The impact of monitoring HIV patients prior to treatment in resource-poor settings : insights from mathematical modelling

The roll-out of antiretroviral treatment (ART) in developing countries concentrates on finding patients currently in need, but over time many HIV-infected individuals will be identified who will require treatment in the future. We investigated the potential influence of alternative patient managemen...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:PLoS medicine 2008-03, Vol.5 (3), p.403-412
Hauptverfasser: HALLETT, T.B, GREGSON, S, GARNETT, G.P
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 412
container_issue 3
container_start_page 403
container_title PLoS medicine
container_volume 5
creator HALLETT, T.B
GREGSON, S
GARNETT, G.P
description The roll-out of antiretroviral treatment (ART) in developing countries concentrates on finding patients currently in need, but over time many HIV-infected individuals will be identified who will require treatment in the future. We investigated the potential influence of alternative patient management and ART initiation strategies on the impact of ART programmes in sub-Saharan Africa. We developed a stochastic mathematical model representing disease progression, diagnosis, clinical monitoring, and survival in a cohort of 1,000 hypothetical HIV-infected individuals in Africa. If individuals primarily enter ART programmes when symptomatic, the model predicts that only 25% will start treatment and, on average, 6 life-years will be saved per person treated. If individuals are recruited to programmes while still healthy and are frequently monitored, and CD4(+) cell counts are used to help decide when to initiate ART, three times as many are expected to be treated, and average life-years saved among those treated increases to 15. The impact of programmes can be improved further by performing a second CD4(+) cell count when the initial value is close to the threshold for starting treatment, maintaining high patient follow-up rates, and prioritising monitoring the oldest (> or = 35 y) and most immune-suppressed patients (CD4(+) cell count < or = 350). Initiating ART at higher CD4(+) cell counts than WHO recommends leads to more life-years saved, but disproportionately more years spent on ART. The overall impact of ART programmes will be limited if rates of diagnosis are low and individuals enter care too late. Frequently monitoring individuals at all stages of HIV infection and using CD4 cell count information to determine when to start treatment can maximise the impact of ART.
doi_str_mv 10.1371/journal.pmed.0050053
format Article
fullrecord <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_1288084756</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A202254580</galeid><doaj_id>oai_doaj_org_article_5ab9edce2b854fa5ba7001164f3345c6</doaj_id><sourcerecordid>A202254580</sourcerecordid><originalsourceid>FETCH-LOGICAL-c792t-ce712734676cad0d86aa20b979f793b865f521b94322d3ee32eb6709e2f967ea3</originalsourceid><addsrcrecordid>eNqVk11r1EAUhoMotlb_gWhALHix62Q-MokXQilqF4oFrb0dJpOT7JRkZp2ZFfvvPeumtSt7oUlIwjnPe76Gk2XPCzIvmCzeXvt1cHqYr0Zo54QIfNiD7LAQvJ4VpSwf3v5TKQ-yJzFeE0JrUpPH2UFRMVaSkh9mN5dLyO240iblvstH72zywbo-P1tc5SudLLgU81WwPuTJ5ymATiPacuvyABGLMDBbefRGSAmFMX-Hvmj7Jeq64Md81GkJ-LJGD5ihhWFA7mn2qNNDhGfT9yj79vHD5enZ7Pzi0-L05HxmZE3TzIDEDhjHjoxuSVuVWlPS1LLuZM2aqhSdoEVTc0ZpywAYhaaUpAba1aUEzY6yl9u4q8FHNU0tqoJWFam4FCUSiy3Ren2tsNVRhxvltVW_DT70SgesfgAldFNDa4A2leCdFo2WhBRFyTvGuDCbWO-nbOtm3JAuBT3sBN31OLtUvf-hKC2FFDUGOJ4CBP99DTGp0UaDI9MO_DoqSTjnDK-j7NVf4P7eJqrXWL51ncesZhNSnVBCqeCiIkjN9lA9OMASvYPOonmHn-_h8W5htGav4M2OAJkEP1Ov1zGqxdcv_8F-_nf24mqXPb7HLkEPaRn9sE7Wu7gL8i1ogo8xQHd3fAVRm927nbTa7J6adg9lL-4f_R_RtGwIvJ4AHXEVuqCdsfGOo0RQXnDKfgHBfDWe</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1288084756</pqid></control><display><type>article</type><title>The impact of