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

An analysis of spatial and temporal uncertainty propagation in agent-based models

Spatially explicit simulations of complex systems lead to inherent uncertainties in spatial outcomes. Visualizing the temporal propagation of spatial uncertainties is crucial to communicate the reliability of such models. However, the current Uncertainty Analyses (UAs) either consider spatial uncertainty at the end of model runs, or consider non-spatial uncertainties at different model states. To address this, we propose a Spatio-Temporal UA (ST-UA) approach to generate an uncertainty propagation index and visualize the temporal propagation of different uncertainty measures between two temporal model states. We select the total effects sensitivity measure (a Sobol index) for a sample application within the ST-UA approach. The application is the Tobacco Town ABM, a spatial model simulating smoking behaviours. We showcase the effect of the statistical distributions of wages and smoking rates on the propensity to buy cigarettes, which leads to the propagation of uncertainty in the number of purchased cigarettes by individuals. The findings highlight the usefulness of the ST-UA in (i) communicating the reliability of the spatial outcomes of the model; and (ii) guiding modellers towards the spatial areas with relatively high uncertainties at different temporal steps. This approach can be readily transferred to other application areas that are characterized with spatio-temporal uncertainty.This article is part of the theme issue 'Uncertainty quantification for healthcare and biological systems (Part 2)'.

Informing Public Health Policies with Models for Disease Burden, Impact Evaluation, and Economic Evaluation

Conducting real-world public health experiments is often costly, time-consuming, and ethically challenging, so mathematical models have a long-standing history of being used to inform policy. Applications include estimating disease burden, performing economic evaluation of interventions, and responding to health emergencies such as pandemics. Models played a pivotal role during the COVID-19 pandemic, providing early detection of SARS-CoV-2's pandemic potential and informing subsequent public health measures. While models offer valuable policy insights, they often carry limitations, especially when they depend on assumptions and incomplete data. Striking a balance between accuracy and timely decision-making in rapidly evolving situations such as disease outbreaks is challenging. Modelers need to explore the extent to which their models deviate from representing the real world. The uncertainties inherent in models must be effectively communicated to policy makers and the public. As the field becomes increasingly influential, it needs to develop reporting standards that enable rigorous external scrutiny.

Economic research in waterpipe tobacco smoking: reflections on data, demand, taxes, equity and health modelling

Economic evaluation of tobacco control policies is common in high-income settings and mainly focuses on cigarette smoking. Evidence suggests that increasing the excise tax of tobacco products is a consistently effective tool for reducing tobacco use and is an efficient mechanism for increasing government revenues. However, less research has been conducted in low/middle-income countries where other tobacco forms are common. This paper presents insights from our work on the economics of waterpipe tobacco smoking conducted in the Eastern Mediterranean Region where waterpipe smoking originated and is highly prevalent. The specific areas related to economics of waterpipe smoking considered herein are: price elasticity, taxation, government revenue, expenditure and healthcare costs. This paper aims to provide practical guidance for researchers investigating the economics of waterpipe tobacco with potential implications for other novel tobacco products. We present lessons learnt across five thematic areas: data, demand, taxes, equity and health modelling. We also highlight knowledge gaps to be addressed in future research. Research implications include designing comprehensive assessment tools that investigate heterogeneity in waterpipe smoking patterns; accounting for cross-price elasticity of demand with other tobacco products; exploring the change in waterpipe tobacco smoking in response to a tax increase and analysing the equity impact of waterpipe tobacco control interventions.

Tobacco endgame in the WHO European Region: Feasibility in light of current tobacco control status

INTRODUCTION

To assess the feasibility of developing World Health Organization (WHO) European Region countries' goals and measures in line with tobacco endgame objectives, information on the current tobacco control context and capacity is needed. The aim of this study was to assess the implementation of the Framework Convention on Tobacco Control (WHO FCTC) and MPOWER measures in the region.

METHODS

In this cross-sectional study we used data from the WHO FCTC implementation reports and MPOWER from 2020 in 53 WHO European Region countries. Six domains (i.e. capacity, taxation and price policies, other national key regulations, public awareness raising and communication, tobacco use cessation, and monitoring) were formed. Subsequently, available indicators under these domains were scored and the level of implementation was computed for each country. Mann-Whitney tests were carried out to compare the scores between the group of countries with and without official endgame goals.

RESULTS

Overall, implementation of the WHO FCTC with the selected indicators at the country level ranged from 28% to 86%, and of MPOWER from 31% to 96%. Full implementation was achieved by 28% of WHO FCTC Parties in the region in taxation and price policies, 12% in public awareness raising and communication, and 42% in monitoring. In capacity, tobacco use cessation and other national key regulations, none of the Parties in the region reached full implementation. Overall median WHO FCTC scores were significantly higher in countries with official endgame goals than in those without (p<0.001).

CONCLUSIONS

There is unequal implementation of both WHO FCTC and MPOWER measures among WHO European Region countries. MPOWER and WHO FCTC provide all the measures for the necessary first steps, followed by innovative measures, to accomplish tobacco endgame goals.

Using System Dynamics to Understand Transnational Corporate Power in Diet-Related Non-communicable Disease Prevention Policy-Making: A Case Study of South Africa

BACKGROUND

Complex interactions between political economy factors and corporate power are increasingly recognized to prevent transformative policy action on non-communicable disease (NCD) prevention. System science offers promising methods for analysing such causal complexity. This study uses qualitative system dynamics methods to map the political economy of diet-related NCD (DR-NCD) prevention policy-making aiming to better understand the policy inertia observed in this area globally.

METHODS

We interviewed 25 key policy actors. We analysed the interviews using purposive text analysis (PTA). We developed individual then combined casual loop diagrams to generate a shared model representing the DR-NCD prevention policy-making system. Key variables/linkages identified from the literature were also included in the model. We validated the model in several steps including through stakeholder validation interviews.

RESULTS

We identified several inter-linked feedback processes related to political economy factors that may entrench different forms of corporate power (instrumental, structural, and discursive) in DR-NCD prevention policy-making in South Africa over time. We also identified a number of feedback processes that have the potential to limit corporate power in this setting.

CONCLUSION

Using complex system methods can be useful for more deeply understanding DR-NCD policy inertia. It is also useful for identifying potential leverage points within the system which may shift the existing power dynamics to facilitate greater political commitment for healthy, equitable, and sustainable food system transformation.

Effect of tobacco taxation on smoking prevalence and smoking-attributable deaths in India

Background

Higher taxes are the single most effective way to encourage tobacco users to quit tobacco use and prevent youth from initiation.

Objectives

The present study aims to estimate the effect of raising the tax on smoked tobacco products on its consumption and smoking-attributable deaths in India.

Materials and Methods

A mathematical model was developed which used the projected population of India, taxation rates on smoked tobacco products, smoking prevalence, and price elasticity of demand of cigarette and bidi from 2017 to 2025. Four scenarios of tax increment (0%, 25%, 50%, and 100%) on smoked tobacco products were created which were modeled to calculate smoking prevalence and smoking-attributable deaths due to respiratory diseases, heart diseases, stroke tuberculosis, and cancer in country till 2025.

