This article examines the implementation of an artificial intelligence tool designed to improve tuberculosis detection in Haryana, India, highlighting its effectiveness and the challenges that remain in combating the disease.
In a significant public health initiative, health workers in Ambala, Haryana, are utilizing a new artificial intelligence (AI) tool to enhance tuberculosis (TB) detection as part of the National TB Elimination Programme. This innovative approach, known as Vulnerability Mapping for Tuberculosis (VMTB), leverages data from nearly 30 open-source geospatial datasets to identify high-risk areas where TB cases are most likely to occur. The initiative was piloted in Haryana and Assam before being adopted nationwide during an ongoing 100-day campaign aimed at increasing TB screening and diagnosis.
The VMTB tool uses various indicators, including population density, nutritional profiles, and access to healthcare facilities, to create a detailed map highlighting vulnerable populations. Dr. Neeraj Agrawal, chief programme officer at Wadhwani AI, which developed the VMTB tool, explained that the AI can predict geospatial vulnerability down to specific village and ward levels. This precision enables health workers to efficiently allocate resources and focus their screening efforts where they are most needed.
Identifying Vulnerable Populations
Traditionally, identifying vulnerable populations for TB has been challenging due to the lack of a nationwide registry for at-risk individuals. Smokers, individuals with diabetes or other respiratory conditions, and those experiencing malnutrition are especially susceptible to TB. While community health workers, known as ASHA (Accredited Social Health Activist) workers, often know these individuals in their respective areas, there has been no consolidated data to streamline the identification process.
Dr. Rajesh Raju, the state TB officer for Haryana, noted that out of the 6,237 gram panchayats in Haryana, approximately 35% were declared TB-free in the previous year, as they reported an incidence of fewer than one case per million residents. This leaves around 4,080 gram panchayats that require focused attention to combat TB effectively. Through the VMTB tool, Raju indicated that they have identified 2,111 high-risk areas, allowing health workers to concentrate their efforts on these regions during the current campaign, thereby enhancing both efficiency and effectiveness.
Enhanced Screening Strategies
The introduction of VMTB has altered the screening strategy during the current 100-day programme. Health workers are now screening the entire adult population in identified high-risk villages, rather than focusing solely on vulnerable individuals. This includes an ambitious goal of achieving 100% X-ray coverage for adults in these communities.
Accompanying this AI-driven mapping is another technological advancement: portable hand-held X-ray machines that provide rapid screening capabilities. Community health officer Avaneeta Sandhu described the impact of these devices, explaining that they allow for immediate X-ray results, significantly reducing the need for patients to travel long distances to health centers. This convenience, coupled with routine health checks for blood pressure and blood sugar, helps mitigate the stigma associated with TB testing.
In practical terms, the increased efficiency of the VMTB tool has resulted in a substantial rise in the number of sputum samples collected during screening camps. Previously, health workers might gather around 10 samples per camp; this number has surged to between 70 and 80, according to Sandhu.
Early Identification of TB Cases
Preliminary data from the implementation of the VMTB tool in Haryana and Assam suggest promising results. There was a 251% relative increase in the yield of TB cases in Haryana and a 61% increase in Assam last year. Dr. Agarwal emphasized the importance of active case finding, which involves proactive outreach by health staff rather than waiting for patients to seek help. This method has contributed to the diagnosis of over 200,000 TB cases through active screening, accounting for nearly 10% of the 2.5 million cases detected nationwide in the previous year.
The persistent burden of tuberculosis in India remains a critical public health concern, with an estimated 2.71 million cases and over 300,000 deaths reported in 2024, according to the Global TB Report 2025. Despite a reduction in TB incidence by 21% and deaths by 28% from 2015 to 2024, India is not on track to meet the World Health Organization’s target of reducing TB incidence by 50% and TB deaths by 75% by 2025.
Conclusion
The VMTB tool represents a significant advancement in the fight against tuberculosis in India, allowing health workers to effectively target high-risk populations and enhance screening efforts. As the country continues to grapple with the TB epidemic, innovative solutions like VMTB may play a crucial role in improving public health outcomes and, ultimately, achieving TB elimination goals.
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