title: Estimating future trends in paediatric HIV.
abstract: BACKGROUND
  Paediatric treatment continues to lag behind adult treatment and significant efforts are urgently needed to scale up antiretroviral therapy (ART) for children. As efforts to prevent mother-to-child transmission expand, better understanding of future trends and age characterization of the population that will be in need of ART is needed to inform policymakers, as well as drug developers and manufacturers.
  
  
  METHODS
  The Spectrum model was used to estimate the total number of expected paediatric infections by 2020 in 21 priority countries in Africa. Different ART scale-up scenarios were investigated and age characterization of the population was explored.
  
  
  RESULTS
  By 2020, new paediatric infections in the 21 countries will decline in all the scenarios. Total paediatric infections will also decline in the 21 high-burden countries, but with a differential effect by scenario and age group. On the basis of the optimal scale-up scenario, 1 940 000 [1 760 000-2 120 000] children will be expected to be living with HIV in 2020. The number of children dying of AIDS is notably different in the three models. Assuming optimal scale-up and based on 2013 treatment initiation criteria, the estimates of children to receive ART in the 21 high-burden countries will increase to 1 670 000 (1 500 000-1 800 000).
  
  
  CONCLUSIONS
  By 2020, even under the most optimistic scenarios, a considerable number of children will still be living with HIV. Age-appropriate drugs and formulations will be needed to meet the treatment needs of this vulnerable population. Improved estimates will be critical to guide the development and forecasting of commodities to close the existing paediatric treatment gap.
authors.affiliation: aHIV Department, WHO bProgramme Branch, UNAIDS, Geneva, Switzerland cFutures institute, Glastonbury, CT, USA.
authors.forename: Martina
authors.initials: M
authors.lastname: Penazzato
authors.forename: Victoria
authors.initials: V
authors.lastname: Bendaud
authors.forename: Lisa
authors.initials: L
authors.lastname: Nelson
authors.forename: John
authors.initials: J
authors.lastname: Stover
authors.forename: Mary
authors.initials: M
authors.lastname: Mahy
mesh_terms: D000293:Adolescent; D000328:Adult; D000349:Africa / Q000453:epidemiology; D000367:Age Factors; D044966:Anti-Retroviral Agents / Q000627:therapeutic use*; D002648:Child; D002675:Child, Preschool; D004363:Drug Utilization / Q000639:trends*; D004812:Epidemiologic Methods; D005260:Female; D015658:HIV Infections / Q000453:epidemiology*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D015233:Models, Statistical; D011247:Pregnancy; D015995:Prevalence
chemical_list: D044966:Anti-Retroviral Agents