Results

A relative decrease of 6.2% in the prevalence of smoking was observed between the existing tax rates and its increment to 100% over the last increment of 6%. Similarly, smoking-attributable deaths (SAD) decreased by 6.04% on increasing the tax rates to 100% of the existing taxation rates. There has been a steady increase in SAD in scenario 1 which decreases effectively in scenario 4, which in turn leads to the saving of around 33,000 lives due to tobacco-related diseases by 2025.

Conclusion

The consumption of cigarettes and bidis can be reduced by raising the price of these products. The model will help policymakers in deciding to fix the tax and ultimately the price of cigarettes and bidi to reduce its consumption and smoking-attributable mortality.

A Decision-Theoretic Public Health Framework for Heated Tobacco and Nicotine Vaping Products

Markets for nicotine vaping products (NVPs) and heated tobacco products (HTPs) have grown as these products became positioned as harm-reduction alternatives to combusted tobacco products. Herein, we present a public health decision-theoretic framework incorporating different patterns of HTP, NVP, and cigarette use to examine their impacts on population health. Our framework demonstrates that, for individuals who would have otherwise smoked, HTP use may provide public health benefits by enabling cessation or by discouraging smoking initiation and relapse. However, the benefits are reduced if more harmful HTP use replaces less harmful NVP use. HTP use may also negatively impact public health by encouraging smoking by otherwise non-smokers or by encouraging initiation or relapse into smoking. These patterns are directly influenced by industry behavior as well as public policy towards HTPs, NVPs, and cigarettes. While substantial research has been devoted to NVPs, much less is known about HTPs. Better information is needed to more precisely define the health risks of HTPs compared to cigarettes and NVPs, the relative appeal of HTPs to consumers, and the likelihood of later transitioning to smoking or quitting all products. While our analysis provides a framework for gaining that information, it also illustrates the complexities in distinguishing key factors.

Optimizing global COVID-19 vaccine allocation: An agent-based computational model of 148 countries

BACKGROUND

Based on the principles of equity and effectiveness, the World Health Organization and COVAX formulate vaccine allocation as a mathematical optimization problem. This study aims to solve the optimization problem using agent-based simulations.

METHODS

We built open-sourced agent-based models to simulate virus transition among a demographically representative sample of 198 million people in 148 countries using advanced computational services. All countries continuing their current vaccine progress is defined as the baseline scenario. Comparison scenarios include achieving minimum vaccination rates and allocating vaccines based on pandemic levels.

FINDINGS

The simulations are fitted using the pandemic data from 148 countries from January 2020 to June 2021. Under the baseline scenario, the world will add 24.36 million cases and 468,945 deaths during the projection period of three months. Inoculating at least 10%, 20%, and 26% of populations in all countries requires 1.12, 3.31, and 5.00 million additional vaccine doses every day, respectively. Achieving these benchmarks reduces new cases by 0.56, 2.74, and 3.32 million, respectively. If allocated by the current global distribution, 5.00 million additional vaccine doses will only avert 1.45 million new cases. If those 5.00 million vaccines are allocated based on projected cases in each country, the averted cases will increase more than six-fold to 9.20 million. Similar differences between allocation methods are observed in averted deaths.

CONCLUSION

The global distribution of COVID-19 vaccines can be optimized to achieve better outcomes in terms of both equity and effectiveness. Alternative vaccine allocation methods may avert several times more cases and deaths than the current global distribution. With reasonable requirements on additional vaccines, COVAX could adopt alternative allocation strategies that reduce cross-country inequity and save more lives.

Assessing the Dynamic Outcomes of Containment Strategies against COVID-19 under Different Public Health Governance Structures: A Comparison between Pakistan and Bangladesh

COVID-19 scenarios were run using an epidemiological mathematical model (system dynamics model) and counterfactual analysis to simulate the impacts of different control and containment measures on cumulative infections and deaths in Bangladesh and Pakistan. The simulations were based on national-level data concerning vaccination level, hospital capacity, and other factors, from the World Health Organization, the World Bank, and the Our World in Data web portal. These data were added to cumulative infections and death data from government agencies covering the period from 18 March 2020 to 28 February 2022. Baseline curves for Pakistan and Bangladesh were obtained using piecewise fitting with a consideration of different events against the reported data and allowing for less than 5% random errors in cumulative infections and deaths. The results indicate that Bangladesh could have achieved more reductions in each key outcome measure by shifting its initial lockdown at least five days backward, while Pakistan would have needed to extend its lockdown to achieve comparable improvements. Bangladesh's second lockdown appears to have been better timed than Pakistan's. There were potential benefits from starting the third lockdown two weeks earlier for Bangladesh and from combining this with the fourth lockdown or canceling the fourth lockdown altogether. Adding a two-week lockdown at the beginning of the upward slope of the second wave could have led to a more than 40 percent reduction in cumulative infections and a 35 percent reduction in cumulative deaths for both countries. However, Bangladesh's reductions were more sensitive to the duration of the lockdown. Pakistan's response was more constrained by medical resources, while Bangladesh's outcomes were more sensitive to both vaccination timing and capacities. More benefits were lost when combining multiple scenarios for Bangladesh compared to the same combinations in Pakistan. Clearly, cumulative infections and deaths could have been highly impacted by adjusting the control and containment measures in both national settings. However, COVID-19 outcomes were more sensitive to adjustment interventions for the Bangladesh context. Disaggregated analyses, using a wider range of factors, may reveal several sub-national dynamics. Nonetheless, the current research demonstrates the relevance of lockdown timing adjustments and discrete adjustments to several other control and containment measures.

Assessing the dynamic impacts of non-pharmaceutical and pharmaceutical intervention measures on the containment results against COVID-19 in Ethiopia

The rapid spread of COVID-19 in Ethiopia was attributed to joint effects of multiple factors such as low adherence to face mask-wearing, failure to comply with social distancing measures, many people attending religious worship activities and holiday events, extensive protests, country election rallies during the pandemic, and the war between the federal government and Tigray Region. This study built a system dynamics model to capture COVID-19 characteristics, major social events, stringencies of containment measures, and vaccination dynamics. This system dynamics model served as a framework for understanding the issues and gaps in the containment measures against COVID-19 in the past period (16 scenarios) and the spread dynamics of the infectious disease over the next year under a combination of different interventions (264 scenarios). In the counterfactual analysis, we found that keeping high mask-wearing adherence since the outbreak of COVID-19 in Ethiopia could have significantly reduced the infection under the condition of low vaccination level or unavailability of the vaccine supply. Reducing or canceling major social events could achieve a better outcome than imposing constraints on people's routine life activities. The trend analysis found that increasing mask-wearing adherence and enforcing more stringent social distancing were two major measures that can significantly reduce possible infections. Higher mask-wearing adherence had more significant impacts than enforcing social distancing measures in our settings. As the vaccination rate increases, reduced efficacy could cause more infections than shortened immunological periods. Offsetting effects of multiple interventions (strengthening one or more interventions while loosening others) could be applied when the levels or stringencies of one or more interventions need to be adjusted for catering to particular needs (e.g., less stringent social distancing measures to reboot the economy or cushion insufficient resources in some areas).

