India has developed its own mathematical system to estimate the burden of tuberculosis (TB) cases, becoming the first country to do so. The system aims to improve the estimation of TB burden, particularly in terms of incidence and mortality, which has been a challenging task in the past.
India’s efforts to improve TB surveillance and treatment
India has made significant efforts over the past decade to increase program coverage, find missing cases, and generate more evidence for TB diagnosis and treatment. Ni-kshay, a case-based web-based surveillance system, has improved the standard of notification material since its introduction and rapid scale-up in 2012. Laboratory services have also been decentralized and scaled up with high-quality rapid diagnostic tests, such as the Nucleic Acid Amplification Test (NAAT). Private sector engagement has also increased, with mandatory notification leading to a seven-fold increase in private sector notification since 2014.
The development of India’s own mathematical model
India’s own TB model utilizes data from various sources, such as Ni-kshay, active case finding, and the National TB Prevalence Survey. The model takes into account the natural history of the disease, individual infection status, healthcare seeking, missed or correct diagnosis, treatment coverage, and outcomes including cure and death. Mobility data was also used as a proxy for the reduction in population movement impacting TB transmission during COVID-related disruptions. The model was adjusted for the years 2011 to 2025.
Advantages of the new TB burden estimation system
India’s new TB burden estimation system provides several advantages. India has become the first country to estimate the burden of TB cases in-country. The incidence and mortality estimates for India will be available by March every year, six months earlier than the estimates provided by the World Health Organization (WHO) in October every year. India can also make such estimates for the state level in the future. The trend of incidence estimates has been reversed, overcoming COVID-related disruptions. This has led to a reduction in missing cases and thereby, mortality estimates have also been reduced.
