Service interruption on Monday 11 July from 12:30 to 13:00: all the sites of the CCSD (HAL, EpiSciences, SciencesConf, AureHAL) will be inaccessible (network hardware connection).
Skip to Main content Skip to Navigation
Journal articles

Improving incidence estimation in practice-based sentinel surveillance networks using spatial variation in general practitioner density

Abstract : Background: In surveillance networks based on voluntary participation of health-care professionals, there is little choice regarding the selection of participants’ characteristics. External information about participants, for example local physician density, can help reduce bias in incidence estimates reported by the surveillance network. Methods: There is an inverse association between the number of reported influenza-like illness (ILI) cases and local general practitioners (GP) density. We formulated and compared estimates of ILI incidence using this relationship. To compare estimates, we simulated epidemics using a spatially explicit disease model and their observation by surveillance networks with different characteristics: random, maximum coverage, largest cities, etc. Results: In the French practice-based surveillance network – the “Sentinelles” network – GPs reported 3.6% (95% CI [3;4]) less ILI cases as local GP density increased by 1 GP per 10,000 inhabitants. Incidence estimates varied markedly depending on scenarios for participant selection in surveillance. Yet accounting for change in GP density for participants allowed reducing bias. Applied on data from the Sentinelles network, changes in overall incidence ranged between 1.6 and 9.9%. Conclusions: Local GP density is a simple measure that provides a way to reduce bias in estimating disease incidence in general practice. It can contribute to improving disease monitoring when it is not possible to choose the characteristics of participants.
Document type :
Journal articles
Complete list of metadata

Cited literature [27 references]  Display  Hide  Download
Contributor : Gestionnaire HAL-UPMC Connect in order to contact the contributor
Submitted on : Monday, November 21, 2016 - 4:27:10 PM
Last modification on : Sunday, June 26, 2022 - 10:02:34 AM
Long-term archiving on: : Monday, March 27, 2017 - 9:16:38 AM


Publication funded by an institution


Distributed under a Creative Commons Attribution 4.0 International License



Cécile Souty, Pierre-yves Boëlle. Improving incidence estimation in practice-based sentinel surveillance networks using spatial variation in general practitioner density. BMC Medical Research Methodology, BioMed Central, 2016, 16, pp.156. ⟨10.1186/s12874-016-0260-x⟩. ⟨hal-01400246⟩



Record views


Files downloads