Integrating Social Dynamics Into Modeling Cigarette and E-Cigarette Use

A systematic review of the modelling and economic evaluation studies assessing regulatory options for e-cigarette use

BACKGROUND

Governments around the world are considering regulating access to nicotine e-cigarettes to prevent uptake among youth however people that smoke tobacco may use them to assist with smoking cessation. The health and cost implications of regulating e-cigarette use among populations are unknown but have been explored in modelling studies. We reviewed health economic evaluation and simulation modelling studies that assessed long-term consequences and interpret their potential usefulness for decision-makers.

METHODS

A systematic review with a narrative synthesis was undertaken. Six databases were searched for modelling studies evaluating population-level e-cigarette control policies or interventions restricting e-cigarette use versus more liberalized use. Studies were required to report the outcomes of life years, quality-adjusted life years (QALYs) and/or healthcare costs. The quality of the studies was assessed using two quality assessment tools.

RESULTS

In total, 15 studies were included with nine for the United States and one each for the United Kingdom, Italy, Australia, Singapore, Canada, and New Zealand. Three studies included cost-utility analyses. Most studies involved health state transition (or Markov) closed cohort models. Many studies had limitations with their model structures, data input quality and transparency, and insufficient analyses handling model uncertainty. Findings were mixed with 11 studies concluding that policies permitting e-cigarette use lead to net benefits and 4 studies concluding net losses in life-years or QALYs and/or healthcare costs.Five studies had industry conflicts of interest.

CONCLUSIONS

While authors did conclude net benefit than net harm in more of the studies so far conducted, the significant limitations that we identified with many of the studies in this review, make it uncertain whether or not countries can expect net population harms or benefits of restrictive versus unrestrictive e-cigarette policies. The generalizability of the findings is limited for decision-makers. In light of the deep uncertainty around the health and economic outcomes of e-cigarettes, simulation modelling methods and uncertainty analyses should be strengthened.

Predicting the long-term effects of electronic cigarette use on population health: a systematic review of modelling studies

OBJECTIVE

To systematically review and synthesise the findings of modelling studies on the population impacts of e-cigarette use and to identify potential gaps requiring future investigation.

DATA SOURCE AND STUDY SELECTION

Four databases were searched for modelling studies of e-cigarette use on population health published between 2010 and 2023. A total of 32 studies were included.

DATA EXTRACTION

Data on study characteristics, model attributes and estimates of population impacts including health outcomes and smoking prevalence were extracted from each article. The findings were synthesised narratively.

DATA SYNTHESIS

The introduction of e-cigarettes was predicted to lead to decreased smoking-related mortality, increased quality-adjusted life-years and reduced health system costs in 29 studies. Seventeen studies predicted a lower prevalence of cigarette smoking. Models that predicted negative population impacts assumed very high e-cigarette initiation rates among non-smokers and that e-cigarette use would discourage smoking cessation by a large margin. The majority of the studies were based on US population data and few studies included factors other than smoking status, such as jurisdictional tobacco control policies or social influence.

CONCLUSIONS

A population increase in e-cigarette use may result in lower smoking prevalence and reduced burden of disease in the long run, especially if their use can be restricted to assisting smoking cessation. Given the assumption-dependent nature of modelling outcomes, future modelling studies should consider incorporating different policy options in their projection exercises, using shorter time horizons and expanding their modelling to low-income and middle-income countries where smoking rates remain relatively high.

Agent-based model of the impact of higher influenza vaccine efficacy on seasonal influenza burden

Introduction

Current influenza vaccines have limited effectiveness. COVID-19 vaccines using mRNA technology have demonstrated very high efficacy, suggesting that mRNA vaccines could be more effective for influenza. Several such influenza vaccines are in development. FRED, an agent-based modeling platform, was used to estimate the impact of more effective influenza vaccines on seasonal influenza burden.

Methods

Simulations were performed using an agent-based model of influenza that included varying levels of vaccination efficacy (40-95 % effective). In some simulations, level of infectiousness and/or length of infectious period in agents with breakthrough infections was also decreased. Impact of increased and decreased levels of vaccine uptake were also modeled. Outcomes included number of symptomatic influenza cases estimated for the US.

