use. The model is validated using survey data through 2017. The model was used to estimate the impact on smoking and SLT prevalence and attributable deaths of policies implemented between 1993 and 2018 and the impact of stronger future policies implemented in 2018 and maintained through 2060.

RESULTS

SimSmoke generally reflects trends in exclusive cigarette use from the TUS-CPS and the Behavioral Risk Factor Surveillance System (BRFSS), but underestimated the increase in SLT prevalence in recent years. SimSmoke projects that policies implemented between 1993 and 2018 reduced male and female cigarette use by 23.7% and 23.0%, and male and female SLT use by 4.9% by 2018, averting 9018 tobacco-attributable deaths by 2018, increasing to 89 547 by 2060. The largest reductions in cigarette and SLT use were attributed to cigarette price increases. Strengthening tobacco control policies could reduce smoking prevalence by 41% and 40%, and reduce SLT prevalence by 33% and 25% for males and females by 2060.

CONCLUSION

Our results suggest that cigarette-oriented policies were effective in reducing SLT use but have been less successful in recent years. Future use rates can be further reduced through more restrictive statewide policies, which also target non-combustible nicotine products.

The Minnesota SimSmoke Tobacco Control Policy Model of Smokeless Tobacco and Cigarette Use

INTRODUCTION

A previous Minnesota SimSmoke tobacco control policy model is extended to more recent years and to include smokeless tobacco use.

METHODS

Using data from the 1993 Tobacco Use Supplement and information on state policies, the Minnesota SimSmoke model was updated and extended to incorporate smokeless tobacco (both exclusive and dual use) and smokeless tobacco-attributable deaths. The model was then validated against the 2002, 2006/2007, and 2014/2015 Tobacco Use Supplement and the 1999, 2007, 2014, and 2018 Minnesota Adult Tobacco Survey and used to estimate the impact of policies implemented between 1993 and 2018. Analysis was conducted in April 2019.

RESULTS

The model validated well for cigarette and earlier smokeless tobacco use, but it predicted smokeless tobacco use less well in recent years. The model projected that male (female) smoking prevalence was 35% (36%) lower in relative terms by 2018 and 43% (44%) lower by 2040 owing to policies, with lesser reductions projected for male smokeless tobacco use. Tobacco-attributable deaths were reduced by 7,800 by 2018 and 46,900 by 2040. Price increases, primarily through taxes, were projected to have had the greatest impact on cigarette use followed by smoke-free air laws, cessation treatment policies, tobacco control campaign expenditures, and youth access enforcement. Similar effects were projected for smokeless tobacco use, except that smoke-free air laws had smaller effects.

CONCLUSIONS

As cigarettes remain the dominant form of nicotine delivery product, cigarette-oriented policies may be an effective means of reducing the use of all nicotine delivery products. However, noncigarette-oriented policies may also play an important role.

The US SimSmoke tobacco control policy model of smokeless tobacco and cigarette use

Background

Smokeless tobacco (SLT) prevalence had been declining in the US prior to 2002 but has since increased. Knowledge about the impact of tobacco control policies on SLT and cigarette use is limited. This study examines the interrelationship between policies, cigarette use, and SLT use by applying the SimSmoke tobacco control policy simulation model.

Methods

Using data from large-scale Tobacco Use Supplement and information on policies implemented, US SimSmoke was updated and extended to incorporate SLT use. The model distinguishes between exclusive SLT and dual use of SLT and cigarettes, and considers the effect of implementing individual and combined tobacco control policies on smoking and SLT use, and on deaths attributable to their use. After validating against Tobacco Use Supplement (TUS) survey data through 2015, the model was used to estimate the impact of policies implemented between 1993 and 2017.

Results

SimSmoke reflected trends in exclusive cigarette use from the TUS, but over-estimated the reductions, especially among 18–24 year olds, until 2002 and under-estimated the reductions from 2011 to 2015. By 2015, SimSmoke projections of exclusive SLT and dual use were close to TUS estimates, but under-estimated reductions in both from 1993 to 2002 and failed to estimate the growth in male exclusive SLT use, especially among 18–24 year olds, from 2011 to 2015. SimSmoke projects that policies implemented between 1993 and 2017 reduced exclusive cigarette use by about 35%, dual use by 32.5% and SLT use by 16.5%, yielding a reduction of 7.5 million tobacco-attributable deaths by 2067. The largest reductions were attributed to tax increases.

Conclusions

Our results indicate that cigarette-oriented policies may be effective in also reducing the use of other tobacco products. However, further information is needed on the effect of tobacco control policies on exclusive and dual SLT use and the role of industry.

