Outlook for tuberculosis elimination in California: An individual-based stochastic model
As part of the End TB Strategy, the World Health Organization calls for low-tuberculosis (TB) incidence settings to achieve pre-elimination (
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| Veröffentlicht in: | PloS one 2019-04, Vol.14 (4), p.e0214532-e0214532 |
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| creator | Goodell, Alex J Shete, Priya B Vreman, Rick McCabe, Devon Porco, Travis C Barry, Pennan M Flood, Jennifer Marks, Suzanne M Hill, Andrew Cattamanchi, Adithya Kahn, James G |
| description | As part of the End TB Strategy, the World Health Organization calls for low-tuberculosis (TB) incidence settings to achieve pre-elimination ( |
| doi_str_mv | 10.1371/journal.pone.0214532 |
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| fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_2208023824</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A581813762</galeid><doaj_id>oai_doaj_org_article_a459607d64f943eb8aa59ab7c3832369</doaj_id><sourcerecordid>A581813762</sourcerecordid><originalsourceid>FETCH-LOGICAL-c692t-91db62a94cbc219d58b23cf8df5833f159500fb27426c815a4da03c0b4df688e3</originalsourceid><addsrcrecordid>eNqNk9-L1DAQx4so3nn6H4gWBNGHXfOraeKDsCz-WDhY8Be-hWmS7mZNm7VpD_3vzd72jq3cg-QhYfKZ70wmM1n2FKM5piV-swtD14Kf70Nr54hgVlByLzvHkpIZJ4jePzmfZY9i3CFUUMH5w-yMIsmZKMV59mM99D6En3kdurwfKtvpwYfoYm69a1wLvQtt7tp8Cd4lpnXwNl8cLMZdOTOAn1UQrcljH_QWYu903gRj_ePsQQ0-2ifjfpF9-_D-6_LT7HL9cbVcXM40l6SfSWwqTkAyXWmCpSlERaiuhakLQWmNC1kgVFekZIRrgQtgBhDVqGKm5kJYepE9P-ruU9pqLEpUhCCBCBWEJWJ1JEyAndp3roHujwrg1LUhdBsFXcrbWwWskByVhrNaMmorAVBIqEpNBSWUy6T1bow2VI012rZ9B34iOr1p3VZtwpXirOBYoiTwahTowq_Bxl41LmrrPbQ2DNd5l5gTjHFCX_yD3v26kdpAeoBr65Di6oOoWhQCi9QrnCRqfgeVlrGN06mDapfsE4fXE4fE9PZ3v4EhRrX68vn_2fX3KfvyhN1a8P02Bj8c2ixOQXYEdRdi7Gx9W2SM1GEAbqqhDgOgxgFIbs9OP-jW6abj6V8o6AAB</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2208023824</pqid></control><display><type>article</type><title>Outlook for tuberculosis elimination in California: An individual-based stochastic model</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><source>Public Library of Science (PLoS)</source><creator>Goodell, Alex J ; Shete, Priya B ; Vreman, Rick ; McCabe, Devon ; Porco, Travis C ; Barry, Pennan M ; Flood, Jennifer ; Marks, Suzanne M ; Hill, Andrew ; Cattamanchi, Adithya ; Kahn, James G</creator><contributor>Wilkinson, Katalin Andrea</contributor><creatorcontrib>Goodell, Alex J ; Shete, Priya B ; Vreman, Rick ; McCabe, Devon ; Porco, Travis C ; Barry, Pennan M ; Flood, Jennifer ; Marks, Suzanne M ; Hill, Andrew ; Cattamanchi, Adithya ; Kahn, James G ; Wilkinson, Katalin Andrea</creatorcontrib><description>As part of the End TB Strategy, the World Health Organization calls for low-tuberculosis (TB) incidence settings to achieve pre-elimination (<10 cases per million) and elimination (<1 case per million) by 2035 and 2050, respectively. These targets require testing and treatment for latent tuberculosis infection (LTBI).
To estimate the ability and costs of testing and treatment for LTBI to reach pre-elimination and elimination targets in California.
We created an individual-based epidemic model of TB, calibrated to historical cases. We evaluated the effects of increased testing (QuantiFERON-TB Gold) and treatment (three months of isoniazid and rifapentine). We analyzed four test and treat targeting strategies: (1) individuals with medical risk factors (MRF), (2) non-USB, (3) both non-USB and MRF, and (4) all Californians. For each strategy, we estimated the effects of increasing test and treat by a factor of 2, 4, or 10 from the base case. We estimated the number of TB cases occurring and prevented, and net and incremental costs from 2017 to 2065 in 2015 U.S. dollars. Efficacy, costs, adverse events, and treatment dropout were estimated from published data. We estimated the cost per case averted and per quality-adjusted life year (QALY) gained.
In the base case, 106,000 TB cases are predicted to 2065. Pre-elimination was achieved by 2065 in three scenarios: a 10-fold increase in the non-USB and persons with MRF (by 2052), and 4- or 10-fold increase in all Californians (by 2058 and 2035, respectively). TB elimination was not achieved by any intervention scenario. The most aggressive strategy, 10-fold in all Californians, achieved a case rate of 8 (95% UI 4-16) per million by 2050. Of scenarios that reached pre-elimination, the incremental net cost was $20 billion (non-USB and MRF) to $48 billion. These had an incremental cost per QALY of $657,000 to $3.1 million. A more efficient but somewhat less effective single-lifetime test strategy reached as low as $80,000 per QALY.
Substantial gains can be made in TB control in coming years by scaling-up current testing and treatment in non-USB and those with medical risks.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0214532</identifier><identifier>PMID: 30964878</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Age ; Algorithms ; Antitubercular agents ; Antitubercular Agents - therapeutic use ; Biology and Life Sciences ; Calibration ; California - epidemiology ; Computer Simulation ; Consortia ; Cost-Benefit Analysis ; Costs ; Critical care ; Data buses ; Diagnosis ; Disease control ; Disease eradication ; Disease Eradication - methods ; Disease prevention ; Epidemics ; Epidemiology ; Fees & charges ; Gold ; Health ; Health care policy ; Health risks ; Hepatitis ; Historical metallurgy ; HIV ; Human immunodeficiency virus ; Humans ; Incidence ; Infections ; Inflammatory bowel disease ; Isoniazid ; Isoniazid - pharmacology ; Laboratories ; Mass Screening - economics ; Medical research ; Medicine ; Medicine and Health Sciences ; People and places ; Physical sciences ; Population ; Prevention ; Public health ; Quality-Adjusted Life Years ; Research and analysis methods ; Rheumatoid arthritis ; Rifampin - analogs & derivatives ; Rifampin - pharmacology ; Rifapentine ; Risk analysis ; Risk Factors ; Scaling ; Social Sciences ; Stochastic models ; Stochastic Processes ; Stochasticity ; Strategy ; Transplants & implants ; Tuberculin Test - economics ; Tuberculosis ; Tuberculosis - epidemiology ; Tuberculosis - prevention & control ; Tumor necrosis factor-TNF ; USB (Universal serial bus) ; World Health Organization</subject><ispartof>PloS one, 2019-04, Vol.14 (4), p.e0214532-e0214532</ispartof><rights>COPYRIGHT 2019 Public Library of Science</rights><rights>This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication: https://creativecommons.org/publicdomain/zero/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-91db62a94cbc219d58b23cf8df5833f159500fb27426c815a4da03c0b4df688e3</citedby><cites>FETCH-LOGICAL-c692t-91db62a94cbc219d58b23cf8df5833f159500fb27426c815a4da03c0b4df688e3</cites><orcidid>0000-0002-2324-5858</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6456190/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6456190/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30964878$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Wilkinson, Katalin Andrea</contributor><creatorcontrib>Goodell, Alex J</creatorcontrib><creatorcontrib>Shete, Priya B</creatorcontrib><creatorcontrib>Vreman, Rick</creatorcontrib><creatorcontrib>McCabe, Devon</creatorcontrib><creatorcontrib>Porco, Travis C</creatorcontrib><creatorcontrib>Barry, Pennan M</creatorcontrib><creatorcontrib>Flood, Jennifer</creatorcontrib><creatorcontrib>Marks, Suzanne M</creatorcontrib><creatorcontrib>Hill, Andrew</creatorcontrib><creatorcontrib>Cattamanchi, Adithya</creatorcontrib><creatorcontrib>Kahn, James G</creatorcontrib><title>Outlook for tuberculosis elimination in California: An individual-based stochastic model</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>As part of the End TB Strategy, the World Health Organization calls for low-tuberculosis (TB) incidence settings to achieve pre-elimination (<10 cases per million) and elimination (<1 case per million) by 2035 and 2050, respectively. These targets require testing and treatment for latent tuberculosis infection (LTBI).
