Posters

      Population Health Impact Model Web Application

      Djurdjevic, S.; Martin, F.; Baker, G.; Weitkunat, R.
      Conference date
      Jun 14, 2019
      Conference name
      Global Forum on Nicotine (GFN) 2019
      Topic
      Summary

      Smoking-related mortality is a major public health issue. Tobacco harm reduction strategies consist of encouraging smokers to quit smoking but also introducing new reduced-risk tobacco and/or nicotine-containing products (RRP)* aimed at reducing harm in smokers who would otherwise continue smoking. Estimating the long-term population health impact of introducing an RRP into a population brings considerable challenges; we need to rely on computational models, such as the Population Health Impact Model (PHIM) developed for this purpose. The PHIM is used to assess the population health impact of the introduction of an RRP in different markets. This modeling is necessary, given the lack of epidemiological data on any long-term risks from RRPs in markets where such products are already, or may be, marketed. The PHIM is based on publicly available data on smoking prevalence and the relationship between smoking-related disease-specific mortality and various aspects of cigarette smoking, together with an estimate of exposure to the RRP compared to exposure to cigarettes. The model is global and allows for the exploration of possible scenarios regarding the effect of RRP introduction on the prevalence of cigarette and RRP use, individually and in combination. By comparing attributable mortality in a scenario where the RRP is introduced with one where it is not, the model can estimate the mortality attributable to cigarette smoking and RRP use as well as the reduction in the deaths attributable to the introduction of the RRP. In addition to smoking-attributable mortality, the model predicts years of life lost due to lung cancer, ischemic heart disease, stroke, and chronic obstructive pulmonary disease by considering two scenarios: a null scenario without RRP and an RRP scenario with RRP. Modeling predictions are based on hypothetical populations targeting the historical period of 1990–2010. Simulations were run from data available in various countries.The evaluation of the population health impact of introducing an RRP will be facilitated by the PHIM web application. This application is intended to support exploratory research beyond PMI and allows full disclosure of health impact modelinggenerated outcomes. The application is intended to be fully flexible and can accommodate modeling for any country of interest by adding required data to the PHIM platform. We intend to launch the web application this year.