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

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 hi...

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Veröffentlicht in:PLoS medicine 2014-07, Vol.11 (7), p.e1001674-e1001674
Hauptverfasser: Salje, Henrik, Andrews, Jason R, Deo, Sarang, Satyanarayana, Srinath, Sun, Amanda Y, Pai, Madhukar, Dowdy, David W
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container_title PLoS medicine
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Andrews, Jason R
Deo, Sarang
Satyanarayana, Srinath
Sun, Amanda Y
Pai, Madhukar
Dowdy, David W
description 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. 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. 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.
doi_str_mv 10.1371/journal.pmed.1001674
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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. 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 &gt;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. 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. 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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. 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 &gt;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. 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. 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Andrews, Jason R ; Deo, Sarang ; Satyanarayana, Srinath ; Sun, Amanda Y ; Pai, Madhukar ; Dowdy, David W</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c590t-3ad18b081e5f5beaa2cf42eaf79df71663635e0997189a2709e97cf3124395ed3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Analysis</topic><topic>Antibiotics</topic><topic>Biology and Life Sciences</topic><topic>Care and treatment</topic><topic>Complications and side effects</topic><topic>Demographic aspects</topic><topic>Health aspects</topic><topic>HIV patients</topic><topic>Human immunodeficiency virus</topic><topic>Humans</topic><topic>India</topic><topic>India - epidemiology</topic><topic>Management</topic><topic>Mathematical models</topic><topic>Medical care</topic><topic>Medical research</topic><topic>Medicine and Health Sciences</topic><topic>Microscopy</topic><topic>Models, Theoretical</topic><topic>Mycobacterium</topic><topic>Mycobacterium tuberculosis</topic><topic>Patients</topic><topic>Public sector</topic><topic>Risk factors</topic><topic>Studies</topic><topic>Tuberculosis</topic><topic>Tuberculosis, Multidrug-Resistant - diagnosis</topic><topic>Tuberculosis, Multidrug-Resistant - epidemiology</topic><topic>Tuberculosis, Multidrug-Resistant - transmission</topic><topic>Tuberculosis, Pulmonary - diagnosis</topic><topic>Tuberculosis, Pulmonary - epidemiology</topic><topic>Tuberculosis, Pulmonary - transmission</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Salje, Henrik</creatorcontrib><creatorcontrib>Andrews, Jason R</creatorcontrib><creatorcontrib>Deo, Sarang</creatorcontrib><creatorcontrib>Satyanarayana, Srinath</creatorcontrib><creatorcontrib>Sun, Amanda Y</creatorcontrib><creatorcontrib>Pai, Madhukar</creatorcontrib><creatorcontrib>Dowdy, David W</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Environmental Sciences and Pollution Management</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><collection>PLoS Medicine</collection><jtitle>PLoS medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Salje, Henrik</au><au>Andrews, Jason R</au><au>Deo, Sarang</au><au>Satyanarayana, Srinath</au><au>Sun, Amanda Y</au><au>Pai, Madhukar</au><au>Dowdy, David W</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The importance of implementation strategy in scaling up Xpert MTB/RIF for diagnosis of tuberculosis in the Indian health-care system: a transmission model</atitle><jtitle>PLoS medicine</jtitle><addtitle>PLoS Med</addtitle><date>2014-07-01</date><risdate>2014</risdate><volume>11</volume><issue>7</issue><spage>e1001674</spage><epage>e1001674</epage><pages>e1001674-e1001674</pages><issn>1549-1676</issn><issn>1549-1277</issn><eissn>1549-1676</eissn><abstract>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. 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 &gt;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. 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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>25025235</pmid><doi>10.1371/journal.pmed.1001674</doi><oa>free_for_read</oa></addata></record>
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subjects Analysis
Antibiotics
Biology and Life Sciences
Care and treatment
Complications and side effects
Demographic aspects
Health aspects
HIV patients
Human immunodeficiency virus
Humans
India
India - epidemiology
Management
Mathematical models
Medical care
Medical research
Medicine and Health Sciences
Microscopy
Models, Theoretical
Mycobacterium
Mycobacterium tuberculosis
Patients
Public sector
Risk factors
Studies
Tuberculosis
Tuberculosis, Multidrug-Resistant - diagnosis
Tuberculosis, Multidrug-Resistant - epidemiology
Tuberculosis, Multidrug-Resistant - transmission
Tuberculosis, Pulmonary - diagnosis
Tuberculosis, Pulmonary - epidemiology
Tuberculosis, Pulmonary - transmission
title The importance of implementation strategy in scaling up Xpert MTB/RIF for diagnosis of tuberculosis in the Indian health-care system: a transmission model
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