Research on Key Interventional Technologies for Controlling the Epidemic in High-prevalence Areas of Tuberculosis in Guangxi, China

Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age15+
SponsorUniversity of Toronto

About this trial

The goal of this study is to find out if using mobile vans with advanced technology can help reduce tuberculosis (TB) in rural Guangxi, China. The study will also examine how practical and cost-effective this approach is. The main questions it aims to answer are: 1) Does this new screening method lower the number of TB cases among high-risk groups? and 2) Is this method practical and acceptable for communities and healthcare workers? Participants in the study will: 1) undergo TB screening with mobile vans that use artificial intelligence (AI) to read chest X-rays, 2) answer a short questionnaire about their symptoms and health history, and 3) provide sputum samples for GeneXpert testing if needed.

Some communities will receive the new screening method, while others will continue with usual care. Researchers will compare TB rates in the two groups over three years to see if the new approach works better for TB control. If successful, this method could be used to improve TB control in other areas.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

all residents who are elderly (i.e., aged 65 and above)

all residents who are aged 15 to 64 with one of the following conditions: being patients previously treated for TB or close contacts of a patient with a TB patient diagnosed within the last three years; having been clinically diagnosed with diabetes, HIV positive, or worked as a miner

Have signed consent form

Disqualifiers

Residents who refuse participation.

Trial design

Design model

Parallel

Treatments tested in this trial

  • Active case finding

    Diagnostic test

    Villagers will be informed through public announcements and social workers. Before the campaign, social workers and village doctors will recruit participants and obtain consent through door-to-door visits. A mobile van equipped with an AI-assisted digital radiography (DR) machine and a refrigerator will visit villages on agreed dates. Participants will complete a TB symptom questionnaire and undergo DR screening. Those with TB symptoms or abnormal DR results will provide on-site sputum samples and collect additional morning and night samples. Trained staff will ensure proper collection and offer nebulizer support if needed. Samples will be transported daily to hospitals for testing using smear, culture, and GeneXpert. Participants with negative bacteriological results but abnormal findings will be referred for further clinical assessment.

Treatment groups

72,000 Participants
are divided into 2 treatment groups
Group A: InterventionExperimental treatment 1 intervention
Group B: ControlNo intervention 0 interventions

Trial outcomes

Primary outcomes

1

Prevalence rate of bacteriologically positive TB

Prevalence rate of bacteriologically positive TB in Year 3 among the high-risk populations , including those of 65 and older, those who are under 65 but have a history of tuberculosis treatment or have been in close contact with a person diagnosed of TB within the past three years, have been clinically diagnosed with diabetes, HIV, or have a background of working as a miner.

Time frame
In year 3 after recruitment

Secondary outcomes

1

Prevalence rate of active TB

Prevalence rate of active TB, including both bacteriologically positive and negative cases, among the high-risk populations in Year 3

Time frame
In Year 3 after recruitment
2

Notification rates of bacteriologically positive TB

Notification rates of bacteriologically positive TB cases among all populations in Year 3

Time frame
In Year 3 after recruitment
3

Notification rates of active TB cases

Notification rates of active TB cases, including both bacteriologically positive and negative cases among all populations in Year 3

Time frame
In Year 3 after recruitment

Other outcomes

Sponsors and contacts

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University of Toronto

Lead sponsor

Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control

Collaborator