Computational Models Used to Assess US Tobacco Control Policies

INTRODUCTION

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.

IMPLICATIONS

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 role of public policies in reducing smoking prevalence: results from the Michigan SimSmoke tobacco policy simulation model

INTRODUCTION

Michigan has implemented several of the tobacco control policies recommended by the World Health Organization MPOWER goals. We consider the effect of those policies and additional policies consistent with MPOWER goals on smoking prevalence and smoking-attributable deaths (SADs).

METHODS

The SimSmoke tobacco control policy simulation model is used to examine the effect of past policies and a set of additional policies to meet the MPOWER goals. The model is adapted to Michigan using state population, smoking, and policy data starting in 1993. SADs are estimated using standard attribution methods. Upon validating the model, SimSmoke is used to distinguish the effect of policies implemented since 1993 against a counterfactual with policies kept at their 1993 levels. The model is then used to project the effect of implementing stronger policies beginning in 2014.

RESULTS

SimSmoke predicts smoking prevalence accurately between 1993 and 2010. Since 1993, a relative reduction in smoking rates of 22 % by 2013 and of 30 % by 2054 can be attributed to tobacco control policies. Of the 22 % reduction, 44 % is due to taxes, 28 % to smoke-free air laws, 26 % to cessation treatment policies, and 2 % to youth access. Moreover, 234,000 SADs are projected to be averted by 2054. With additional policies consistent with MPOWER goals, the model projects that, by 2054, smoking prevalence can be further reduced by 17 % with 80,000 deaths averted relative to the absence of those policies.

CONCLUSIONS

Michigan SimSmoke shows that tobacco control policies, including cigarette taxes, smoke-free air laws, and cessation treatment policies, have substantially reduced smoking and SADs. Higher taxes, strong mass media campaigns, and cessation treatment policies would further reduce smoking prevalence and SADs.

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

OBJECTIVES

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Enhancing dissemination and implementation research using systems science methods

BACKGROUND

Dissemination and implementation (D&I) research seeks to understand and overcome barriers to adoption of behavioral interventions that address complex problems, specifically interventions that arise from multiple interacting influences crossing socio-ecological levels. It is often difficult for research to accurately represent and address the complexities of the real world, and traditional methodological approaches are generally inadequate for this task. Systems science methods, expressly designed to study complex systems, can be effectively employed for an improved understanding about dissemination and implementation of evidence-based interventions.

PURPOSE

The aims of this study were to understand the complex factors influencing successful D&I of programs in community settings and to identify D&I challenges imposed by system complexity.

METHOD

Case examples of three systems science methods-system dynamics modeling, agent-based modeling, and network analysis-are used to illustrate how each method can be used to address D&I challenges.

RESULTS

The case studies feature relevant behavioral topical areas: chronic disease prevention, community violence prevention, and educational intervention. To emphasize consistency with D&I priorities, the discussion of the value of each method is framed around the elements of the established Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework.

CONCLUSION

Systems science methods can help researchers, public health decision makers, and program implementers to understand the complex factors influencing successful D&I of programs in community settings and to identify D&I challenges imposed by system complexity.

Estimating the Potential Impact of Tobacco Control Policies on Adverse Maternal and Child Health Outcomes in the United States Using the SimSmoke Tobacco Control Policy Simulation Model

INTRODUCTION

Numerous studies document the causal relationship between prenatal smoking and adverse maternal and child health (MCH) outcomes. Studies also reveal the impact that tobacco control policies have on prenatal smoking. The purpose of this study is to estimate the effect of tobacco control policies on prenatal smoking prevalence and adverse MCH outcomes.

METHODS

The US SimSmoke simulation model was extended to consider adverse MCH outcomes. The model estimates prenatal smoking prevalence and, applying standard attribution methods, uses estimates of MCH prevalence and relative smoking risks to estimate smoking-attributable MCH outcomes over time. The model then estimates the effect of tobacco control policies on adverse birth outcomes averted.

RESULTS

Different tobacco control policies have varying impacts on the number of smoking-attributable adverse MCH birth outcomes. Higher cigarette taxes and comprehensive marketing bans individually have the biggest impact with a 5% to 10% reduction across all outcomes for the period from 2015 to 2065. The policies with the lowest impact (2%-3% decrease) during this period are cessation treatment, health warnings, and complete smoke-free laws. Combinations of all policies with each tax level lead to 23% to 28% decreases across all outcomes.

