The Role of Artificial Intelligence in Predicting Epidemics

Despite tremendous advances in public health, epidemics remain a major concern due to variables such as fast population expansion, increasing travel, and migration. Given the rapidity with which modern epidemics spread, traditional strategies for epidemic prediction and management have frequently proven ineffective. Artificial intelligence (AI) provides a disruptive approach to forecasting and controlling outbreaks. This study investigates the evolution of epidemic prediction, from old statistical methods to modern AI-powered models. It looks at how various AI approaches, such as machine learning and natural language processing, can be used to anticipate epidemic outbreaks. The study uses case examples to demonstrate the effectiveness of AI in forecasting epidemics while also highlighting the limitations and ethical implications connected with these technologies. The findings highlight AI’s ability to improve epidemic preparedness and response, providing insights into how these technologies might be optimised for future public health concerns. Keywords: Artificial Intelligence, Epidemic Prediction, Machine Learning, Big Data, Public Health Surveillance