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About us
4-CAGE-TB brings together African and European scientists to develop a mobile phone-based cough triage test for Tuberculosis (TB).
Who is CAGE-TB?
The Cough Audio triaGE for TB (4-CAGE-TB) project aims at promoting the adoption of mobile health-based cough audio triage testing for active pulmonary tuberculosis in health facilities in high-burden settings.
Specifically the study aims are;
a.) to generate and separately validate a cough audio classifier that meets the criteria for the World Health Organization (WHO) triage test target product profile for sensitivity and specificity,
b.) to produce data on potential cost savings, and
c.) to package the underlying technology into an easy-to-use smartphone app built using human-centred design ready-for-use in large-scale clinical evaluations.
It will do so through:
- Collecting cough audio data in a discovery cohort of patients with a prolonged cough who present to primary care clinics in Cape Town, South Africa; and optimising a classifier scheme;
- Validating the audio classifier algorithm in separate clinical validation cohorts in Cape Town, South Africa and Kampala, Uganda and calculate potential cost savings; and
- Using a human-centred design process to integrate the classifier into a smartphone application and identifying potential barriers and facilitators to its successful deployment.
Our Funders
Our mission
To improve TB screening by using a smartphone app that can detect a TB cough.
Objective
- To promote the adoption of mobile health-based cough radio triage testing for active pulmonary tuberculosis in health facilities in high burden settings.
- To generate and separately validate a cough audio classifier that meets WHO triage test TPP sensitivity and specificity criteria.
- To produce data on potential cost savings of mHealth triage testing.
- To package the underlying technology into an easy-to-use smartphone app built using human-centred design ready-for-use in large-scale clinical evaluations.
- To facilitate significant and diverse capacity building, including training North-South co-supervised African students, post-graduates and post-doctoral fellows in digital signal processing for respiratory health, diagnostic accuracy evaluations, costing analyses and implementation research, and mHealth.