title: Testing the hypothesis that treatment can eliminate HIV: a nationwide, population-based study of the Danish HIV epidemic in men who have sex with men.
abstract: Worldwide, approximately 35 million individuals are infected with HIV; about 25 million of these live in sub-Saharan Africa. WHO proposes using treatment as prevention (TasP) to eliminate HIV. Treatment suppresses viral load, decreasing the probability an individual transmits HIV. The elimination threshold is one new HIV infection per 1000 individuals. Here, we test the hypothesis that TasP can substantially reduce epidemics and eliminate HIV. We estimate the impact of TasP, between 1996 and 2013, on the Danish HIV epidemic in men who have sex with men (MSM), an epidemic UNAIDS has identified as a priority for elimination.
  
  
  
  We use a CD4-staged Bayesian back-calculation approach to estimate incidence, and the hidden epidemic (the number of HIV-infected undiagnosed MSM). To develop the back-calculation model, we use data from an ongoing nationwide population-based study: the Danish HIV Cohort Study.
  
  
  
  Incidence, and the hidden epidemic, decreased substantially after treatment was introduced in 1996. By 2013, incidence was close to the elimination threshold: 1·4 (median, 95% Bayesian credible interval [BCI] 0·4-2·1) new HIV infections per 1000 MSM and there were only 617 (264-858) undiagnosed MSM. Decreasing incidence and increasing treatment coverage were highly correlated; a treatment threshold effect was apparent.
  
  
  
  Our study is the first to show that TasP can substantially reduce a country's HIV epidemic, and bring it close to elimination. However, we have shown the effectiveness of TasP under optimal conditions: very high treatment coverage, and exceptionally high (98%) viral suppression rate. Unless these extremely challenging conditions can be met in sub-Saharan Africa, the WHO's global elimination strategy is unlikely to succeed.
  
  
  
  National Institute of Allergy and Infectious Diseases.
authors.affiliation: Center for Biomedical Modelling, Semel Institute for Neuroscience and Human Behaviour, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
authors.forename: Justin T
authors.initials: JT
authors.lastname: Okano
authors.affiliation: Center for Biomedical Modelling, Semel Institute for Neuroscience and Human Behaviour, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
authors.forename: Danielle
authors.initials: D
authors.lastname: Robbins
authors.affiliation: Center for Biomedical Modelling, Semel Institute for Neuroscience and Human Behaviour, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
authors.forename: Laurence
authors.initials: L
authors.lastname: Palk
authors.affiliation: Department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.
authors.forename: Jan
authors.initials: J
authors.lastname: Gerstoft
authors.affiliation: Department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.
authors.forename: Niels
authors.initials: N
authors.lastname: Obel
authors.affiliation: Center for Biomedical Modelling, Semel Institute for Neuroscience and Human Behaviour, David Geffen School of Medicine, University of California, Los Angeles, CA, USA. Electronic address: sblower@mednet.ucla.edu.
authors.forename: Sally
authors.initials: S
authors.lastname: Blower
mesh_terms: D015331:Cohort Studies; D003718:Denmark; D058872:Epidemics / Q000517:prevention & control*; D015658:HIV Infections / Q000188:drug therapy / Q000453:epidemiology* / Q000517:prevention & control; D018451:Homosexuality, Male; D006801:Humans; D015994:Incidence; D008297:Male; D015233:Models, Statistical; D019562:Viral Load / Q000706:statistics & numerical data