Sensory swap: Modelling the impact of swapping discretionary choices for similar tasting core foods on the energy, nutrients and sensory properties of Australian diets

Food choice is strongly driven by the sensory characteristics of foods with sweet, salty and fatty mouthfeel considered highly palatable and rewarding. Attempts to improve diet quality have not addressed sensory characteristics of diets before. This report describes a data modelling exercise that could underpin a dietary strategy to help support consumption of higher quality diets without compromising sensory preferences. This study used the Australian National Nutrition and Physical Activity Survey data (in 9341 adults) and the CSIRO sensory-diet database. A method was developed to find core food swaps which had a similar sensory profile as discretionary foods. This study investigated the impact of such swaps on energy and nutrient intake and the impact of the swaps on servings of food groups. The modelling resulted in a similar sensory profile of core foods to that of discretionary foods with hardness, sweetness and fatty mouthfeel all within 1-3% but the saltiness approached a 4% change. There was a small (3.6%) increase in energy intake. This swap strategy decreased the intake of risk nutrients such as saturated fat and added sugars, but not sodium, while increasing the intake of beneficial nutrients like calcium, zinc and vitamin C. Results also show that there was an increase in the intake of servings of core food groups such as fruits, grains, and dairy products but little change in vegetables. In conclusion, similar sensory swaps are possible and could underpin a diet strategy, that could be further refined through food appropriateness, to improve quality.

US Nicotine Vaping Product SimSmoke Simulation Model: The Effect of Vaping and Tobacco Control Policies on Smoking Prevalence and Smoking-Attributable Deaths

The public health impact of nicotine vaping products (NVPs) is subject to a complex set of uncertain transitions between NVP and cigarette use. Instead, we apply an indirect method to gauge the impact of NVP use on smoking prevalence and smoking-attributable deaths (SADs) using the well-established SimSmoke tobacco control policy simulation model. Upon validating the model before NVPs were more widely used, we project a No-NVP (i.e., in the absence of NVPs) while controlling for the impact of cigarette-oriented policies. The net impact of NVPs on smoking prevalence is inferred by comparing the projected No-NVP smoking trends to corresponding trends from two US national surveys. Using the TUS-CPS estimates for the period 2012-2018, we estimate that adult smoking prevalence declined in relative terms by 9.7% (95% CI: 7.5-11.7%) for males and 10.7% (95% CI: 9.1-13.0%) for females. Compared to NHIS, smoking prevalence declined by 10.7% (95% CI: 6.8-14.6%) for males and 11.3% (95% CI: 7.4-15.6%) for females. These impacts were confined mainly to ages 18-44. Vaping-related reductions in smoking prevalence were projected to avert nearly 0.4 million SADs between 2012 and 2052. Our analysis indicates that NVP use is associated with substantial reductions in US smoking prevalence among younger adults.

England SimSmoke: the impact of nicotine vaping on smoking prevalence and smoking-attributable deaths in England

BACKGROUND AND AIMS

Whereas the use of nicotine vaping products (NVPs) is widespread, their impact on smoking prevalence is controversial. This study considered the potential impact of NVPs on smoking prevalence in England.

DESIGN

Indirect simulation model. The England SimSmoke model is validated through 2012, before NVP use became more widely used by smokers. Because information on NVP-related transitions is limited, an indirect method is used; the difference in observed smoking prevalence (reflecting NVPs) is compared with a 2012-2019 counterfactual No-NVP scenario (without NVPs) to estimate the impact of NVPs on smoking and smoking-attributable deaths.

SETTING

England, 2000-2019.

PARTICIPANTS

Nationally representative sample of population.

MEASUREMENTS

England's population, mortality rates and smoking prevalence estimates from three national surveys and tobacco control policies.

FINDINGS

Between 2000 and 2012, SimSmoke projected a decline in age 18+ smoking prevalence of 23.5% in men and 27.0% in women. These projections, as well as those by specific age groups, were generally consistent with findings from the three national surveys. Comparing 2012-2019 relative reduction in age 18+ prevalence from the Annual Population Survey (males, 27.5%) with the model-predicted No-NVP reduction (males, 7.3%), the implied NVP-attributable relative reduction in adult smoking prevalence was 20.2% (95% CI, 18.8%-22.0%) for males and 20.4% (18.7%-22.2%) for females. The NVP-attributable reduction was 27.2% (22.8%-31.6%) for males and 31.7% (27.4%-36.5%) for females ages 18-24 and 18.6% (15.2%-21.8%) for males and 15.0% (11.1%-18.8%) for females ages 25-34, with similar reductions for ages 35+. The implied reduction in smoking prevalence between 2012 and 2019 equates to 165 660 (132 453-199 501) averted deaths by 2052. Other surveys yielded smaller, but relatively consistent results.

CONCLUSIONS

An indirect method of simulation modelling indicates that substantial reductions in smoking prevalence occurred in England from 2012-2019 coinciding with the growth in nicotine vaping product use.

Estimating future smoking in Danish youth – effects of three prevention strategies

Aims: Preventing smoking and aiding cessation among youth and young adults carries the possibility of reducing future smoking prevalence significantly. This paper estimates the impact on future smoking prevalence of 25 year olds by increasing tobacco prices, securing indoor smoke-free homes and implementing school-based multi-tiered interventions. Methods: Utilizing a multi-state Markov model, a status quo projection of the smoking prevalence from years 2017 to 2030 were compared with projections of the smoking prevalence in 2030 considering the impact of the three prevention strategies. Results: In a status quo projection, 27.0% of Danish 25-year-old females are expected to be smokers in 2030, while 13.2% would be smokers in 2030 were all three prevention strategies in effect from 2019. By itself, increasing tobacco prices by 50% reduced the prevalence of smokers among 25-year-old females to 14.8% in 2030, a relative reduction of 47.5%. For 25-year-old males in 2030 the reductions were similar, with a prevalence of 16.6% when all three prevention strategies were in effect, a relative reduction of 51.5%. Conclusions: Implementing increasing tobacco prices, indoor smoke-free homes and school-based multi-tiered interventions in Denmark is likely to significantly decrease youth smoking prevalence in the future. However, these three strategies will not produce a smoke-free generation without other initiatives.

Using Simulation Modeling to Guide the Design of the Girl Scouts Fierce & Fit Program

OBJECTIVE

The study aim was to help the Girl Scouts of Central Maryland evaluate, quantify, and potentially modify the Girl Scouts Fierce & Fit program.

METHODS

From 2018 to 2019, our Public Health Informatics, Computational, and Operations Research team developed a computational simulation model representing the 250 adolescent girls participating in the Fierce & Fit program and how their diets and physical activity affected their BMI and subsequent outcomes, including costs.

RESULTS

Changing the Fierce & Fit program from a 6-week program meeting twice a week, with 5 minutes of physical activity each session, to a 12-week program meeting twice a week with 30 minutes of physical activity saved an additional $84,828 ($80,130-$89,526) in lifetime direct medical costs, $81,365 ($76,528-$86,184) in lifetime productivity losses, and 7.85 (7.38-8.31) quality-adjusted life-years. The cost-benefit of implementing this program was $95,943. Based on these results, the Girl Scouts of Central Maryland then implemented these changes in the program.

CONCLUSIONS

This is an example of using computational modeling to help evaluate and revise the design of a program aimed at increasing physical activity among girls.

Applied systems thinking: a viable approach to identify leverage points for accelerating progress towards ending neglected tropical diseases

BACKGROUND

Systems thinking is a conceptual approach that can assist stakeholders in understanding complexity and making progress on persistent public health challenges. Neglected tropical diseases (NTDs), a complex global health problem, are responsible for a large disease burden among impoverished populations around the world. This aim of this study was to better discern the many complexities of the global NTD system in order to identify and act on leverage points to catalyse progress towards ending NTDs.

METHODS

Existing frameworks for systems change were adapted to form the conceptual framework for the study. Using a semi-structured interview guide, key informant interviews were conducted with NTD stakeholders at the global level and at the country level in Nigeria. The interview data were coded and analysed to create causal loop diagrams that resulted in a qualitative model of the global NTD system.

RESULTS

The complete qualitative model is discussed and presented visually as six separate sub-components that highlight key forces and feedback loops within the global NTD system.

CONCLUSIONS

We identified five leverage points for NTD system change, namely (1) clarify the potential for and assess realistic progress towards NTD elimination, (2) increase support for interventions besides drug delivery, (3) reduce dependency on international donors, (4) create a less insular culture within the global NTD community, and (5) systemically address the issue of health worker incentives. The specific findings for NTDs raise a number of uncomfortable questions that have not been addressed, at least in part, because it is easier to continue focusing on 'quick win' solutions. The study provides a model of a systems thinking approach that can be applied to other complex global health and development challenges in order to understand complexity and identify leverage points for system change.

A Systems Thinking Approach to Inform Coherent Policy Action for NCD Prevention Comment on "How Neoliberalism Is Shaping the Supply of Unhealthy Commodities and What This Means for NCD Prevention"

Lencucha and Thow tackle the enormous public health challenge of developing non-communicable disease (NCD) policy coherence within a world structured and ruled by neoliberalism. Their work compliments scholarship on other causal mechanisms, including the commercial determinants of health, that have contributed to creating the risk commodity environment and barriers to NCD prevention policy coherence. However, there remain significant gaps in the understanding of how these causal mechanisms interact within a whole system. As such, public health researchers’ suggestions for how to effectively prevent NCDs through addressing the risk commodity environment tend to remain fragmented, incomplete and piecemeal. We suggest this is, in part, because conventional policy analysis methods tend to be reductionist, considering causal mechanisms in relative isolation and conceptualizing them as linear chains of cause and effect. This commentary discusses how a systems thinking approach offers methods that could help with better understanding the risk commodity environment problem, identifying a more comprehensive set of effective solutions across sectors and its utility more broadly for gaining insight into how to ensure recommended solutions are translated into policy, including though transformation at the paradigmatic level.

Modelling the impact of menthol sales restrictions and retailer density reduction policies: insights from tobacco town Minnesota

Introduction

Tobacco control policies focused on the retail environment have the potential to reduce tobacco use and tobacco-related health disparities through increasing direct and indirect costs. Recently, national and subnational governments have begun to restrict the sale of menthol products and reduce tobacco retailer density.

Methods

We developed an agent-based model to project the impact of menthol cigarette sales restrictions and retailer density reduction policies for six types of communities and three priority populations. During each simulated day, agents smoke cigarettes, travel in the community and make purchase decisions—whether, where and which product type to purchase—based on a combination of their own properties and the current retail environment.

Results

Of the policies tested, restricting all cigarette sales or menthol cigarette sales to tobacco specialty shops may have the largest effect on the total (direct and indirect) costs of purchasing cigarettes. Coupling one of these policies with one that establishes a minimum distance between tobacco retailers may enhance the impact. Combining these policies could also make the costs of acquiring cigarettes more equal across communities and populations.

Discussion

Our simulations revealed the importance of context, for example, lower income communities in urban areas begin with higher retailer density and may need stronger policies to show impact, as well as the need to focus on differential effects for priority populations, for example, combinations of policies may equalise the average distance travelled to purchase. Adapting and combining policies could enhance the sustainability of policy effects and reduce tobacco use.

Increasing Price and Reducing Access to Tobacco in New York City

This paper describes novel tobacco control laws passed in New York City in 2017. These laws are designed to improve the city's strategy of using price to decrease tobacco consumption, and over time, change the city's landscape by making tobacco less accessible.

Is the decline of active travel to school unavoidable by-products of economic growth and urbanization in developing countries?

BACKGROUND

Economic growth and urbanization may contribute to the decline of active travel to school (ATS). We aim to explain the change of ATS in China between 1997 and 2011 and to predict the prevalence of ATS in China within the next 30 years using various scenario.

METHODS

We developed a system dynamics model to study ATS and the model assumes the prevalence of ATS is determined by the dynamic interaction of four exogenous and eight endogenous variables.

RESULTS

The simulated prevalence of ATS is roughly consistent with empirical data. Economic development and urban sprawl are more influential than urban design and crime in terms of ATS. Under a relatively reasonable scenario, the prevalence of ATS is projected to decrease from 73% in 2011 to 65% in 2014, and the prevalence of childhood overweight & obesity is projected to increase from 24% in 2011 to 34% in 2041. With the maintaining of economic development grow, to control urban sprawl is the most effective measure to promote ATS and decrease childhood obesity.

CONCLUSIONS

Overall, the model enabled us to conduct experiments to test the possible effects of changing one or more factors taking into account their dynamic interrelationship, and our study may provide implications for policy intervention.

Simulated impacts and potential cost effectiveness of Communities Putting Prevention to Work: Tobacco control interventions in 21 U.S. communities, 2010-2020

In 2010, the Centers for Disease Control and Prevention (CDC) funded communities to implement policy, systems, and environmental (PSE) changes under the Communities Putting Prevention to Work (CPPW) program to make it easier for people to make healthier choices to prevent chronic disease. Twenty-one of 50 funded communities implemented interventions intended to reduce tobacco use. To examine the potential cost-effectiveness of tobacco control changes implemented under CPPW from a healthcare system perspective, we compared program cost estimates with estimates of potential impacts. We used an existing simulation model, the Prevention Impacts Simulation Model (PRISM), to estimate the potential cumulative impact of CPPW tobacco interventions on deaths and medical costs averted through 2020. We collected data on the costs to implement CPPW tobacco interventions from 2010 to 2013. We adjusted all costs to 2010 dollars. CPPW tobacco interventions cost $130.5 million across all communities, with an average community cost of $6.2 million. We found $735 million in potentially averted medical costs cumulatively from 2010 through 2020 because of the CPPW-supported interventions. If the CPPW tobacco control PSE changes are sustained through 2020 without additional funding after 2013, we find that medical costs averted will likely exceed program costs by $604 million. Our results suggest that the medical costs averted through 2020 may more than offset the initial investment in CPPW tobacco control interventions, implying that such interventions may be cost saving, especially over the long term.

