Predicting pneumonia and influenza mortality from morbidity data.
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.
Denoeud
Lise
L
Université Pierre et Marie Curie-Paris 6, UMR-S 707, Paris, France.
Turbelin
Clément
C
Ansart
Séverine
S
Valleron
Alain-Jacques
AJ
Flahault
Antoine
A
Carrat
Fabrice
F
D006801:Humans; D007251:Influenza, Human / Q000453:epidemiology / Q000401:mortality*; D011014:Pneumonia / Q000453:epidemiology / Q000401:mortality*; D016012:Poisson Distribution; D011159:Population Surveillance; D012621:Seasons