Salje, HenrikAndrews, Jason R.Deo, SarangSatyanarayana, SrinathSun, Amanda Y.Pai, MadhukarDowdy, David W.2014-08-132014Salje, Henrik, Jason R. Andrews, Sarang Deo, Srinath Satyanarayana, Amanda Y. Sun, Madhukar Pai, and David W. Dowdy. 2014. “The Importance of Implementation Strategy in Scaling Up Xpert MTB/RIF for Diagnosis of Tuberculosis in the Indian Health-Care System: A Transmission Model.” PLoS Medicine 11 (7): e1001674. doi:10.1371/journal.pmed.1001674. http://dx.doi.org/10.1371/journal.pmed.1001674.1549-1277http://nrs.harvard.edu/urn-3:HUL.InstRepos:12717518Background: 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' Summaryen-USBiology and Life SciencesComputational BiologyPopulation ModelingInfectious Disease ModelingMedicine and Health SciencesEpidemiologyInfectious DiseasesBacterial DiseasesTuberculosisInfectious Disease ControlJournal Article2014-08-1310.1371/journal.pmed.1001674