Evidence map›Paper›PMID 40756219›Full record

ArticleNatural hazards (Dordrecht, Netherlands)2025

Tropical cyclone impact data in the Philippines: implications for disaster risk research.

Elizabeth G Galloway, Jennifer L Catto, Chunbo Luo, Stefan Siegert

Abstract read
In one paragraph

Article in Natural hazards (Dordrecht, Netherlands), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Elizabeth G GallowayUKRI Centre for Doctoral Training in Environmental Intelligence: Data Science and AI for Sustainable Futures, University of Exeter, Exeter, UK.ORCID 0009-0002-8003-8000
Jennifer L CattoDepartment of Mathematics and Statistics, University of Exeter, Exeter, UK.
Chunbo LuoDepartment of Computer Science, University of Exeter, Exeter, UK.
Stefan SiegertDepartment of Mathematics and Statistics, University of Exeter, Exeter, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural hazards such as tropical cyclones (TCs) cause widespread destruction. Historical impact data provides a resource for understanding TC impacts and associated societal vulnerabilities which is essential for building resilience. However, characteristics of impact data such as resolution and coverage can influence its utility for disaster risk reduction (DRR) applications. With this in mind, we present a province-level impact dataset for TCs in the Philippines between 2010 and 2020 for deaths, affected population, housing damage and economic loss curated for DRR applications. Specifically, we evaluate the effect of the dataset's spatial resolution and its coverage of hazard intensities, impact magnitudes and impact types and discuss the implications for DRR applications. Considering the utility of impact data within the context of DRR is crucial, and a dataset with comprehensive coverage of impact and hazard magnitudes and appropriate spatial resolution is pivotal for DRR applications. The research presents a guide for others using this dataset and data more generally in DRR applications. Supplementary Information: The online version contains supplementary material available at 10.1007/s11069-025-07394-x.

Indexed as

ApplicationsImpact dataRiskTropical cyclonesUtility

Identifiers

PMID40756219
PMCPMC12310784

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.