title: Predicting pneumonia and influenza mortality from morbidity data.
abstract: BACKGROUND
  Few European countries conduct reactive surveillance of influenza mortality, whereas most monitor morbidity.
  
  
  RESULTS
  We developed a simple model based on Poisson seasonal regression to predict excess cases of pneumonia and influenza mortality during influenza epidemics, based on influenza morbidity data and the dominant types/subtypes of circulating viruses. Epidemics were classified in three levels of mortality burden ("high", "moderate" and "low"). The model was fitted on 14 influenza seasons and was validated on six subsequent influenza seasons. Five out of the six seasons in the validation set were correctly classified. The average absolute difference between observed and predicted mortality was 2.8 per 100,000 (18% of the average excess mortality) and Spearman's rank correlation coefficient was 0.89 (P = 0.05).
  
  
  CONCLUSIONS
  The method described here can be used to estimate the influenza mortality burden in countries where specific pneumonia and influenza mortality surveillance data are not available.
authors.affiliation: Université Pierre et Marie Curie-Paris 6, UMR-S 707, Paris, France.
authors.forename: Lise
authors.initials: L
authors.lastname: Denoeud
authors.forename: Clément
authors.initials: C
authors.lastname: Turbelin
authors.forename: Séverine
authors.initials: S
authors.lastname: Ansart
authors.forename: Alain-Jacques
authors.initials: AJ
authors.lastname: Valleron
authors.forename: Antoine
authors.initials: A
authors.lastname: Flahault
authors.forename: Fabrice
authors.initials: F
authors.lastname: Carrat
mesh_terms: D006801:Humans; D007251:Influenza, Human / Q000453:epidemiology / Q000401:mortality*; D011014:Pneumonia / Q000453:epidemiology / Q000401:mortality*; D016012:Poisson Distribution; D011159:Population Surveillance; D012621:Seasons