I casi studio per testare utilità e validità dell'Atlante Aria Salute: definizione del quadro concettuale.

OBJECTIVES: to describe the process of selecting and applying a shared conceptual model for the analysis of case studies designed to test the usefulness and validity of the Air and Health Atlas in supporting decision-making, in its current version and in its potential future developments. DESIGN: methodological and descriptive study of the application of a conceptual framework to a series of case studies. SETTING AND PARTICIPANTS: the setting is represented by the national ATLAS project promoted by the Ministry of Health, involving 22 partners from 10 Italian Regions. Nine case studies conducted in six regions were analyzed, including urban, regional, and sub-regional contexts, with the involvement of epidemiologists and environmental experts. MAIN OUTCOME MEASURES: assessment of the feasibility and usefulness of the Driving forces-Pressures-State-Exposure-Effects-Actions (DPSEEA) model in organizing the case studies; ability of the framework to support: the identification and evaluation of environmental and health indicators, and the assessment of counterfactual scenarios. RESULTS: based on a review of the existing literature, the DPSEEA model was selected as the most flexible and comprehensive among several models examined. It was successfully applied to all nine case studies, enabling a consistent structuring of information and the identification of indicators along the environment-health causal chain. The case studies were classified into validation studies (supporting air quality planning) and exploratory studies (development of new metrics and outcomes). The approach enhanced comparability across different contexts, supported the definition of intervention scenarios, and informed study design for evaluating new fine-scale exposure metrics and new health outcomes. CONCLUSIONS: the application of the DPSEEA model proved feasible and useful within the ATLAS project, supporting case study design, indicator selection, and intervention assessment. The framework represents an effective tool for integrating environmental and health data and for supporting decision-making processes.