To estimate the ability and costs of testing and treatment for LTBI to reach pre-elimination and elimination targets in California.
We created an individual-based epidemic model of TB, calibrated to historical cases. We evaluated the effects of increased testing (QuantiFERON-TB Gold) and treatment (three months of isoniazid and rifapentine). We analyzed four test and treat targeting strategies: (1) individuals with medical risk factors (MRF), (2) non-USB, (3) both non-USB and MRF, and (4) all Californians. For each strategy, we estimated the effects of increasing test and treat by a factor of 2, 4, or 10 from the base case. We estimated the number of TB cases occurring and prevented, and net and incremental costs from 2017 to 2065 in 2015 U.S. dollars. Efficacy, costs, adverse events, and treatment dropout were estimated from published data. We estimated the cost per case averted and per quality-adjusted life year (QALY) gained.
In the base case, 106,000 TB cases are predicted to 2065. Pre-elimination was achieved by 2065 in three scenarios: a 10-fold increase in the non-USB and persons with MRF (by 2052), and 4- or 10-fold increase in all Californians (by 2058 and 2035, respectively). TB elimination was not achieved by any intervention scenario. The most aggressive strategy, 10-fold in all Californians, achieved a case rate of 8 (95% UI 4-16) per million by 2050. Of scenarios that reached pre-elimination, the incremental net cost was $20 billion (non-USB and MRF) to $48 billion. These had an incremental cost per QALY of $657,000 to $3.1 million. A more efficient but somewhat less effective single-lifetime test strategy reached as low as $80,000 per QALY.
Substantial gains can be made in TB control in coming years by scaling-up current testing and treatment in non-USB and those with medical risks.</description><subject>Age</subject><subject>Algorithms</subject><subject>Antitubercular agents</subject><subject>Antitubercular Agents - therapeutic use</subject><subject>Biology and Life Sciences</subject><subject>Calibration</subject><subject>California - epidemiology</subject><subject>Computer Simulation</subject><subject>Consortia</subject><subject>Cost-Benefit Analysis</subject><subject>Costs</subject><subject>Critical care</subject><subject>Data buses</subject><subject>Diagnosis</subject><subject>Disease control</subject><subject>Disease eradication</subject><subject>Disease Eradication - methods</subject><subject>Disease prevention</subject><subject>Epidemics</subject><subject>Epidemiology</subject><subject>Fees & charges</subject><subject>Gold</subject><subject>Health</subject><subject>Health care policy</subject><subject>Health risks</subject><subject>Hepatitis</subject><subject>Historical metallurgy</subject><subject>HIV</subject><subject>Human immunodeficiency virus</subject><subject>Humans</subject><subject>Incidence</subject><subject>Infections</subject><subject>Inflammatory bowel disease</subject><subject>Isoniazid</subject><subject>Isoniazid - pharmacology</subject><subject>Laboratories</subject><subject>Mass Screening - economics</subject><subject>Medical research</subject><subject>Medicine</subject><subject>Medicine and Health Sciences</subject><subject>People and places</subject><subject>Physical sciences</subject><subject>Population</subject><subject>Prevention</subject><subject>Public health</subject><subject>Quality-Adjusted Life Years</subject><subject>Research and analysis methods</subject><subject>Rheumatoid arthritis</subject><subject>Rifampin - analogs & derivatives</subject><subject>Rifampin - pharmacology</subject><subject>Rifapentine</subject><subject>Risk analysis</subject><subject>Risk Factors</subject><subject>Scaling</subject><subject>Social Sciences</subject><subject>Stochastic models</subject><subject>Stochastic Processes</subject><subject>Stochasticity</subject><subject>Strategy</subject><subject>Transplants & implants</subject><subject>Tuberculin Test - economics</subject><subject>Tuberculosis</subject><subject>Tuberculosis - epidemiology</subject><subject>Tuberculosis - prevention & control</subject><subject>Tumor necrosis factor-TNF</subject><subject>USB (Universal serial bus)</subject><subject>World Health Organization</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqNk9-L1DAQx4so3nn6H4gWBNGHXfOraeKDsCz-WDhY8Be-hWmS7mZNm7VpD_3vzd72jq3cg-QhYfKZ70wmM1n2FKM5piV-swtD14Kf70Nr54hgVlByLzvHkpIZJ4jePzmfZY9i3CFUUMH5w-yMIsmZKMV59mM99D6En3kdurwfKtvpwYfoYm69a1wLvQtt7tp8Cd4lpnXwNl8cLMZdOTOAn1UQrcljH_QWYu903gRj_ePsQQ0-2ifjfpF9-_D-6_LT7HL9cbVcXM40l6SfSWwqTkAyXWmCpSlERaiuhakLQWmNC1kgVFekZIRrgQtgBhDVqGKm5kJYepE9P-ruU9pqLEpUhCCBCBWEJWJ1JEyAndp3roHujwrg1LUhdBsFXcrbWwWskByVhrNaMmorAVBIqEpNBSWUy6T1bow2VI012rZ9B34iOr1p3VZtwpXirOBYoiTwahTowq_Bxl41LmrrPbQ2DNd5l5gTjHFCX_yD3v26kdpAeoBr65Di6oOoWhQCi9QrnCRqfgeVlrGN06mDapfsE4fXE4fE9PZ3v4EhRrX68vn_2fX3KfvyhN1a8P02Bj8c2ixOQXYEdRdi7Gx9W2SM1GEAbqqhDgOgxgFIbs9OP-jW6abj6V8o6AAB</recordid><startdate>20190409</startdate><enddate>20190409</enddate><creator>Goodell, Alex J</creator><creator>Shete, Priya B</creator><creator>Vreman, Rick</creator><creator>McCabe, Devon</creator><creator>Porco, Travis C</creator><creator>Barry, Pennan M</creator><creator>Flood, Jennifer</creator><creator>Marks, Suzanne M</creator><creator>Hill, Andrew</creator><creator>Cattamanchi, Adithya</creator><creator>Kahn, James G</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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-2324-5858</orcidid></search><sort><creationdate>20190409</creationdate><title>Outlook for tuberculosis elimination in California: An individual-based stochastic model</title><author>Goodell, Alex J ; Shete, Priya B ; Vreman, Rick ; McCabe, Devon ; Porco, Travis C ; Barry, Pennan M ; Flood, Jennifer ; Marks, Suzanne M ; Hill, Andrew ; Cattamanchi, Adithya ; Kahn, James G</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-91db62a94cbc219d58b23cf8df5833f159500fb27426c815a4da03c0b4df688e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Age</topic><topic>Algorithms</topic><topic>Antitubercular agents</topic><topic>Antitubercular Agents - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Goodell, Alex J</au><au>Shete, Priya B</au><au>Vreman, Rick</au><au>McCabe, Devon</au><au>Porco, Travis C</au><au>Barry, Pennan M</au><au>Flood, Jennifer</au><au>Marks, Suzanne M</au><au>Hill, Andrew</au><au>Cattamanchi, Adithya</au><au>Kahn, James G</au><au>Wilkinson, Katalin Andrea</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Outlook for tuberculosis elimination in California: An individual-based stochastic model</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2019-04-09</date><risdate>2019</risdate><volume>14</volume><issue>4</issue><spage>e0214532</spage><epage>e0214532</epage><pages>e0214532-e0214532</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>As part of the End TB Strategy, the World Health Organization calls for low-tuberculosis (TB) incidence settings to achieve pre-elimination (<10 cases per million) and elimination (<1 case per million) by 2035 and 2050, respectively. These targets require testing and treatment for latent tuberculosis infection (LTBI).
