Simulation modeling and tobacco control: creating more robust public health policies

Russia SimSmoke: the long-term effects of tobacco control policies on smoking prevalence and smoking-attributable deaths in Russia

BACKGROUND

Russia has high smoking rates and weak tobacco control policies. A simulation model is used to examine the effect of tobacco control policies on past and future smoking prevalence and premature mortality in Russia.

METHODS

The Russia model was developed using the SimSmoke tobacco control model previously developed for the USA and other nations. The model inputs population size, birth, death and smoking rates specific to Russia. It assesses, individually and in combination, the effect of seven types of policies consistent with the WHO Framework Convention on Tobacco Control (FCTC): taxes, smoke-free air, mass media campaign, advertising bans, warning labels, cessation treatment and youth access policies. Outcomes are smoking prevalence and the number of smoking-attributable deaths by age and gender from 2009 to 2055.

RESULTS

Increasing cigarette taxes to 70% of retail price, stronger smoke-free air laws, a high-intensity media campaign and comprehensive treatment policies are each potent policies to reduce smoking prevalence and smoking-attributable premature deaths in Russia. With the stronger set of policies, the model estimates that, relative to the status quo trend, smoking prevalence can be reduced by as much as 30% by 2020, with a 50% reduction projected by 2055. This translates into 2 684 994 male and 1 011 985 female premature deaths averted from 2015-2055.

CONCLUSIONS

SimSmoke results highlight the relative contribution of policies to reducing the tobacco health burden in Russia. Significant inroads to reducing smoking prevalence and premature mortality can be achieved through strengthening tobacco control policies in line with FCTC recommendations.

Smoking-related deaths averted due to three years of policy progress

OBJECTIVE

To evaluate the global impact of adopting highest-level MPOWER tobacco control policies in different countries and territories from 2007 to 2010.

METHODS

Policy effect sizes based on previously-validated SimSmoke models were applied to determine the reduction in the number of smokers as a result of policy adoption during this period. Based on previous research suggesting that half of all smokers die from smoking, we also derived the estimated smoking-attributable deaths (SADs) averted due to MPOWER policy implementation. The results from use of this simple yet powerful method are consistent with those predicted by using previously validated SimSmoke models.

FINDINGS

In total, 41 countries adopted at least one highest-level MPOWER policy between 2007 and 2010. As a result of all policies adopted during this period, the number of smokers is estimated to have dropped by 14.8 million, with a total of 7.4 million SADs averted. The largest number of SADs was averted as a result of increased cigarette taxes (3.5 million), smoke-free air laws (2.5 million), health warnings (700,000), cessation treatments (380,000), and bans on tobacco marketing (306,000).

CONCLUSION

From 2007 to 2010, 41 countries and territories took action that will collectively prevent nearly 7.5 million smoking-related deaths globally. These findings demonstrate the magnitude of the actions already taken by countries and underscore the potential for millions of additional lives to be saved with continued adoption of MPOWER policies.

Simulation modeling of policies directed at youth sugar-sweetened beverage consumption

Childhood obesity is a significant public health problem requiring innovative solutions. While recent reviews indicate that some policies show promise, there is a lack of information regarding which policies, and policy combinations, work best. Low-nutrition, energy-dense foods and beverages such as sugar-sweetened beverages (SSBs) have been identified as a major contributor to the problem. The purpose of this paper is to use simulation modeling to show how changes in three categories of SSB policies-school nutrition, school-based education, and taxes-impact SSB and other food consumption. The model shows that policies directed at SSBs, particularly tax hikes, could lead to substantial reductions in the number of calories consumed by youth. The estimates, however, are subject to a high degree of uncertainty. Estimates from school-based nutrition and school-based education policies, while also helping to reduce caloric intake, generally show smaller effects than tax policies and considerable variation around parameter estimates for individual and combined policies. We conclude with a discussion of the limits of the model, and suggest where additional information is needed. Limitations notwithstanding, simulation modeling is a promising methodology that can help advance our understanding of policy effects, thereby helping policymakers to better formulate effective policies to reduce obesity prevalence and the associated social harms.

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.

