Evidence map›Paper›PMID 39433977›Full record

ArticleCommunications medicine2024

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

Junyu Wang, Nikolaos Nikolaou, Matthias An der Heiden, Christopher Irrgang

Abstract read
In one paragraph

Article in Communications medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Urban heat above and below ground: towards improved understanding, modelling, mitigation and adaptation.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025
    Article
  5. [Applications, challenges and a trustworthy use of artificial intelligence in public health].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2025
    Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Junyu WangCentre for Artificial Intelligence in Public Health Research, Robert Koch Institute, Berlin, Germany. WangJ@rki.de.ORCID http://orcid.org/0000-0001-9525-5281
Nikolaos NikolaouInstitute of Epidemiology, Helmholtz Munich, German Research Center for Environmental Health, Neuherberg, Germany.ORCID http://orcid.org/0000-0003-0346-3142
Matthias An der HeidenDepartment of Infectious Disease Epidemiology, Robert Koch Institute, Berlin, Germany.ORCID http://orcid.org/0000-0001-5863-4549
Christopher IrrgangCentre for Artificial Intelligence in Public Health Research, Robert Koch Institute, Berlin, Germany.ORCID http://orcid.org/0000-0001-8274-1678

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHeat 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.

methodUsing 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.

resultsWe estimate a total of 48,000 heat-related deaths in Germany during the last decade (2014-2023), and the majority of heat-related deaths occur during specific heatwave events. Aggregating our results over larger regions, we reach good agreement with previously published reports from Robert Koch Institute (RKI). In 2023, the heatwave of July 7-14 contributes approximately 1100 cases (28%) to a total of approximately 3900 heat-related deaths for 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 extreme heat under static sociodemographic developments assumptions.

conclusionsOur 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.

Identifiers

PMID39433977
PMCPMC11494177

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.