Simulation modeling to assist with childhood obesity control: perceptions of Baltimore City policymakers

Computational simulation models have potential to inform childhood obesity prevention efforts. To guide their future use in obesity prevention policies and programs, we assessed Baltimore City policymakers' perceptions of computational simulation models. Our research team conducted 15 in-depth interviews with stakeholders (policymakers in government and non-profit sectors), then transcribed and coded them for analysis. We learned that informants had limited understanding of computational simulation modeling. Although they did not understand how the model was developed, they perceived the tool to be useful when applying for grants, adding to the evidence base for decision-making, piloting programs and policies, and visualizing data. Their concerns included quality and relevance of data used to support the model. Key recommendations for model design included a visual display with explanations to facilitate understanding and a formal method for gathering feedback during model development.

Tobacco Free Ireland 2025: SimSmoke prediction for the end game

INTRODUCTION

This study estimates the impact of tobacco control policies implemented between 1998 and 2016 on smoking prevalence reduction in Ireland by 2016. It then assesses the potential of further strong policies, relative to a scenario of inaction, to see if Tobacco Free Ireland 2025 is feasible.

METHODS

SimSmoke, the dynamic simulation model of tobacco control policy, was adapted to examine the impact of Irish tobacco control policies on smoking prevalence, through initiation and cessation, and smoking-attributable deaths and to make predictions for the future.

RESULTS

Between 1998 and 2016, the model prediction of smoking prevalence is reasonably close to those from several surveys. As a result of policies implemented in this period, the smoking rate was reduced by 42% from 32.2% in 1998 to 18.7% in 2016. If tobacco control policies remain unchanged from their 2016 levels, smoking prevalence is projected to be 15.8% in 2025. With the introduction of stricter MPOWER-compliant policies in 2017, the smoking prevalence could be reduced to 12.4% in 2025.

CONCLUSIONS

Predictions from the SimSmoke Ireland model confirm that the policies implemented between 1998 and 2016 have had a considerable effect. In addition, implementing policies fully compliant with MPOWER could further reduce the smoking prevalence afterwards. However, even under the stricter MPOWER-compliant policies, there is still a gap between the predicted rate in 2025 and the Tobacco Free Ireland target of 5%. Therefore, new policies going beyond MPOWER are needed.

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.

Agent-Based Modeling in Public Health: Current Applications and Future Directions

Agent-based modeling is a computational approach in which agents with a specified set of characteristics interact with each other and with their environment according to predefined rules. We review key areas in public health where agent-based modeling has been adopted, including both communicable and noncommunicable disease, health behaviors, and social epidemiology. We also describe the main strengths and limitations of this approach for questions with public health relevance. Finally, we describe both methodologic and substantive future directions that we believe will enhance the value of agent-based modeling for public health. In particular, advances in model validation, comparisons with other causal modeling procedures, and the expansion of the models to consider comorbidity and joint influences more systematically will improve the utility of this approach to inform public health research, practice, and policy.

Systems Thinking and Simulation Modeling to Inform Childhood Obesity Policy and Practice

OBJECTIVES

In 2007, 31.7% of Georgia adolescents in grades 9-12 were overweight or obese. Understanding the impact of policies and interventions on obesity prevalence among young people can help determine statewide public health and policy strategies. This article describes a systems model, originally launched in 2008 and updated in 2014, that simulates the impact of policy interventions on the prevalence of childhood obesity in Georgia through 2034.

METHODS

In 2008, using information from peer-reviewed reports and quantitative estimates by experts in childhood obesity, physical activity, nutrition, and health economics and policy, a group of legislators, legislative staff members, and experts trained in systems thinking and system dynamics modeling constructed a model simulating the impact of policy interventions on the prevalence of childhood obesity in Georgia through 2034. Use of the 2008 model contributed to passage of a bill requiring annual fitness testing of schoolchildren and stricter enforcement of physical education requirements. We updated the model in 2014.

RESULTS

With no policy change, the updated model projects that the prevalence of obesity among children and adolescents aged ≤18 in Georgia would hold at 18% from 2014 through 2034. Mandating daily school physical education (which would reduce prevalence to 12%) and integrating moderate to vigorous physical activity into elementary classrooms (which would reduce prevalence to 10%) would have the largest projected impact. Enacting all policies simultaneously would lower the prevalence of childhood obesity from 18% to 3%.

CONCLUSIONS

Systems thinking, especially with simulation models, facilitates understanding of complex health policy problems. Using a simulation model to educate legislators, educators, and health experts about the policies that have the greatest short- and long-term impact should encourage strategic investment in low-cost, high-return policies.

Public health benefits from pictorial health warnings on US cigarette packs: a SimSmoke simulation

INTRODUCTION

While many countries have adopted prominent pictorial warning labels (PWLs) for cigarette packs, the USA still requires only small, text-only labels located on one side of the cigarette pack that have little effect on smoking-related outcomes. Tobacco industry litigation blocked implementation of a 2011 Food and Drug Administration's (FDA) rule requiring large PWLs. To inform FDA action on PWLs, this study provides research-based estimates of their public health impacts.

METHODS

Literature was reviewed to identify the impact of cigarette PWLs on smoking prevalence, cessation and initiation. Based on this analysis, the SimSmoke model was used to estimate the effect of requiring PWLs in the USA on smoking prevalence and, using standard attribution methods, on smoking-attributable deaths (SADs) and key maternal and child health outcomes.

RESULTS

Available research consistently shows a direct association between PWLs and increased cessation and reduced smoking initiation and prevalence. The SimSmoke model projects that PWLs would reduce smoking prevalence by 5% (2.5%-9%) relative to the status quo over the short term and by 10% (4%-19%) over the long term. Over the next 50 years, PWLs are projected to avert 652 800 (327 000-1 190 500) SADs, 46 600 (17 500-92 300) low-birth-weight cases, 73 600 (27 800-145 100) preterm births and 1000 (400-2000) cases of sudden infant death syndrome.

CONCLUSIONS

Requiring PWLs on all US cigarette packs would be appropriate for the protection of the public health, because it would substantially reduce smoking prevalence and thereby reduce SADs and the morbidity and medical costs associated with adverse smoking-attributable birth outcomes.

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.

Tobacco Town: Computational Modeling of Policy Options to Reduce Tobacco Retailer Density

OBJECTIVES

To identify the behavioral mechanisms and effects of tobacco control policies designed to reduce tobacco retailer density.