SimSmokeFinn: how far can tobacco control policies move Finland toward tobacco-free 2040 goals?

AIMS

Finland is the first country to stipulate in law that its aim is to end the use of tobacco products containing compounds that are toxic to humans and that create addiction. This paper describes the development of a simulation model examining the potential effect of tobacco control policies in Finland on smoking prevalence and associated future premature mortality.

METHODS

The model is developed using the SimSmoke simulation model of tobacco control policy, previously developed for other nations. The model uses population, smoking rates, and tobacco control policy data for Finland. 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 can be decreased by as much as 15% in the first few years, increasing to 29% by 20 years and 34% by 30 years. By 2040, 1300 deaths can be averted in that year alone with the stronger set of policies. Without effective tobacco control policies, 23,000 additional lives will be lost due to smoking over all years through 2040.

CONCLUSIONS

The model shows that significant inroads to reducing smoking prevalence and premature mortality can be achieved through tax increases, a high-intensity media campaign complete with programmes to encourage cessation, a comprehensive cessation treatment programme, stronger health warnings, and enforcement of youth access laws. Other policies will be needed to further reduce tobacco use.

Tobacco control policy in the UK: blueprint for the rest of Europe?

INTRODUCTION

With male smoking prevalence at ~30% in 1998, the UK implemented stricter tobacco control policies, including a comprehensive cessation treatment programme. We evaluate their effect.

METHODS

Data for the UK (excluding Northern Ireland) 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, the model is used to distinguish the effect of policies implemented between 1998 and 2009 on smoking prevalence. Using standard attribution methods, the model estimates lives saved as a result of policies.

RESULTS

The model predicts smoking prevalence accurately between 1998 and 2009. A relative reduction of 23% in smoking rates over that period is attributed to tobacco control policies, mainly tax increases, smoke-free air laws, advertising restrictions and cessation treatment programmes. The model estimates that 210 000 deaths will be averted by the year 2040, as a consequence of policies implemented between 1998 and 2010.

CONCLUSIONS

The results document the UK's success in reducing smoking prevalence and prolonging lives, thereby providing an example for other European nations. When Framework Convention for Tobacco Control- (FCTC) consistent policies are also implemented, the model projects that smoking prevalence will fall by another 28% with an additional 168,000 deaths averted by 2040.

The effect of tobacco control policies on smoking prevalence and smoking-attributable deaths in Ireland using the IrelandSS simulation model

OBJECTIVES

This study estimates the relative contribution of policies implemented between 1998 and 2010 to reductions in smoking prevalence by 2010. It then models the impact of implementing stronger policies, relative to a scenario of inaction, on smoking prevalence and smoking-attributable mortality in Ireland.

METHODS

IrelandSS is an adapted version of SimSmoke, a dynamic simulation model used to examine the effect of tobacco control policies on smoking prevalence, through initiation and cessation, and associated future premature mortality.

RESULTS

Model predictions for smoking prevalence are reasonably close to those from surveys. As a result of tobacco control policies implemented between 1998 and 2010, there was a 22% relative reduction in smoking prevalence and 1716 fewer smoking-attributable deaths (SADs) by 2010 increasing to a 29% relative reduction in prevalence and 50 215 fewer SADs by 2040. With the introduction of stricter FCTC-compliant policies in 2011, the smoking prevalence can be decreased by as much as 13% initially, increasing to 28% by 30 years. With these stronger policies, a total of 24 768 SADs will be averted by 2040.

CONCLUSIONS

Predictions from the IrelandSS model suggest that policies implemented between 1998 and 2010 have had considerable effect; however, appreciable reductions in smoking prevalence and SADs can still be achieved through increasing taxes, maintaining a high-intensity tobacco control media campaign, introducing graphic health warnings and improving smoking cessation services.

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.

