Advances in medical technologies, that came with the inclusion of Artificial Intelligence (AI), Machine Learning, Internet of Things (IoT), and deep tech, have revolutionised diagnosis of tuberculosis (TB) — the world’s largest infectious disease killer — in India, said experts on Thursday ahead of the World Tuberculosis Day.
World Tuberculosis Day is observed every year on March 24. “Yes! We can end TB!” is the theme for this year, and urges leaders from around the world to act to stop the TB epidemic.
TB afflicts more than 10 million people each year. India contributes to over 30 per cent of the global TB burden. In 2021, India had estimated 30 lakh new TB cases. About 38 per cent of the global TB deaths took place in India.
The disease is preventable, treatable, and curable, but early diagnosis remains the key. Accurate diagnosis of TB early in the infection cycle can help accelerate therapy and curb the spread of the disease.
“Given the current infrastructure in India, the early diagnosis of TB continues to be the biggest hurdle in treatment compliance. For TB to be completely eradicated, we need a public health infrastructure that is equipped to detect infectious pulmonary cases early before the disease has a chance to spread,” Pavan Choudary, Chairman, Medical Technology Association of India (MTaI), told IANS.
AI and ML have shown more promise in automating early detection, more than the traditional screening for TB via a simple lung X-ray.
AI-powered deep learning neural networks are increasingly being used to analyse medical images, such as chest radiographs or x-rays.
“Modern advances in digital radiology, AI/ML and Nucleic Acid Amplification techniques have now come together to provide rapid, accurate and affordable diagnostics across multiple settings including remote point of care locations, without the need to have well-trained technicians or very extensive infrastructure,” Chandrasekhar Nair, Director & CTO, Molbio Diagnostics, told IANS.
“India is the first country globally to roll out point of care molecular detection of TB as a replacement to sputum smear microscopy even at remote locations across the country. This results in very early diagnosis of TB patients and their enrollment in the cascade of care of the National TB elimination programme,” he said.
Further, India has deployed digital health platforms like India’s ‘Nikshay’ which integrate all TB patient diagnosis and monitoring data, including patient nutrition, have started making a significant difference in the management of TB care in India.
A few states in India have also integrated private players for last-mile delivery of TB drugs. Various adherence solutions from the low-cost 99 dots using SMS services, video observed therapy to IoT-based pill boxes are improving adherence to therapy and leveraging technology to provide an alternative to directly observed therapy methodology.
Speaking to IANS, Chandra Ganjoo, Group Chief Executive Officer, Trivitron Healthcare highlighted that advancements including the PCR/NAAT based molecular diagnostic tests, digital X-rays, telemedicine, mobile apps and wearable devices, electronic health records among others have made diagnosis of TB in India faster, more accurate, and more accessible to patients, especially those living in remote areas.
“These have also improved the overall TB treatment outcomes, reduced the burden of the disease, and saved countless lives,” Ganjoo said.
Besides early detection, “AI and ML are also helping accelerate the development of new drugs and therapies for TB by identifying new drug targets and biomarkers, designing more effective drugs, and optimising clinical trial design,” Ganjoo said.
But it remains to evaluate the cost effectiveness of these diagnostic solutions.
According to Susmita Chatterjee, Senior Health Economist, The George Institute for Global Health, India, in the process of TB elimination efforts of the country, the economic consequence of the disease is generally ignored.
In a recent study conducted by the George Institute, and published in the journal PLOS Global Public Health, researchers observed that the total cost of TB treatment from the onset of symptoms to one-year post-treatment ranged from Rs 26,500-30,500 per patient despite free diagnosis and treatment provided by the government.
“The major reason for high cost associated with TB treatment is because the patients with TB symptoms visit on average 12 healthcare providers before they are diagnosed as TB and during this period, they spend about 58 per cent of their total treatment cost,” said Chaterjee, while stressing the need for reduction of cost incurred before initiation of treatment.
