Literature DB >> 27046183

Intra-Weekly Variations of Influenza-Like Illness in Military Populations.

Pete Riley1, Angelia A Cost2, Steven Riley1.   

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. Reprint &
Copyright © 2016 Association of Military Surgeons of the U.S.

Entities:  

Mesh:

Year:  2016        PMID: 27046183     DOI: 10.7205/MILMED-D-15-00226

Source DB:  PubMed          Journal:  Mil Med        ISSN: 0026-4075            Impact factor:   1.437


  3 in total

1.  Correcting for day of the week and public holiday effects: improving a national daily syndromic surveillance service for detecting public health threats.

Authors:  Elizabeth Buckingham-Jeffery; Roger Morbey; Thomas House; Alex J Elliot; Sally Harcourt; Gillian E Smith
Journal:  BMC Public Health       Date:  2017-05-19       Impact factor: 3.295

2.  Seasonal and Monthly Patterns, Weekly Variations, and the Holiday Effect of Outpatient Visits for Type 2 Diabetes Mellitus Patients in China.

Authors:  Yanran Huang; Jiajing Li; Hongying Hao; Lizheng Xu; Stephen Nicholas; Jian Wang
Journal:  Int J Environ Res Public Health       Date:  2019-07-25       Impact factor: 3.390

3.  Accurate influenza forecasts using type-specific incidence data for small geographic units.

Authors:  James Turtle; Pete Riley; Michal Ben-Nun; Steven Riley
Journal:  PLoS Comput Biol       Date:  2021-07-29       Impact factor: 4.475

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.