Systems science methods in public health: dynamics, networks, and agents

Complex systems abound in public health. Complex systems are made up of heterogeneous elements that interact with one another, have emergent properties that are not explained by understanding the individual elements of the system, persist over time, and adapt to changing circumstances. Public health is starting to use results from systems science studies to shape practice and policy, for example in preparing for global pandemics. However, systems science study designs and analytic methods remain underutilized and are not widely featured in public health curricula or training. In this review we present an argument for the utility of systems science methods in public health, introduce three important systems science methods (system dynamics, network analysis, and agent-based modeling), and provide three case studies in which these methods have been used to answer important public health science questions in the areas of infectious disease, tobacco control, and obesity.

The SmokingPaST Framework: Illustrating the Impact of Quit Attempts, Quit Methods, and New Smokers on Smoking Prevalence, Years of Life Saved, Medical Costs Saved, Programming Costs, Cost Effectiveness, and Return on Investment

Purpose.

Describe the specifications of the Smoking Prevalence, Savings, and Treatment (SmokingPaST) Framework and show how it can illustrate the impact of quit attempts, quit method, number of new smokers, smoking rates of immigrants and emigrants, and death rates of smokers and nonsmokers on future smoking prevalence rates, program costs, years of life saved, medical costs saved, cost effectiveness of programs, and return on investment (ROI).

Framework Specifications.

Mathematical relationships among factors in SmokingPaST are described. Input variables include baseline smoking rates among current adults, new adults, immigrants, and emigrants; population counts for these groups; annual quit attempts; and distribution of quit methods. Assumption variables include success rate by quit method, death rates of smokers and nonsmokers, annual medical costs of smoking, costs per person for four tobacco treatment methods, age distribution of quitters, and distribution of medical cost funding by source. Output variables include year-end adult smoking rates, successful quitters, years of life saved by quitting, medical costs saved by quitting and by not hiring smokers, total costs of smoking treatment programs, cost per quitter, cost per life-year saved, distribution of medical cost savings from quitting, and ROI of treatment costs.

Applications.

The Framework was applied at the employer, county, state, and national levels.

Conclusions.

The SmokingPaST Framework provides a conceptually simple framework that can be applied to any population. It illustrates that significant drops in smoking rates can be achieved and significant savings in medical costs can be captured by employers as well as state and federal governments through tobacco treatment and prevention programs. Savings are especially important for reducing state and federal government deficits and enhancing job competitiveness.

Development and validation of a microsimulation economic model to evaluate the disease burden associated with smoking and the cost-effectiveness of tobacco control interventions in Latin America

OBJECTIVE

To describe the development and validation of a health economic model (HEM) to address the tobacco disease burden and the cost-effectiveness of smoking cessation interventions (SCI) in seven Latin American countries.

METHODS

The preparatory stage included the organization of the research network, analysis of availability of epidemiologic data, and a survey to health decision makers to explore country-specific information needs. The development stage involved the harmonization of a methodology to retrieve local relevant parameters and develop the model structure. Calibration and validation was performed using a selected country dataset (Argentina 2005). Predicted event rates were compared to the published rates used as model inputs. External validation was undertaken against epidemiologic studies that were not used to provide input data.

RESULTS

Sixty-eight decision makers were surveyed. A microsimulation HEM was built considering the availability and quality of epidemiologic data and relevant outcomes conceived to suit the identified information needs of decision makers. It considers all tobacco-related diseases (i.e., heart, cerebrovascular and chronic obstructive pulmonary disease, pneumonia/influenza, lung cancer, and nine other neoplasms) and can incorporate individual- and population-level interventions. The calibrated model showed all simulated event rates falling within ± 10% of the sources (-9%-+5%). External validation showed a high correlation between published data and model results.

CONCLUSIONS

This evidence-based, internally and externally valid HEM for the assessment of the effects of smoking and SCIs incorporates a broad spectrum of tobacco related diseases, SCI, and benefit measures. It could be a useful policy-making tool to estimate tobacco burden and cost-effectiveness of SCI.

