Towards evidence-based policies - exploring the potential impact fraction for policy planning

Abstract The Potential Impact Fraction (PIF) is a complementary approach within Burden of Disease (BoD) analyses that estimates how much disease burden could be avoided through realistic, achievable changes in exposure to risk factors. Unlike the Population Attributable Fraction (PAF) method, which assumes complete elimination of exposure to a risk factor, the PIF enables policy-relevant estimations under feasible scenarios such as a 10% reduction in smoking prevalence or targeted interventions among high-risk groups. Through concrete examples, the presentation will demonstrate how the PIF method can support the evaluation of health policies by comparing their potential impact. For instance, the analysis might reveal that an intervention like restricting tobacco advertising could yield greater health gains than broader measures such as increasing cigarette prices. This kind of assessment helps inform the design of more efficient policies that better reach intended populations. We will introduce a menu of intervention scenarios, from broad population-level changes to more targeted measures, highlighting the variable reach and effectiveness of each. As a part of this workshop, we aim to share this knowledge with colleagues from other countries, showing how PIF-based findings can support practical recommendations in different contexts. By providing a bridge between BoD estimates and real-world policy planning, the PIF method encourages more actionable conversations around disease prevention and resource allocation. Audience engagement will focus on discussing the interpretability and limitations of this approach in the public health context.