Author(s)

Chen Bian ¹

Affiliation(s)

¹ Guangzhou City Construction College, Guangzhou City, China

Corresponding Author

Chen Bian

ABSTRACT

This paper studies the use of artificial intelligence technology to build a scientific, comprehensive, and practical "technology-management-capability" trinity system for the prevention and control of major infectious diseases in colleges and universities, providing theoretical support and practical guidance for Chinese universities to effectively respond to future epidemics. The method applied in this paper is a literature review, analysing China's regulations and systems for supervising sudden infectious diseases or epidemic events in universities. Case analysis was conducted to analyze typical cases of AI technology used for epidemic prevention and control in six universities in China and other countries (Tongji University in China, Beijing University of Posts and Telecommunications in China, Shanghai University in China, University of California, Los Angeles in the United States, University of Cambridge in the United Kingdom, and University of Tokyo in Japan). The overall status, representative achievements, and key implementation processes of AI technology used in campus epidemic prevention and control in Chinese universities were summarised. Successful experiences and existing problems were summarised, and a "technology-management-capability" trinity prevention and control system framework was proposed. This study can provide a theoretical basis and practical reference for Chinese universities to respond to future epidemics, and will also help to maximize the health and safety of teachers and students, maintain normal teaching order and social stability in Chinese universities.

KEYWORDS

University; Epidemic; Infectious Disease; AI; Prevention and Control

CITE THIS PAPER

Chen Bian, AI Empowerment: A Brief Discussion on the Analysis and Construction of China's University Epidemic Prevention and Control System. Social Medicine and Health Management (2025) Vol. 6: 9-14. DOI: http://dx.doi.org/10.23977/socmhm.2025.060202.

REFERENCES

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