Simulation models of obesity: a review of the literature and implications for research and policy

Simulation models (SMs) combine information from a variety of sources to provide a useful tool for examining how the effects of obesity unfold over time and impact population health. SMs can aid in the understanding of the complex interaction of the drivers of diet and activity and their relation to health outcomes. As emphasized in a recently released report of the Institute or Medicine, SMs can be especially useful for considering the potential impact of an array of policies that will be required to tackle the obesity problem. The purpose of this paper is to present an overview of existing SMs for obesity. First, a background section introduces the different types of models, explains how models are constructed, shows the utility of SMs and discusses their strengths and weaknesses. Using these typologies, we then briefly review extant obesity SMs. We categorize these models according to their focus: health and economic outcomes, trends in obesity as a function of past trends, physiologically based behavioural models, environmental contributors to obesity and policy interventions. Finally, we suggest directions for future research.

Can a deterministic spatial microsimulation model provide reliable small-area estimates of health behaviours? An example of smoking prevalence in New Zealand

Models created to estimate neighbourhood level health outcomes and behaviours can be difficult to validate as prevalence is often unknown at the local level. This paper tests the reliability of a spatial microsimulation model, using a deterministic reweighting method, to predict smoking prevalence in small areas across New Zealand. The difference in the prevalence of smoking between those estimated by the model and those calculated from census data is less than 20% in 1745 out of 1760 areas. The accuracy of these results provides users with greater confidence to utilize similar approaches in countries where local-level smoking prevalence is unknown.

Application of a system dynamics model to inform investment in smoking cessation services in New Zealand

OBJECTIVES

We estimated the long-term effects of smoking cessation interventions to inform government decision-making regarding investment in tobacco control.

METHODS

We extracted data from the 2006 New Zealand Tobacco Use Survey and other sources and developed a system dynamics model with the iThink computer simulation package. The model derived estimates of population cessation rates from smoking behaviors and applied these over a 50-year period, from 2001 to 2051, under business-as-usual and enhanced cessation intervention scenarios.

RESULTS

The model predicted larger effects by 2051 with the enhanced cessation than with the business-as-usual scenario, including: an 11% greater decline in adult current smoking prevalence (9 versus 10 per 100 people), 16% greater decline in per capita tobacco consumption (370 versus 440 cigarette equivalents per year), and 11% greater reduction in tobacco-attributable mortality (3000 versus 3300 deaths per year).

CONCLUSIONS

The model generated reliable estimates of the effects on health and on tobacco use of interventions designed to enhance smoking cessation. These results informed a decision announced in May 2007 to increase funding for smoking cessation by NZ $42 million over 4 years.

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.

Exploring scenarios to dramatically reduce smoking prevalence: a simulation model of the three-part cessation process

OBJECTIVES

We used a simulation model to analyze whether the Healthy People 2010 goal of reducing smoking prevalence from the current 19.8% rate to 12% by 2010 could be accomplished by increasing quit attempts, increasing the use of treatments, or increasing the effectiveness of treatment.

METHODS

We expanded on previous versions of the tobacco control simulation model SimSmoke to assess the effects of an increase in quit attempts, treatment use, and treatment effectiveness to reduce smoking prevalence. In the model, we considered increases in each of these parameters individually and in combination.

RESULTS

Individually, 100% increases in quit attempts, treatment use, and treatment effectiveness reduced the projected 2020 prevalence to 13.9%, 16.7%, and 15.9%, respectively. With a combined 100% increase in all components, the goal of a 12% adult smoking prevalence could be reached by 2012.

CONCLUSIONS

If we are to come close to reaching Healthy People 2010 goals in the foreseeable future, we must not only induce quit attempts but also increase treatment use and effectiveness. Simulation models provide a useful tool for evaluating the potential to reach public health targets.

Legislative smoking bans for reducing secondhand smoke exposure, smoking prevalence and tobacco consumption

BACKGROUND

Smoking bans have been implemented in a variety of settings, as well as being part of policy in many jurisdictions to protect the public and employees from the harmful effects of secondhand smoke (SHS). They also offer the potential to influence social norms and smoking behaviour of those populations they affect.

OBJECTIVES

To assess the extent to which legislation-based smoking bans or restrictions reduce exposure to SHS, help people who smoke to reduce tobacco consumption or lower smoking prevalence and affect the health of those in areas which have a ban or restriction in place.

SEARCH STRATEGY

We searched the Cochrane Tobacco Addiction Group Specialised Register, MEDLINE, EMBASE, PsycINFO, CINAHL, Conference Paper Index, and reference lists and bibliographies of included studies. We also checked websites of various organisations. Date of most recent search; July 1st 2009.

SELECTION CRITERIA

We considered studies that reported legislative smoking bans and restrictions affecting populations. The minimum standard was having a ban explicitly in the study and a minimum of six months follow-up for measures of smoking behaviour. We included randomized controlled trials, quasi-experimental studies (i.e. non-randomized controlled studies), controlled before and after studies, interrupted-time series as defined by the Cochrane Effective Practice and Organization of Care Group, and uncontrolled pre- and post-ban data.

DATA COLLECTION AND ANALYSIS

Characteristics and content of the interventions, participants, outcomes and methods of the included studies were extracted by one author and checked by a second. Because of heterogeneity in the design and content of the studies, we did not attempt a meta-analysis. We evaluated the studies using qualitative narrative synthesis.

MAIN RESULTS

There were 50 studies included in this review. Thirty-one studies reported exposure to secondhand smoke (SHS) with 19 studies measuring it using biomarkers. There was consistent evidence that smoking bans reduced exposure to SHS in workplaces, restaurants, pubs and in public places. There was a greater reduction in exposure to SHS in hospitality workers compared to the general population. We failed to detect any difference in self-reported exposure to SHS in cars. There was no change in either the prevalence or duration of reported exposure to SHS in the home as a result of implementing legislative bans. Twenty-three studies reported measures of active smoking, often as a co-variable rather than an end-point in itself, with no consistent evidence of a reduction in smoking prevalence attributable to the ban. Total tobacco consumption was reduced in studies where prevalence declined. Twenty-five studies reported health indicators as an outcome. Self-reported respiratory and sensory symptoms were measured in 12 studies, with lung function measured in five of them. There was consistent evidence of a reduction in hospital admissions for cardiac events as well as an improvement in some health indicators after the ban.

AUTHORS' CONCLUSIONS

Introduction of a legislative smoking ban does lead to a reduction in exposure to passive smoking. Hospitality workers experienced a greater reduction in exposure to SHS after implementing the ban compared to the general population. There is limited evidence about the impact on active smoking but the trend is downwards. There is some evidence of an improvement in health outcomes. The strongest evidence is the reduction seen in admissions for acute coronary syndrome. There is an increase in support for and compliance with smoking bans after the legislation.

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.

Boosting population quits through evidence-based cessation treatment and policy

Only large increases in adult cessation will rapidly reduce population smoking prevalence. Evidence-based smoking-cessation treatments and treatment policies exist but are underutilized. More needs to be done to coordinate the widespread, efficient dissemination and implementation of effective treatments and policies. This paper is the first in a series of three to demonstrate the impact of an integrated, comprehensive systems approach to cessation treatment and policy. This paper provides an analytic framework and selected literature review that guide the two subsequent computer simulation modeling papers to show how critical leverage points may have an impact on reductions in smoking prevalence. Evidence is reviewed from the U.S. Public Health Service 2008 clinical practice guideline and other sources regarding the impact of five cessation treatment policies on quit attempts, use of evidence-based treatment, and quit rates. Cessation treatment policies would: (1) expand cessation treatment coverage and provider reimbursement; (2) mandate adequate funding for the use and promotion of evidence-based state-sponsored telephone quitlines; (3) support healthcare systems changes to prompt, guide, and incentivize tobacco treatment; (4) support and promote evidence-based treatment via the Internet; and (5) improve individually tailored, stepped-care approaches and the long-term effectiveness of evidence-based treatments. This series of papers provides an analytic framework to inform heuristic simulation models in order to take a new look at ways to markedly increase population smoking cessation by implementing a defined set of treatments and treatment-related policies with the potential to improve motivation to quit, evidence-based treatment use, and long-term effectiveness.

