Narrative Review on AI-Driven and Social Media-Enhanced Early Detection, Mitigation, and Public Health Preparedness in Natural Disaster-Prone Areas

Abstract The increasing frequency and severity of natural disasters, such as tsunamis and earthquakes, have underscored the urgent need for advanced strategies in early detection, risk mitigation, and public health response. This narrative review delves into the incorporation of artificial intelligence (AI) technologies alongside social media use in disaster management, specifically targeting areas vulnerable to tsunamis and earthquakes. By employing AI methodologies like machine learning (ML), deep learning (DL), and real-time social media analytics, substantial progress has been achieved in enhancing the precision, rapidity, and dissemination of early warning systems, as well as in risk evaluation and health preparedness. This review synthesizes the current state of AI and social media-enhanced disaster management, highlights key advancements, and identifies gaps in the literature that present opportunities for future research. The findings suggest that AI, when combined with social media, has the potential to revolutionize disaster resilience by enabling more proactive, informed, and efficient responses, ultimately reducing the human and economic toll of these catastrophic events. The review concludes with recommendations for integrating AI and social media analytics into disaster management frameworks to enhance public health safety and community resilience.