Evidence map›Paper›PMID 39753701›Full record

ArticleScientific reports2025

Perennial disaster patterns in Central Europe since 2000 and implications for hospital preparedness planning - a cross-sectional analysis.

Maik von der Forst, Maximilian Dietrich, Felix C F Schmitt, Erik Popp, Markus Ries

Registry-linked trialAbstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07440329 (KAEPacity - Eine Vergleichende Analyse Der Krankenhausalarm- Und Einsatzpläne), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

NCT07440329 recruitingnot on this mapstarted 2026, after this paper: background citation

KAEPacity - Eine Vergleichende Analyse Der Krankenhausalarm- Und Einsatzpläne (KAEP) Deutscher Krankenhäuser

TypeobservationalSponsorLea KölschRan2026 to 2026Enrolled319ConditionsDisaster Planning, Emergency Medical Services, Germany
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Observational
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

5 authors.

Maik von der ForstHeidelberg University, Medical Faculty Heidelberg, Department of Anesthesiology, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany. maik.forst@med.uni-heidelberg.de.
Maximilian DietrichHeidelberg University, Medical Faculty Heidelberg, Department of Anesthesiology, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany.
Felix C F SchmittHeidelberg University, Medical Faculty Heidelberg, Department of Anesthesiology, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany.
Erik PoppHeidelberg University, Medical Faculty Heidelberg, Department of Anesthesiology, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany.
Markus RiesHeidelberg University, Medical Faculty Heidelberg, Center for Pediatrics and Adolescent Medicine, Pediatric Neurology and Metabolic Medicine, Im Neuenheimer Feld 430, 69120, Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The goal of this analysis is to describe seasonal disaster patterns in Central Europe in order to raise awareness and improve hospital disaster planning and resilience, particularly during peak events. Hospitals are essential pillars of a country's critical infrastructure, vital for sustaining healthcare services and supporting public well-being-a key issue of national security. Disaster planning for hospitals is crucial to ensure their functionality under special circumstances. But the impact of climate change and seasonal variations in the utilization of hospital services are raising challenges. Therefore, the knowledge of perennial disaster patterns could help strengthen the resilience of hospitals. We conducted a cross-sectional analysis of the Emergency Events Database EM-DAT for disasters in Central Europe (Germany, France, Denmark, The Netherlands, Belgium, Luxembourg, Switzerland, Austria, Czech Republic, and Poland) between January 2000 and December 2023. Time distribution of disasters, patterns and longitudinal trends, were analyzed to discuss impact on disaster preparedness in hospitals. Out of 474 events, 83% were associated with a natural hazard and only 80 events (17%) were of technological cause. While technological disasters were spread equally over the whole year, the vast majority of disasters related to natural hazards (n = 394), i.e. storms (n = 178, 45%), floods (n = 101, 26%), and extreme temperatures (n = 93, 24%) peaked during summer and winter months. Fewer disasters were registered during autumn and especially spring seasons. More than 50% of the technological disasters were categorized in the transport accident subgroup. Technological disasters were spread equally over the whole year. Looking at the three most common disaster types, extreme temperatures, floods, and storms are clearly dominating and cause over 90% of the disasters due to natural hazards in central Europe. Overall, the number of events per year fluctuates without a clear trend, only the technological events appear to become less frequent with 70% (n = 56) of the registered disasters occurring in the first half of the study period (2000-2011). An overlap of hospital admissions due to seasonal effects and catastrophic events, mainly triggered by disasters of natural cause in vulnerable periods may lead to a partial collapse of the health care system. To close knowledge gaps, future comprehensive data collection is vital for informed decision-making. Awareness and preparedness are key: an "all-hazards" approach to manage diverse, potentially simultaneous seasonal threats is often the most versatile strategy for hospital emergency planning.

Indexed as

Disaster PlanningClimate ChangeCross-Sectional StudiesDisastersEuropeFloodsGermanyHospitalsHumansSeasonsCritical infrastructureDisasterHospital disaster planningMass casualty incidentNatural hazardTechnological hazard

Identifiers

PMID39753701
PMCPMC11698994

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Registered trials

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.