METHODS

We developed the Tobacco Town agent-based simulation model to examine 4 types of retailer reduction policies: (1) random retailer reduction, (2) restriction by type of retailer, (3) limiting proximity of retailers to schools, and (4) limiting proximity of retailers to each other. The model examined the effects of these policies alone and in combination across 4 different types of towns, defined by 2 levels of population density (urban vs suburban) and 2 levels of income (higher vs lower).

RESULTS

Model results indicated that reduction of retailer density has the potential to decrease accessibility of tobacco products by driving up search and purchase costs. Policy effects varied by town type: proximity policies worked better in dense, urban towns whereas retailer type and random retailer reduction worked better in less-dense, suburban settings.

CONCLUSIONS

Comprehensive retailer density reduction policies have excellent potential to reduce the public health burden of tobacco use in communities.

Comparing the Nutritional Impact of Dietary Strategies to Reduce Discretionary Choice Intake in the Australian Adult Population: A Simulation Modelling Study

Dietary strategies to reduce discretionary choice intake are commonly utilized in practice, but evidence on their relative efficacy is lacking. The aim was to compare the potential impact on nutritional intake of three strategies to reducing discretionary choices intake in the Australian adult (19-90 years) population. Dietary simulation modelling using data from the National Nutrition and Physical Activity Survey 2011-2012 was conducted (n = 9341; one 24 h dietary recall). Strategies modelled were: moderation (reduce discretionary choices by 50%, with 0%, 25% or 75% energy compensation); substitution (replace 50% of discretionary choices with core choices); reformulation (replace 50% SFA with unsaturated fats, reduce added sugars by 25%, and reduce sodium by 20%). Compared to the base case (observed) intake, modelled intakes in the moderation scenario showed: -17.3% lower energy (sensitivity analyses, 25% energy compensation -14.2%; 75% energy compensation -8.0%), -20.9% lower SFA (-17.4%; -10.5%), -43.3% lower added sugars (-41.1%; -36.7%) and 17.7% lower sodium (-14.3%; -7.5%). Substitution with a range of core items, or with fruits, vegetables and core beverages only, resulted in similar changes in energy intake (-13.5% and -15.4%), SFA (-17.7% and -20.1%), added sugars (-42.6% and -43%) and sodium (-13.7% and -16.5%), respectively. Reformulating discretionary choices had minimal impact on reducing energy intake but reduced SFA (-10.3% to -30.9%), added sugars (-9.3% to -52.9%), and alcohol (-25.0% to -49.9%) and sodium (-3.3% to -13.2%). The substitution and reformulation scenarios minimized negative changes in fiber, protein and micronutrient intakes. While each strategy has strengths and limitations, substitution of discretionary choices with core foods and beverages may optimize the nutritional impact.

A system dynamics modelling approach to assess the impact of launching a new nicotine product on population health outcomes

In 2012 the US FDA suggested the use of mathematical models to assess the impact of releasing new nicotine or tobacco products on population health outcomes. A model based on system dynamics methodology was developed to project the potential effects of a new nicotine product at a population level. A model representing traditional smoking populations (never, current and former smokers) and calibrated using historical data was extended to a two-product model by including electronic cigarettes use statuses. Smoking mechanisms, such as product initiation, switching, transition to dual use, and cessation, were represented as flows between smoking statuses (stocks) and the potential effect of smoking renormalisation through a feedback system. Mortality over a 50-year period (2000-2050) was the health outcome of interest, and was compared between two scenarios, with and without e-cigarettes being introduced. The results suggest that by 2050, smoking prevalence in adults was 12.4% in the core model and 9.7% (including dual users) in the counterfactual. Smoking-related mortality was 8.4% and 8.1%, respectively. The results suggested an overall beneficial effect from launching e-cigarettes and that system dynamics could be a useful approach to assess the potential population health effects of nicotine products when epidemiological data are not available.

A framework for evaluating the public health impact of e-cigarettes and other vaporized nicotine products

The use of vaporized nicotine products (VNPs), especially e-cigarettes and, to a lesser extent, pressurized aerosol nicotine products and heat-not-burn tobacco products, are being adopted increasingly as an alternative to smoking combusted products, primarily cigarettes. Considerable controversy has accompanied their marketing and use. We propose a framework that describes and incorporates patterns of VNP and combustible cigarette use in determining the total amount of toxic exposure effects on population health. We begin by considering toxicity and the outcomes relevant to population health. We then present the framework and define different measures of VNP use; namely, trial and long-term use for exclusive cigarette smokers, exclusive VNP and dual (cigarette and VNP) use. Using a systems thinking framework and decision theory we considered potential pathways for current, former and never users of VNPs. We then consider the evidence to date and the probable impacts of VNP use on public health, the potential effects of different policy approaches and the possible influence of the tobacco industry on VNP and cigarette use.

Complying with the framework convention for tobacco control: an application of the Abridged SimSmoke model to Israel

BACKGROUND

The World Health Organization Framework Convention for Tobacco Control (FCTC) established the MPOWER policy package to provide practical country-level guidance on implementing effective policies to reduce smoking rates. The Abridged SimSmoke tobacco control policy simulation model is applied to Israel to estimate the effects on reducing smoking-attributable mortality resulting from full implementation of MPOWER policies.

METHODS

Smoking prevalence from the 2014 Israel National Health Interview Survey 3 and population data from the Israel Central Bureau of Statistics were used to calculate the number of current smokers. The status of current Israeli policy was determined using information from MPOWER 2015 and from local sources. Based on existing knowledge that between 50 % and 65 % of smokers will die prematurely from smoking, the model is used to determine mortality reductions among current smokers from full implementation of MPOWER policies.

RESULTS

We estimate that between 547 and 711 thousand smokers of the current 1.1 million Israeli smokers will prematurely die due smoking. Within 40 years, complete implementation of MPOWER policies is projected to reduce smoking prevalence among current smokers by 34% and avert between 187 and 243 thousand deaths. Taxes, smoke-free air laws, marketing restrictions and media campaigns each reduce smoking by about 5 % within 5 years. Improved cessation treatment and health warnings each have smaller effects in the next five years, but their effects grow rapidly over time.

CONCLUSIONS

Israel Abridged SimSmoke shows that complete implementation of the MPOWER strategies has the potential to substantially reduce smoking prevalence, and avert premature deaths due to smoking. Additional benefits are also expected from reduced morbidity, reduced initiation among nonsmokers, and reduction in exposure of nonsmokers to tobacco smoke.

Application of the Abridged SimSmoke model to four Eastern Mediterranean countries

INTRODUCTION

The WHO established the MPOWER policy package to boost the implementation of the WHO Framework Convention for Tobacco Control (WHO FCTC) in 2008 and to provide practical guidance on policies effective at reducing smoking rates. An easily applied Abridged SimSmoke was developed to help countries gauge the effect of these policies using data from the WHO MPOWER/WHO Report (MPOWER Report) and is applied to four Eastern Mediterranean countries.

METHODS

The number of smokers in a country is calculated using the country's smoking prevalence and population. Policy effect sizes, based on previously validated SimSmoke models, are applied to the smoker populations to determine the reduction in the number of smokers resulting from implementing policies. The number of smoking-attributable deaths is derived based on findings that half of those smokers alive today will die from smoking.

