AI-Enhanced Public Health Strategies for Infectious Disease Prediction and Control

Artificial Intelligence (AI) has revolutionized many domains, and its integration into public health has provenparticularly crucial in the prediction and control of infectious diseases. With the increasing frequency of disease outbreaks andthe global interconnectedness of societies, traditional public health approaches often fall short in providing timely and effectiveresponses. AI offers robust solutions through predictive analytics, real-time data processing, and pattern recognition to forecastdisease trends, identify hotspots, and optimize intervention strategies. This paper explores the role of AI in enhancing publichealth systems to combat infectious diseases by leveraging machine learning algorithms, natural language processing, and datadriven models. It highlights successful case studies, discusses the integration of AI with epidemiological tools, and addresses the ethical and infrastructural challenges involved. The discussion aims to demonstrate how AI can transform public healthstrategies into proactive, scalable, and efficient systems capable of mitigating the spread of infectious diseases.