title: Prediction of serotypes causing invasive pneumococcal disease in unvaccinated and vaccinated populations.
abstract: BACKGROUND
  Before the introduction of the heptavalent pneumococcal conjugate vaccine (Prevnar-7), the relative prevalence of serotypes of Streptococcus pneumoniae was fairly stable worldwide. We sought to develop a statistical tool to predict the relative frequency of different serotypes among disease isolates in the pre- and post-Prevnar-7 eras using the limited amount of data that is widely available.
  
  
  METHODS
  We initially used pre-Prevnar-7 carriage prevalence and estimates of invasiveness derived from case-fatality data as predictors for the relative abundance of serotypes causing invasive pneumococcal disease during the pre- and post-Prevnar-7 eras, using negative binomial regression. We fit the model to pre-Prevnar-7 invasive pneumococcal disease data from England and Wales and used these data to (1) evaluate the performance of the model using several datasets and (2) evaluate the utility of the country-specific carriage data. We then fit an alternative model that used polysaccharide structure, a correlate of prevalence that does not require country-specific information and could be useful in determining the postvaccine population structure, as a predictor.
  
  
  RESULTS
  Predictions from the initial model fit data from several pediatric populations in the pre-Prevnar-7 era. After the introduction of Prevnar-7, the model still had a good negative predictive value, though substantial unexplained variation remained. The alternative model had a good negative predictive value but poor positive predictive value. Both models demonstrate that the pneumococcal population follows a somewhat predictable pattern even after vaccination.
  
  
  CONCLUSIONS
  This approach provides a preliminary framework to evaluate the potential patterns and impact of serotypes causing invasive pneumococcal disease.
authors.affiliation: Department of Immunology and Infectious Diseases, Harvard School of Public Health, 665 Huntington Ave, Boston, MA 02115, USA. dweinber@gmail.com
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Weinberger
authors.forename: Zitta B
authors.initials: ZB
authors.lastname: Harboe
authors.forename: Stefan
authors.initials: S
authors.lastname: Flasche
authors.forename: J Anthony
authors.initials: JA
authors.lastname: Scott
authors.forename: Marc
authors.initials: M
authors.lastname: Lipsitch
mesh_terms: D004739:England / Q000453:epidemiology; D005260:Female; D005544:Forecasting; D006801:Humans; D007114:Immunization; D007630:Kenya / Q000453:epidemiology; D008297:Male; D015233:Models, Statistical; D011008:Pneumococcal Infections / Q000209:etiology* / Q000401:mortality / Q000517:prevention & control; D022242:Pneumococcal Vaccines / Q000627:therapeutic use; D012703:Serotyping / Q000706:statistics & numerical data*; D013296:Streptococcus pneumoniae / Q000145:classification* / Q000472:pathogenicity; D014481:United States / Q000453:epidemiology; D018074:Vaccines, Conjugate / Q000627:therapeutic use; D014852:Wales / Q000453:epidemiology
chemical_list: D022242:Pneumococcal Vaccines; D018074:Vaccines, Conjugate