To estimate the ability and costs of testing and treatment for LTBI to reach pre-elimination and elimination targets in California.
We created an individual-based epidemic model of TB, calibrated to historical cases. We evaluated the effects of increased testing (QuantiFERON-TB Gold) and treatment (three months of isoniazid and rifapentine). We analyzed four test and treat targeting strategies: (1) individuals with medical risk factors (MRF), (2) non-USB, (3) both non-USB and MRF, and (4) all Californians. For each strategy, we estimated the effects of increasing test and treat by a factor of 2, 4, or 10 from the base case. We estimated the number of TB cases occurring and prevented, and net and incremental costs from 2017 to 2065 in 2015 U.S. dollars. Efficacy, costs, adverse events, and treatment dropout were estimated from published data. We estimated the cost per case averted and per quality-adjusted life year (QALY) gained.
In the base case, 106,000 TB cases are predicted to 2065. Pre-elimination was achieved by 2065 in three scenarios: a 10-fold increase in the non-USB and persons with MRF (by 2052), and 4- or 10-fold increase in all Californians (by 2058 and 2035, respectively). TB elimination was not achieved by any intervention scenario. The most aggressive strategy, 10-fold in all Californians, achieved a case rate of 8 (95% UI 4-16) per million by 2050. Of scenarios that reached pre-elimination, the incremental net cost was $20 billion (non-USB and MRF) to $48 billion. These had an incremental cost per QALY of $657,000 to $3.1 million. A more efficient but somewhat less effective single-lifetime test strategy reached as low as $80,000 per QALY.
Substantial gains can be made in TB control in coming years by scaling-up current testing and treatment in non-USB and those with medical risks.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>30964878</pmid><doi>10.1371/journal.pone.0214532</doi><tpages>e0214532</tpages><orcidid>https://orcid.org/0000-0002-2324-5858</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2019-04, Vol.14 (4), p.e0214532-e0214532 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2208023824 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Age Algorithms Antitubercular agents Antitubercular Agents - therapeutic use Biology and Life Sciences Calibration California - epidemiology Computer Simulation Consortia Cost-Benefit Analysis Costs Critical care Data buses Diagnosis Disease control Disease eradication Disease Eradication - methods Disease prevention Epidemics Epidemiology Fees & charges Gold Health Health care policy Health risks Hepatitis Historical metallurgy HIV Human immunodeficiency virus Humans Incidence Infections Inflammatory bowel disease Isoniazid Isoniazid - pharmacology Laboratories Mass Screening - economics Medical research Medicine Medicine and Health Sciences People and places Physical sciences Population Prevention Public health Quality-Adjusted Life Years Research and analysis methods Rheumatoid arthritis Rifampin - analogs & derivatives Rifampin - pharmacology Rifapentine Risk analysis Risk Factors Scaling Social Sciences Stochastic models Stochastic Processes Stochasticity Strategy Transplants & implants Tuberculin Test - economics Tuberculosis Tuberculosis - epidemiology Tuberculosis - prevention & control Tumor necrosis factor-TNF USB (Universal serial bus) World Health Organization |
| title | Outlook for tuberculosis elimination in California: An individual-based stochastic model |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-31T04%3A15%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Outlook%20for%20tuberculosis%20elimination%20in%20California:%20An%20individual-based%20stochastic%20model&rft.jtitle=PloS%20one&rft.au=Goodell,%20Alex%20J&rft.date=2019-04-09&rft.volume=14&rft.issue=4&rft.spage=e0214532&rft.epage=e0214532&rft.pages=e0214532-e0214532&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0214532&rft_dat=%3Cgale_plos_%3EA581813762%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2208023824&rft_id=info:pmid/30964878&rft_galeid=A581813762&rft_doaj_id=oai_doaj_org_article_a459607d64f943eb8aa59ab7c3832369&rfr_iscdi=true |