title: Estimating incidence from prevalence in generalised HIV epidemics: methods and validation.
abstract: BACKGROUND
  HIV surveillance of generalised epidemics in Africa primarily relies on prevalence at antenatal clinics, but estimates of incidence in the general population would be more useful. Repeated cross-sectional measures of HIV prevalence are now becoming available for general populations in many countries, and we aim to develop and validate methods that use these data to estimate HIV incidence.
  
  
  RESULTS
  Two methods were developed that decompose observed changes in prevalence between two serosurveys into the contributions of new infections and mortality. Method 1 uses cohort mortality rates, and method 2 uses information on survival after infection. The performance of these two methods was assessed using simulated data from a mathematical model and actual data from three community-based cohort studies in Africa. Comparison with simulated data indicated that these methods can accurately estimates incidence rates and changes in incidence in a variety of epidemic conditions. Method 1 is simple to implement but relies on locally appropriate mortality data, whilst method 2 can make use of the same survival distribution in a wide range of scenarios. The estimates from both methods are within the 95% confidence intervals of almost all actual measurements of HIV incidence in adults and young people, and the patterns of incidence over age are correctly captured.
  
  
  CONCLUSIONS
  It is possible to estimate incidence from cross-sectional prevalence data with sufficient accuracy to monitor the HIV epidemic. Although these methods will theoretically work in any context, we have able to test them only in southern and eastern Africa, where HIV epidemics are mature and generalised. The choice of method will depend on the local availability of HIV mortality data.
authors.affiliation: Imperial College London, London, United Kingdom. timothy.hallett@imperial.ac.uk
authors.forename: Timothy B
authors.initials: TB
authors.lastname: Hallett
authors.forename: Basia
authors.initials: B
authors.lastname: Zaba
authors.forename: Jim
authors.initials: J
authors.lastname: Todd
authors.forename: Ben
authors.initials: B
authors.lastname: Lopman
authors.forename: Wambura
authors.initials: W
authors.lastname: Mwita
authors.forename: Sam
authors.initials: S
authors.lastname: Biraro
authors.forename: Simon
authors.initials: S
authors.lastname: Gregson
authors.forename: J Ties
authors.initials: JT
authors.lastname: Boerma
mesh_terms: D000293:Adolescent; D000328:Adult; D000349:Africa; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D004196:Disease Outbreaks; D015658:HIV Infections / Q000453:epidemiology* / Q000401:mortality; D006801:Humans; D015994:Incidence; D008875:Middle Aged; D015233:Models, Statistical; D011159:Population Surveillance; D015995:Prevalence; D012494:Sampling Studies; D016036:Seroepidemiologic Studies