title: A Comparison of South African National HIV Incidence Estimates: A Critical Appraisal of Different Methods.
abstract: BACKGROUND
  The interpretation of HIV prevalence trends is increasingly difficult as antiretroviral treatment programs expand. Reliable HIV incidence estimates are critical to monitoring transmission trends and guiding an effective national response to the epidemic.
  
  
  RESULTS
  We used a range of methods to estimate HIV incidence in South Africa: (i) an incidence testing algorithm applying the Limiting-Antigen Avidity Assay (LAg-Avidity EIA) in combination with antiretroviral drug and HIV viral load testing; (ii) a modelling technique based on the synthetic cohort principle; and (iii) two dynamic mathematical models, the EPP/Spectrum model package and the Thembisa model. Overall, the different incidence estimation methods were in broad agreement on HIV incidence estimates among persons aged 15-49 years in 2012. The assay-based method produced slightly higher estimates of incidence, 1.72% (95% CI 1.38 - 2.06), compared with the mathematical models, 1.47% (95% CI 1.23 - 1.72) in Thembisa and 1.52% (95% CI 1.43 - 1.62) in EPP/Spectrum, and slightly lower estimates of incidence compared to the synthetic cohort, 1.9% (95% CI 0.8 - 3.1) over the period from 2008 to 2012. Among youth aged 15-24 years, a declining trend in HIV incidence was estimated by all three mathematical estimation methods.
  
  
  CONCLUSIONS
  The multi-method comparison showed similar levels and trends in HIV incidence and validated the estimates provided by the assay-based incidence testing algorithm. Our results confirm that South Africa is the country with the largest number of new HIV infections in the world, with about 1 000 new infections occurring each day among adults aged 15-49 years in 2012.
authors.affiliation: Human Sciences Research Council, Cape Town, South Africa; Centre for Infectious Disease Epidemiology and Research, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa.
authors.forename: Thomas
authors.initials: T
authors.lastname: Rehle
authors.affiliation: Centre for Infectious Disease Epidemiology and Research, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa.
authors.forename: Leigh
authors.initials: L
authors.lastname: Johnson
authors.affiliation: Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
authors.forename: Timothy
authors.initials: T
authors.lastname: Hallett
authors.affiliation: UNAIDS, Geneva, Switzerland.
authors.forename: Mary
authors.initials: M
authors.lastname: Mahy
authors.affiliation: Centers for Disease Control and Prevention, Center for Global Health, Division of Global HIV/AIDS, Atlanta, GA, United States of America.
authors.forename: Andrea
authors.initials: A
authors.lastname: Kim
authors.affiliation: UNAIDS, Pretoria, South Africa.
authors.forename: Helen
authors.initials: H
authors.lastname: Odido
authors.affiliation: Human Sciences Research Council, Cape Town, South Africa.
authors.forename: Dorina
authors.initials: D
authors.lastname: Onoya
authors.affiliation: Human Sciences Research Council, Cape Town, South Africa.
authors.forename: Sean
authors.initials: S
authors.lastname: Jooste
authors.affiliation: Human Sciences Research Council, Cape Town, South Africa; Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa.
authors.forename: Olive
authors.initials: O
authors.lastname: Shisana
authors.affiliation: National Institute for Communicable Diseases, Johannesburg, South Africa.
authors.forename: Adrian
authors.initials: A
authors.lastname: Puren
authors.affiliation: Centers for Disease Control and Prevention, Center for Global Health, Division of Global HIV/AIDS, Atlanta, GA, United States of America.
authors.forename: Bharat
authors.initials: B
authors.lastname: Parekh
authors.affiliation: Futures Institute, Glastonbury, CT, United States of America.
authors.forename: John
authors.initials: J
authors.lastname: Stover
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D005260:Female; D015658:HIV Infections / Q000453:epidemiology*; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D013019:South Africa / Q000453:epidemiology; D055815:Young Adult