1887
Research article Open Access
Like 0

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.

Loading

Article metrics loading...

/content/10.2807/1560-7917.ES.2017.22.32.30593
2017-08-10
2017-12-12
http://instance.metastore.ingenta.com/content/10.2807/1560-7917.ES.2017.22.32.30593
Loading
Loading full text...

Full text loading...

/deliver/fulltext/eurosurveillance/22/32/eurosurv-22-32-3.html?itemId=/content/10.2807/1560-7917.ES.2017.22.32.30593&mimeType=html&fmt=ahah

References

  1. Influenza surveillance teams.Surveillance de la grippe en France métropolitaine. Saison 2014-2015.[Influenza activity in mainland France: 2014-15 season]. Bull Epidemiol Hebd (Paris). 2015;32-33:593-8.
  2. Valleron AJ, Garnerin P. Computerised surveillance of communicable diseases in France. Commun Dis Rep CDR Rev. 1993;3(6):R82-7. PMID: 7693158 
  3. Costagliola D, Flahault A, Galinec D, Garnerin P, Menares J, Valleron AJ. A routine tool for detection and assessment of epidemics of influenza-like syndromes in France. Am J Public Health. 1991;81(1):97-9.  https://doi.org/10.2105/AJPH.81.1.97  PMID: 1983924 
  4. Caserio-Schönemann C, Bousquet V, Fouillet A, Henry Vfor the SurSaUD team. Le système de surveillance syndromique SurSaUD. [The French syndromic surveillance system SUrSaUD]. Bull Epidemiol Hebd (Paris). 2014;3-4:38-44. French.
  5. Caserio-Schönemann C, Meynard JB. Ten years experience of syndromic surveillance for civil and military public health, France, 2004-2014. Euro Surveill. 2015;20(19):21126.  https://doi.org/10.2807/1560-7917.ES2015.20.19.21126  PMID: 25990360 
  6. Josseran L, Nicolau J, Caillère N, Astagneau P, Brücker G. Syndromic surveillance based on emergency department activity and crude mortality: two examples. Euro Surveill. 2006;11(12):225-9. PMID: 17370967 
  7. Réseau Sentinelles. Bilan annuel 2015. [Annual report 2015.] Paris: Institut Pierre Louis d'Epidémiologie et de Santé Publique; 2016. French. Available from: http://www.sentiweb.fr/document/3583
  8. Souty C, Turbelin C, Blanchon T, Hanslik T, Le Strat Y, Boëlle PY. Improving disease incidence estimates in primary care surveillance systems. Popul Health Metr. 2014;12(1):19.  https://doi.org/10.1186/s12963-014-0019-8  PMID: 25435814 
  9. Schaeffer R, Mendenhall W, Ott L. Elementary survey sampling. 3rd ed. Boston: Prindle, Weber and Schmidt; 1986.
  10. R Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2015. Available from: http://www.R-project.org/
  11. Serfling RE. Methods for current statistical analysis of excess pneumonia-influenza deaths. Public Health Rep. 1963;78(6):494-506.  https://doi.org/10.2307/4591848  PMID: 19316455 
  12. Pelat C, Boëlle PY, Cowling BJ, Carrat F, Flahault A, Ansart S, et al. Online detection and quantification of epidemics. BMC Med Inform Decis Mak. 2007;7(1):29.  https://doi.org/10.1186/1472-6947-7-29  PMID: 17937786 
  13. Muscatello DJ, Cretikos MA, Macintyre CR. All-cause mortality during first wave of pandemic (H1N1) 2009, New South Wales, Australia, 2009. Emerg Infect Dis. 2010;16(9):1396-402.  https://doi.org/10.3201/eid1609.091723  PMID: 20735923 
  14. Venables WN, Ripley BD. Modern applied statistics with S. 4th ed. New York: Springer; 2002.
  15. Le Strat Y, Carrat F. Monitoring epidemiologic surveillance data using hidden Markov models. Stat Med. 1999;18(24):3463-78.  https://doi.org/10.1002/(SICI)1097-0258(19991230)18:24<3463::AID-SIM409>3.0.CO;2-I  PMID: 10611619 
  16. Martínez-Beneito MA, Conesa D, López-Quílez A, López-Maside A. Bayesian Markov switching models for the early detection of influenza epidemics. Stat Med. 2008;27(22):4455-68.  https://doi.org/10.1002/sim.3320  PMID: 18618414 
  17. Rath TM, Carreras M, Sebastiani P. Automated detection of influenza epidemics with Hidden Markov Models. Lect notes comput sc. 2003;2810:521-32.
  18. Watkins RE, Eagleson S, Veenendaal B, Wright G, Plant AJ. Disease surveillance using a hidden Markov model. BMC Med Inform Decis Mak. 2009;9(1):39.  https://doi.org/10.1186/1472-6947-9-39  PMID: 19664256 
  19. Harte D. HiddenMarkov: Hidden Markov models. R package version 1.8-7. Wellington2016. Available from: https://cran.r-project.org/web/packages/HiddenMarkov/HiddenMarkov.pdf
  20. Chang W, Cheng J, Allaire J, Xie Y, McPherson J. shiny: web application framework for R. R package version 0.13.0. 2016. Available from: https://CRAN.R-project.org/package=shiny
  21. Influenza surveillance teams.Surveillance de la grippe en France métropolitaine, saison 2015-2016. [Influenza activity in mainland France, season 2015-2016]. Bull Epidemiol Hebd (Paris). 2016;32-33:558-63. French.
  22. Fleming DM, Durnall H, Warburton F, Ellis JS, Zambon MC. Is the onset of influenza in the community age-related? Epidemiol Infect. 2016;144(11):2295-305.  https://doi.org/10.1017/S0950268816000510  PMID: 27350234 
  23. Vega T, Lozano JE, Meerhoff T, Snacken R, Mott J, Ortiz de Lejarazu R, et al. Influenza surveillance in Europe: establishing epidemic thresholds by the moving epidemic method. Influenza Other Respi Viruses. 2013;7(4):546-58.  https://doi.org/10.1111/j.1750-2659.2012.00422.x  PMID: 22897919 
  24. Green HK, Charlett A, Moran-Gilad J, Fleming D, Durnall H, Thomas DR, et al. Harmonizing influenza primary-care surveillance in the United Kingdom: piloting two methods to assess the timing and intensity of the seasonal epidemic across several general practice-based surveillance schemes. Epidemiol Infect. 2015;143(1):1-12.  https://doi.org/10.1017/S0950268814001757  PMID: 25023603 
  25. Schanzer DL, Saboui M, Lee L, Domingo FR, Mersereau T. Leading Indicators and the Evaluation of the Performance of Alerts for Influenza Epidemics. PLoS One. 2015;10(10):e0141776.  https://doi.org/10.1371/journal.pone.0141776  PMID: 26513364 
/content/10.2807/1560-7917.ES.2017.22.32.30593
Loading

Data & Media loading...

Comment has been disabled for this content
Submit comment
Close
Comment moderation successfully completed
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error