title: Assessment of epidemic projections using recent HIV survey data in South Africa: a validation analysis of ten mathematical models of HIV epidemiology in the antiretroviral therapy era.
abstract: BACKGROUND
  Mathematical models are widely used to simulate the effects of interventions to control HIV and to project future epidemiological trends and resource needs. We aimed to validate past model projections against data from a large household survey done in South Africa in 2012.
  
  
  METHODS
  We compared ten model projections of HIV prevalence, HIV incidence, and antiretroviral therapy (ART) coverage for South Africa with estimates from national household survey data from 2012. Model projections for 2012 were made before the publication of the 2012 household survey. We compared adult (age 15-49 years) HIV prevalence in 2012, the change in prevalence between 2008 and 2012, and prevalence, incidence, and ART coverage by sex and by age groups between model projections and the 2012 household survey.
  
  
  RESULTS
  All models projected lower prevalence estimates for 2012 than the survey estimate (18·8%), with eight models' central projections being below the survey 95% CI (17·5-20·3). Eight models projected that HIV prevalence would remain unchanged (n=5) or decline (n=3) between 2008 and 2012, whereas prevalence estimates from the household surveys increased from 16·9% in 2008 to 18·8% in 2012 (difference 1·9, 95% CI -0·1 to 3·9). Model projections accurately predicted the 1·6 percentage point prevalence decline (95% CI -0·3 to 3·5) in young adults aged 15-24 years, and the 2·2 percentage point (0·5 to 3·9) increase in those aged 50 years and older. Models accurately represented the number of adults on ART in 2012; six of ten models were within the survey 95% CI of 1·54-2·12 million. However, the differential ART coverage between women and men was not fully captured; all model projections of the sex ratio of women to men on ART were lower than the survey estimate of 2·22 (95% CI 1·73-2·71).
  
  
  CONCLUSIONS
  Projections for overall declines in HIV epidemics during the ART era might have been optimistic. Future treatment and HIV prevention needs might be greater than previously forecasted. Additional data about service provision for HIV care could help inform more accurate projections.
  
  
  BACKGROUND
  Bill & Melinda Gates Foundation.
authors.affiliation: Department of Infectious Disease Epidemiology, Imperial College London, London, UK. Electronic address: jeffrey.eaton@imperial.ac.uk.
authors.forename: Jeffrey W
authors.initials: JW
authors.lastname: Eaton
authors.affiliation: Institut de Recherche pour le Développement (IRD), Bondy, France.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Bacaër
authors.affiliation: Institute for Disease Modeling, Intellectual Ventures, Bellevue, WA, USA.
authors.forename: Anna
authors.initials: A
authors.lastname: Bershteyn
authors.affiliation: Research Department of Infection and Population Health, University College London, London, UK.
authors.forename: Valentina
authors.initials: V
authors.lastname: Cambiano
authors.affiliation: MRC Centre for Outbreak Analysis and Modelling, Imperial College London, London, UK.
authors.forename: Anne
authors.initials: A
authors.lastname: Cori
authors.affiliation: Centre for Actuarial Research, University of Cape Town, Cape Town, South Africa.
authors.forename: Rob E
authors.initials: RE
authors.lastname: Dorrington
authors.affiliation: MRC Centre for Outbreak Analysis and Modelling, Imperial College London, London, UK.
authors.forename: Christophe
authors.initials: C
authors.lastname: Fraser
authors.affiliation: Department of Mechanical and Industrial Engineering, University of Massachusetts, Amherst, MA, USA.
authors.forename: Chaitra
authors.initials: C
authors.lastname: Gopalappa
authors.affiliation: Department of Public Health, Erasmus MC, Erasmus University Medical Center Rotterdam, Rotterdam, Netherlands; Nijmegen International Center for Health System Analysis and Education, Department of Primary and Community Care, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands; Africa Centre for Health and Population Studies, University of KwaZulu-Natal, Mtubatuba, South Africa.
authors.forename: Jan A C
authors.initials: JA
authors.lastname: Hontelez
authors.affiliation: Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa.
authors.forename: Leigh F
authors.initials: LF
authors.lastname: Johnson
authors.affiliation: Institute for Disease Modeling, Intellectual Ventures, Bellevue, WA, USA.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Klein
authors.affiliation: Research Department of Infection and Population Health, University College London, London, UK.
authors.forename: Andrew N
authors.initials: AN
authors.lastname: Phillips
authors.affiliation: Avenir Health, Glastonbury, CT, USA.
authors.forename: Carel
authors.initials: C
authors.lastname: Pretorius
authors.affiliation: Avenir Health, Glastonbury, CT, USA.
authors.forename: John
authors.initials: J
authors.lastname: Stover
authors.affiliation: Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa; Human Sciences Research Council, Cape Town, South Africa.
authors.forename: Thomas M
authors.initials: TM
authors.lastname: Rehle
authors.affiliation: Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
authors.forename: Timothy B
authors.initials: TB
authors.lastname: Hallett
mesh_terms: D000293:Adolescent; D000328:Adult; D019380:Anti-HIV Agents / Q000627:therapeutic use; D005260:Female; D005544:Forecasting / Q000379:methods; D015658:HIV Infections / Q000188:drug therapy / Q000453:epidemiology* / Q000517:prevention & control; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D015995:Prevalence; D013019:South Africa / Q000453:epidemiology; D055815:Young Adult
chemical_list: D019380:Anti-HIV Agents