High-resolution modeling and projection of heat-related mortality in Germany under climate change.

ABSTRACT:

Background

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 often fragmented data archives over different agglomeration levels.

Method

Using Germany as a case study, we develop a multi-scale machine learning model to estimate heat-related mortality with variable temporal and spatial resolution. This approach allows us to estimate heat-related mortality at different scales, such as regional heat risk during a specific heatwave, annual and nationwide heat risk, or future heat risk under climate change scenarios.

Results

We estimate a total of 48,000 heat-related deaths in G

SUBMITTER: Wang J 

PROVIDER: S-EPMC11494177 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature