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Abstract：
We propose a compartmental model for investigating smoking dynamics in an Italian region (Tuscany). Calibrating the model on local data from 1993 to 2019, we estimate the probabilities of starting and quitting smoking and the probability of smoking relapse. Then, we forecast the evolution of smoking prevalence until 2043 and assess the impact on mortality in terms of attributable deaths. We introduce elements of novelty with respect to previous studies in this field, including a formal definition of the equations governing the model dynamics and a flexible modelling of smoking probabilities based on cubic regression splines. We estimate model parameters by defining a two-step procedure and quantify the sampling variability via a parametric bootstrap. We propose the implementation of cross-validation on a rolling basis and variance-based Global Sensitivity Analysis to check the robustness of the results and support our findings. Our results suggest a decrease in smoking prevalence among males and stability among females, over the next two decades. We estimate that, in 2023, 18% of deaths among males and 8% among females are due to smoking. We test the use of the model in assessing the impact on smoking prevalence and mortality of different tobacco control policies, including the tobacco-free generation ban recently introduced in New Zealand.
摘要：
我们提出了一种用于调查意大利地区（托斯卡纳）吸烟动态的隔室模型。根据1993年至2019年的当地数据对模型进行校准，我们估计了开始和戒烟的概率以及吸烟复发的概率。然后，我们预测了2043年前吸烟率的演变,并评估了归因死亡对死亡率的影响.我们介绍了关于该领域先前研究的新颖性元素，包括控制模型动力学的方程的正式定义和基于三次回归样条的吸烟概率的灵活建模。我们通过定义两步程序来估计模型参数，并通过参数引导来量化采样变异性。我们建议在滚动基础上实施交叉验证和基于方差的全局敏感性分析，以检查结果的稳健性并支持我们的发现。我们的结果表明男性吸烟率下降，女性吸烟率稳定，在接下来的二十年里。我们估计,在2023年，18%的男性和8%的女性死亡是由于吸烟。我们测试了该模型在评估不同烟草控制政策对吸烟率和死亡率的影响时的使用，包括最近在新西兰推出的无烟草发电禁令。
