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1- Department of Medical Emergencies, School of Nursing, Alborz University of Medical Sciences, Alborz, Iran.
2- Health in Disasters and Emergencies Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran. & Emergency Medicine Management Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran. ,dehghani.am64@gmail.om
2- Health in Disasters and Emergencies Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran. & Emergency Medicine Management Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran. ,
Abstract: (11 Views)
Background: The application of artificial intelligence (AI) in disaster management is increasingly recognized for its potential to enhance decision-making and service delivery. Given the technological advancements and Iran's vulnerability to natural disasters, this study explores AI applications across the disaster management cycle from the perspective of Iranian experts.
Materials and Methods: A qualitative study was conducted using semi-structured interviews with 14 participants. Participants included experts, policymakers, senior and middle managers, and specialists in disaster management, artificial intelligence, and information technology. All participants were willing to take part in the study and possessed relevant scientific expertise and practical experience.
Conclusion:Analysis yielded 298 codes organized into four main categories corresponding to the disaster management cycle. In the mitigation phase, AI applications included disaster monitoring and prediction, modeling, and early warning system design. The preparedness phase comprised planning, coordination and communication, and training and empowerment. The response phase revealed six subcategories: information and communication management, rapid decision-making, situation assessment, rescue operations, monitoring and evaluation, and resource management. The recovery phase included monitoring, knowledge management, post-disaster support services, and psychosocial support. This framework can inform policymakers and practitioners in developing integrated, human-centered AI strategies for disaster management.
Ethics code:This study was approved by the Ethics Committee of Alborz University of Medical Sciences, under the code IR.ABZUMS.REC.1401.231
Materials and Methods: A qualitative study was conducted using semi-structured interviews with 14 participants. Participants included experts, policymakers, senior and middle managers, and specialists in disaster management, artificial intelligence, and information technology. All participants were willing to take part in the study and possessed relevant scientific expertise and practical experience.
Conclusion:Analysis yielded 298 codes organized into four main categories corresponding to the disaster management cycle. In the mitigation phase, AI applications included disaster monitoring and prediction, modeling, and early warning system design. The preparedness phase comprised planning, coordination and communication, and training and empowerment. The response phase revealed six subcategories: information and communication management, rapid decision-making, situation assessment, rescue operations, monitoring and evaluation, and resource management. The recovery phase included monitoring, knowledge management, post-disaster support services, and psychosocial support. This framework can inform policymakers and practitioners in developing integrated, human-centered AI strategies for disaster management.
Ethics code:This study was approved by the Ethics Committee of Alborz University of Medical Sciences, under the code IR.ABZUMS.REC.1401.231
Keywords: Artificial Intelligence, Disaster Management, Qualitative Research, Iran, Emergency Preparedness
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This is an open access article distributed under the terms of the Creative Commons Attribution License (CC-By-NC), which permits use, distribution, and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
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