Past, present, and future heat-related mortality in Germany

Abstract Heat has become a leading cause of preventable deaths during summer. Understanding the link between high temperatures and excess mortality is crucial for designing effective prevention and adaptation plans. Yet, data analyses are challenging due to non-linear heat-mortality dynamics and oftentimes fragmented data archives over different agglomeration levels. We introduced a multi-scale machine learning model to estimate heat-related mortality with variable temporal and spatial resolution. This approach allows to estimate heat-related mortality at different scales, such as regional heat risk during a specific heatwave, annual and nation-wide heat risk, or future heat risk under climate change. Using Germany as a case study, we calculated heat-related excess mortality rates at the district level and visualized local health risks during a selected heatwave. Overall, we estimated 48,000 heat-related deaths in Germany during the last decade (2014-2023), whereof most cases can be attributed to individual heatwaves. In 2023, the heatwave of July 7--14 contributed approximately 1,100 cases (28%) to a total of approximately 3,900 heat-related deaths of the whole year. Combining our model with shared socio-economic pathways (SSPs) of future climate change provides evidence that heat-related mortality in Germany could further increase by a factor of 2.5 (SSP245) to 9 (SSP370) without adaptation to the extreme heat. Our approach is a valuable tool for climate-driven public health strategies, aiding in the identification of local risks during heatwaves and long-term resilience planning.