monitoring HIV patients prior to treatment in resource-poor settings : insights from mathematical modelling</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Public Library of Science (PLoS) Journals Open Access</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><creator>HALLETT, T.B ; GREGSON, S ; GARNETT, G.P</creator><contributor>Salomon, Joshua A</contributor><creatorcontrib>HALLETT, T.B ; GREGSON, S ; GARNETT, G.P ; Salomon, Joshua A</creatorcontrib><description>The roll-out of antiretroviral treatment (ART) in developing countries concentrates on finding patients currently in need, but over time many HIV-infected individuals will be identified who will require treatment in the future. We investigated the potential influence of alternative patient management and ART initiation strategies on the impact of ART programmes in sub-Saharan Africa. We developed a stochastic mathematical model representing disease progression, diagnosis, clinical monitoring, and survival in a cohort of 1,000 hypothetical HIV-infected individuals in Africa. If individuals primarily enter ART programmes when symptomatic, the model predicts that only 25% will start treatment and, on average, 6 life-years will be saved per person treated. If individuals are recruited to programmes while still healthy and are frequently monitored, and CD4(+) cell counts are used to help decide when to initiate ART, three times as many are expected to be treated, and average life-years saved among those treated increases to 15. The impact of programmes can be improved further by performing a second CD4(+) cell count when the initial value is close to the threshold for starting treatment, maintaining high patient follow-up rates, and prioritising monitoring the oldest (&gt; or = 35 y) and most immune-suppressed patients (CD4(+) cell count &lt; or = 350). Initiating ART at higher CD4(+) cell counts than WHO recommends leads to more life-years saved, but disproportionately more years spent on ART. The overall impact of ART programmes will be limited if rates of diagnosis are low and individuals enter care too late. Frequently monitoring individuals at all stages of HIV infection and using CD4 cell count information to determine when to start treatment can maximise the impact of ART.</description><identifier>ISSN: 1549-1277</identifier><identifier>ISSN: 1549-1676</identifier><identifier>EISSN: 1549-1676</identifier><identifier>DOI: 10.1371/journal.pmed.0050053</identifier><identifier>PMID: 18336064</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acquired immune deficiency syndrome ; Adult ; AIDS ; Anti-Retroviral Agents - administration &amp; dosage ; Bacterial infections ; Biological and medical sciences ; CD4 Lymphocyte Count ; Developing countries ; Disease ; Disease Progression ; Evidence-Based Healthcare ; Global health ; Health care ; Health Policy ; HIV ; HIV Infection/AIDS ; HIV Infections - drug therapy ; Human immunodeficiency virus ; Humans ; Immune system ; Infections ; Infectious Diseases ; International organizations ; LDCs ; Mathematical models ; Medical sciences ; Medicine in Developing Countries ; Miscellaneous ; Models, Theoretical ; Patients ; Prevention and actions ; Public Health and Epidemiology ; Public health. Hygiene ; Public health. Hygiene-occupational medicine ; Resource Allocation ; Stochastic Processes</subject><ispartof>PLoS medicine, 2008-03, Vol.5 (3), p.403-412</ispartof><rights>COPYRIGHT 2008 Public Library of Science</rights><rights>2008 Hallett et al. 