Smart Analysis and Decision-Making for Emerging Infectious Diseases (SMART-ID)

June 30, 2026 updated by: Liu Jue, Peking University

AI-enabled Emergency Clinical Research for Emerging and Re-emerging Infectious Diseases: Protocol for an International Consensus

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.

Study Overview

Status

Enrolling by invitation

Conditions

Intervention / Treatment

Detailed Description

This is a multicenter, cluster-randomized controlled trial (cRCT) with a single-blind design (blinding of statisticians). The study will be conducted across five provinces/municipalities: Guangdong, Zhejiang, Hubei, Sichuan, and Shanghai. A total of 52 district/county/city-level Centers for Disease Control and Prevention (CDCs) will be selected as study clusters and randomized 1:1 to either the intervention group (26 clusters) or the control group (26 clusters).

Randomization Procedure: For the four provinces (Zhejiang, Guangdong, Hubei, Sichuan), CDC clusters will be stratified by socioeconomic level (high, medium, low), with 2 prefecture-level CDCs randomly selected from each stratum and allocated to intervention or control. For Shanghai municipality, CDCs will be stratified by urban functional zone (central urban vs. new/suburban districts), with 2 district-level CDCs selected from each stratum and randomly allocated.

Intervention: The intervention group will use a multi-agent integrated toolkit (including data-knowledge agent, assessment agent, decision agent, and evaluation agent) to assist with epidemic risk perception, situational assessment, and emergency decision-making, in addition to routine practices. The control group will follow routine practices only.

Follow-up Plan: The intervention period is 3 months, timed to coincide with peak seasons for specific infectious diseases (winter/spring for respiratory infections; summer/autumn for vector-borne diseases like dengue). Follow-up assessments will occur every 3 months, with the endpoint defined as the conclusion of an emerging infectious disease event.

Sample Size: Using PASS software (α=0.05, Power=80%, ICC=0.05, CV=0.5, average cluster size m=15), assuming an 80% improvement in decision-making efficiency in the intervention group (response time reduced from 24 to approximately 19 hours), with a 10% attrition rate, a minimum of 28 clusters is required. This study will enroll 52 clusters (approximately 780 participants), exceeding the minimum requirement.

Data Management: Dual independent data entry will be performed. Data will be stored on Peking University's encrypted servers, with backups on the university cloud platform and offline encrypted hard drives (AES-256 encryption). All data will be physically destroyed after the retention period.

Missing Data: Analysis will follow the intention-to-treat (ITT) principle. Missing primary outcome data will be handled using the last observation carried forward (LOCF) method.

Safety Evaluation: Adverse events include headache and absenteeism, classified using a five-level attribution scale (definitely, probably, possibly, probably not, definitely not related), with the first three categories counted as adverse reaction rates. Any serious adverse event must be reported immediately to the sponsor and/or ethics committee.

Early Termination: The study may be terminated early under the following conditions: (1) identification of serious safety issues; (2) the toolkit proves ineffective or futile; (3) major protocol flaws or implementation deviations; (4) request by the applicant or administrative authority.

Study Type

Interventional

Enrollment (Estimated)

780

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • Beijing Municipality
      • Beijing, Beijing Municipality, China, 100191
        • Jue Liu

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Working at a district/county/city-level CDC in one of the five participating provinces/municipalities (Zhejiang, Guangdong, Hubei, Sichuan, or Shanghai) where at least one emerging infectious disease (COVID-19, mpox, influenza, dengue, chikungunya, or avian influenza) has occurred.
  • Currently responsible for or involved in infectious disease epidemic prevention and control work, including information collection, risk perception, risk assessment, decision-making, risk management, and emergency response at the CDC.
  • Willing to voluntarily participate in this study and provide written informed consent.

Exclusion Criteria:

  • Under 18 years of age.
  • Diagnosed with severe mental illness or other conditions that impede normal communication.
  • Employed in the current CDC position for less than 1 year.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Prevention
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Intervention Group
Participants in this arm will receive the multi-agent integrated smart toolkit, consisting of Data-Knowledge, Assessment, Decision, and Evaluation agents, in addition to routine infectious disease prevention and control practices. The toolkit is designed to assist CDC staff with epidemic risk perception, situational assessment, and emergency decision-making throughout the 3-month intervention period, alongside their routine CDC workflow.
Other: 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.
Other Names:
  • SMART-ID Toolkit
Active Comparator: Control Group
Participants in this arm will follow routine infectious disease prevention and control practices only, without access to the multi-agent integrated smart toolkit, including standard epidemic surveillance, information collection, risk assessment, and emergency response procedures currently implemented at their respective CDC, and will continue their regular workflow without any additional intervention during the 3-month study period.
Other: 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Response Time for Risk Assessment Report Generation and Submission
Time Frame: Measured at baseline (enrollment) and at the end of the 3-month intervention period
Response time consists of two components measured in hours: (1) Report generation time - time from the diagnosis of the index case in a cluster outbreak to the system's automatic generation of the first risk assessment report and decision-support recommendations; and (2) Report submission time - time from report generation to its official submission. Measured via electronic questionnaire and CDC reporting logs.
Measured at baseline (enrollment) and at the end of the 3-month intervention period

