Calculating potential impact fractions to assess the impact of tobacco control policies

Abstract This presentation will provide a straightforward and accessible method for evaluating the effectiveness of various tobacco control policies in reducing the smoking-associated disease burden. To estimate numbers and proportions of potentially avoidable disease cases under different policy intervention scenarios (such as cigarette tax/price increases, comprehensive marketing ban, and plain packaging), this approach entails the calculation of age- and sex-specific potential impact fractions, representing the percentage change in disease risk following changes in exposure to smoking. The approach can account for lag and latency periods between reductions in smoking prevalence and declines in disease excess risks. The future disease burden is estimated by combining data on the incidence or mortality of the disease of interest, published effect sizes of tobacco control policies, and national smoking prevalence data. Intervention scenarios are compared against a status quo scenario that assumes the continuation of recent smoking trends. The presentation will outline the approach, using the example of smoking-associated cancer, and discuss model assumptions, required data, and sensitivity analyses. This straightforward modelling framework enables the comparison of different health policy measures’ impacts, providing valuable insights for policymakers and public health officials regarding the potential public health impact of tobacco control policy measures.