A Prognostic Algorithm for Heat-Related Mortality in Older Adults: Development in Milan

Climate change is increasing the frequency and intensity of heatwaves, with substantial health impacts and higher mortality among vulnerable groups including older adults and individuals with chronic diseases. Risk stratification tools may support public health systems in identifying high-risk individuals and implementing targeted preventive interventions. This population-based study included Milan residents aged ≥75 years during the summers of 2022–2023 and aimed to test an algorithm for stratifying heat-related health risk. By combining individuals’ classification as ill, treated, and deprived, four heat-related risk levels were defined. The algorithm was developed on the 2022 cohort and validated on the 2023 cohort. A logistic regression model with cross-validation was used, and performance was assessed using AUC, calibration, and Brier score. A total of 192,063 (2022) and 181,509 (2023) residents aged ≥75 years were included. Approximately 56% were classified as high or very high risk, with slightly higher proportions in 2023. Mortality increased with risk level and multimorbidity. The model showed good overall accuracy, fair discrimination, and good calibration in the development cohort. Higher mortality was associated with male, older age (≥85 years), and higher risk strata, while living alone showed inconsistent associations. This prognostic algorithm may contribute to the stratification of heat-related mortality risk among older adults and could support targeted prevention and timely responses to heatwave.