In the effort to combat tuberculosis in East Africa, AI-powered tools are enabling faster and earlier detection. Led by the Aga Khan University’s School of Nursing and Midwifery, the Kikohozi project, named after the Swahili word for “cough”, leverages artificial intelligence to analyze cough patterns. This technology aims to provide early detection of respiratory diseases in primary care and community settings, particularly in semi-urban and rural areas of Tanzania where access to traditional laboratory equipment remains a significant challenge.
This collaborative effort brings together the expertise of the Emerging Technologies for Health Lab at Muhimbili University of Health and Allied Sciences and the University of Warwick (UK). Supported by a research grant from the United Kingdom Research and Innovation-Medical Research Council (UKRI-MRC), the project represents a significant step forward in the country’s broader agenda for health sector innovation.
AI Integration in Tanzania’s Healthcare System
Tanzania’s adoption of AI in healthcare marks a significant evolution from traditional diagnostic approaches toward data-driven solutions. The Kikohozi Classifier uses machine learning to analyze cough sounds and support the identification of illnesses such as covid, tuberculosis, pneumonia, asthma, and bronchitis. This enhances early diagnosis, supports timely treatment, andultimately strengthens disease surveillance. By embedding AI into routine screening and diagnosis, Tanzania is equipping healthcare professionals with advanced tools to improve accuracy and speed. This is critical in settings where access to laboratory diagnostics and specialists remains limited.
Expanding Access Across Regions
The project is being piloted across diverse regions including Dar es Salaam, Dodoma, Kilimanjaro, Shinyanga, and Iringa. As Dr Riziki Kisonga, Programme Manager at the National Tuberculosis and Leprosy Programme under the Ministry of Health, noted that the trial phase will help determine whether it can be extended nationwide. By capturing data from varied populations, the system is being refined to reflect real-world conditions, making it more reliable and inclusive. This aligns closely with national health priorities and demonstrates how technological innovation can directly support public health strategies.
Investment Perspective
As Tanzania continues to integrate AI into its healthcare system, the opportunity for investment becomes increasingly compelling. The Kikohozi Classifier is more than a research project. It is a real-world solution with the potential to transform diagnostics across East Africa, particularly Tanzania. For investors, this is a chance to support a high-impact innovation at the intersection of technology and public health. Strategic funding can enhance system capabilities and expand reach into underserved communities. Investing in Tanzania’s AI-driven healthcare is a commitment to shaping the future of global health.
