Counting the lives saved by DOTS in India: a model-based approach

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• Global tuberculosis (TB) control requires better methods to assess program impact, including reduced transmission.
• Vital registration data in India are insufficient for accurate TB mortality estimates.

Purpose of the Study:

• To develop and apply a mathematical model to estimate the impact of India's Revised National TB Control Programme (RNTCP) on TB mortality and transmission.
• To quantify lives saved by the RNTCP, considering both treatment outcomes and transmission reduction.

Main Methods:

• Developed a mathematical model of TB transmission dynamics and mortality in India.
• Utilized Bayesian evidence synthesis to calibrate the model with literature data and TB burden estimates.
• Simulated the TB epidemic with and without the DOTS program to calculate lives saved.

Main Results:

• The RNTCP saved an estimated 7.75 million lives between 1997 and 2016 (95% Bayesian credible interval: 6.29-8.82 million).
• Approximately 42% of the RNTCP's impact is attributed to averting TB transmission, in addition to improving treatment outcomes.

Conclusions:

• High-quality TB services provide substantial preventive and curative benefits.
• Mathematical modeling is a valuable tool for estimating the population-level impact of major disease control programs like the RNTCP.