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AI applications in disaster governance with health approach: A scoping review
Pirhossein Kolivand1,2,3, Samad Azari2,4, Ahad Bakhtiari5,6,7
1Research Center for Emergency and Disaster Resilience, Red Crescent Society of the Islamic Republic of Iran, Tehran, Iran.
Introduction:
The 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.
Methods:
A 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.
Findings:
The 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.
Conclusions:
This 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.
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