The role of artificial intelligence in enhancing disaster management: implications for medical and public health preparedness

Ayesha Jamshed; Mostafa A. Khalifa; Muhammad Essa; Sana Iftikhar; Khaled M. Abdelrazek; Nouraiz Abbas; Vaneesa Ali; Maria Qadri; Javed Iqbal; Muhammad Umar

doi:10.18203/issn.2454-2156.IntJSciRep20253767

Authors

Ayesha Jamshed Department of Public Health, National University of Medical Sciences, Rawalpindi, Punjab, Pakistan
Mostafa A. Khalifa Faculty of Medicine, Cairo University, Cairo, Egypt
Muhammad Essa Department of Medicine, Khairpur Medical College, Khairpur Mir's, Sindh, Pakistan
Sana Iftikhar Department of Medicine, Sheikh Khalifa Bin Zayed Al-Nahyan Medical and Dental College, Lahore, Punjab, Pakistan
Khaled M. Abdelrazek Misr University for Science and Technology, Cairo, Egypt
Nouraiz Abbas Department of Medicine, Abwa Medical College, Faisalabad, Pakistan
Vaneesa Ali Department of Medicine, Khairpur Medical College, Khairpur Mir's, Sindh, Pakistan
Maria Qadri Department of Medicine, Jinnah Sindh Medical University, Karachi, Sindh Pakistan
Javed Iqbal Nursing Department Hamad Medical Corporation Doha, Qatar
Muhammad Umar Khairpur Medical College, Khairpur Mir's, Sindh, Pakistan

DOI:

https://doi.org/10.18203/issn.2454-2156.IntJSciRep20253767

Keywords:

AI, Disaster, Public Health, Management

Abstract

Natural disasters, including earthquakes, wildfires, floods, and disease outbreaks, have catastrophic consequences for human lives, infrastructure, and economies worldwide. Their increasing frequency and intensity, exacerbated by climate change and urbanization, present significant challenges to disaster management. Traditional approaches often struggle to cope with the scale and complexity of modern disasters. This narrative review examines the potential of artificial intelligence (AI) to transform disaster management, exploring its applications across the disaster cycle. By assessing AI's role in damage assessment, early warning systems, resource allocation, and post-disaster rehabilitation, the review identifies opportunities to enhance disaster response and recovery efforts. Additionally, it addresses challenges related to AI implementation, such as algorithmic bias, data quality, and ethical considerations, to develop equitable and robust AI-driven disaster management strategies. A comprehensive literature review was conducted to identify key research on AI’s role in early warning systems, disaster management, damage control, resource allocation, and post-disaster recovery. AI holds significant potential to improve disaster response and recovery. It can enhance early warning systems, optimize resource allocation, and improve damage assessment. Furthermore, AI can support post-disaster repair and rehabilitation efforts. However, challenges such as data quality, ethical concerns, and algorithmic bias must be addressed to ensure the responsible and effective application of AI in disaster management. By harnessing the power of AI, we can build more resilient societies and reduce the impact of future disasters. To fully realize AI’s potential, it is essential to integrate it into research, development, and ethical frameworks, ensuring its responsible and efficient implementation.

Metrics

Metrics Loading ...

References

Hidalgo J, Baez AA. Natural Disasters. Crit Care Clin. 2019;35(4):591-607. DOI: https://doi.org/10.1016/j.ccc.2019.05.001

Saeed SA, Gargano SP. Natural disasters and mental health. Int Rev Psychiatry. 2022;34(1):16-25. DOI: https://doi.org/10.1080/09540261.2022.2037524

Thekdi S, Tatar U, Santos J, Chatterjee S. Disaster risk and artificial intelligence: A framework to characterize conceptual synergies and future opportunities. Risk Anal. 2023;43(8):1641-56. DOI: https://doi.org/10.1111/risa.14038

Bari LF, Ahmed I, Ahamed R, Zihan TA, Sharmin S, Pranto AH, et al. Potential Use of Artificial Intelligence (AI) in Disaster Risk and Emergency Health Management: A Critical Appraisal on Environmental Health. Environ Health Insights. 2023;17:11786302231217808. DOI: https://doi.org/10.1177/11786302231217808

Kao CL, Chien LC, Wang MC, Tang JS, Huang PC, Chuang CC, et al. The development of new remote technologies in disaster medicine education: A scoping review. Front Public Health. 2023;11:1029558. DOI: https://doi.org/10.3389/fpubh.2023.1029558

Tin D, Cheng L, Le D, Hata R, Ciottone G. Natural disasters: a comprehensive study using EMDAT database 1995-2022. Public Health. 2024;226:255-60. DOI: https://doi.org/10.1016/j.puhe.2023.11.017

Shamman AH, Hadi AA, Ramul AR, Abdul Zahra MM, Gheni HM. The artificial intelligence (AI) role for tackling against COVID-19 pandemic. Mater Today Proc. 2023;80:3663-7. DOI: https://doi.org/10.1016/j.matpr.2021.07.357

Swayamsiddha S, Prashant K, Shaw D, Mohanty C. The prospective of Artificial Intelligence in COVID-19 Pandemic. Health Technol (Berl). 2021;11(6):1311-20. DOI: https://doi.org/10.1007/s12553-021-00601-2

Khan SM, Shafi I, Butt WH, Diez ID, Flores MA, Galán JC, et al. A systematic review of disaster management systems: approaches, challenges, and future directions. Land. 2023;12(8):1514.