Results

Highly effective vaccines significantly reduced estimated influenza cases in the model. When vaccine efficacy was increased from 40 % to a maximum of 95 %, estimated influenza cases in the US decreased by 43 % to > 99 %. The base simulation (40 % efficacy) resulted in ∼ 28 million total yearly cases in the US, while the most effective vaccine modeled (95 % efficacy) decreased estimated cases to ∼ 22,000.

Discussion

Highly effective vaccines could dramatically reduce influenza burden. Model estimates suggest that even modest increases in vaccine efficacy could dramatically reduce seasonal influenza disease burden.

Impact of Low Rates of Influenza on Next-Season Influenza Infections

INTRODUCTION

Interventions to curb the spread of COVID-19 during the 2020-2021 influenza season essentially eliminated influenza during that season. Given waning antibody titers over time, future residual population immunity against influenza will be reduced. The implication for the subsequent 2021-2022 influenza season is unknown.

METHODS

An agent-based model of influenza implemented in the Framework for Reconstructing Epidemiological Dynamics simulation platform was used to estimate cases and hospitalizations over 2 successive influenza seasons. The impact of reduced residual immunity owing to protective measures in the first season was estimated over varying levels of similarity (cross-immunity) between influenza strains over the seasons.

RESULTS

When cross-immunity between first- and second-season strains was low, a decreased first season had limited impact on second-season cases. High levels of cross-immunity resulted in a greater impact on the second season. This impact was modified by the transmissibility of strains in the 2 seasons. The model estimated a possible increase of 13.52%-46.95% in cases relative to that in a normal season when strains have the same transmissibility and 40%-50% cross-immunity in a season after a very low one.

CONCLUSIONS

Given the light 2020-2021 influenza season, cases may increase by as much as 50% in 2021-2022, although the increase could be much less, depending on cross-immunity from past infection and transmissibility of strains. Enhanced vaccine coverage or continued interventions to reduce transmission could reduce this high season. Young children may have a higher risk in 2021-2022 owing to limited exposure to infection in the previous year.

Conceptual model for the evaluation of attractiveness, addictiveness and toxicity of tobacco and related products: The example of JUUL e-cigarettes

Many new tobacco and related products (nTRP) have emerged on the market, with unknown health risks. Here, we present a conceptual model containing the factors and relations between them that contribute to the nTRP's health effects. Factors that determine attractiveness, addictiveness and toxicity of nTRP were defined based on previous assessments, literature, and expert discussions. Our model will aid in identifying key risk factors contributing to increased risk of adverse health effects for a product in a qualitative manner. Additionally, it can gauge attractiveness for specific user groups, as a determinant for population prevalence of use. Our model can be used to identify aspects of nTRP that require attention for public information or product regulation. As an example, we applied this to JUUL, a popular e-cigarette in the US. Aspects of concern for JUUL are its attractive and discrete shape, user-friendly prefilled pods, flavors, high aerosol nicotine levels, and liquids containing nicotine salts instead of free-based nicotine. The addictiveness and especially attractiveness are sufficiently high to have a large potential impact on population health due to its contribution to use and hence exposure. Products and their use can change over time; therefore market research and monitoring are crucial.

Adolescent Susceptibility to E-Cigarettes: An Update From the 2018 National Youth Tobacco Survey

PURPOSE

Examine correlates of e-cigarette susceptibility among adolescents.

DESIGN

Secondary data analyses using the 2018 National Youth Tobacco Survey, excluding participants under 12 and over 17.

SETTING

United States middle and high schools.

SUBJECTS

Never e-cigarette users (n = 12,439) ages 12-17.

MEASURES

Relationships between e-cigarette susceptibility and age, sex, race/ethnicity, ever tobacco use, perceived ease of purchasing tobacco products, perceived harm, relative addictiveness, household use of e-cigarettes/tobacco were examined.

ANALYSIS

Odds of susceptibility were modeled with weighted multivariable logistic regressions.

