title: Cost and Impact of Voluntary Medical Male Circumcision in South Africa: Focusing the Program on Specific Age Groups and Provinces.
abstract: BACKGROUND
  In 2012, South Africa set a goal of circumcising 4.3 million men ages 15-49 by 2016. By the end of March 2014, 1.9 million men had received voluntary medical male circumcision (VMMC). In an effort to accelerate progress, South Africa undertook a modeling exercise to determine whether circumcising specific client age groups or geographic locations would be particularly impactful or cost-effective. Results will inform South Africa's efforts to develop a national strategy and operational plan for VMMC.
  
  
  RESULTS
  The study team populated the Decision Makers' Program Planning Tool, Version 2.0 (DMPPT 2.0) with HIV incidence projections from the Spectrum/AIDS Impact Module (AIM), as well as national and provincial population and HIV prevalence estimates. We derived baseline circumcision rates from the 2012 South African National HIV Prevalence, Incidence and Behaviour Survey. The model showed that circumcising men ages 20-34 offers the most immediate impact on HIV incidence and requires the fewest circumcisions per HIV infection averted. The greatest impact over a 15-year period is achieved by circumcising men ages 15-24. When the model assumes a unit cost increase with client age, men ages 15-29 emerge as the most cost-effective group. When we assume a constant cost for all ages, the most cost-effective age range is 15-34 years. Geographically, the program is cost saving in all provinces; differences in the VMMC program's cost-effectiveness across provinces were obscured by uncertainty in HIV incidence projections.
  
  
  CONCLUSIONS
  The VMMC program's impact and cost-effectiveness vary by age-targeting strategy. A strategy focusing on men ages 15-34 will maximize program benefits. However, because clients older than 25 access VMMC services at low rates, South Africa could consider promoting demand among men ages 25-34, without denying services to those in other age groups. Uncertainty in the provincial estimates makes them insufficient to support geographic targeting.
authors.affiliation: Health Policy Project, Avenir Health, Washington, District of Columbia, United States of America.
authors.forename: Katharine
authors.initials: K
authors.lastname: Kripke
authors.affiliation: Health Policy Project, Futures Group, Washington, District of Columbia, United States of America.
authors.forename: Ping-An
authors.initials: PA
authors.lastname: Chen
authors.affiliation: Health Policy Project, Futures Group, Washington, District of Columbia, United States of America.
authors.forename: Andrea
authors.initials: A
authors.lastname: Vazzano
authors.affiliation: U.S. Agency for International Development, Pretoria, South Africa.
authors.forename: Ananthy
authors.initials: A
authors.lastname: Thambinayagam
authors.affiliation: National Department of Health, Pretoria, South Africa.
authors.forename: Yogan
authors.initials: Y
authors.lastname: Pillay
authors.affiliation: National Department of Health, Pretoria, South Africa.
authors.forename: Dayanund
authors.initials: D
authors.lastname: Loykissoonlal
authors.affiliation: National Department of Health, Pretoria, South Africa.
authors.forename: Collen
authors.initials: C
authors.lastname: Bonnecwe
authors.affiliation: School of Public health, University of the Witwatersrand, Johannesburg, South Africa.
authors.forename: Peter
authors.initials: P
authors.lastname: Barron
authors.affiliation: Joint United Nations Programme on HIV/AIDS, Pretoria, South Africa.
authors.forename: Eva
authors.initials: E
authors.lastname: Kiwango
authors.affiliation: U.S. Office of the Global AIDS Coordinator, Washington, District of Columbia, United States of America.
authors.forename: Delivette
authors.initials: D
authors.lastname: Castor
authors.affiliation: U.S. Agency for International Development, Washington, District of Columbia, United States of America.
authors.forename: Emmanuel
authors.identifier: http://orcid.org/0000-0001-5370-4827
authors.initials: E
authors.lastname: Njeuhmeli
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D002944:Circumcision, Male / Q000191:economics* / Q000706:statistics & numerical data; D003362:Cost-Benefit Analysis; D015658:HIV Infections / Q000453:epidemiology / Q000517:prevention & control*; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009313:National Health Programs / Q000191:economics*; D015995:Prevalence; D012984:Software; D013019:South Africa / Q000453:epidemiology; D035141:Voluntary Programs / Q000191:economics*; D055815:Young Adult