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Abstract

The 2014/15 influenza epidemic caused a work overload for healthcare facilities in France. The French national public health agency announced the start of the epidemic – based on indicators aggregated at the national level – too late for many hospitals to prepare. It was therefore decided to improve the influenza alert procedure through (i) the introduction of a pre-epidemic alert level to better anticipate future outbreaks, (ii) the regionalisation of surveillance so that healthcare structures can be informed of the arrival of epidemics in their region, (iii) the standardised use of data sources and statistical methods across regions. A web application was developed to deliver statistical results of three outbreak detection methods applied to three surveillance data sources: emergency departments, emergency general practitioners and sentinel general practitioners. This application was used throughout the 2015/16 influenza season by the epidemiologists of the headquarters and regional units of the French national public health agency. It allowed them to signal the first influenza epidemic alert in week 2016-W03, in Brittany, with 11 other regions in pre-epidemic alert. This application received positive feedback from users and was pivotal for coordinating surveillance across the agency’s regional units.

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2017-08-10
2024-11-21
http://instance.metastore.ingenta.com/content/10.2807/1560-7917.ES.2017.22.32.30593
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Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France
<p class="citation"> <span>Citation style for this article:</span> <span class="meta-value authors"> <a href="/search?value1=Camille+Pelat&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Pelat Camille</a>, <a href="/search?value1=Isabelle+Bonmarin&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Bonmarin Isabelle</a>, <a href="/search?value1=Marc+Ruello&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Ruello Marc</a>, <a href="/search?value1=Anne+Fouillet&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Fouillet Anne</a>, <a href="/search?value1=C%C3%A9line+Caserio-Sch%C3%B6nemann&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Caserio-Schönemann Céline</a>, <a href="/search?value1=Daniel+Levy-Bruhl&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Levy-Bruhl Daniel</a>, <a href="/search?value1=Yann+Le+Strat&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Le Strat Yann</a>, <a href="/search?value1=the+Regional+Influenza+study+group&option1=author&noRedirect=true" class="nonDisambigAuthorLink">the Regional Influenza study group</a></span>. Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France. <a href="/content/ecdc">Euro Surveill.</a> 2017;22(32):pii=30593. <a href="https://doi.org/10.2807/1560-7917.ES.2017.22.32.30593" title="doi link" target="_blank">https://doi.org/10.2807/1560-7917.ES.2017.22.32.30593</a> <span class="ES_Article_citation"> <span class="generated">Received</span>: 24 Oct 2016;&nbsp;&nbsp; <span class="generated">Accepted</span>: 19 Apr 2017 </span> </p>
/content/10.2807/1560-7917.ES.2017.22.32.30593
/content/10.2807/1560-7917.ES.2017.22.32.30593
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