Tamil Nadu Pioneers Predictive Model to Combat Tuberculosis Deaths

In a groundbreaking initiative, the government of Tamil Nadu has become the first state in India to incorporate a predictive model aimed at reducing tuberculosis (TB) mortality rates among patients. This innovative approach integrates advanced analytics into the existing State TB elimination programme, enabling healthcare professionals to identify severely ill TB patients promptly and prioritize them for hospital admission. The model was launched on July 1, 2025, and is anticipated to significantly enhance the state's capacity to manage TB cases effectively.

The predictive model, developed by the Indian Council of Medical Research (ICMR) National Institute of Epidemiology (NIE), is based on data collected from approximately 56,000 TB patients diagnosed in public health facilities across Tamil Nadu from July 2022 to June 2023. Asha Frederick, the State TB Officer, emphasized the importance of this model in reducing the average time from diagnosis to hospital admission, which currently stands at one day, with some severely ill patients experiencing delays of up to six days.

According to Dr. Hemant Shewade, a senior scientist at NIE, the new feature will be integrated with the existing TB SeWA (Severe TB Web Application) used since 2022 under the Tamil Nadu Kasanoi Erappila Thittam (TN-KET) initiative. The application will alert frontline healthcare workers to key indicators that signal severe illness in TB patients, such as low body weight and inability to stand without support. This proactive approach aims to ensure that high-risk patients receive immediate treatment, thereby reducing mortality rates, which can be as high as 50% among those flagged as severely ill. In contrast, the predicted probability of death for those not flagged is significantly lower, estimated at just 1% to 4%.

The urgency of this initiative cannot be overstated. Tuberculosis remains one of the leading causes of morbidity and mortality globally, with India accounting for the highest burden of TB. The World Health Organization reports that two people die from TB every three minutes in the country. A substantial proportion of these deaths occur within the first two months of treatment, highlighting the critical need for timely intervention.

Research published in the Journal of Infectious Diseases indicates that factors such as old age, co-infection with HIV, and low baseline body weight are significant contributors to mortality among TB patients. This underscores the necessity for targeted interventions, including special follow-ups and nutritional support for at-risk populations, as suggested by the authors of the study, particularly those conducted by Dr. Abebe Kebede and colleagues in 2023.

While the integration of predictive modeling into public health initiatives is a promising advancement, some experts caution against over-reliance on technology without adequate training for healthcare workers. Dr. Priya Narayan, a public health expert at the Indian Institute of Public Health, noted, "The success of such initiatives hinges not only on the technology but also on the capacity of healthcare providers to interpret and act on the data effectively. Continuous training and resources are essential."

The implications of Tamil Nadu's initiative extend beyond the state, potentially serving as a model for other regions grappling with high TB burdens. As countries worldwide strive to meet the United Nations' Sustainable Development Goals, which include ending the TB epidemic by 2030, the lessons learned from Tamil Nadu's approach could inform policy and practice at a national and international level. Furthermore, the initiative aligns with the global health community's emphasis on utilizing data-driven strategies to enhance healthcare delivery.

Looking ahead, the Tamil Nadu government plans to scale up the use of the predictive model across all 2,800 public health facilities in the state, from primary health centers to medical colleges. As this initiative unfolds, health officials remain optimistic that it will lead to a significant decline in TB mortality rates and set a precedent for innovative healthcare solutions in India and beyond.