Hydroclimate extremes, such as floods and heatwaves, significantly threaten public health. This research addresses existing gaps by developing a novel deep learning modeling framework to quantify the health impacts of these events, considering socio-environmental dynamics and adaptation actions. By focusing on two high-impact extremes—floods and heatwaves—the study provides critical insights to support future scenarios within the FORMAS DATE project. My sub-studies involved quantifying the health impacts of the 2018 Stockholm heatwave, by developing deep learning models to simulate the dynamics of heatwave events and analysing impact of climatic extremes on public health and other socio-economic factors, and integrating these models into a Dynamic Adaptive Policy Pathways framework. The outcomes will inform effective public health strategies and policies, contributing to sustainable and resilient communities.