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: Hallett TB, Gregson S, Dube S, Garnett GP (2008) The Impact of Monitoring HIV Patients Prior to Treatment in Resource-Poor Settings: Insights from Mathematical Modelling. PLoS Med 5(3): e53. doi:10.1371/journal.pmed.0050053</rights><rights>2008 Hallett et al. 2008</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c792t-ce712734676cad0d86aa20b979f793b865f521b94322d3ee32eb6709e2f967ea3</citedby><cites>FETCH-LOGICAL-c792t-ce712734676cad0d86aa20b979f793b865f521b94322d3ee32eb6709e2f967ea3</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/PMC2265759/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2265759/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2095,2914,23846,27903,27904,53769,53771,79346,79347</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=20524142$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18336064$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Salomon, Joshua A</contributor><creatorcontrib>HALLETT, T.B</creatorcontrib><creatorcontrib>GREGSON, S</creatorcontrib><creatorcontrib>GARNETT, G.P</creatorcontrib><title>The impact of monitoring HIV patients prior to treatment in resource-poor settings : insights from mathematical modelling</title><title>PLoS medicine</title><addtitle>PLoS Med</addtitle><description>The roll-out of antiretroviral treatment (ART) in developing countries concentrates on finding patients currently in need, but over time many HIV-infected individuals will be identified who will require treatment in the future. We investigated the potential influence of alternative patient management and ART initiation strategies on the impact of ART programmes in sub-Saharan Africa. We developed a stochastic mathematical model representing disease progression, diagnosis, clinical monitoring, and survival in a cohort of 1,000 hypothetical HIV-infected individuals in Africa. If individuals primarily enter ART programmes when symptomatic, the model predicts that only 25% will start treatment and, on average, 6 life-years will be saved per person treated. If individuals are recruited to programmes while still healthy and are frequently monitored, and CD4(+) cell counts are used to help decide when to initiate ART, three times as many are expected to be treated, and average life-years saved among those treated increases to 15. The impact of programmes can be improved further by performing a second CD4(+) cell count when the initial value is close to the threshold for starting treatment, maintaining high patient follow-up rates, and prioritising monitoring the oldest (&gt; or = 35 y) and most immune-suppressed patients (CD4(+) cell count &lt; or = 350). Initiating ART at higher CD4(+) cell counts than WHO recommends leads to more life-years saved, but disproportionately more years spent on ART. The overall impact of ART programmes will be limited if rates of diagnosis are low and individuals enter care too late. Frequently monitoring individuals at all stages of HIV infection and using CD4 cell count information to determine when to start treatment can maximise the impact of ART.</description><subject>Acquired immune deficiency syndrome</subject><subject>Adult</subject><subject>AIDS</subject><subject>Anti-Retroviral Agents - administration &amp; dosage</subject><subject>Bacterial infections</subject><subject>Biological and medical sciences</subject><subject>CD4 Lymphocyte Count</subject><subject>Developing countries</subject><subject>Disease</subject><subject>Disease Progression</subject><subject>Evidence-Based Healthcare</subject><subject>Global health</subject><subject>Health care</subject><subject>Health Policy</subject><subject>HIV</subject><subject>HIV Infection/AIDS</subject><subject>HIV Infections - drug therapy</subject><subject>Human immunodeficiency virus</subject><subject>Humans</subject><subject>Immune system</subject><subject>Infections</subject><subject>Infectious Diseases</subject><subject>International organizations</subject><subject>LDCs</subject><subject>Mathematical models</subject><subject>Medical sciences</subject><subject>Medicine in Developing Countries</subject><subject>Miscellaneous</subject><subject>Models, Theoretical</subject><subject>Patients</subject><subject>Prevention