Cost-Effectiveness of Strategies Addressing Environmental Noise: A Systematic Literature Review

Environmental noise, a significant public health concern, is associated with adverse health effects, including cardiovascular diseases, cognitive impairments, and psychological distress. Noise reduction strategies are essential for mitigating these effects. Despite evidence of their health benefits, limited information exists on the cost-effectiveness of such strategies to guide resource allocation. This study systematically reviewed economic evaluation studies of interventions aimed at reducing environmental noise to assess their cost-effectiveness and inform policymaking. A systematic review following PRISMA 2020 guidelines was conducted across MEDLINE, EMBASE, and Web of Science. Eligible studies were full economic evaluations addressing environmental noise reduction strategies, assessing both costs and health effects. Screening and data extraction were performed independently by two reviewers. Quality appraisal employed the CHEERS 2022 checklist. Narrative synthesis was used to analyze findings due to heterogeneity in study designs, methodologies, and outcomes. Costs were standardized to 2024 euros. From 2906 identified records, five studies met the inclusion criteria, primarily focused on traffic-related noise. Three studies conducted cost-utility analyses, and two employed cost–benefit analyses. Reported interventions included sound insulation, take-off trajectory adjustments, and noise barriers. Economic evaluations varied significantly in methodologies, cost categories, and health outcomes. The health economic studies yielded mixed results, ranging from findings that demonstrated cost-effectiveness to those where the costs exceeded the benefits. There are currently too few health economic evaluations to draw robust conclusions about the cost-effectiveness of environmental noise mitigation strategies. Future research should adopt standardized approaches and robust sensitivity analyses to enhance evidence quality, enabling informed policy and resource allocation decisions.