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Consistency of Risk Assessment Results between Multi-Agent Toolkit and Expert Panel
Time Frame: Assessed at the end of the 3-month intervention period
Measured by the level of agreement (including risk level classification) between the risk assessment outcomes generated by the multi-agent toolkit and those produced by an independent expert panel. Assessed via comparison of risk reports generated during outbreak events.
Assessed at the end of the 3-month intervention period
Epidemic Control Effectiveness
Time Frame: Assessed continuously throughout the 3-month intervention period and summarized at the end of the intervention
Measured by: (1) duration of each cluster outbreak (days from the first case to the last case); and (2) number of secondary cases generated during the outbreak period. Data are derived from routine surveillance systems and epidemiological investigation reports (de-identified, aggregated data only).
Assessed continuously throughout the 3-month intervention period and summarized at the end of the intervention
User Experience and Satisfaction with the Smart Toolkit
Time Frame: Measured at the end of the 3-month intervention period
Quantitative evaluation via electronic questionnaire measuring overall user acceptance and integration of the tool among participating CDC staff. Three subscales (user satisfaction, perceived usefulness, and workflow integration) will be assessed, each scored on a Likert scale. The total score will be calculated as the mean of the three subscale scores, ranging from 1 to 5, with higher scores indicating greater overall acceptance and integration.
Measured at the end of the 3-month intervention period
Healthcare Resource Consumption
Time Frame: Assessed at the end of the 3-month intervention period
Assessment of healthcare resource consumption associated with the intervention, measured in monetary value (local currency, CNY), evaluated through Difference-in-Differences (DID) models.
Assessed at the end of the 3-month intervention period
Prevention and Control Resource Inputs
Time Frame: Assessed at the end of the 3-month intervention period
Assessment of resource inputs for prevention and control activities, measured in monetary value (local currency, CNY), evaluated through Difference-in-Differences (DID) models.
Assessed at the end of the 3-month intervention period
Reduction in Hospitalization Burden
Time Frame: Assessed at the end of the 3-month intervention period
Assessment of the reduction in hospitalization burden attributable to the intervention, measured as the number of hospitalizations avoided, evaluated through Markov decision tree models.
Assessed at the end of the 3-month intervention period
Reduction in Severe Disease Burden
Time Frame: Assessed at the end of the 3-month intervention period
Assessment of the reduction in severe disease burden attributable to the intervention, measured as the number of severe cases avoided, evaluated through Markov decision tree models.
Assessed at the end of the 3-month intervention period
Cost-Effectiveness Ratio
Time Frame: Assessed at the end of the 3-month intervention period
Assessment of the cost-effectiveness of the intervention, measured as cost per quality-adjusted life year (QALY) gained or cost per disability-adjusted life year (DALY) averted, evaluated through Markov decision tree models.
Assessed at the end of the 3-month intervention period
Macroeconomic Impact
Time Frame: Assessed at the end of the 3-month intervention period
Assessment of the broader macroeconomic impact of the intervention, measured as percentage change in GDP or monetary value in local currency, evaluated through Computable General Equilibrium (CGE) models.
Assessed at the end of the 3-month intervention period

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Peking University

Collaborators

National Health Commission's Pharmaceutical and Health Technology Development Research Center

Investigators

  • Principal Investigator: Jue Liu, Doctor, Peking University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

July 17, 2026

Primary Completion (Estimated)

July 17, 2027

Study Completion (Estimated)

July 31, 2027

Study Registration Dates

First Submitted

June 24, 2026

First Submitted That Met QC Criteria

June 30, 2026

First Posted (Actual)

July 1, 2026

Study Record Updates

Last Update Posted (Actual)

July 1, 2026

Last Update Submitted That Met QC Criteria

June 30, 2026

Last Verified

June 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • PKUINF-2026

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on COVID-19

Search Similar Trials

Sponsors and Collaborators

Medical Conditions

Drug Interventions

CROs by country

CROs in United Kingdom

Conditions

Rare Diseases

Drug Interventions

Dietary Supplements

Sponsor/Collaborators

Locations

3
Subscribe