and actions</subject><subject>Public Health and Epidemiology</subject><subject>Public health. Hygiene</subject><subject>Public health. Hygiene-occupational medicine</subject><subject>Resource Allocation</subject><subject>Stochastic Processes</subject><issn>1549-1277</issn><issn>1549-1676</issn><issn>1549-1676</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>DOA</sourceid><recordid>eNqVk11r1EAUhoMotlb_gWhALHix62Q-MokXQilqF4oFrb0dJpOT7JRkZp2ZFfvvPeumtSt7oUlIwjnPe76Gk2XPCzIvmCzeXvt1cHqYr0Zo54QIfNiD7LAQvJ4VpSwf3v5TKQ-yJzFeE0JrUpPH2UFRMVaSkh9mN5dLyO240iblvstH72zywbo-P1tc5SudLLgU81WwPuTJ5ymATiPacuvyABGLMDBbefRGSAmFMX-Hvmj7Jeq64Md81GkJ-LJGD5ihhWFA7mn2qNNDhGfT9yj79vHD5enZ7Pzi0-L05HxmZE3TzIDEDhjHjoxuSVuVWlPS1LLuZM2aqhSdoEVTc0ZpywAYhaaUpAba1aUEzY6yl9u4q8FHNU0tqoJWFam4FCUSiy3Ren2tsNVRhxvltVW_DT70SgesfgAldFNDa4A2leCdFo2WhBRFyTvGuDCbWO-nbOtm3JAuBT3sBN31OLtUvf-hKC2FFDUGOJ4CBP99DTGp0UaDI9MO_DoqSTjnDK-j7NVf4P7eJqrXWL51ncesZhNSnVBCqeCiIkjN9lA9OMASvYPOonmHn-_h8W5htGav4M2OAJkEP1Ov1zGqxdcv_8F-_nf24mqXPb7HLkEPaRn9sE7Wu7gL8i1ogo8xQHd3fAVRm927nbTa7J6adg9lL-4f_R_RtGwIvJ4AHXEVuqCdsfGOo0RQXnDKfgHBfDWe</recordid><startdate>20080301</startdate><enddate>20080301</enddate><creator>HALLETT, T.B</creator><creator>GREGSON, S</creator><creator>GARNETT, G.P</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>IQODW</scope><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>ISN</scope><scope>ISR</scope><scope>3V.</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><scope>CZK</scope></search><sort><creationdate>20080301</creationdate><title>The impact of monitoring HIV patients prior to treatment in resource-poor settings : insights from mathematical modelling</title><author>HALLETT, T.B ; GREGSON, S ; GARNETT, G.P</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c792t-ce712734676cad0d86aa20b979f793b865f521b94322d3ee32eb6709e2f967ea3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Acquired immune deficiency syndrome</topic><topic>Adult</topic><topic>AIDS</topic><topic>Anti-Retroviral Agents - administration &amp; dosage</topic><topic>Bacterial infections</topic><topic>Biological and medical sciences</topic><topic>CD4 Lymphocyte Count</topic><topic>Developing countries</topic><topic>Disease</topic><topic>Disease Progression</topic><topic>Evidence-Based Healthcare</topic><topic>Global health</topic><topic>Health care</topic><topic>Health Policy</topic><topic>HIV</topic><topic>HIV Infection/AIDS</topic><topic>HIV Infections - drug therapy</topic><topic>Human immunodeficiency virus</topic><topic>Humans</topic><topic>Immune system</topic><topic>Infections</topic><topic>Infectious Diseases</topic><topic>International organizations</topic><topic>LDCs</topic><topic>Mathematical models</topic><topic>Medical sciences</topic><topic>Medicine in Developing Countries</topic><topic>Miscellaneous</topic><topic>Models, Theoretical</topic><topic>Patients</topic><topic>Prevention and actions</topic><topic>Public Health and Epidemiology</topic><topic>Public health. Hygiene</topic><topic>Public health. Hygiene-occupational medicine</topic><topic>Resource Allocation</topic><topic>Stochastic Processes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>HALLETT, T.B</creatorcontrib><creatorcontrib>GREGSON, S</creatorcontrib><creatorcontrib>GARNETT, G.P</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Canada</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</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>HALLETT, T.B</au><au>GREGSON, S</au><au>GARNETT, G.P</au><au>Salomon, Joshua A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The impact of monitoring HIV patients prior to treatment in resource-poor settings : insights from mathematical modelling</atitle><jtitle>PLoS medicine</jtitle><addtitle>PLoS Med</addtitle><date>2008-03-01</date><risdate>2008</risdate><volume>5</volume><issue>3</issue><spage>403</spage><epage>412</epage><pages>403-412</pages><issn>1549-1277</issn><issn>1549-1676</issn><eissn>1549-1676</eissn><abstract>The