RESULTS

Thirty-five percent (unweighted n = 4,436) of adolescents were susceptible to e-cigarettes. Adolescents who were female (aOR = 1.2), Hispanic (aOR = 1.3), perceived e-cigarettes as anything less than "a lot of harm" (aOR = 2.2-4.9) and "easy" to purchase (aOR = 1.4), had ever used combustible tobacco (aOR = 2.9), or reported household use of e-cigarettes (aOR = 1.5) were susceptible. Non-Hispanic black respondents (vs. non-Hispanic white; aOR = 0.72) had significantly lower odds of susceptibility to e-cigarettes.

CONCLUSION

In the 2018 NYTS adolescent sample, perceptions of harm and ease of tobacco product purchase appear to be significantly related to higher odds of e-cigarette susceptibility, in addition to other demographic factors. Longitudinal data, particularly cohort data following adolescents from susceptible to actual or no use, are needed to assess predictors of e-cigarette use initiation.

Implementation of a cluster randomized controlled trial: Identifying student peer leaders to lead E-cigarette interventions

E-cigarette use has been increasing among middle school students. Intervention programs to prevent e-cigarette initiation administered by authority figures are met with more resistance from youth compared to peer-led programs. Therefore, this study aimed to assess the feasibility, acceptability, and implementation process of using social network analysis (SNA) to identify student peer leaders in schools and train them to deliver e-cigarette prevention programming to their peers. Nine schools were recruited to participate in the study during the 2019-2020 school year. Schools were assigned to one of three conditions: (1) expert; (2) peer-random (selected peer-leaders would teach to random students); and (3) peer-fixed (selected peer-leaders would teach to assigned students based on nominations). Study participation varied by day due to school attendance, with 686 participants at baseline and 608 at posttest. Almost all students who did not complete the study resulted from the interruption of schools being closed due to COVID-19. Implementation issues fell into three categories: (1) scheduling, (2) day-of logistics, and (3) student group dynamics. Overall, the results showed positive satisfaction among teachers, who unanimously found the program appropriate for the grade-level and that peer-leaders worked well within their groups. Peer-led students-both random and assigned-reported having more fun and willing to tell friends to try the program compared to expert-led students. This study demonstrated the feasibility of implementing a peer-led e-cigarette prevention program for 6th grade students, using SNA to provide intervention rigidity and validity.

Identifying student opinion leaders to lead e-cigarette interventions: protocol for a randomized controlled pragmatic trial

Background

After the US Surgeon General declared youth electronic cigarette (e-cigarette) use an epidemic in 2018, the number of youth e-cigarette users continued to surge, growing from 3.8 million in 2018 to over 5 million 2019. Youth who use e-cigarettes are at a substantially higher risk of transitioning to traditional cigarettes, becoming regular cigarette smokers, and increasing their risk of developing tobacco-related cancer.

A majority of youth are misinformed about e-cigarettes, often believing they are not harmful or contain no nicotine. Middle school students using e-cigarettes have been affected by its normalization leading to influence by their peers. However, social and group dynamics can be leveraged for a school-based peer-led intervention to identify and recruit student leaders to be anti-e-cigarette champions to prevent e-cigarette initiation. This study outlines a project to use social network analysis to identify student opinion-leaders in schools and train them to conduct anti-e-cigarette programming to their peers.

Methods

In the 2019–2020 academic school year, 6th grade students from nine schools in the Pittsburgh area were recruited. A randomized controlled trial (RCT) was conducted with three arms—expert, elected peer-leader, and random peer-leader—for e-cigarette programming. Sixth grade students in each school completed a network survey that assessed the friendship networks in each class. Students also completed pre-intervention and post-intervention surveys about their intention-to-use, knowledge, and attitudes towards e-cigarettes. Within each peer-led arm, social network analysis was conducted to identify peer-nominated opinion leaders. An e-cigarette prevention program was administered by (1) an adult content-expert, (2) a peer-nominated opinion leader to assigned students, or (3) a peer-nominated opinion leader to random students.

Discussion

This study is the first to evaluate the feasibility of leveraging social network analysis to identify 6th grade opinion leaders to lead a school-based e-cigarette intervention.

Trial registration

ClinicalTrials.gov NCT04083469. Registered on September 10, 2019.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-020-04990-z.