ReviewScientific data2022
Human and economic impacts of natural disasters: can we trust the global data?
Review in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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.
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.
Who cites it
15 citing papers in PubMed.
- Beyond the battlefield: how conflict type drives acute child malnutrition in Africa.BMC public health · 2026Article
- Inequality in human development amplifies climate-related disaster risk.Nature communications · 2026Article
- The MERGE Dataset: A Harmonized Global Resource for Climate Disaster Impacts and Human Vulnerability.Scientific data · 2026Article
- A multi-temporal framework for assessing flood risk to cultural heritage: spatiotemporal evidence from Shandong Province (2000-2020).Scientific reports · 2026Article
- Pollution cost dynamics and regime transitions in emerging Asia: a dissipative-Logit approach.Scientific reports · 2026Article
- Synergistic impact of marine heat waves and rapid intensification exacerbates tropical cyclone destructive power worldwide.Science advances · 2026Article
- Review
- Political development predicts reduced human cost of flooding.Nature communications · 2025Article
- Article
- Article
- Trajectories of quality of life among disaster victims: A national longitudinal study.International nursing review · 2025Article
- Tropical cyclone impact data in the Philippines: implications for disaster risk research.Natural hazards (Dordrecht, Netherlands) · 2025Article
- [Effects of the volcano eruptions on human health].Revista medica del Instituto Mexicano del Seguro Social · 2024Review
- PROTOCOL: Effectiveness of economic development interventions in humanitarian settings in low- and middle-income countries: A mixed-method systematic review.Campbell systematic reviews · 2023Article
- Evaluating the representation of disaster hazards in SNOMED CT: gaps and opportunities.Journal of the American Medical Informatics Association : JAMIA · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Reliable and complete data held in disaster databases are imperative to inform effective disaster preparedness and mitigation policies. Nonetheless, disaster databases are highly prone to missingness. In this article, we conduct a missing data diagnosis of the widely-cited, global disaster database, the Emergency Events Database (EM-DAT) to identify the extent and potential determinants of missing data within EM-DAT. In addition, through a review of prominent empirical literature, we contextualise how missing data within EM-DAT has been handled previously. A large proportion of missing data was identified for disasters attributed to natural hazards occurring between 1990 and 2020, particularly on the economic losses. The year the disaster occurred, income-classification of the affected country and disaster type were all significant predictors of missingness for key human and economic loss variables. Accordingly, data are unlikely to be missing completely at random. Advanced statistical methods to handle missing data are thus warranted when analysing disaster data to minimise the risk of biasing statistical inferences and to ensure global disaster data can be trusted.
Identifiers
What OpenQuestion holds
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.