Researching a local heroin market as a complex adaptive system

This project applies agent-based modeling (ABM) techniques to better understand the operation, organization, and structure of a local heroin market. The simulation detailed was developed using data from an 18-month ethnographic case study. The original research, collected in Denver, CO during the 1990s, represents the historic account of users and dealers who operated in the Larimer area heroin market. Working together, the authors studied the behaviors of customers, private dealers, street-sellers, brokers, and the police, reflecting the core elements pertaining to how the market operated. After evaluating the logical consistency between the data and agent behaviors, simulations scaled-up interactions to observe their aggregated outcomes. While the concept and findings from this study remain experimental, these methods represent a novel way in which to understand illicit drug markets and the dynamic adaptations and outcomes they generate. Extensions of this research perspective, as well as its strengths and limitations, are discussed.

Mathematical modeling and the epidemiological research process

The authors of this paper advocate for the expanded use of mathematical models in epidemiology and provide an overview of the principles of mathematical modeling. Mathematical models can be used throughout the epidemiological research process. Initially they may help to refine study questions by visually expressing complex systems, directing literature searches, and identifying sensitive variables. In the study design phase, models can be used to test sampling strategies, to estimate sample size and power, and to predict outcomes for studies impractical due to time or ethical considerations. Once data are collected, models can assist in the interpretation of results, the exploration of causal pathways, and the combined analysis of data from multiple sources. Finally, models are commonly used in the process of applying research findings to public health practice by estimating population risk, predicting the effects of interventions, and contributing to the evaluation of ongoing programs. Mathematical modeling has the potential to make significant contributions to the field of epidemiology by enhancing the research process, serving as a tool for communicating findings to policymakers, and fostering interdisciplinary collaboration.

The role of tobacco control policies in reducing smoking and deaths caused by smoking in an Eastern European nation: results from the Albania SimSmoke simulation model

The Albania SimSmoke simulation model is used to examine the effects of tobacco control policies. The model is used to consider the projected trends in smoking prevalence and associated smoking-attributable deaths in the absence of new policies, and then to examine the effect of new policies that are consistent with the Framework Convention for Tobacco Control (FCTC) on these outcomes. The model shows that significant inroads to reducing smoking prevalence and premature mortality can be achieved through tax increases. Acomprehensive strategy to further reduce smoking rates should include a media campaign complete with programs to publicize and enforce clean air laws, a comprehensive cessation treatment program, strong health warnings, advertising bans, and youth access laws. Besides presenting the benefits of a comprehensive tobacco control strategy, the model helps to identify important information needed for both modeling and policymaking. The effectiveness of future tobacco control policy will require proper surveillance and evaluation schemes for Albania.

Linking tobacco control policies and practices to early cancer endpoints: surveillance as an agent for change

State tobacco control programs provide an important laboratory for the development, implementation, and evaluation of comprehensive tobacco control interventions. Studies have shown that states and municipalities with aggressive tobacco control programs have experienced more rapid decreases in per capita cigarette sales, smoking prevalence, lung cancer, and heart disease than entities without such programs. Despite strong evidence that population-level interventions are critical in achieving large and sustained reductions in tobacco use, states do not fund tobacco control efforts at levels recommended by the Centers for Disease Control and Prevention. Research on the effectiveness and cost effectiveness of these activities is essential to inform and strengthen tobacco control at the state level. A workshop, co-organized by the American Cancer Society, the National Cancer Institute, the American Association for Cancer Research, and the Centers for Disease Control and Prevention, was held in Philadelphia in December, 2007, to discuss the topic "Linking tobacco control policies and practices to early cancer endpoints: surveillance as an agent for change." Participants represented three different disciplines. Tobacco surveillance researchers described the data currently collected on state-level tobacco control policies, protobacco countermeasures by the industry, public attitudes toward tobacco use, and measures of smoking prevalence and consumption. Cancer registry experts described the geographic coverage of high quality, population-based cancer registries. Mathematical modeling experts discussed various modeling approaches that can be used to relate upstream tobacco promotion and control activities to downstream measures such as public attitudes, changes in tobacco use, and trends in tobacco-related diseases. The most important recommendation of the Workshop was a call for national leadership to enhance the collection and integration of data from multiple sources as a resource to further study and strengthen the scientific basis for tobacco control.

