ArticleBMC public health2023
The smoking and vaping model, A user-friendly model for examining the country-specific impact of nicotine VAPING product use: application to Germany.
Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Association between electronic cigarette use and respiratory outcomes among people with no established smoking history: a comprehensive review and critical appraisal.Internal and emergency medicine · 2025Review
- Prevention Lab: a predictive model for estimating the impact of prevention interventions in a simulated Italian cohort.BMC public health · 2024Article
- Increased e-cigarette use prevalence is associated with decreased smoking prevalence among US adults.Harm reduction journal · 2024Article
- The potential impact of removing a ban on electronic nicotine delivery systems using the Mexico smoking and vaping model (SAVM).medRxiv : the preprint server for health sciences · 2024Article
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Authors and funding
10 authors.
Funding
Abstract
backgroundSimulation models play an increasingly important role in tobacco control. Models examining the impact of nicotine vaping products (NVPs) and smoking tend to be highly specialized and inaccessible. We present the Smoking and Vaping Model (SAVM),a user-friendly cohort-based simulation model, adaptable to any country, that projects the public health impact of smokers switching to NVPs.
methodsSAVM compares two scenarios. The No-NVP scenario projects smoking rates in the absence of NVPs using population projections, deaths rates, life expectancy, and smoking prevalence. The NVP scenario models vaping prevalence and its impact on smoking once NVPs became popular. NVP use impact is estimated as the difference in smoking- and vaping-attributable deaths (SVADs) and life-years lost (LYLs) between the No-NVP and NVP scenarios. We illustrate SAVM's adaptation to the German adult ages 18+ population, the Germany-SAVM by adjusting the model using population, mortality, smoking and NVP use data.
resultsAssuming that the excess NVP mortality risk is 5% that of smoking, Germany-SAVM projected 4.7 million LYLs and almost 300,000 SVADs averted associated with NVP use from 2012 to 2060. Increasing the excess NVP mortality risk to 40% with other rates constant resulted in averted 2.8 million LYLs and 200,000 SVADs during the same period.
conclusionsSAVM enables non-modelers, policymakers, and other stakeholders to analyze the potential population health effects of NVP use and public health interventions.
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