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

BMC Medicine
Sandip MandalNimalan Arinaminpathy

Abstract

Against the backdrop of renewed efforts to control tuberculosis (TB) worldwide, there is a need for improved methods to estimate the public health impact of TB programmes. Such methods should not only address the improved outcomes amongst those receiving care but should also account for the impact of TB services on reducing transmission. Vital registration data in India are not sufficiently reliable for estimates of TB mortality. As an alternative approach, we developed a mathematical model of TB transmission dynamics and mortality, capturing the scale-up of DOTS in India, through the rollout of the Revised National TB Control Programme (RNTCP). We used available data from the literature to calculate TB mortality hazards amongst untreated TB; amongst cases treated under RNTCP; and amongst cases treated under non-RNTCP conditions. Using a Bayesian evidence synthesis framework, we combined these data with current estimates for the TB burden in India to calibrate the transmission model. We simulated the national TB epidemic in the presence and absence of the DOTS programme, measuring lives saved as the difference in TB deaths between these scenarios. From 1997 to 2016, India's RNTCP has saved 7.75 million lives (95% Bayesian credi...Continue Reading

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Citations

Oct 9, 2020·Science Translational Medicine·Rebecca C HarrisRichard G White
Apr 16, 2020·Physica a·Abhishek SenapatiJoydev Chattopadhyay
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Related Concepts

Bayesian Prediction
Theoretical Study
Tuberculosis
Aftercare
Patient Care
Health Services
Literature
National Health Programs
Tuberculosis Vaccines
Disease Transmission

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