Abstract The economic analysis within Health Impact Assessments (HIA) is a critical component in informing public policy decisions by assessing the financial implications of health outcomes associated with the different intervention options. Health metrics play a role defining the cost-effectiveness and societal value associated with the interventions. These metrics, quantifying the health impacts, include quality-adjusted life years (QALYs), years of life lost (YLLs) or disability-adjusted life years (DALYs). On another level, such metrics need to be translated into cost-effectiveness and societal value in which other methods play a role, such as the value of statistical life (VSL) or the value of a life year (VOLY). While VSL quantifies the value individuals place on reducing mortality risk, VOLY evaluates the value attributed to extending life expectancy. On another hand, uncertainties related to economic valuation pose challenges to the accuracy and reliability of cost estimates within HIA. These come from several factors, including data quality, methodological differences across studies, and subjective judgments involved in valuing health states. In fact, estimating the economic value of a prevented death involves multifaceted considerations and important assumptions. Additionally, assigning monetary values to non-fatal health outcomes, such as disability or reduced quality of life, involves subjective assessments and value judgments. By selecting appropriate metrics, considering diverse data sources, and addressing methodological steps and uncertainties, HIA practitioners can improve the utility of economic assessments, facilitating evidence-based decision-making in public health policy and resource allocation. This work was supported by National Funds through FCT - Fundação para a Ciência e a Tecnologia,I.P., within CINTESIS, R&D Unit (reference UIDP/4255/2020).
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