Public health is concerned with the prevention and control of disease through population surveillance and the promotion of healthy behaviors. Changing disease patterns and escalating costs of care make prevention, health promotion, and public health pressing concerns and vital parts of addressing the challenges facing health systems. The technical capacity now exists to pursue a new type of precision public health by applying the principles and technology of precision medicine to disease prevention and public health policy. With the Internet of Things, the digital world is generating data at a significant and still increasing rate. While this big data presents novel opportunities to understand public health, it holds still greater potential for research and practice. As the need for evidence-based policies grows, with the aid of artificial intelligence technology, big data holds the key to dramatic, rapid improvements in the promotion of health and prevention of disease.

At the same time, health systems have been slow to adopt new technologies and must consider how these new approaches will affect privacy. In the face of these developments, public health policy makers need to discern the most effective ways in which they can leverage big data, as well as how to best address the challenges associated with these novel technologies. Artificial intelligence, big data, and big data analytics in the Internet of Things can all be used at all three levels of health promotion and disease prevention. However, the public health sector has been a relatively slow adopter of big data analytics. While efforts to leverage big data in public health policy making are starting to gain momentum, a risk also exists in deploying scarce resources to accumulate more health knowledge that then remains unused. Leveraging big data to help distil knowledge into clear public health interventions remains a major challenge.

This Special Issue aims to solicit relevant research on the use of artificial intelligence and big data analytics to enhance public health at the research, surveillance, and intervention levels. We hope to provide scholars and industry practitioners with a timely opportunity to discuss, share, and disseminate current innovations in big data-enabled public health. Authors are invited to present original research and review articles that will stimulate continuing efforts in this field. We hope that this Special Issue proposes techniques, directions, strategies, and solutions that enhance the development and application of big data analysis technologies in public health policy, intelligent healthcare, telemedicine, and health privacy protection.

Potential topics include but are not limited to the following:

• Intelligent disease prevention based on big data analysis
• Big data mining for improving public health
• Big data-based risk assessment and prevention in public health
• Blockchain-based health data security and health privacy protection
• Federated learning for processing big data in telemedicine
• Information fusion and data integration for processing heterogeneous health data
• New public health policies in the big data era
• New models of disease prevention and control driven by healthcare big data analysis
• Big data-based public health protection in smart cities
• Empowering public health governance systems based on big data analysis
• Development and construction of public healthcare big data platforms