CONCLUSIONS

Our findings demonstrate the substantial impact of strong tobacco control policies for preventing adverse MCH outcomes, including long-term health implications for children exposed to low birth weight and preterm birth. These benefits are often overlooked in discussions of tobacco control.

Germany SimSmoke: the effect of tobacco control policies on future smoking prevalence and smoking-attributable deaths in Germany

INTRODUCTION

Although Germany has recently implemented some tobacco control policies, there is considerable scope to strengthen policies consistent with the MPOWER guidelines. This article describes the development of a simulation model projecting the effect of future tobacco control policies in Germany on smoking prevalence and associated premature mortality.

METHODS

Germany SimSmoke-an adapted version of the SimSmoke simulation model of tobacco control policy-uses population, smoking rates, and policy data for Germany. It assesses, individually and in combination, the effect of seven types of policies: taxes, smoke-free air laws, mass media campaigns, advertising bans, warning labels, cessation treatment, and youth access policies.

RESULTS

With a comprehensive set of policies, smoking prevalence within the first few years can be reduced by about 22.0% relative to the status quo and by 37.9% (40.5%) for males (females) in 30 years. By 2040, 39,548 deaths could be averted in that year alone. Without stronger policies, 700,000 additional smoking-attributable deaths (SADs) would occur in Germany over the next 30 years.

CONCLUSIONS

The model indicates that the consequences of inaction are considerable; without the implementation of a stronger set of policies, smoking prevalence rates will remain relatively stable, and SADs among women will continue to rise over a 30-year horizon. Significant inroads into reducing smoking prevalence and premature mortality can be achieved through strengthening tobacco control policies in line with MPOWER recommendations.

The Brazil SimSmoke policy simulation model: the effect of strong tobacco control policies on smoking prevalence and smoking-attributable deaths in a middle income nation

BACKGROUND

Brazil has reduced its smoking rate by about 50% in the last 20 y. During that time period, strong tobacco control policies were implemented. This paper estimates the effect of these stricter policies on smoking prevalence and associated premature mortality, and the effect that additional policies may have.

METHODS AND FINDINGS

The model was developed using the SimSmoke tobacco control policy model. Using policy, population, and smoking data for Brazil, the model assesses the effect on premature deaths of cigarette taxes, smoke-free air laws, mass media campaigns, marketing restrictions, packaging requirements, cessation treatment programs, and youth access restrictions. We estimate the effect of past policies relative to a counterfactual of policies kept to 1989 levels, and the effect of stricter future policies. Male and female smoking prevalence in Brazil have fallen by about half since 1989, which represents a 46% (lower and upper bounds: 28%-66%) relative reduction compared to the 2010 prevalence under the counterfactual scenario of policies held to 1989 levels. Almost half of that 46% reduction is explained by price increases, 14% by smoke-free air laws, 14% by marketing restrictions, 8% by health warnings, 6% by mass media campaigns, and 10% by cessation treatment programs. As a result of the past policies, a total of almost 420,000 (260,000-715,000) deaths had been averted by 2010, increasing to almost 7 million (4.5 million-10.3 million) deaths projected by 2050. Comparing future implementation of a set of stricter policies to a scenario with 2010 policies held constant, smoking prevalence by 2050 could be reduced by another 39% (29%-54%), and 1.3 million (0.9 million-2.0 million) out of 9 million future premature deaths could be averted.

CONCLUSIONS

Brazil provides one of the outstanding public health success stories in reducing deaths due to smoking, and serves as a model for other low and middle income nations. However, a set of stricter policies could further reduce smoking and save many additional lives. Please see later in the article for the Editors' Summary.

The role of public policies in reducing smoking: the Minnesota SimSmoke tobacco policy model

BACKGROUND

Following the landmark lawsuit and settlement with the tobacco industry, Minnesota pursued the implementation of stricter tobacco control policies, including tax increases, mass media campaigns, smokefree air laws, and cessation treatment policies. Modeling is used to examine policy effects on smoking prevalence and smoking-attributable deaths.

PURPOSE

To estimate the effect of tobacco control policies in Minnesota on smoking prevalence and smoking-attributable deaths using the SimSmoke simulation model.

METHODS

Minnesota data starting in 1993 are applied to SimSmoke, a simulation model used to examine the effect of tobacco control policies over time on smoking initiation and cessation. Upon validating the model against smoking prevalence, SimSmoke is used to distinguish the effect of policies implemented since 1993 on smoking prevalence. Using standard attribution methods, SimSmoke also estimates deaths averted as a result of the policies.

