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AI x-rays and mobile testing aim to catch missed TB and COVID cases

NCT ID NCT05220163

Knowledge-focused Sponsor: University of Cape Town Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing This study
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study tests whether AI-powered X-ray analysis and portable molecular tests can help find tuberculosis (TB) and COVID-19 cases in African communities where many cases go undetected. Over 26,000 adults will be screened using these tools, and researchers will measure how quickly and accurately cases are identified. The goal is to see if these technologies can improve disease detection and reduce the number of missed cases.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
CAD (AI software for X-ray analysis) and Xpert (molecular test for TB)
What this could lead to
If successful, this could show that AI-assisted X-rays and community-based testing can find more TB and COVID-19 cases, helping to control these diseases in high-burden areas.
What could go wrong
This is an observational study, not a treatment trial. The tools may not work as well in real-world settings, and results may not apply to other regions.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Phase

Not a phased trial

Phase numbers describe drug development. The registry uses this when they do not apply, as it does for trials of devices, procedures or behaviour changes, and for observational studies.

Participants

About 26,200 people

The number the study aims to enrol. It can still change while the study runs.

Started

Feb 2022

Expected to finish

Dec 2026

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Ages

18 years and older

Sex

Anyone

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Participants willing to complete community-based symptom screening, finger-prick and venepuncture blood sampling, urine testing, and/or undergo TB and/or COVID-19 diagnostic testing. * Provision of informed consent. * Participant 18 years or above. * HIV-positive or negative participants will be included. Exclusion Criteria: * Inability to provide informed consent (e.g., mentally impaired). * Participants who have completed TB treatment in the last two months, or who have self-presented to their local TB clinic and are currently being worked up for suspected TB. * Participants already diagnosed with active TB on treatment. * Participants unable to commit to at least a two-month follow-up. * Female participants who are pregnant or who refuse a urine pregnancy test. * Participants in the community who cannot access healthcare due to severe ill health or lack of access to the local clinic.

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Conditions

The condition(s) this trial relates to.

COVID-19 HIV infectious disease tuberculosis

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

COVID -19 HIV infections Tuberculosis

Contacts and locations

Locations

  • Helen Ayles

    Lusaka, Zambia

  • Junior Mutsvangwa

    Harare, Zimbabwe

  • University of Cape Town

    Cape Town, Western Cape, South Africa

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