RESULTS

Within 40 years, implementing the complete set of MPOWER policies is projected to reduce smoking prevalence by 29% (range 15%, 41%) and avert almost 1 (range 0.5, 1.4) million deaths in Egypt, reduce smoking prevalence by 52% (range 36%, 66%) and avert 156 000 (106 000, 196 000) deaths in Lebanon, reduce smoking prevalence by 56% (range 40%, 69%) and avert 3.5 (range 2.5, 4.3) million deaths in Pakistan, and reduce smoking prevalence by 37% (range 21%, 51%) and avert 245 000 (range 138 000, 334 000) deaths in Tunisia.

CONCLUSIONS

The Abridged SimSmoke model has been used to show the number of deaths from smoking and how MPOWER policies can be used to reach the WHO non-communicable deaths voluntary target for cigarette use reduction in four countries.

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.

Community-Based Interventions to Decrease Obesity and Tobacco Exposure and Reduce Health Care Costs: Outcome Estimates From Communities Putting Prevention to Work for 2010-2020

INTRODUCTION

In 2010, the Centers for Disease Control and Prevention (CDC) launched Communities Putting Prevention to Work (CPPW), a $485 million program to reduce obesity, tobacco use, and exposure to secondhand smoke. CPPW awardees implemented evidence-based policy, systems, and environmental changes to sustain reductions in chronic disease risk factors. This article describes short-term and potential long-term benefits of the CPPW investment.

METHODS

We used a mixed-methods approach to estimate population reach and to simulate the effects of completed CPPW interventions through 2020. Each awardee developed a community action plan. We linked plan objectives to a common set of interventions across awardees and estimated population reach as an early indicator of impact. We used the Prevention Impacts Simulation Model (PRISM), a systems dynamics model of cardiovascular disease prevention, to simulate premature deaths, health care costs, and productivity losses averted from 2010 through 2020 attributable to CPPW.

RESULTS

Awardees completed 73% of their planned objectives. Sustained CPPW improvements may avert 14,000 premature deaths, $2.4 billion (in 2010 dollars) in discounted direct medical costs, and $9.5 billion (in 2010 dollars) in discounted lifetime and annual productivity losses through 2020.

CONCLUSION

PRISM results suggest that large investments in community preventive interventions, if sustained, could yield cost savings many times greater than the original investment over 10 to 20 years and avert 14,000 premature deaths.

Mexico SimSmoke: how changes in tobacco control policies would impact smoking prevalence and smoking attributable deaths in Mexico

We examined the effect of tobacco control policies in Mexico on smoking prevalence and smoking-related deaths using the Mexico SimSmoke model. The model is based on the previously developed SimSmoke simulation model of tobacco control policy, and uses population size, smoking rates and tobacco control policy data for Mexico. It assesses, individually, and in combination, the effect of six tobacco control policies on smoking prevalence and smoking-related deaths. Policies included: cigarette excise taxes, smoke-free laws, anti-smoking public education campaigns, marketing restrictions, access to tobacco cessation treatments and enforcement against tobacco sales youth. The model estimates that, if Mexico were to adopt strong tobacco control policies compared to current policy levels, smoking prevalence could be reduced by 30% in the next decade and by 50% by 2053; an additional 470,000 smoking-related premature deaths could be averted over the next 40 years. The greatest impact on smoking and smoking-related deaths would be achieved by raising excise taxes on cigarettes from 55% to at least 70% of the retail price, followed by strong youth access enforcement and access to cessation treatments. Implementing tobacco control policies in Mexico could reduce smoking prevalence by 50%, and prevent 470,000 smoking-related deaths by 2053.

The influence of societal individualism on a century of tobacco use: modelling the prevalence of smoking

Background

Smoking of tobacco is estimated to have caused approximately six million deaths worldwide in 2014. Responding effectively to this epidemic requires a thorough understanding of how smoking behaviour is transmitted and modified.

Methods

We present a new mathematical model of the social dynamics that cause cigarette smoking to spread in a population, incorporating aspects of individual and social utility. Model predictions are tested against two independent data sets spanning 25 countries: a newly compiled century-long composite data set on smoking prevalence, and Hofstede’s individualism/collectivism measure (IDV).

Results

The general model prediction that more individualistic societies will show faster adoption and cessation of smoking is supported by the full 25 country smoking prevalence data set. Calibration of the model to the available smoking prevalence data is possible in a subset of 7 countries. Consistency of fitted model parameters with an additional, independent, data set further supports our model: the fitted value of the country-specific model parameter that determines the relative importance of social and individual factors in the decision of whether or not to smoke, is found to be significantly correlated with Hofstede’s IDV for the 25 countries in our data set.

Conclusions

Our model in conjunction with extensive data on smoking prevalence provides evidence for the hypothesis that individualism/collectivism may have an important influence on the dynamics of smoking prevalence at the aggregate, population level. Significant implications for public health interventions are discussed.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-015-2576-6) contains supplementary material, which is available to authorized users.

Tobacco Policies in Louisiana: Recommendations for Future Tobacco Control Investment from SimSmoke, a Policy Simulation Model

Despite the presence of tobacco control policies, Louisiana continues to experience a high smoking burden and elevated smoking-attributable deaths. The SimSmoke model provides projections of these health outcomes in the face of existing and expanded (simulated) tobacco control polices. The SimSmoke model utilizes population data, smoking rates, and various tobacco control policy measures from Louisiana to predict smoking prevalence and smoking-attributable deaths. The model begins in 1993 and estimates are projected through 2054. The model is validated against existing Louisiana smoking prevalence data. The most powerful individual policy measure for reducing smoking prevalence is cigarette excise tax. However, a comprehensive cessation treatment policy is predicted to save the most lives. A combination of tobacco control policies provides the greatest reduction in smoking prevalence and smoking-attributable deaths. The existing Louisiana excise tax ranks as one of the lowest in the country and the legislature is against further increases. Alternative policy measures aimed at lowering prevalence and attributable deaths are: cessation treatments, comprehensive smoke-free policies, and limiting youth access. These three policies have a substantial effect on smoking prevalence and attributable deaths and are likely to encounter more favor in the Louisiana legislature than increasing the state excise tax.

Public Health Effects of Restricting Retail Tobacco Product Displays and Ads

OBJECTIVES

To estimate the public health impact from restricting US retail point-of-sale (POS) tobacco product displays and advertising.

METHODS

Based on existing research, this paper estimates the effects on initiation and cessation rates from restricting POS tobacco product displays and ads in the US and uses the SimSmoke simulation model to project related smoking declines and health benefits.

RESULTS

New comprehensive POS restrictions are projected to reduce smoking prevalence by approximately 16% [range=3%-31%] relative to the status quo by 2065, preventing about 630,000 smoking-attributable deaths [range=108,000-1,225,000], 215,000 low birth weight births [range=33,000-421,000], 140,000 preterm births [range=22,000-271,000], and 1900 infant deaths from SIDSs [range=300-3800].

