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Smart Analysis and Decision-Making for Emerging Infectious Diseases
Sponsor: Peking University
Summary
Emerging infectious diseases, such as COVID-19, mpox, and dengue fever, are characterized by rapid transmission, wide impact, and high uncertainty, posing ongoing threats to global public health. While China achieved significant success in COVID-19 control, the response also revealed key challenges, including fragmented information, delayed risk perception, experience-dependent assessment, and inefficiencies in complex decision-making. This study aims to establish a smart technology system covering the full chain of "risk perception-situational assessment-intelligent decision-making-comprehensive evaluation." Specific objectives include: Constructing a global disease burden database and knowledge graph for emerging infectious diseases; Developing early risk assessment models covering the full transmission spectrum (cross-species, imported, and local outbreak); Building an AI-driven collective intelligence decision-support tool for epidemic control; Developing precise intervention frameworks and comprehensive evaluation indicators for key populations (e.g., elderly, students); Integrating the above technologies into a multi-agent toolkit and evaluating its effectiveness through a cluster randomized controlled trial across 52 CDC sites in five provinces (Guangdong, Zhejiang, Hubei, Sichuan, and Shanghai). The study population includes public health professionals and managers responsible for epidemic surveillance, risk assessment, decision-making, and emergency response at the city/district/county CDC levels across the five provinces. Approximately 780 participants will be enrolled. The intervention group will use the smart toolkit alongside routine practices, while the control group will follow routine practices only. The primary outcome is response time for epidemic assessment and decision-making (hours from risk perception to decision completion). Secondary outcomes include epidemic control effectiveness, user satisfaction, and socioeconomic benefits. The intervention period is 3 months, starting around July 2026 and ending in December 2027. This study has been approved by the Peking University Biomedical Ethics Committee. The study does not involve individual patient data; all data are aggregated at the district/county level from CDC sources or publicly available data. Anonymous questionnaires do not collect any personal identifiable information.
Official title: AI-enabled Emergency Clinical Research for Emerging and Re-emerging Infectious Diseases: Protocol for an International Consensus
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
780
Start Date
2026-07-17
Completion Date
2027-07-31
Last Updated
2026-07-01
Healthy Volunteers
No
Conditions
Interventions
Multi-Agent Integrated Smart Toolkit for Emerging Infectious Diseases
The multi-agent integrated smart toolkit consists of four integrated agents: (1) Data-Knowledge Agent - for early risk perception based on historical event experience; (2) Assessment Agent - for risk assessment and situational analysis; (3) Decision Agent - for emergency decision support; and (4) Evaluation Agent - for effect simulation and comprehensive evaluation. The toolkit is designed to assist CDC staff with epidemic risk perception, situational assessment, and emergency decision-making. It is used alongside routine infectious disease prevention and control practices.
Routine Practices
Routine infectious disease prevention and control practices currently implemented at the CDC, including standard epidemic surveillance, information collection, risk assessment, and emergency response procedures.
Locations (1)
Jue Liu
Beijing, Beijing Municipality, China