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PLoS Med. 2014 Jul 15;11(7):e1001674. doi: 10.1371/journal.pmed.1001674. eCollection 2014 Jul.

The importance of implementation strategy in scaling up Xpert MTB/RIF for diagnosis of tuberculosis in the Indian health-care system: a transmission model.

Author information

1
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
2
Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
3
Indian School of Business, Hyderabad, India.
4
Department of Epidemiology and Biostatistics, McGill University, Montreal, Quebec, Canada; McGill International TB Centre, McGill University Health Centre, Montreal, Quebec, Canada.
5
Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.
6
Department of Epidemiology and Biostatistics, McGill University, Montreal, Quebec, Canada; McGill International TB Centre, McGill University Health Centre, Montreal, Quebec, Canada; Montreal Chest Institute, McGill University Health Centre, Montreal, Quebec, Canada.
7
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America; Center for Tuberculosis Research, Johns Hopkins University, Baltimore, Maryland, United States of America.

Abstract

BACKGROUND:

India has announced a goal of universal access to quality tuberculosis (TB) diagnosis and treatment. A number of novel diagnostics could help meet this important goal. The rollout of one such diagnostic, Xpert MTB/RIF (Xpert) is being considered, but if Xpert is used mainly for people with HIV or high risk of multidrug-resistant TB (MDR-TB) in the public sector, population-level impact may be limited.

METHODS AND FINDINGS:

We developed a model of TB transmission, care-seeking behavior, and diagnostic/treatment practices in India and explored the impact of six different rollout strategies. Providing Xpert to 40% of public-sector patients with HIV or prior TB treatment (similar to current national strategy) reduced TB incidence by 0.2% (95% uncertainty range [UR]: -1.4%, 1.7%) and MDR-TB incidence by 2.4% (95% UR: -5.2%, 9.1%) relative to existing practice but required 2,500 additional MDR-TB treatments and 60 four-module GeneXpert systems at maximum capacity. Further including 20% of unselected symptomatic individuals in the public sector required 700 systems and reduced incidence by 2.1% (95% UR: 0.5%, 3.9%); a similar approach involving qualified private providers (providers who have received at least some training in allopathic or non-allopathic medicine) reduced incidence by 6.0% (95% UR: 3.9%, 7.9%) with similar resource outlay, but only if high treatment success was assured. Engaging 20% of all private-sector providers (qualified and informal [providers with no formal medical training]) had the greatest impact (14.1% reduction, 95% UR: 10.6%, 16.9%), but required >2,200 systems and reliable treatment referral. Improving referrals from informal providers for smear-based diagnosis in the public sector (without Xpert rollout) had substantially greater impact (6.3% reduction) than Xpert scale-up within the public sector. These findings are subject to substantial uncertainty regarding private-sector treatment patterns, patient care-seeking behavior, symptoms, and infectiousness over time; these uncertainties should be addressed by future research.

CONCLUSIONS:

The impact of new diagnostics for TB control in India depends on implementation within the complex, fragmented health-care system. Transformative strategies will require private/informal-sector engagement, adequate referral systems, improved treatment quality, and substantial resources. Please see later in the article for the Editors' Summary.

PMID:
25025235
PMCID:
PMC4098913
DOI:
10.1371/journal.pmed.1001674
[Indexed for MEDLINE]
Free PMC Article
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