title: Improving disease incidence estimates in primary care surveillance systems.
abstract: BACKGROUND
  In primary care surveillance systems based on voluntary participation, biased results may arise from the lack of representativeness of the monitored population and uncertainty regarding the population denominator, especially in health systems where patient registration is not required.
  
  
  METHODS
  Based on the observation of a positive association between number of cases reported and number of consultations by the participating general practitioners (GPs), we define several weighted incidence estimators using external information on consultation volume in GPs. These estimators are applied to data reported in a French primary care surveillance system based on voluntary GPs (the Sentinelles network) for comparison.
  
  
  RESULTS
  Depending on hypotheses for weight computations, relative changes in weekly national-level incidence estimates up to 3% for influenza, 6% for diarrhea, and 11% for varicella were observed. The use of consultation-weighted estimates led to bias reduction in the estimates. At the regional level (NUTS2 level - Nomenclature of Statistical Territorial Units Level 2), relative changes were even larger between incidence estimates, with changes between -40% and +55%. Using bias-reduced weights decreased variation in incidence between regions and increased spatial autocorrelation.
  
  
  CONCLUSIONS
  Post-stratification using external administrative data may improve incidence estimates in surveillance systems based on voluntary participation.
authors.affiliation: INSERM, UMR_S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris F-75012, France ; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris F-75012, France.
authors.forename: Cécile
authors.initials: C
authors.lastname: Souty
authors.affiliation: INSERM, UMR_S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris F-75012, France ; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris F-75012, France.
authors.forename: Clément
authors.initials: C
authors.lastname: Turbelin
authors.affiliation: INSERM, UMR_S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris F-75012, France ; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris F-75012, France.
authors.forename: Thierry
authors.initials: T
authors.lastname: Blanchon
authors.affiliation: INSERM, UMR_S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris F-75012, France ; AP-HP, Hôpital Ambroise Paré, service de médecine interne, Boulogne-Billancourt F-92100, France ; Université Versailles Saint-Quentin-en-Yvelines, Versailles F-78000, France.
authors.forename: Thomas
authors.initials: T
authors.lastname: Hanslik
authors.affiliation: Département des maladies infectieuses, Institut de Veille Sanitaire (InVS), St Maurice F-94415, France.
authors.forename: Yann
authors.initials: Y
authors.lastname: Le Strat
authors.affiliation: INSERM, UMR_S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris F-75012, France ; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris F-75012, France ; AP-HP, Hôpital Saint-Antoine, unité de santé publique, Paris F-75012, France.
authors.forename: Pierre-Yves
authors.initials: PY
authors.lastname: Boëlle
keywords: Adjustment; General practitioners; Incidence estimation; Sentinel network; Surveillance; Volume of consultations