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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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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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.</description><identifier>ISSN: 1549-1676</identifier><identifier>ISSN: 1549-1277</identifier><identifier>EISSN: 1549-1676</identifier><identifier>DOI: 10.1371/journal.pmed.1001674</identifier><identifier>PMID: 25025235</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>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</subject><ispartof>PLoS medicine, 2014-07, Vol.11 (7), p.e1001674-e1001674</ispartof><rights>COPYRIGHT 2014 Public Library of Science</rights><rights>2014 Salje et al 2014 Salje et al</rights><rights>2014 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Salje H, Andrews JR, Deo S, Satyanarayana S, Sun AY, Pai M, et al. (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 Med 11(7): e1001674. doi:10.1371/journal.pmed.1001674</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c590t-3ad18b081e5f5beaa2cf42eaf79df71663635e0997189a2709e97cf3124395ed3</citedby><cites>FETCH-LOGICAL-c590t-3ad18b081e5f5beaa2cf42eaf79df71663635e0997189a2709e97cf3124395ed3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4098913/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4098913/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79569,79570</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25025235$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><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><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</title><title>PLoS medicine</title><addtitle>PLoS Med</addtitle><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.</description><subject>Analysis</subject><subject>Antibiotics</subject><subject>Biology and Life Sciences</subject><subject>Care and treatment</subject><subject>Complications and side effects</subject><subject>Demographic aspects</subject><subject>Health aspects</subject><subject>HIV patients</subject><subject>Human immunodeficiency virus</subject><subject>Humans</subject><subject>India</subject><subject>India - epidemiology</subject><subject>Management</subject><subject>Mathematical models</subject><subject>Medical care</subject><subject>Medical research</subject><subject>Medicine and Health Sciences</subject><subject>Microscopy</subject><subject>Models, Theoretical</subject><subject>Mycobacterium</subject><subject>Mycobacterium tuberculosis</subject><subject>Patients</subject><subject>Public sector</subject><subject>Risk factors</subject><subject>Studies</subject><subject>Tuberculosis</subject><subject>Tuberculosis, Multidrug-Resistant - diagnosis</subject><subject>Tuberculosis, Multidrug-Resistant - epidemiology</subject><subject>Tuberculosis, Multidrug-Resistant - transmission</subject><subject>Tuberculosis, Pulmonary - diagnosis</subject><subject>Tuberculosis, Pulmonary - epidemiology</subject><subject>Tuberculosis, Pulmonary - transmission</subject><issn>1549-1676</issn><issn>1549-1277</issn><issn>1549-1676</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>DOA</sourceid><recordid>eNqNktFu0zAUhiMEYmPwBggsISFu2tlxHMdcII2JQaUhJFQk7qxTx25dOXFmO0h9FZ4WZ-2m9o6rHDvf-X_7-C-K1wTPCeXkcuvH0IObD51u5wRjUvPqSXFOWCVmua6fHtVnxYsYtxiXAgv8vDgrGS5ZSdl58Xe50ch2gw8JeqWRN9PK6U73CZL1PYopQNLrHbK5VuBsv0bjgH4POiT0ffn58ufiBhkfUGth3fto4ySSxpUOanT369yZss2iz0iPNhpc2swUBI3iLibdfUSAsksfOxvj5Nn5VruXxTMDLupXh-9F8evmy_L62-z2x9fF9dXtTDGB04xCS5oVbohmhq00QKlMVWowXLSGk7qmNWUaC8FJI6DkWGjBlaGkrKhguqUXxdu97pBPKw9jjZLUDaOcUywysdgTrYetHILtIOykByvvN3xYSwjJKqelao1hhuIV5qwilWqauuSEKUJNAyU0WevTwW1c5ZdTec4B3Ino6Z_ebuTa_5EVFo0gNAt8OAgEfzfqmGSemtLOQa_9mM_NakwwpxX-D7RinHNMJ9V3e3QN-Ra2Nz6bqwmXV7QpBcuSPFPvj6j9Q0bvxiko8RSs9qAKPsagzeMFCZZTfB_mLKf4ykN8c9ub4-E8Nj3klf4DUEbueQ</recordid><startdate>20140701</startdate><enddate>20140701</enddate><creator>Salje, Henrik</creator><creator>Andrews, Jason R</creator><creator>Deo, Sarang</creator><creator>Satyanarayana, Srinath</creator><creator>Sun, Amanda Y</creator><creator>Pai, Madhukar</creator><creator>Dowdy, David W</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7QL</scope><scope>C1K</scope><scope>5PM</scope><scope>DOA</scope><scope>CZK</scope></search><sort><creationdate>20140701</creationdate><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</title><author>Salje, Henrik ; 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 >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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