title: Incorporating incidence information within the UNAIDS Estimation and Projection Package framework: a study based on simulated incidence assay data.
abstract: OBJECTIVE
  The objective of this study is to extend the UNAIDS incidence estimation model, the UNAIDS Estimation and Projection Package (EPP), so that it can incorporate data from incidence assays.
  
  
  METHODS
  We propose combining the likelihood of the incidence assay data with the likelihood of other data, in a manner that is consistent with the biomarker-based incidence estimator using incidence assay data. Two calibrating parameters specify the performance of the incidence assays: the false recent rate and the mean duration of recent infection. We then use synthetic data, based on prevalence data obtained from antenatal clinic surveillances, and in some cases household surveys, from 24 countries, to examine the impact of including incidence assay data, under circumstances wherein the incidence assay data imply the same or a different incidence rate as that inferred from the prevalence data alone, and wherein incorrect calibrating parameters for the incidence assay data are used.
  
  
  RESULTS
  Using incidence assay data, in addition to prevalence data, can improve estimate by narrowing uncertainty intervals in derived HIV incidence estimates, and by providing information on levels or trends in incidence that were not apparent in the prevalence data alone. However, the effect is relatively modest if the sample size of the incidence assay survey is small and results can be biased if the calibrating parameters for the incidence assay data are not known accurately.
  
  
  CONCLUSIONS
  Incorporating information from incidence assays in the manner proposed has the potential to improve estimates. Further work will examine in more detail the circumstances under which the contribution of incidence assay data would be most valuable.
authors.affiliation: aDepartment of Statistics, the Pennsylvania State University, University Park, Pennsylvania, USA bDepartment of Infectious Disease Epidemiology, Imperial College London, London, UK.
authors.forename: Le
authors.initials: L
authors.lastname: Bao
authors.forename: Jingyi
authors.initials: J
authors.lastname: Ye
authors.forename: Timothy B
authors.initials: TB
authors.lastname: Hallett
mesh_terms: D000293:Adolescent; D000328:Adult; D003198:Computer Simulation; D004812:Epidemiologic Methods; D005260:Female; D015658:HIV Infections / Q000453:epidemiology*; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D055815:Young Adult