TB is the single biggest infectious cause of death (1.5 million died in 2018), killing more HIV-positive people than any other disease, and is arguably the most important poverty-related disease in the world. TB's estimated incidence in Africa has been declining over recent years but progress is slow and plateauing. To avert stagnation, truly innovative and ambitious technologies are needed, especially those that improve case finding and time-to-diagnosis as, in mathematical models based on the TB care cascade framework, interventions that accomplish this will have the most impact on disrupting population-level transmission, including when deployed at facilities where patients are readily accessible. Critically, these interventions (triage tests) must promote access to confirmatory testing (e.g., Xpert MTB/RIF Ultra) by enabling patients to be referred rapidly and efficiently during the same visit. The investigators will optimise and evaluate a technology that, aside from the investigators early case-controlled study to show feasibility, is hitherto not meaningfully investigated for TB. This gap is alarming given, on one hand, the enormity of the TB epidemic and the need for a triage test and, on the other hand, promising proofs-of-concept that demonstrate high diagnostic accuracy of cough audio classifier for respiratory diseases such as pneumonia, asthma. pertussis, croup, and COPD. In some cases, these classification systems are CE-marked, awaiting FDA-approval, and subject to late-stage clinical trials. This demonstrates the promise of the underlying technological principle. CAGE-TB's innovation is further enhanced by: applying advanced machine learning methods that the team have specifically developed for TB patient cough audio analysis, use of mixed methods research - drawing from health economics, implementation science, and medical anthropology - to inform product design and assess barriers and facilitators to implementation, and uniquely for a TB diagnostic test, its potential deployment as a pure mHealth (smartphone-based) innovation that mitigates many barriers that typically jeopardise TPP criteria fulfilment.

CAGE-TB is a diagnostic evaluation study that assesses a TB cough audio signature's potential to be used in a smartphone application to detect potential TB from a cough sound to screen (triage) TB. The purpose of CAGE-TB is to promote the adoption of mobile health (mHealth) based cough audio triage testing for active pulmonary TB in health facilities located in high burden settings. The study is funded by the EDCTP2 programme supported by the European Union and involves four international partners. The study participants, older than 12 years, include participants who have a cough for a duration exceeding two weeks that present to healthcare clinics where the investigators have clinical recruitment infrastructure and permissions to conduct TB research. In this two-phase observational, cross-sectional study, each participant will be seen once only, at diagnosis, and no intervention is planned. In the first phase, the investigators will collect data from a discovery cohort, which will be used to train a machine learning algorithm. During the second phase, data will be collected from a validation cohort, comprising a larger number of participants from two geographically distinct study sites, which will be used to evaluate the performance of the algorithm. The aims of this study are to: (1) generate and separately validate a cough audio classifier that meets WHO triage test TPP sensitivity and specificity criteria. This aim lays the foundation for CAGE-TB by generating a classifier and a common public resource (cough sounds database) for potential later use in other studies. (2) Produce data on potential cost savings of cough audio app for triage by collecting primary data to demonstrate potential cost savings estimated using state-of-the-art methods to satisfy a key TPP criterion (\

Inclusion Criteria:

• participant must be at least 12 years old
• participant must have a prolonged cough (for at least two weeks)
• participant must provide informed consent
• participant shall have a known HIV status or be willing to undergo standard of care HIV testing and counseling

Exclusion Criteria:

• individuals who refuse informed consent
• individuals who have received treatment for TB in the 60 days prior to enrolment
• individuals who are unable to provide a sputum specimen for microbiological testing
• individuals who have haemoptysis or a bloody cough with any forced coughs for audio recordings

Patients with a cough of at least two weeks duration self-reporting to primary care clinics in Cape Town and Kampala, in areas with a high prevalence of TB.

Individual data will be stored and handled confidentially and anonymously. Research data will be stored under an identification code that relates to individual participants. Only the code number will be used for study documentation, annual progress reports and research publications. To trace data to an individual participant, an identification code list will be made to link the encoded data to the subject. Only the members of the research team, the site-independent monitors, members of the health care inspection, and members of the relevant Medical Ethics Committee can view research data that can be linked to individual participants. Access to the central database will be controlled via a combination of user roles and study configuration. Users are only granted privileges defined for their role in the study. The applicants will need to submit a proposal to the Trial Steering Committee for review, the applicants will also need to sign a DTA with Stellenbosch University.

Data will be shared one year after study completion.

Applicants will need to submit an application to the Trial Steering Committee for data access. The Trial Steering Committee will review the application. The applicant will also need to sign a DTA with Stellenbosch University.