Influenza A and B epidemic criteria based on time-series analysis of health services surveillance data
- PMID: 9663521
- DOI: 10.1023/a:1007467814485
Influenza A and B epidemic criteria based on time-series analysis of health services surveillance data
Abstract
Many countries now have epidemiological surveillance systems using health services-based indicators that allow detection of influenza epidemics. However, there is no accepted criterion for defining an influenza epidemic. An epidemic criterion has been developed, based on a time-series analysis of health services-based indicators collected on a weekly basis by a surveillance network implemented in the Paris region since 1984: the Groupe Regional d'Observation de la Grippe (GROG). For each new season, an epidemic threshold is independently defined for each health services-based indicator as the upper limit of the one-sided confidence interval of the expected value calculated from the weekly differences between the observed number of events and those predicted by a SARIMA model fitted on the non-epidemic data of previous seasons. Epidemic criteria for influenza A and B are then defined from the combination of both viral indicators and epidemic thresholds of individual health services-based indicators. Among health indicators, sick-leave data collected from GP's or the Health Insurance system, emergency home medical visits, and influenza-like-illness reported by GP's are the most sensitive indicators for the early recognition of epidemics. The exceeding of the above mentioned thresholds combined with virological data allows the specific detection of influenza A or B epidemics. This time-series method of analysing surveillance data provides early and reliable recognition of these epidemics.
Similar articles
-
Sensitivity, specificity and predictive values of health service based indicators for the surveillance of influenza A epidemics.Int J Epidemiol. 1994 Aug;23(4):849-55. doi: 10.1093/ije/23.4.849. Int J Epidemiol. 1994. PMID: 8002201
-
Monitoring sick leave data for early detection of influenza outbreaks.BMC Infect Dis. 2021 Jan 11;21(1):52. doi: 10.1186/s12879-020-05754-5. BMC Infect Dis. 2021. PMID: 33430793 Free PMC article.
-
A new influenza surveillance system in France: the Ile-de-France "GROG". 2. Validity of indicators (1984-1989).Eur J Epidemiol. 1991 Nov;7(6):579-87. doi: 10.1007/BF00218667. Eur J Epidemiol. 1991. PMID: 1783052
-
Virtual surveillance of communicable diseases: a 20-year experience in France.Stat Methods Med Res. 2006 Oct;15(5):413-21. doi: 10.1177/0962280206071639. Stat Methods Med Res. 2006. PMID: 17089946 Review.
-
[Various sides of influenza. Part II--epidemiology, influenza surveillance and prophylaxis].Pol Merkur Lekarski. 2006 Sep;21(123):277-85. Pol Merkur Lekarski. 2006. PMID: 17163191 Review. Polish.
Cited by
-
The predictive skill of convolutional neural networks models for disease forecasting.PLoS One. 2021 Jul 9;16(7):e0254319. doi: 10.1371/journal.pone.0254319. eCollection 2021. PLoS One. 2021. PMID: 34242349 Free PMC article.
-
Physician surveillance of influenza: collaboration between primary care and public health.Can Fam Physician. 2014 Jan;60(1):e7-15. Can Fam Physician. 2014. PMID: 24452584 Free PMC article.
-
Climatic drivers of seasonal influenza epidemics in French Guiana, 2006-2010.J Infect. 2013 Aug;67(2):141-7. doi: 10.1016/j.jinf.2013.03.018. Epub 2013 Apr 15. J Infect. 2013. PMID: 23597784 Free PMC article.
-
Nationwide surveillance of 18 respiratory viruses in patients with influenza-like illnesses: a pilot feasibility study in the French Sentinel Network.J Med Virol. 2011 Aug;83(8):1451-7. doi: 10.1002/jmv.22113. Epub 2011 Jun 2. J Med Virol. 2011. PMID: 21638286 Free PMC article.
-
Acute diarrheal syndromic surveillance: effects of weather and holidays.Appl Clin Inform. 2010 Apr 14;1(2):79-95. doi: 10.4338/ACI-2009-12-RA-0024. Print 2010. Appl Clin Inform. 2010. PMID: 23616829 Free PMC article.
References
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical