title: Intra-Weekly Variations of Influenza-Like Illness in Military Populations.
abstract: In this report, we describe and analyze a periodic pattern in influenza-like illness within active military populations, derived from the Defense Medical Surveillance System data set. We find that there is a well-defined pattern with peak incidence on Monday, decaying to Friday, and remaining roughly constant over the weekend. Moreover, we find that the pattern systematically changes in response to public holidays. We quantitatively describe the effect of this modulation, and show how these results may be used to detrend military and, by extension, civilian data sets. As medical data streams become more timely, these results may be used to infer near-real-time daily estimates of influenza-like illness incidence, which may form the basis of a forecasting tool for imminent outbreaks.
authors.affiliation: Predictive Science Inc., 9990 Mesa Rim Road, Suite 170, San Diego, CA 92121.
authors.forename: Pete
authors.initials: P
authors.lastname: Riley
authors.affiliation: Armed Forces Health Surveillance Center, 11800 Tech Road, Suite 220, Silver Spring, MD 20910.
authors.forename: Angelia A
authors.initials: AA
authors.lastname: Cost
authors.affiliation: Predictive Science Inc., 9990 Mesa Rim Road, Suite 170, San Diego, CA 92121.
authors.forename: Steven
authors.initials: S
authors.lastname: Riley
mesh_terms: D000554:Ambulatory Care Facilities / Q000706:statistics & numerical data*; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005544:Forecasting; D006801:Humans; D015994:Incidence; D007251:Influenza, Human / Q000453:epidemiology*; D008887:Military Medicine; D008889:Military Personnel / Q000706:statistics & numerical data*; D011159:Population Surveillance / Q000379:methods*; D013997:Time Factors; D014481:United States / Q000453:epidemiology