6,111 TB cases detected in 35 days, 11,091 villages termed high-risk

2 min readMumbaiJun 24, 2026 10:15 PM IST

Maharashtra TB officials said the villages were not identified because they had confirmed outbreaks, but because they were predicted to be more vulnerable to TB transmission. (Photo: Freepik)

Maharashtra has detected 6,111 new tuberculosis (TB) cases within the first 35 days of the Centre’s 100-day TB Mukt Bharat Abhiyan, while an artificial intelligence-based assessment has identified 11,091 villages across the state as being at high risk for the disease, Public Health Minister Prakash Abitkar informed the Legislative Assembly on Wednesday.

Replying to a starred question raised by Dr Nitin Raut and 12 other legislators, including Dr Jitendra Awhad, Amit Deshmukh and Sunil Raut, Abitkar confirmed that the AI-based system had flagged the villages for intensified screening and surveillance under the campaign launched on March 24.

The minister’s reply came amid concerns over the state’s TB burden and questions regarding the availability of diagnostic infrastructure and manpower in vulnerable areas.

According to the government, the high-risk villages were identified through an AI-based assessment carried out by the Centre. State TB officials said the villages were not identified because they had confirmed outbreaks, but because they were predicted to be more vulnerable to TB transmission.

“The Government of India used an artificial intelligence-based predictive tool developed by Wadhwani AI to identify villages that may be at a higher risk of tuberculosis transmission. The model analyses 32 indicators, including previous TB cases, contact history of TB patients, sanitation conditions, undernutrition, vaccination status, literacy levels, comorbidities such as diabetes and hypertension, tobacco and alcohol use, population density, and other geospatial and social determinants. Based on this assessment, more than 11,000 villages and wards in Maharashtra were identified as high-risk and included under the Centre’s 100-day TB-Free India campaign,” a senior State TB Department official told The Indian Express.

The official said the AI model drew on 32 indicators grouped under geospatial features, health and social determinants, and National TB Elimination Programme (NTEP) data. These included pollution levels, vegetation cover, population density, sanitation indicators, child undernutrition, literacy levels, previous TB cases, geolocation of diagnosed patients, prevalence of diabetes and hypertension, and tobacco and alcohol use.

In his written reply, Abitkar stated that villages including 482 in Nagpur district, 539 in Yavatmal, 504 in Amravati, and 488 each in Nashik and Raigad had been categorised as high-risk through the AI-based system.