Akhyar A, Zulkifley MA, Lee J, Song T, Han J, Cho C, et al. Deep artificial intelligence applications for natural disaster management systems: A methodological review. Ecological Indicators. 2024;163:112067. DOI: https://doi.org/10.1016/j.ecolind.2024.112067

Schofield M. An Artificial Intelligence (AI) Approach to Controlling Disaster Scenarios. Future Role of Sustainable Innovative Technologies in Crisis Management. 2022;28-46. DOI: https://doi.org/10.4018/978-1-7998-9815-3.ch003

Khan SM, Shafi I, Butt WH, Diez ID, Flores MA, Galán JC, et al. A systematic review of disaster management systems: approaches, challenges, and future directions. Land. 2023;12(8):1514. DOI: https://doi.org/10.3390/land12081514

Abid SK, Sulaiman N, Chan SW, Nazir U, Abid M, Han H, et al. Toward an integrated disaster management approach: how artificial intelligence can boost disaster management. Sustainability. 2021;13(22):12560. DOI: https://doi.org/10.3390/su132212560

Kuglitsch MM, Pelivan I, Ceola S, Menon M, Xoplaki E. Facilitating adoption of AI in natural disaster management through collaboration. Natur Commun. 2022;13(1):1579. DOI: https://doi.org/10.1038/s41467-022-29285-6

Arfan M, Khan Z, Qadri N, Hameed MH, Amir AR. Role of Artificial Intelligence (AI) in Combined Disaster Management. Organization Theory Rev. 2019;3(2):97-121. DOI: https://doi.org/10.32350/OTR.0302.05

Varsha VR, Naganandini S, Hariharan C. Utilizing AI and machine learning for natural disaster management: predicting natural disasters with AI and machine learning. Internet of Things and AI for Natural Disaster Management and Prediction. 2024;279-304. DOI: https://doi.org/10.4018/979-8-3693-4284-8.ch013

Saravi S, Kalawsky R, Joannou D, Rivas Casado M, Fu G, et al. Use of artificial intelligence to improve resilience and preparedness against adverse flood events. Water. 2019;11(5):973. DOI: https://doi.org/10.3390/w11050973

Abdalzaher MS, Krichen M, Falcone F. Leveraging internet of things and emerging technologies for earthquake disaster management: Challenges and future directions. Prog Disaster Sci. 2024:100347. DOI: https://doi.org/10.1016/j.pdisas.2024.100347

Maraveas C, Loukatos D, Bartzanas T, Arvanitis KG. Applications of artificial intelligence in fire safety of agricultural structures. Applied Sci. 2021;11(16):7716. DOI: https://doi.org/10.3390/app11167716

Chang RH, Peng YT, Choi S, Cai C. Applying Artificial Intelligence (AI) to improve fire response activities. Emerg Manag Sci Technol. 2022;2(1):1-6. DOI: https://doi.org/10.48130/EMST-2022-0007

Kaur I, Behl T, Aleya L, Rahman H, Kumar A, Arora S, et al. Artificial intelligence as a fundamental tool in management of infectious diseases and its current implementation in COVID-19 pandemic. Environ Sci Pollution Res. 2021;28(30):40515-32. DOI: https://doi.org/10.1007/s11356-021-13823-8

Cao L. AI in combating the COVID-19 pandemic. IEEE Intelligent Systems. 2022;37(2):3-13. DOI: https://doi.org/10.1109/MIS.2022.3164313

Abdul S, Adeghe EP, Adegoke BO, Adegoke AA, Udedeh EH. AI-enhanced healthcare management during natural disasters: conceptual insights. Eng Sci Technol J. 2024;5(5):1794-816. DOI: https://doi.org/10.51594/estj.v5i5.1155

Aboualola M, Abualsaud K, Khattab T, Zorba N, Hassanein HS. Edge technologies for disaster management: a survey of social media and artificial intelligence integration. IEEE Access. 2023;11:73782-802. DOI: https://doi.org/10.1109/ACCESS.2023.3293035

Adefemi A, Ukpoju EA, Adekoya O, Abatan A, Adegbite AO. Artificial intelligence in environmental health and public safety: a comprehensive review of USA strategies. World J Adv Res Rev. 2023;20(3):1420-34. DOI: https://doi.org/10.30574/wjarr.2023.20.3.2591

Shafik W. Community and artificial intelligence-enabled disaster management and preparedness. In: Navigating Natural Hazards in Mountainous Topographies: Exploring the Challenges and Opportunities of Living. Springer. 2024;243-66. DOI: https://doi.org/10.1007/978-3-031-65862-4_13

Schmitt T, Eisenberg J, Rao RR. Improving disaster management: the role of IT in mitigation, preparedness, response, and recovery. Washington (DC): National Academies Press. 2007

Olawade DB, Wada OJ, David-Olawade AC, Kunonga E, Abaire O, Ling J. Using artificial intelligence to improve public health: a narrative review. Front Public Health. 2023;11:1196397. DOI: https://doi.org/10.3389/fpubh.2023.1196397

Prabhod KJ. The role of artificial intelligence in reducing healthcare costs and improving operational efficiency. Q J Emerg Technol Innov. 2024;9(2):47-59.

Adekugbe AP, Ibeh CV. Harnessing data insights for crisis management in US public health: lessons learned and future directions. Int Med Sci Res J. 2024;4(4):391-405. DOI: https://doi.org/10.51594/imsrj.v4i4.998