title: Detection of excess influenza severity: associating respiratory hospitalization and mortality data with reports of influenza-like illness by primary care physicians.
abstract: OBJECTIVE
  We explored whether excesses in influenza severity can be detected by combining respiratory syndromic hospital and mortality data with data on influenza-like illness (ILI) cases obtained from general practitioners.
  
  
  METHODS
  To identify excesses in the severity of influenza infections in the population of the Netherlands between 1999 and 2005, we looked for increases in influenza-associated hospitalizations and mortality that were disproportionate to the number of ILI cases reported by general practitioners. We used generalized estimating equation regression models to associate syndromic hospital and mortality data with ILI surveillance data obtained from general practitioners. Virus isolation and antigenic characterization data were used to interpret the results.
  
  
  RESULTS
  Disproportionate increases in hospitalizations and mortality (relative to ILI cases reported by general practitioners) were identified in 2003/04 during the A/Fujian/411/02(H3N2) drift variant epidemic.
  
  
  CONCLUSIONS
  Combined surveillance of respiratory hospitalizations and mortality and ILI data obtained from general practitioners can capture increases in severe influenza-associated illness that are disproportionate to influenza incidence rates. Therefore, this novel approach should complement traditional seasonal and pandemic influenza surveillance in efforts to detect increases in influenza case fatality rates and percentages of patients hospitalized.
authors.affiliation: National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, Netherlands. kees.van.den.wijngaard@rivm.nl
authors.forename: Cees C
authors.initials: CC
authors.lastname: van den Wijngaard
authors.forename: Liselotte
authors.initials: L
authors.lastname: van Asten
authors.forename: Adam
authors.initials: A
authors.lastname: Meijer
authors.forename: Wilfrid
authors.initials: W
authors.lastname: van Pelt
authors.forename: Nico J D
authors.initials: NJ
authors.lastname: Nagelkerke
authors.forename: Gé A
authors.initials: GA
authors.lastname: Donker
authors.forename: Marianne A B
authors.initials: MA
authors.lastname: van der Sande
authors.forename: Marion P G
authors.initials: MP
authors.lastname: Koopmans
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D002648:Child; D002675:Child, Preschool; D004196:Disease Outbreaks / Q000706:statistics & numerical data; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D015994:Incidence; D007223:Infant; D007251:Influenza, Human / Q000453:epidemiology* / Q000401:mortality; D008875:Middle Aged; D009426:Netherlands / Q000453:epidemiology; D010821:Physicians, Family / Q000706:statistics & numerical data; D011159:Population Surveillance / Q000379:methods; D012044:Regression Analysis; D012140:Respiratory Tract Diseases / Q000453:epidemiology; D012621:Seasons; D012720:Severity of Illness Index; D055815:Young Adult