By using real world data, mathematical models can help policymakers reach patients who would benefit most from an intervention, and better identify their needs
A march to advocate for better care for TB patients in Delhi. Delays in payments for nutritional support by the government can reduce treatment success rates for TB patients. Photo credit: Article 25 Flickr, Wikimedia Commons
By using real world data, mathematical models can help policymakers reach patients who would benefit most from an intervention, and better identify their needs
Tuberculosis (TB) is the leading cause of death from a single infectious agent, and among the top 10 causes of death, according to the WHO. In 2024, over a million people died from TB, making it a significant public health challenge.
The disease burden, however, is skewed. Over a quarter of the world’s estimated TB cases are in India — each year, approximately 2.7 million new cases are being reported.
