Lessons from the 2012 National HIV Household Survey to improve mathematical modelling for HIV policy

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dc.date.accessioned 2015-12-21 en
dc.date.accessioned 2022-08-17T16:09:49Z
dc.date.available 2022-08-17T16:09:49Z
dc.date.issued 2016-01-12 en
dc.identifier.uri http://hdl.handle.net/20.500.11910/1690
dc.description.abstract Since the start of the HIV epidemic in sub-Saharan Africa, mathematical models fitted to surveillance data have been heavily relied on for estimating and projecting the future course of HIV epidemics. The establishment of HIV surveillance at antenatal clinics in the late 1980s created routinely available data for systematically monitoring HIV epidemics across Africa, but mathematical models are needed to relate these data to the outcomes that matter most for responding to HIV epidemics: HIV in the general population, new HIV infections, and HIV deaths. en
dc.format.medium Intranet en
dc.subject HIV/AIDS en
dc.subject POLICY FORMULATION en
dc.subject SUB-SAHARAN AFRICA en
dc.subject DATA ANALYSIS en
dc.title Lessons from the 2012 National HIV Household Survey to improve mathematical modelling for HIV policy en
dc.type Journal Article en
dc.description.version N en
dc.ProjectNumber N/A en
dc.Volume November en
dc.BudgetYear 2015/16 en
dc.ResearchGroup HIV/AIDS, STIs and TB en
dc.SourceTitle Sacema Quarterly en
dc.ArchiveNumber 8934 en
dc.PageNumber Online en
dc.outputnumber 7709 en
dc.bibliographictitle Eaton, J.W., Johnson, L.F. & Rehle, T. (2015) Lessons from the 2012 National HIV Household Survey to improve mathematical modelling for HIV policy. Sacema Quarterly. November:Online. http://hdl.handle.net/20.500.11910/1690 en
dc.publicationyear 2015 en
dc.contributor.author1 Eaton, J.W. en
dc.contributor.author2 Johnson, L.F. en
dc.contributor.author3 Rehle, T. en


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