Leveraging AI to Predict and Manage Infectious Disease Outbreaks: Insights Gained from COVID-19

Abstract

The COVID-19 pandemic has underlined the transformation potential of artificial intelligence in predicting and managing infectious diseases. This article attempts to discuss in detail the role of AI in the burden reduction of an epidemic or pandemic by early detection, real-time contact tracing, and resource allocation with a best-optimization approach. The huge data of genomic sequences, mobility, and clinical records were used by the ML models during COVID-19 times for the prediction of disease spread, defining hotspots, and smoothing health responses. AI-driven systems enabled diagnostics at a quicker pace, efficient vaccine distribution, and effective public health interventions. It draws from experiences in COVID-19 to assess various successes and challenges encountered in the integration of AI into pandemic management and goes deep into the fight against the outbreaks of the future. Key lessons learned include robust data infrastructure, cross-sector collaboration, and ethics in deploying AI technologies. In all, these findings underline the potential
of AI to revolutionize the management of infectious diseases by providing scalable, proactive, and exact solutions that fit global health crises.