RESULTS

SimSmoke predicts smoking prevalence accurately between 1993 and 2011. Since 1993, a relative reduction in smoking rates of 29% by 2011 and of 41% by 2041 can be attributed to tobacco control policies, mainly tax increases, smokefree air laws, media campaigns, and cessation treatment programs. Moreover, 48,000 smoking-attributable deaths will be averted by 2041.

CONCLUSIONS

Minnesota SimSmoke demonstrates that tobacco control policies, especially taxes, have substantially reduced smoking prevalence and smoking-attributable deaths. Taxes, smokefree air laws, mass media, cessation treatment policies, and youth-access enforcement contributed to the decline in prevalence and deaths averted, with the strongest component being taxes. With stronger policies, for example, increasing cigarette taxes to $4.00 per pack, Minnesota's smoking rate could be reduced by another 13%, and 7200 deaths could be averted by 2041.

Italy SimSmoke: the effect of tobacco control policies on smoking prevalence and smoking attributable deaths in Italy

Background

While Italy has implemented some tobacco control policies over the last few decades, which resulted in a decreased smoking prevalence, there is still considerable scope to strengthen tobacco control policies consistent with the World Health Organization (WHO) policy guidelines. The present study aims to evaluate the effect of past and project the effect of future tobacco control policies on smoking prevalence and associated premature mortality in Italy.

Methods

To assess, individually and in combination, the effect of seven types of policies, we used the SimSmoke simulation model of tobacco control policy. The model uses population, smoking rates and tobacco control policy data for Italy.

Results

Significant reductions of smoking prevalence and premature mortality can be achieved through tobacco price increases, high intensity media campaigns, comprehensive cessation treatment program, strong health warnings, stricter smoke-free air regulations and advertising bans, and youth access laws. With a comprehensive approach, the smoking prevalence can be decreased by as much as 12% soon after the policies are in place, increasing to a 30% reduction in the next twenty years and a 34% reduction by 30 years in 2040. Without effective tobacco control policies, a total of almost 300 thousand lives will be prematurely lost due to smoking by the year 2040.

Conclusion

Besides presenting the benefits of a comprehensive tobacco control strategy, the model helps identify information gaps in surveillance and evaluation schemes that will promote the effectiveness of future tobacco control policy in Italy.

Knowledge of the New Tobacco Hazards Prevention Act Is Associated With Smokers’ Behavior of Seeking Help in Smoking Cessation in Taiwan

Evidence that smoking area restrictions and raising cigarette taxes affect smokers’ behavior of seeking help in cessation is limited. The authors conducted a case-control study of 200 participants in Taipei City, Taiwan, from December 2008 to June 2009 to evaluate the association between knowledge on legislation and the behavior of seeking help in smoking cessation. They compared smokers who sought assistance in clinics/classes and smokers who did not, matching for age, gender, and recruitment time. In a univariate model, both banning smoking and increasing prices had positive effects on smokers’ behavior, but the effect size of the latter was larger ( P = .021). A better knowledge of the regulations was associated with cessation effort (odds ratio [OR] = 2.74; 95% confidence interval [CI] = 1.44-5.23), as were being more influenced by increased prices (OR = 2.44; 95% CI = 1.38-4.34) and by smoking bans (OR = 2.32; 95% CI = 1.29-4.16). Increased knowledge of the regulations is associated with seeking help for smoking.

The effect of tobacco control policies on smoking prevalence and smoking-attributable deaths. Findings from the Netherlands SimSmoke Tobacco Control Policy Simulation Model

AIM

To develop a simulation model projecting the effect of tobacco control policies in the Netherlands on smoking prevalence and smoking-attributable deaths.

DESIGN, SETTING AND PARTICIPANTS

Netherlands SimSmoke-an adapted version of the SimSmoke simulation model of tobacco control policy-uses population, smoking rates and tobacco control policy data for the Netherlands to predict the effect of seven types of policies: taxes, smoke-free legislation, mass media, advertising bans, health warnings, cessation treatment and youth access policies.

MEASUREMENTS

Outcome measures were smoking prevalence and smoking-attributable deaths.

FINDINGS

With a comprehensive set of policies, as recommended by MPOWER, smoking prevalence can be decreased by as much as 21% in the first year, increasing to a 35% reduction in the next 20 years and almost 40% by 30 years. By 2040, 7706 deaths can be averted in that year alone with the stronger set of policies. Without effective tobacco control policies, almost a million lives will be lost to tobacco-related diseases between 2011 and 2040. Of those, 145,000 can be saved with a comprehensive tobacco control package.

