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Comparative Study
. 2015 Dec 9;10(12):e0143791.
doi: 10.1371/journal.pone.0143791. eCollection 2015.

Comparing Observed with Predicted Weekly Influenza-Like Illness Rates during the Winter Holiday Break, United States, 2004-2013

Affiliations
Comparative Study

Comparing Observed with Predicted Weekly Influenza-Like Illness Rates during the Winter Holiday Break, United States, 2004-2013

Hongjiang Gao et al. PLoS One. .

Abstract

In the United States, influenza season typically begins in October or November, peaks in February, and tapers off in April. During the winter holiday break, from the end of December to the beginning of January, changes in social mixing patterns, healthcare-seeking behaviors, and surveillance reporting could affect influenza-like illness (ILI) rates. We compared predicted with observed weekly ILI to examine trends around the winter break period. We examined weekly rates of ILI by region in the United States from influenza season 2003-2004 to 2012-2013. We compared observed and predicted ILI rates from week 44 to week 8 of each influenza season using the auto-regressive integrated moving average (ARIMA) method. Of 1,530 region, week, and year combinations, 64 observed ILI rates were significantly higher than predicted by the model. Of these, 21 occurred during the typical winter holiday break period (weeks 51-52); 12 occurred during influenza season 2012-2013. There were 46 observed ILI rates that were significantly lower than predicted. Of these, 16 occurred after the typical holiday break during week 1, eight of which occurred during season 2012-2013. Of 90 (10 HHS regions x 9 seasons) predictions during the peak week, 78 predicted ILI rates were lower than observed. Out of 73 predictions for the post-peak week, 62 ILI rates were higher than observed. There were 53 out of 73 models that had lower peak and higher post-peak predicted ILI rates than were actually observed. While most regions had ILI rates higher than predicted during winter holiday break and lower than predicted after the break during the 2012-2013 season, overall there was not a consistent relationship between observed and predicted ILI around the winter holiday break during the other influenza seasons.

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Conflict of interest statement

Competing Interests: The authors have the following interests: JS is employed by Chenega Time Solutions. There are no patents, products in development or marketed products to declare. This does not alter their adherence to all the PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. a) Number of predicted that are significantly lower(the upper bound of 95% prediction interval lower than the observed) than observed across influenza season and weeks, b) Number of predicted that are significantly higher(the lower bound of 95% prediction interval higher than the observed) than observed across influenza season and weeks.
Fig 2
Fig 2. Average total number of patient visits (red line, scales on the left-side y-axis) and average total number of ILI visits (blue line, scales on the right-side y-axis) across all HHS regions between 2003–2004 and 2012–2013 influenza seasons.

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References

    1. Textbook of Influenza. Second ed. John Wiley & Son, Ltd, The Atrium, Southern Gate, Chichester, Wesr Sussex, PO 19 8SQ, UK: Wiley Blackwell; 2013.
    1. National and Regional Level Outpatient Illness and Viral Surveillance US Centers for Disease Control and Prevention. US Centers for Disease Control and Prevention. Available: http://gis.cdc.gov/grasp/fluview/fluportaldashboard.html. Accessed 21 December 2014.
    1. Earn DJD, He D, Loeb MB, Fonseca K, Lee BE, Dushoff J. Effects of School Closure on Incidence of Pandemic Influenza in Alberta, Canada. Annals of Internal Medicine. 2012;156(3):173–81. 10.7326/0003-4819-156-3-201202070-00005 - DOI - PubMed
    1. Cauchemez S, Valleron AJ, Boelle PY, Flahault A, Ferguson NM. Estimating the impact of school closure on influenza transmission from Sentinel data. Nature. 2008. April 10;452(7188):750–4. Epub 2008/04/11. eng. 10.1038/nature06732 - DOI - PubMed
    1. Heymann AD, Hoch I, Valinsky L, Kokia E, Steinberg DM. School closure may be effective in reducing transmission of respiratory viruses in the community. Epidemiology and infection. 2009. October;137(10):1369–76. Epub 2009/04/09. eng. 10.1017/S0950268809002556 - DOI - PubMed

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