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

OBJECTIVES

Healthy People (HP) 2010 has a goal of reducing adult smoking prevalence to 12% by 2010. Kentucky, with the highest adult smoking rates (28.7% versus a US average of 20.9%) and weak tobacco control policies, has the potential to reduce smoking by implementing stricter policies.

METHODS

The SimSmoke tobacco control policy model is applied to Kentucky, validated over 1993 to 2003. Smoking prevalence evolves over time through initiation and cessation, as behaviors influenced by tobacco control policies.

RESULTS

SimSmoke predicts well over the pre-2007 period, including larger annual decreases in latter years. With policies suggested by HP 2010 goals, smoking prevalence is projected to fall to about 19% by 2011 and 14% by 2026; more than 17,000 smoking-attributable deaths would be avoided by 2026.

CONCLUSIONS

SimSmoke suggests policies can have a large impact on smoking rates and save lives in Kentucky. If HP 2010 goals will be met, states such as Kentucky need to implement strong tobacco control policies.

Integrating a school-based health intervention in times of high-stakes testing: lessons learned from full court press

Because of the growing focus on the production of favorable academic standardized test scores, schools have become increasingly resistant to sponsoring nonacademic programming, such as tobacco cessation services for students. Nevertheless, the need for such programs has not diminished. The purpose of this article is to provide descriptive information about the logistics of establishing and delivering a health intervention in schools that are resistant to nonacademic programming. The data were collected as part of a qualitative retrospective process evaluation of Full Court Press, a 5-year youth tobacco demonstration project funded by the Robert Woods Johnson Foundation and implemented in Tucson, Arizona. Lessons learned about recruiting schools, integrating programs, and managing facilitators are presented.

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

Tobacco control policies are examined utilizing a simulation model for California, the state with the longest running comprehensive program. We assess the impact of the California Tobacco Control Program (CTCP) and surrounding price changes on smoking prevalence and smoking-attributable deaths. Modeling begins in 1988 and progresses chronologically to 2004, and considers four types of policies (taxes, mass media, clean air laws, and youth access policies) independently and as a package. The model is validated against existing smoking prevalence estimates. The difference in trends between predicted smoking rates from the model and other commonly used estimates of smoking prevalence for the overall period were generally small. The model also predicted some important changes in trend, which occurred with changes in policy. The California SimSmoke model estimates that tobacco control policies reduced smoking rates in California by an additional 25% relative to the level that they would have been if policies were kept at their 1988 level. By 2004, the model attributes 59% of the reduction to price increases, 28% of the overall effect to media policies, 11% to clean air laws, and only a small percent to youth access policies. The model estimates that over 5000 lives will be saved in the year 2010 alone as a result of the CTCP and industry-initiated price increases, and that over 50,000 lives were saved over the period 1988-2010. Tobacco control policies implemented as comprehensive tobacco control strategies have significantly impacted smoking rates. Further tax increases should lead to additional lives saved, and additional policies may result in further impacts on smoking rates, and consequently on smoking-attributable health outcomes in the population.

The role of public policies in reducing smoking prevalence and deaths caused by smoking in Arizona: results from the Arizona tobacco policy simulation model

Arizona was one of the first few states to implement a comprehensive tobacco control program. The effect of that program is examined using a computer-simulation model (SimSmoke) developed for the purposes of evaluation, planning, and justifying policies. This approach assesses the impact to date of tobacco control policies on smoking prevalence and generates predictions about the effects of tobacco control policies on past and future smoking prevalence and associated future premature mortality. SimSmoke estimates indicate that tobacco control policies reduced smoking rates in Arizona by about 20 percent over the period 1993-2002. A previous CDC study obtains similar effects, but does not net out the effects of individual policies. SimSmoke attributes much of the reduction, about 61 percent, to price increases and attributes 38 percent of the overall effect to media policies, leaving only a small percentage of the smoking reductions attributed to quitlines, youth access policies, and the weak clean air laws. Tobacco control policies implemented as comprehensive strategies have significantly affected smoking rates in Arizona, which leads to large reductions in deaths attributable to smoking. It will be important to maintain these efforts over time to reduce or keep smoking prevalence down and to minimize smoking-attributable deaths.