CONCLUSIONS

Smoking prevalence and smoking-attributable deaths in the Netherlands can be reduced substantially through tax increases, smoke-free legislation, high-intensity media campaigns, stronger advertising bans and health warnings, comprehensive cessation treatment and youth access laws. The implementation of these FCTC/MPOWER recommended policies could be expected to show similar or even larger relative reductions in smoking prevalence in other countries which currently have weak policies.

Modeling the future effects of a menthol ban on smoking prevalence and smoking-attributable deaths in the United States

We used a validated smoking simulation model and data from the 2003 Tobacco Use Supplement to the Current Population Survey to project the impact that a US menthol ban would have on smoking prevalence and smoking-attributable deaths. In a scenario in which 30% of menthol smokers quit and 30% of those who would have initiated as menthol smokers do not initiate, by 2050 the relative reduction in smoking prevalence would be 9.7% overall and 24.8% for Blacks; deaths averted would be 633,252 overall and 237,317 for Blacks.

Rural print media portrayal of secondhand smoke and smoke-free policy

The purpose of this article is to describe how the print media portrays secondhand smoke and smoke-free policy in rural communities. Baseline print media clips from an ongoing 5-year study of smoke-free policy development in 40 rural communities were analyzed. The authors hypothesized that community population size would be positively associated with media favorability toward smoke-free policy. Conversely, pounds of tobacco produced and adult smoking prevalence would be negatively associated with media favorability. There was a positive correlation between population size and percentage of articles favorable toward smoke-free policy. The authors did not find a correlation between adult smoking or tobacco produced and media favorability toward smoke-free policy, but we did find a positive relationship between tobacco produced and percentage of pro-tobacco articles and a negative relationship between adult smoking prevalence and percentage of articles about health/comfort. Implications for targeting pro-health media in rural communities as well as policy-based initiatives for tobacco control are discussed.

SimSmoke model evaluation of the effect of tobacco control policies in Korea: the unknown success story

OBJECTIVES

We evaluated the effect of strict tobacco control policies, implemented beginning in 1995 in the Republic of Korea, on smoking prevalence and deaths.

METHODS

SimSmoke is a simulation model of the effect of tobacco control policies over time on smoking initiation and cessation. It uses standard attribution methods to estimate lives saved as a result of new policies. After validating the model against smoking prevalence, we used it to determine the Korean policies' effect on smoking prevalence.

RESULTS

The model predicted smoking prevalence accurately between 1995 and 2006. We estimated that 70% of the 24% relative reduction in smoking rates over that period was attributable to tobacco control policies, mainly tax increases and a strong media campaign, and that the policies will prolong 104 812 male lives by the year 2027.

CONCLUSIONS

Our results document Korea's success in reducing smoking prevalence and prolonging lives, which may serve as an example for other Asian nations. Further improvements may be possible with higher taxes and more comprehensive smoke-free laws, cessation policies, advertising restrictions, and health warnings.

Reaching Healthy People 2010 by 2013: A SimSmoke simulation

BACKGROUND

Healthy People (HP2010) set as a goal to reduce adult smoking prevalence to 12% by 2010.

PURPOSE

This paper uses simulation modeling to examine the effects of three tobacco control policies and cessation treatment policies-alone and in conjunction-on population smoking prevalence.

METHODS

Building on previous versions of the SimSmoke model, the effects of a defined set of policies on quit attempts, treatment use, and treatment effectiveness are estimated as potential levers to reduce smoking prevalence. The analysis considers the effects of (1) price increases through cigarette tax increases, (2) smokefree indoor air laws, (3) mass media/educational policies, and (4) evidence-based and promising cessation treatment policies.

RESULTS

Evidence-based cessation treatment policies have the strongest effect, boosting the population quit rate by 78.8% in relative terms. Treatment policies are followed by cigarette tax increases (65.9%); smokefree air laws (31.8%); and mass media/educational policies (18.2%). Relative to the status quo in 2020, the model projects that smoking prevalence is reduced by 14.3% through a nationwide tax increase of $2.00, by 7.2% through smokefree laws, by 4.7% through mass media/educational policies, and by 16.5% through cessation treatment policies alone. Implementing all of the above policies at the same time would increase the quit rate by 296%, such that the HP2010 smoking prevalence goal of 12% is reached by 2013.

CONCLUSIONS

The impact of a combination of policies led to some surprisingly positive possible futures in lowering smoking prevalence to 12% within just several years. Simulation models can be a useful tool for evaluating complex scenarios in which policies are implemented simultaneously, and for which there are limited data.