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BMC Med. 2019 Aug 6;17(1):155. doi: 10.1186/s12916-019-1384-8.

Informing decision-making for universal access to quality tuberculosis diagnosis in India: an economic-epidemiological model.

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Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St., E6529, Baltimore, MD, 21205, USA.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St., E6529, Baltimore, MD, 21205, USA.
Division of Infectious Disease, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK.
Department of Epidemiology & Biostatistics & McGill International TB Centre, McGill University, Montreal, QC, H3A 1A2, Canada.
Manipal McGill Centre for Infectious Diseases, Manipal Academy of Higher Education, Manipal, India.



India and many other high-burden countries have committed to providing universal access to high-quality diagnosis and drug susceptibility testing (DST) for tuberculosis (TB), but the most cost-effective approach to achieve this goal remains uncertain. Centralized testing at district-level hub facilities with a supporting sample transport network can generate economies of scale, but decentralization to the peripheral level may provide faster diagnosis and reduce losses to follow-up (LTFU).


We generated functions to evaluate the costs of centralized and decentralized molecular testing for tuberculosis with Xpert MTB/RIF (Xpert), a WHO-endorsed test which can be performed at centralized and decentralized levels. We merged the cost estimates with an agent-based simulation of TB transmission in a hypothetical representative region in India to assess the impact and cost-effectiveness of each strategy.


Compared against centralized Xpert testing, decentralization was most favorable when testing volume at decentralized facilities and pre-treatment LTFU were high, and specimen transport network was exclusively established for TB. Assuming equal quality of centralized and decentralized testing, decentralization was cost-saving, saving a median $338,000 (interquartile simulation range [IQR] - $222,000; $889,000) per 20 million people over 10 years, in the most cost-favorable scenario. In the most cost-unfavorable scenario, decentralized testing would cost a median $3161 [IQR $2412; $4731] per disability-adjusted life year averted relative to centralized testing.


Decentralization of Xpert testing is likely to be cost-saving or cost-effective in most settings to which these simulation results might generalize. More decentralized testing is more cost-effective in settings with moderate-to-high peripheral testing volumes, high existing clinical LTFU, inability to share specimen transport costs with other disease entities, and ability to ensure high-quality peripheral Xpert testing. Decision-makers should assess these factors when deciding whether to decentralize molecular testing for tuberculosis.


Cost-benefit analysis; Diagnostic techniques and procedures; Systems analysis; Tuberculosis

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