title: Estimating the number of HIV infections averted: an approach and its issues.
abstract: OBJECTIVE
  To propose a methodology to estimate the number of new HIV infections averted. Knowledge of HIV infection has increased tremendously and modelling tools to project current epidemics into the future have greatly improved. Different types of models can be used to estimate HIV infections averted, although the number of new HIV infections averted cannot be measured directly.
  
  
  METHODS
  Using cohort-component population projections, a disease modelling-based approach was used to compare the observed epidemiology of a disease after programme initiation with an expected epidemiology from past trends before programme initiation. The concept of modelling infections averted in a disease modelling-based approach involves a comparison between an "expected" or baseline epidemic with an "estimated" one. A hypothetical example was featured in order to demonstrate the proposed methodology. Using both the Estimation and Projection Package (EPP) and the Spectrum demographic modelling program, the underlying annual incidence levels implied by both the baseline and estimated epidemics were examined.
  
  
  RESULTS
  The difference between baseline and estimated incidence levels is interpreted as "infections averted". Strengths and limitations of the approach are discussed.
  
  
  CONCLUSIONS
  In this study an expected epidemiological approach was compared to one based on observation. Once sufficient data become available, the validation of various country data including HIV prevalence, mortality, and behaviour must be done. Additional information related to behaviour change may be critical to further support arguments for a change in disease trend. It is therefore important to use all available data, consequently strengthening findings from a disease modelling-based approach on HIV infections averted.
authors.affiliation: US Census Bureau, 4600 Silver Hill Road, Washington, USA. Laura.M.Heaton@census.gov
authors.forename: L M
authors.initials: LM
authors.lastname: Heaton
authors.forename: R
authors.initials: R
authors.lastname: Komatsu
authors.forename: D
authors.initials: D
authors.lastname: Low-Beer
authors.forename: T B
authors.initials: TB
authors.lastname: Fowler
authors.forename: P O
authors.initials: PO
authors.lastname: Way
mesh_terms: D000293:Adolescent; D000328:Adult; D003625:Data Collection / Q000379:methods; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D004812:Epidemiologic Methods; D005260:Female; D015658:HIV Infections / Q000453:epidemiology*; D015528:HIV Seroprevalence / Q000639:trends*; D006801:Humans; D008297:Male; D008875:Middle Aged; D015995:Prevalence