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Abstract: Aims: To inform the transferability of tobacco control‐related economic evidence to resource‐poor countries. Methods: We ran a univariate sensitivity analysis on a return on investment (ROI) model, the European study on Quantifying Utility of Investment in Protection from Tobacco model (EQUIPTMOD), to identify key input values to which the ROI estimates were sensitive. The EQUIPTMOD used a Markov‐based state transition model to estimate the ROI of several tobacco control interventions in five European countries (England, Germany, Spain, Hungary and the Netherlands). Base case ROI estimates were obtained through average values of model inputs (throughout the five countries), which were then replaced one at a time with country‐specific values. Tornado diagrams were used to evaluate the significance of sensitivity, defined as a ≥ 10% difference in ROI estimates from the base case estimates. Results: The ROI estimates were sensitive to 18 (of 46) input values. Examples of model inputs to which ROI estimates were sensitive included: smoking rate, costs of smoking‐related diseases (e.g. lung cancer) and general population attributes. Conclusion: Countries that have limited research time and other resources can adapt EQUIPTMOD to their own settings by choosing to collect data on a small number of model inputs. EQUIPTMOD can therefore facilitate transfer of tobacco control related economic evidence to new jurisdictions. [ABSTRACT FROM AUTHOR]

Abstract: Aims: To evaluate potential health and economic returns from implementing smoking cessation interventions in Hungary. Methods: The EQUIPTMOD, a Markov‐based economic model, was used to assess the cost‐effectiveness of three implementation scenarios: (a) introducing a social marketing campaign; (b) doubling the reach of existing group‐based behavioural support therapies and proactive telephone support; and (c) a combination of the two scenarios. All three scenarios were compared with current practice. The scenarios were chosen as feasible options available for Hungary based on the outcome of interviews with local stakeholders. Life‐time costs and quality‐adjusted life years (QALYs) were calculated from a health‐care perspective. The analyses used various return on investment (ROI) estimates, including incremental cost‐effectiveness ratios (ICERs), to compare the scenarios. Probabilistic sensitivity analyses assessed the extent to which the estimated mean ICERs were sensitive to the model input values. Results: Introducing a social marketing campaign resulted in an increase of 0.3014 additional quitters per 1 000 smokers, translating to health‐care cost‐savings of €0.6495 per smoker compared with current practice. When the value of QALY gains was considered, cost‐savings increased to €14.1598 per smoker. Doubling the reach of existing group‐based behavioural support therapies and proactive telephone support resulted in health‐care savings of €0.2539 per smoker (€3.9620 with the value of QALY gains), compared with current practice. The respective figures for the combined scenario were €0.8960 and €18.0062. Results were sensitive to model input values. Conclusions: According to the EQUIPTMOD modelling tool, it would be cost‐effective for the Hungarian authorities introduce a social marketing campaign and double the reach of existing group‐based behavioural support therapies and proactive telephone support. Such policies would more than pay for themselves in the long term. [ABSTRACT FROM AUTHOR]

Abstract: Background and aims: Estimating ‘return on investment’ (ROI) from smoking cessation interventions requires reach and effectiveness parameters for interventions for use in economic models such as the EQUIPT ROI tool ( http://roi.equipt.eu). This paper describes the derivation of these parameter estimates for England that can be adapted to create ROI models for use by other countries. Methods: Estimates were derived for interventions in terms of their reach and effectiveness in: (1) promoting quit attempts and (2) improving the success of quit attempts (abstinence for at least 12 months). The sources were systematic reviews of efficacy supplemented by individual effectiveness evaluations and national surveys. Findings: Quit attempt rates were estimated to be increased by the following percentages (with reach in parentheses): 20% by tax increases raising the cost of smoking 5% above the cost of living index (100%); 10% by enforced comprehensive indoor public smoking bans (100%); 3% by mass media campaigns achieving 400 gross rating points (100%); 40% by brief opportunistic physician advice (21%); and 110% by use of a licensed nicotine product to reduce cigarette consumption (12%). Quit success rates were estimated to be increased by the following ratios: 60% by single‐form nicotine replacement therapy (NRT) (5%); 114% by NRT patch plus a faster‐acting NRT (2%);124% by prescribed varenicline (5%); 60% by bupropion (1%); 100% by nortriptyline (0%), 10) 298% by cytisine (0%); 40% by individual face‐to‐face behavioural support (2%); 37% by telephone support (0.5%); 88% by group behavioural support (1%); 63% by text messaging (0.5%); and 19% by printed self‐help materials (1%). There was insufficient evidence to obtain reliable, country‐specific estimates for interventions such as websites, smartphone applications and e‐cigarettes. Conclusions: Tax increases, indoor smoking bans, brief opportunistic physician advice and use of nicotine replacement therapy (NRT) for smoking reduction can all increase population quit attempt rates. Quit success rates can be increased by provision of NRT, varenicline, bupropion, nortriptyline, cytisine and behavioural support delivered through a variety of modalities. Parameter estimates for the effectiveness and reach of these interventions can contribute to return on investment estimates in support of national or regional policy decisions. [ABSTRACT FROM AUTHOR]