SynthesisArchives of public health = Archives belges de sante publique2025
AI applications in disaster governance with health approach: A scoping review.
Synthesis in Archives of public health = Archives belges de sante publique, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Towards precision medicine in Tourette syndrome: a perspective on AI-driven predictive modelling and personalised care.Frontiers in computational neuroscience · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe increasing frequency and severity of disasters worldwide underscore the urgent need for robust systems that facilitate effective information sharing and decision-making. This study explores the current and potential applications of artificial intelligence (AI) in disaster governance, with a particular focus on health. By examining the transformative capabilities of AI, the study aims to provide practical insights to inform both national and international disaster management policies.
methodsA scoping review methodology was adopted to investigate the role of AI in disaster management. Systematic searches were conducted in PubMed, Scopus, and Web of Science databases, covering the period from 2000 to 2024. The search strategy employed keywords related to artificial intelligence, disaster management, governance, and health.
findingsThe review identified three core themes where AI enhances disaster governance: governance functions, by improving policy mechanisms, legitimacy, and health system resilience; information-based strategies, through real-time data, predictive analytics, and modeling; and operational processes, by strengthening logistics, communication, and social media management. Together, these applications improve preparedness and response capacity.
conclusionsThis study provides a structured framework for integrating artificial intelligence into disaster governance with a health-oriented approach. By synthesizing evidence across three thematic domains-governance functions, information-based strategies, and operational processes-it highlights how AI can enhance decision-making, strengthen system resilience, and enable more coordinated and equitable disaster responses. These findings offer practical guidance for policymakers and health professionals to develop adaptive, data-driven strategies in the face of increasing global disaster risks.
Indexed as
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.