Skip to main content

01.12.2017 | Research article | Ausgabe 1/2017 Open Access

BMC Medicine 1/2017

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

BMC Medicine > Ausgabe 1/2017
Sandip Mandal, Vineet K. Chadha, Ramanan Laxminarayan, Nimalan Arinaminpathy
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​s12916-017-0809-5) contains supplementary material, which is available to authorized users.



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 credible interval 6.29–8.82 million). We estimate that 42% of this impact was due to the ‘indirect’ effects of the RNTCP in averting transmission as well as improving treatment outcomes.


When expanding high-quality TB services, a substantial proportion of overall impact derives from preventive, as well as curative, benefits. Mathematical models, together with sufficient data, can be a helpful tool in estimating the true population impact of major disease control programmes.
Über diesen Artikel

Weitere Artikel der Ausgabe 1/2017

BMC Medicine 1/2017 Zur Ausgabe

Neu im Fachgebiet Allgemeinmedizin

Mail Icon II Newsletter

Bestellen Sie unseren kostenlosen Newsletter Update Allgemeinmedizin und bleiben Sie gut informiert – ganz bequem per eMail.