title: The representativeness of a European multi-center network for influenza-like-illness participatory surveillance.
abstract: BACKGROUND
  The Internet is becoming more commonly used as a tool for disease surveillance. Similarly to other surveillance systems and to studies using online data collection, Internet-based surveillance will have biases in participation, affecting the generalizability of the results. Here we quantify the participation biases of Influenzanet, an ongoing European-wide network of Internet-based participatory surveillance systems for influenza-like-illness.
  
  
  METHODS
  In 2011/2012 Influenzanet launched a standardized common framework for data collection applied to seven European countries. Influenzanet participants were compared to the general population of the participating countries to assess the representativeness of the sample in terms of a set of demographic, geographic, socio-economic and health indicators.
  
  
  RESULTS
  More than 30,000 European residents registered to the system in the 2011/2012 season, and a subset of 25,481 participants were selected for this study. All age classes (10 years brackets) were represented in the cohort, including under 10 and over 70 years old. The Influenzanet population was not representative of the general population in terms of age distribution, underrepresenting the youngest and oldest age classes. The gender imbalance differed between countries. A counterbalance between gender-specific information-seeking behavior (more prominent in women) and Internet usage (with higher rates in male populations) may be at the origin of this difference. Once adjusted by demographic indicators, a similar propensity to commute was observed for each country, and the same top three transportation modes were used for six countries out of seven. Smokers were underrepresented in the majority of countries, as were individuals with diabetes; the representativeness of asthma prevalence and vaccination coverage for 65+ individuals in two successive seasons (2010/2011 and 2011/2012) varied between countries.
  
  
  CONCLUSIONS
  Existing demographic and national datasets allowed the quantification of the participation biases of a large cohort for influenza-like-illness surveillance in the general population. Significant differences were found between Influenzanet participants and the general population. The quantified biases need to be taken into account in the analysis of Influenzanet epidemiological studies and provide indications on populations groups that should be targeted in recruitment efforts.
authors.forename: Pietro
authors.initials: P
authors.lastname: Cantarelli
authors.forename: Marion
authors.initials: M
authors.lastname: Debin
authors.forename: Clément
authors.initials: C
authors.lastname: Turbelin
authors.forename: Chiara
authors.initials: C
authors.lastname: Poletto
authors.forename: Thierry
authors.initials: T
authors.lastname: Blanchon
authors.forename: Alessandra
authors.initials: A
authors.lastname: Falchi
authors.forename: Thomas
authors.initials: T
authors.lastname: Hanslik
authors.forename: Isabelle
authors.initials: I
authors.lastname: Bonmarin
authors.forename: Daniel
authors.initials: D
authors.lastname: Levy-Bruhl
authors.forename: Alessandra
authors.initials: A
authors.lastname: Micheletti
authors.forename: Daniela
authors.initials: D
authors.lastname: Paolotti
authors.forename: Alessandro
authors.initials: A
authors.lastname: Vespignani
authors.forename: John
authors.initials: J
authors.lastname: Edmunds
authors.forename: Ken
authors.initials: K
authors.lastname: Eames
authors.forename: Ronald
authors.initials: R
authors.lastname: Smallenburg
authors.forename: Carl
authors.initials: C
authors.lastname: Koppeschaar
authors.forename: Ana O
authors.initials: AO
authors.lastname: Franco
authors.forename: Vitor
authors.initials: V
authors.lastname: Faustino
authors.forename: AnnaSara
authors.initials: A
authors.lastname: Carnahan
authors.forename: Moa
authors.initials: M
authors.lastname: Rehn
authors.affiliation: INSERM, UMR-S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, 27 rue Chaligny, 75012 Paris, France. vittoria.colizza@inserm.fr.
authors.forename: Vittoria
authors.initials: V
authors.lastname: Colizza
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D002648:Child; D002675:Child, Preschool; D005060:Europe / Q000453:epidemiology; D005260:Female; D006304:Health Status; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007251:Influenza, Human / Q000453:epidemiology*; D020407:Internet; D008297:Male; D008875:Middle Aged; D011159:Population Surveillance; D015995:Prevalence; D012959:Socioeconomic Factors; D055815:Young Adult