Dr Shibu Vijayan, Medical Director, Qure.ai & a TB Survivor stresses that the global plan to end TB calls to reimagine TB care, delivering services through a people-centered approach and reinforcing expanding early diagnosis including at subclinical stages
On World TB Day, we celebrate the progress toward ending Tuberculosis (TB) while acknowledging the challenges ahead. This year’s theme, “Yes we can end TB,” reminds us that we have the tools, the knowledge, and the will to achieve a world free of this disease.
India’s TB strategy sets ambitious targets for eliminating the disease by 2025, five years ahead of the global goal to eradicate it by 2030. In a race to achieve this goal, India has acknowledged the significant potential of innovative digital technologies to tackle TB. These encompass:
Point-of-care screening and diagnostics
- Handheld devices equipped with clinical decision support systems
- Telehealth services
- Electronic health records
- Real-time microbial and disease surveillance
- Supply chain monitoring
The global plan to end TB calls to reimagine TB care, delivering services through a people-centered approach and reinforcing expanding early diagnosis including at subclinical stages. Likewise, the Government of India’s National Strategic Plan (2017-2025) is driven by a DETECT-TREAT-PREVENT-BUILD approach and an emphasis on early diagnosis.
The NSP lists X-ray-based screening as a critical activity to undertake widely. In addition, it calls out the need for Artificial Intelligence (AI) enabled computer-aided diagnosis for X-ray reporting. AI has now become an essential component in lung health management. For example, AI-enabled X-ray interpretation is commonly used in community-based TB screening in remote locations where the lack of X-ray interpretation expertise delays diagnosis. WHO TB screening guidelines also recommend the use of AI for TB screening. AI can expedite diagnosis by reducing turnaround time (TAT) and early detection and treatment initiation; this cuts the disease transmission chain. Any early detection will improve patient outcomes and reduce costs to health systems and people.
AI has been at the forefront of the fight against TB through cutting-edge disease diagnosis and management solutions. AI-powered algorithms have helped to revolutionise TB diagnosis by, providing accurate and reliable detection of TB & other lung diseases on chest X-rays in less than a minute.
The impact of integrating AI within Tuberculosis programs can include:
- Fewer hospitalisations or emergency room visits
- Improved morbidity and mortality due to early disease detection and prompt treatment
- More decentralised care, which lowers healthcare costs or enhances the effectiveness of healthcare delivery
It is important to promote a human-centric approach to technology, encourage increased knowledge sharing in critical sectors like digital public infrastructure, and strongly emphasis digital health. AI technologies are essential for incidental case finding and monitoring as we reimagine TB Programs. I believe, 2023 is the year in which AI solutions will lead to a paradigm shift in TB diagnosis.
Innovation and collaboration are vital in building resilient health systems that can effectively respond to the challenges of TB and other infectious diseases. Partnerships among international health organizations, governments, technical agencies, donors, and industry experts pivotal role in advancing TB research and improving access to care. While the challenges in the fight to end TB must be acknowledged, a strong global community dedicated to ending the disease and improving the health of communities worldwide is key to eradicating TB.
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