title: Reevaluation of epidemiological data demonstrates that it is consistent with cross-immunity among human papillomavirus types.
abstract: BACKGROUND
  The degree of cross-immunity between human papillomavirus (HPV) types is fundamental both to the epidemiological dynamics of HPV and to the impact of HPV vaccination. Epidemiological data on HPV infections has been repeatedly interpreted as inconsistent with cross-immunity.
  
  
  METHODS
  We reevaluate the epidemiological data using a model to determine the odds ratios of multiple to single infections expected in the presence or absence of cross-immunity. We simulate a virtual longitudinal survey to determine the effect cross-immunity has on the prevalence of multiple infections. We calibrate our model to epidemiological data and estimate the extent of type replacement following vaccination against specific HPV types.
  
  
  RESULTS
  We find that cross-immunity can produce odds ratios of infection comparable with epidemiological observations. We show that the sample sizes underlying existing surveys have been insufficient to identify even intense cross-immunity. We also find that the removal of HPV type 16, type 18, and types 6 and 11 would increase the prevalence of nontargeted types by 50%, 29%, and 183%, respectively.
  
  
  CONCLUSIONS
  Cross-immunity between HPV types is consistent with epidemiological data, contrary to previous interpretations. Cross-immunity may cause significant type replacement following vaccination, and therefore should be considered in future vaccine studies and epidemiological models.
authors.affiliation: Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT 06520-8034, USA. david.durham@yale.edu
authors.forename: David P
authors.initials: DP
authors.lastname: Durham
authors.forename: Eric M
authors.initials: EM
authors.lastname: Poolman
authors.forename: Yoko
authors.initials: Y
authors.lastname: Ibuka
authors.forename: Jeffrey P
authors.initials: JP
authors.lastname: Townsend
authors.forename: Alison P
authors.initials: AP
authors.lastname: Galvani
mesh_terms: D003198:Computer Simulation; D056738:Cross Protection; D005260:Female; D006801:Humans; D015233:Models, Statistical; D027383:Papillomaviridae / Q000276:immunology*; D030361:Papillomavirus Infections / Q000453:epidemiology*