roll-out of antiretroviral treatment (ART) in developing countries concentrates on finding patients currently in need, but over time many HIV-infected individuals will be identified who will require treatment in the future. We investigated the potential influence of alternative patient management and ART initiation strategies on the impact of ART programmes in sub-Saharan Africa. We developed a stochastic mathematical model representing disease progression, diagnosis, clinical monitoring, and survival in a cohort of 1,000 hypothetical HIV-infected individuals in Africa. If individuals primarily enter ART programmes when symptomatic, the model predicts that only 25% will start treatment and, on average, 6 life-years will be saved per person treated. If individuals are recruited to programmes while still healthy and are frequently monitored, and CD4(+) cell counts are used to help decide when to initiate ART, three times as many are expected to be treated, and average life-years saved among those treated increases to 15. The impact of programmes can be improved further by performing a second CD4(+) cell count when the initial value is close to the threshold for starting treatment, maintaining high patient follow-up rates, and prioritising monitoring the oldest (&gt; or = 35 y) and most immune-suppressed patients (CD4(+) cell count &lt; or = 350). Initiating ART at higher CD4(+) cell counts than WHO recommends leads to more life-years saved, but disproportionately more years spent on ART. The overall impact of ART programmes will be limited if rates of diagnosis are low and individuals enter care too late. Frequently monitoring individuals at all stages of HIV infection and using CD4 cell count information to determine when to start treatment can maximise the impact of ART.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>18336064</pmid><doi>10.1371/journal.pmed.0050053</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1549-1277
ispartof PLoS medicine, 2008-03, Vol.5 (3), p.403-412
issn 1549-1277
1549-1676
1549-1676
language eng
recordid cdi_plos_journals_1288084756
source MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central
subjects Acquired immune deficiency syndrome
Adult
AIDS
Anti-Retroviral Agents - administration & dosage
Bacterial infections
Biological and medical sciences
CD4 Lymphocyte Count
Developing countries
Disease
Disease Progression
Evidence-Based Healthcare
Global health
Health care
Health Policy
HIV
HIV Infection/AIDS
HIV Infections - drug therapy
Human immunodeficiency virus
Humans
Immune system
Infections
Infectious Diseases
International organizations
LDCs
Mathematical models
Medical sciences
Medicine in Developing Countries
Miscellaneous
Models, Theoretical
Patients
Prevention and actions
Public Health and Epidemiology
Public health. Hygiene
Public health. Hygiene-occupational medicine
Resource Allocation
Stochastic Processes
title The impact of monitoring HIV patients prior to treatment in resource-poor settings : insights from mathematical modelling
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-26T15%3A13%3A11IST&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=The%20impact%20of%20monitoring%20HIV%20patients%20prior%20to%20treatment%20in%20resource-poor%20settings%20:%20insights%20from%20mathematical%20modelling&rft.jtitle=PLoS%20medicine&rft.au=HALLETT,%20T.B&rft.date=2008-03-01&rft.volume=5&rft.issue=3&rft.spage=403&rft.epage=412&rft.pages=403-412&rft.issn=1549-1277&rft.eissn=1549-1676&rft_id=info:doi/10.1371/journal.pmed.0050053&rft_dat=%3Cgale_plos_%3EA202254580%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=1288084756&rft_id=info:pmid/18336064&rft_galeid=A202254580&rft_doaj_id=oai_doaj_org_article_5ab9edce2b854fa5ba7001164f3345c6&rfr_iscdi=true