Heatwave-Related Mortality Prediction Using Machine Learning: Integrating Historical and Future Climate Data
Year: 2025
Type: conference-paper
Abstract: Heatwaves are among the deadliest climate-related hazards, with their intensity and frequency projected to rise. This study develops a machine learning model to predict heatwave-related mortality in Greece under RCP4.5 and RCP8.5 scenarios. Historical mortality and climate data (2015–2024) were combined with future projections (2025–2050) from CORDEX models. Feature engineering included lagged heatwave indicators, seasonal effects, and age group interactions. An optimized XGBoost model revealed increasing mortality trends, especially under RCP8.5 after 2039. These findings highlight the growing public health threat posed by extreme heat and offer a predictive framework for climate adaptation and policy planning.
Authors: Ilias Petrou, Pavlos Kassomenos
Institution: University of Ioannina
Language: English
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4414214346