CONCLUSIONS

Federal, state, or local action to restrict POS tobacco product displays and ads would contribute to a substantial reduction in smoking-attributed death and disease.

Modeling social norms and social influence in obesity

The worldwide increase in obesity has led to changes in what is considered "normal" or desirable weight, especially among populations at higher risk. We show that social norms are key to understanding the obesity epidemic, and that social influence mechanisms provide a necessary linkage between individual obesity-related behaviors and population-level characteristics. Because influence mechanisms cannot be directly observed, we show how three complex systems tools may be used to gain insights into observed epidemiologic patterns: social network analysis, agent-based modeling, and systems dynamics modeling. However, simulation and mathematical modeling approaches raise questions regarding acceptance of findings, especially among policy makers. Nevertheless, we point to modeling successes in obesity and other fields, including the NIH-funded National Collaborative on Childhood Obesity Research (NCCOR) Envison project.

Higher price, fewer packs: evaluating a tobacco tax increase with cigarette sales data

In 2013, Minnesota increased cigarette taxes by $1.75, the largest US state increase since 2000. We obtained convenience store data of cigarette sales from January 2012 to December 2013 from the Nielsen Company. Analysis revealed significantly greater year-to-year reductions in numbers of packs purchased during posttax (-12.1%) than pretax (-3.2%; P<.001) periods. The results provide contemporary evidence that, despite reduced prevalence and increased tobacco control efforts, tax increases remain an effective tobacco control strategy.

Modeling US adult obesity trends: a system dynamics model for estimating energy imbalance gap

OBJECTIVES

We present a system dynamics model that quantifies the energy imbalance gap responsible for the US adult obesity epidemic among gender and racial subpopulations.

METHODS

We divided the adult population into gender-race/ethnicity subpopulations and body mass index (BMI) classes. We defined transition rates between classes as a function of metabolic dynamics of individuals within each class. We estimated energy intake in each BMI class within the past 4 decades as a multiplication of the equilibrium energy intake of individuals in that class. Through calibration, we estimated the energy gap multiplier for each gender-race-BMI group by matching simulated BMI distributions for each subpopulation against national data with maximum likelihood estimation.

RESULTS

No subpopulation showed a negative or zero energy gap, suggesting that the obesity epidemic continues to worsen, albeit at a slower rate. In the past decade the epidemic has slowed for non-Hispanic Whites, is starting to slow for non-Hispanic Blacks, but continues to accelerate among Mexican Americans.

CONCLUSIONS

The differential energy balance gap across subpopulations and over time suggests that interventions should be tailored to subpopulations' needs.

Patterns of birth cohort-specific smoking histories, 1965-2009

BACKGROUND

Characterizing the smoking patterns for different birth cohorts is essential for evaluating the impact of tobacco control interventions and predicting smoking-related mortality, but the process of estimating birth cohort smoking histories has received limited attention.

PURPOSE

Smoking history summaries were estimated beginning with the 1890 birth cohort in order to provide fundamental parameters that can be used in studies of cigarette smoking intervention strategies.

METHODS

U.S. National Health Interview Surveys conducted from 1965 to 2009 were used to obtain cross-sectional information on current smoking behavior. Surveys that provided additional detail on history for smokers including age at initiation and cessation and smoking intensity were used to construct smoking histories for participants up to the date of survey. After incorporating survival differences by smoking status, age-period-cohort models with constrained natural splines were used to estimate the prevalence of current, former, and never smokers in cohorts beginning in 1890. This approach was then used to obtain yearly estimates of initiation, cessation, and smoking intensity for the age-specific distribution for each birth cohort. These rates were projected forward through 2050 based on recent trends.

RESULTS

This summary of smoking history shows clear trends by gender, cohort, and age over time. If current patterns persist, a slow decline in smoking prevalence is projected from 2010 through 2040.

CONCLUSIONS

A novel method of generating smoking histories has been applied to develop smoking histories that can be used in micro-simulation models, and has been incorporated in the National Cancer Institute's Smoking History Generator. These aggregate estimates developed by age, gender, and cohort will provide a complete source of smoking data over time.

Reducing social inequalities in health: the role of simulation modelling in chronic disease epidemiology to evaluate the impact of population health interventions

Reducing health inequalities has become a major public health priority internationally. However, how best to achieve this goal is not well understood. Population health intervention research has the potential to address some of this knowledge gap. This review argues that simulation studies can produce unique evidence to build the population health intervention research evidence base on reducing social inequalities in health. To this effect, the advantages of using simulation models over other population health intervention research methods are discussed. Key questions regarding the potential challenges of developing simulation models to investigate population health intervention research on reducing social inequalities in health and the types of population health intervention research questions that can be answered using this methodology are reviewed. We use the example of social inequalities in coronary heart disease to illustrate how simulation models can elucidate the effectiveness of a number of ‘what-if’ counterfactual population health interventions on reducing social inequalities in coronary heart disease. Simulation models are a flexible, cost-effective, evidence-based research method with the capacity to inform public health policy-makers regarding the implementation of population health interventions to reduce social inequalities in health.

The benefits from complying with the framework convention on tobacco control: a SimSmoke analysis of 15 European nations

INTRODUCTION

This article compares the predicted impact of tobacco tax increases alone and as part of a comprehensive tobacco control strategy on smoking prevalence and smoking-attributable deaths (SADs) across 15 European countries.

METHODS

Country-specific population, smoking prevalence and policy data with modified parameter values have been applied to the previously validated SimSmoke model for 10 high-income and 5 middle-income European nations. The impact of past and potential future policies is modelled.

RESULTS

Models generally validated well across the 15 countries, and showed the impact of past policies. Without stronger future policies, 44 million lives would be lost due to smoking across the 15 study countries between 2011 and 2040, but effective policies could avert 7.7 million of those premature deaths.

CONCLUSIONS

Results suggest that past policies have been effective in reducing smoking rates, but there is also a strong potential for future policies consistent with the Framework Convention on Tobacco Control. When specific taxes are increased to 70% of retail price, strong smoke-free air laws, youth access laws and marketing restrictions are enforced, stronger health warnings are implemented, and cessation treatment and media campaigns are supported, smoking prevalence and SADs will fall substantially in European countries.

A dynamic population model for estimating all-cause mortality due to lifetime exposure history

We developed a comprehensive, flexible dynamic model that estimates all-cause mortality for a hypothetical cohort. All model input is user-specified. In the base case, members of the cohort may be exposed to a high risk product as they age. The counterfactual scenario includes exposure to both a high risk and a lower risk product. The model sorts the population into age and exposure categories, and applies the appropriate mortality rates to each category. The model tracks individual exposure histories, and estimates, at the end of each modeled age category, the number of survivors in the two exposure scenarios (base case and counterfactual), and the difference between them. Markov Chain Monte Carlo techniques are used to estimate the variability of the results. Model output was compared against US and Swedish life tables using population-specific tobacco exposure transition probabilities derived from the literature, and it produced similar survival estimates.