ARTIFICIAL INTELLIGENCE FOR THE PREDICTION OF HEALTH EMERGENCIES AND DISASTERS

Abstract

Amidst unprecedented global health challenges, exemplified by the recent SARS-CoV-2 pandemic and other natural disasters, the imperative for initiative-taking measures is evident. Resilient health systems, initiated by Pan American Health Organization/World Health Organization (PAHO/WHO), seeks to fortify preparedness. This study explores the pivotal role of artificial intelligence (AI) advancements in addressing health crises. A scoping review was conducted on PubMed, Scopus, and LILACS databases. Limited to 2013––2024. Inclusion criteria: freely accessible articles in Spanish, English, or Portuguese on AI in disaster prediction and management. Removed duplicates and irrelevant languages. Subjective selection based on abstract and title. Grouped articles into two categories. Key information was extracted for analysis. Findings underscore the need for targeted exploration in AI applications for epidemic prediction. Ongoing exploration is evident, with a particular emphasis on specific symptom-based predictions. Beyond epidemics, AI excels in predicting a spectrum of natural disasters globally, from sea-level changes to earthquakes. Noteworthy successes include cyclone and flood predictions. Challenges, such as real-time updates, regional complexities, and global communication, must be addressed for widespread adoption. AI is a pivotal force in transforming healthcare and disaster management. The path forward involves a cohesive integration of technological innovation, ethical considerations, and global cooperation to fully unleash the benefits of AI for public health.