Published Paper Details:

Artificial intelligence has become deeply embedded in modern health systems and is reshaping how pandemics are monitored, anticipated, and controlled. By combining machine learning, advanced analytics, and large-scale data integration, AI supports real-time epidemiological modeling, informs public health decision-making, and shortens the timelines for vaccine discovery and development. AI-based models, including extensions of SIR and SIS frameworks, help forecast transmission dynamics, allocate vaccines efficiently, and evaluate the likely impact of interventions on different populations, including low- and middle-income countries. This review outlines how AI contributes to epidemic modeling, vaccine target identification, vaccine design and formulation, clinical and preclinical evaluation, and surveillance, and it also considers applications in cancer immunotherapy and drug discovery. The article further highlights practical, ethical, and implementation issues and emphasizes the need for responsible and strategic integration of AI to strengthen preparedness for future global health threats.