title: Evaluating the cost-effectiveness of pre-exposure prophylaxis (PrEP) and its impact on HIV-1 transmission in South Africa.
abstract: BACKGROUND
  Mathematical modelers have given little attention to the question of how pre-exposure prophylaxis (PrEP) may impact on a generalized national HIV epidemic and its cost-effectiveness, in the context of control strategies such as condom use promotion and expanding ART programs.
  
  
  RESULTS
  We use an age- and gender-structured model of the generalized HIV epidemic in South Africa to investigate the potential impact of PrEP in averting new infections. The model utilizes age-structured mortality, fertility, partnership and condom use data to model the spread of HIV and the shift of peak prevalence to older age groups. The model shows that universal PrEP coverage would have to be impractically high to have a significant effect on incidence reduction while ART coverage expands. PrEP targeted to 15-35-year-old women would avert 10%-25% (resp. 13%-28%) of infections in this group and 5%-12% (resp. 7%-16%) of all infections in the period 2014-2025 if baseline incidence is 0.5% per year at 2025 (resp. 0.8% per year at 2025). The cost would be $12,500-$20,000 per infection averted, depending on the level of ART coverage and baseline incidence. An optimistic scenario of 30%-60% PrEP coverage, efficacy of at least 90%, no behavior change among PrEP users and ART coverage less than three times its 2010 levels is required to achieve this result. Targeting PrEP to 25-35-year-old women (at highest risk of infection) improves impact and cost-effectiveness marginally. Relatively low levels of condom substitution (e.g., 30%) do not nullify the efficacy of PrEP, but reduces cost-effectiveness by 35%-40%.
  
  
  CONCLUSIONS
  PrEP can avert as many as 30% of new infections in targeted age groups of women at highest risk of infection. The cost-effectiveness of PrEP relative to ART decreases rapidly as ART coverage increases beyond three times its coverage in 2010, after which the ART program would provide coverage to more than 65% of HIV(+) individuals. To have a high relative cost-effective impact on reducing infections in generalized epidemics, PrEP must utilize a window of opportunity until ART has been scaled up beyond this level.
authors.affiliation: Futures Institute, Glastonbury, Connecticut, United States of America. cpretorius@futuresinstitute.org
authors.forename: Carel
authors.initials: C
authors.lastname: Pretorius
authors.forename: John
authors.initials: J
authors.lastname: Stover
authors.forename: Lori
authors.initials: L
authors.lastname: Bollinger
authors.forename: Nicolas
authors.initials: N
authors.lastname: Bacaër
authors.forename: Brian
authors.initials: B
authors.lastname: Williams
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000465:Algorithms; D003362:Cost-Benefit Analysis / Q000706:statistics & numerical data; D058872:Epidemics / Q000191:economics / Q000517:prevention & control*; D005260:Female; D015658:HIV Infections / Q000191:economics / Q000453:epidemiology / Q000635:transmission*; D015497:HIV-1; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D018803:Models, Economic; D015995:Prevalence; D012737:Sex Factors; D013019:South Africa / Q000453:epidemiology; D055815:Young Adult