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Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
European Centre for Disease Prevention and Control (ECDC)
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6373610/ https://www.ncbi.nlm.nih.gov/pubmed/28816649 http://dx.doi.org/10.2807/1560-7917.ES.2017.22.32.30593 |
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author | Pelat, Camille Bonmarin, Isabelle Ruello, Marc Fouillet, Anne Caserio-Schönemann, Céline Levy-Bruhl, Daniel Le Strat, Yann |
author_facet | Pelat, Camille Bonmarin, Isabelle Ruello, Marc Fouillet, Anne Caserio-Schönemann, Céline Levy-Bruhl, Daniel Le Strat, Yann |
author_sort | Pelat, Camille |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6373610 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | European Centre for Disease Prevention and Control (ECDC) |
record_format | MEDLINE/PubMed |
spelling | pubmed-63736102019-03-06 Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France Pelat, Camille Bonmarin, Isabelle Ruello, Marc Fouillet, Anne Caserio-Schönemann, Céline Levy-Bruhl, Daniel Le Strat, Yann Euro Surveill Research Article 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. European Centre for Disease Prevention and Control (ECDC) 2017-08-10 /pmc/articles/PMC6373610/ /pubmed/28816649 http://dx.doi.org/10.2807/1560-7917.ES.2017.22.32.30593 Text en This article is copyright of The Authors, 2017. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0) Licence. You may share and adapt the material, but must give appropriate credit to the source, provide a link to the licence, and indicate if changes were made. |
spellingShingle | Research Article Pelat, Camille Bonmarin, Isabelle Ruello, Marc Fouillet, Anne Caserio-Schönemann, Céline Levy-Bruhl, Daniel Le Strat, Yann Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France |
title | Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France |
title_full | Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France |
title_fullStr | Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France |
title_full_unstemmed | Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France |
title_short | Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France |
title_sort | improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in france |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6373610/ https://www.ncbi.nlm.nih.gov/pubmed/28816649 http://dx.doi.org/10.2807/1560-7917.ES.2017.22.32.30593 |
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