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Estimating the capacity for ART provision in Tanzania with the use of data on staff productivity and patient losses

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dc.contributor.author Hanson, S.
dc.contributor.author Thorson, A.
dc.contributor.author Rosling, H.
dc.contributor.author Örtendahl, C.
dc.contributor.author Hanson, C.
dc.contributor.author Killewo, J.
dc.contributor.author Ekström, A. M.
dc.date.accessioned 2012-03-01T11:49:24Z
dc.date.available 2012-03-01T11:49:24Z
dc.date.issued 2009
dc.identifier.issn 1932-6203
dc.identifier.doi http://dx.doi.org/10.1371/journal.pone.0005294
dc.identifier.other ITG-I5B
dc.identifier.other INTER
dc.identifier.other U-ADMIN
dc.identifier.other JIF
dc.identifier.other DOI
dc.identifier.other UPD43
dc.identifier.other FTA
dc.identifier.uri http://hdl.handle.net/10390/6855
dc.description.abstract BACKGROUND: International targets for access to antiretroviral therapy (ART) have over-estimated the capacity of health systems in low-income countries in Sub-Saharan Africa. The WHO target for number on treatment by end 2005 for Tanzania was 10 times higher than actually achieved. The target of the national Care and Treatment Plan (CTP) was also not reached. We aimed at estimating the capacity for ART provision and created five scenarios for ART production given existing resource limitations. METHODS: A situation analysis including scrutiny of staff factors, such as available data on staff and patient factors including access to ART and patient losses, made us conclude that the lack of clinical staff is the main limiting factor for ART scale-up, assuming that sufficient drugs and supplies are provided by donors. We created a simple formula to estimate the number of patients on ART based on availability and productivity of clinical staff, time needed to initiate vs maintain a patient on ART and patient losses using five different scenarios with varying levels of these parameters. FINDINGS: Our scenario assuming medium productivity (40% higher than that observed in 2002) and medium loss of patients (20% in addition to 15% first-year mortality) coincides with the actual reported number of patients initiated on ART up to 2008, but is considerably below the national CTP target of 90% coverage for 2009, corresponding to 420,000 on ART and 710,000 life-years saved (LY's). Our analysis suggests that a coverage of 40% or 175,000 on treatment and 350,000 LY's saved is more achievable. CONCLUSION: A comparison of our scenario estimations and actual output 2006-2008 indicates that a simple user-friendly dynamic model can estimate the capacity for ART scale-up in resource-poor settings based on identification of a limiting staff factor and information on availability of this staff and patient losses. Thus, it is possible to set more achievable targets. en
dc.language English en
dc.subject Viral diseases en
dc.subject HIV en
dc.subject AIDS en
dc.subject National programs en
dc.subject HAART en
dc.subject Antiretrovirals en
dc.subject Health systems en
dc.subject Capacity en
dc.subject Targets en
dc.subject Accessibility en
dc.subject Health workers en
dc.subject Staff shortage en
dc.subject Availability en
dc.subject Productivity en
dc.subject Performance en
dc.subject Compliance en
dc.subject Health facilities en
dc.subject CD4-positive-T-lymphocytes en
dc.subject Monitoring en
dc.subject Mortality rates en
dc.subject Mathematical modeling en
dc.subject Tanzania en
dc.subject Africa, East en
dc.title Estimating the capacity for ART provision in Tanzania with the use of data on staff productivity and patient losses en
dc.type Article-E en
dc.citation.issue 4 en
dc.citation.jtitle PLoS ONE en
dc.citation.volume 4 en
dc.citation.pages e5294 en
dc.identifier.pmid http://www.ncbi.nlm.nih.gov/pubmed/19381270
dc.citation.jabbreviation PLoS ONE en


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