What is the best tobacco control policy in Tuscany? An assessment using uncertainty analysis

Introduction: Cigarette smoking continues to exert a major impact on morbidity and mortality. We aim to provide robust estimates of smoking dynamics and their effects on mortality in Tuscany, Italy, from 1993 to 2019, along with forecasts under alternative tobacco control policies (TCPs). Methods: Smoking dynamics are modelled using a compartmental model combined with Monte Carlo (MC) simulations to propagate uncertainties. A variance-based global sensitivity analysis (GSA) quantifies the contribution of each input to output variance. TCPs are ranked according to the Surface Under the Cumulative Ranking Curve (SUCRA). Results: The MC approach produces results consistent with those obtained when only sampling variability is considered, although with wider uncertainty intervals (UIs). We estimate that in 2023 smoking caused 3348 deaths (90% UI 2761 to 3942) among men and 1749 deaths (1397 to 2888) among women aged over 65. By 2063, these numbers are projected to decline to 1477 (1081 to 2144) and 1436 (742 to 2138), respectively. According to the GSA, the time period used for calibrating the model is the main source of uncertainty in the model outputs, suggesting that the phenomenon has changed over time. The tobacco-free generation policy (TCP1) shows the highest SUCRA for smoking prevalence, while cessation treatments rank highest for mortality impact. Discussion: The approach shows promise for identifying key sources of uncertainty and guiding public health strategies. Although uncertainty limits the precise quantification of future dynamics and impacts, the TCP1 is likely to exert the strongest long-term effect on reducing smoking prevalence, while cessation interventions remain essential for achieving short-term reductions in smoking-attributable mortality.