Predicting virologically confirmed influenza using school absences in Allegheny County, Pennsylvania, USA during the 2007-2015 influenza seasons.

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Abstrakt

Tytuł:: Predicting virologically confirmed influenza using school absences in Allegheny County, Pennsylvania, USA during the 2007-2015 influenza seasons.
Autorzy:: Quandelacy TM; Johns Hopkins University, Baltimore, MD, USA.; University of Colorado, Anschutz Medical Campus, Aurora, CO, USA.
Zimmer S; University of Pittsburgh, Pittsburgh, PA, USA.; University of Colorado, Denver, CO, USA.
Lessler J; Johns Hopkins University, Baltimore, MD, USA.
Vukotich C; University of Pittsburgh, Pittsburgh, PA, USA.
Bieltz R; University of Pittsburgh, Pittsburgh, PA, USA.
Grantz KH; University of Florida, Gainesville, FL, USA.
Galloway D; University of Pittsburgh, Pittsburgh, PA, USA.
Read JM; Lancaster University, Lancaster, UK.
Zheteyeva Y; Centers for Disease Control and Prevention, Atlanta, GA, USA.
Gao H; Centers for Disease Control and Prevention, Atlanta, GA, USA.
Uzicanin A; Centers for Disease Control and Prevention, Atlanta, GA, USA.
Cummings DAT; Johns Hopkins University, Baltimore, MD, USA.; University of Florida, Gainesville, FL, USA.
Źródło:: Influenza and other respiratory viruses [Influenza Other Respir Viruses] 2021 Nov; Vol. 15 (6), pp. 757-766. Date of Electronic Publication: 2021 Sep 03.
Typ publikacji:: Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, P.H.S.
Język:: English
Imprint Name(s):: Original Publication: Oxford, UK : Wiley, c2007-
MeSH Terms:: Influenza, Human*/diagnosis
Influenza, Human*/epidemiology
Child ; Humans ; Pennsylvania/epidemiology ; Schools ; Seasons ; Temperature
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Grant Information:: U01 CK000337 United States CK NCEZID CDC HHS
Contributed Indexing:: Keywords: human influenza; prediction; school-aged children; surveillance
Entry Date(s):: Date Created: 20210903 Date Completed: 20211125 Latest Revision: 20211125
Update Code:: 20240105
PubMed Central ID:: PMC8542956
DOI:: 10.1111/irv.12865
PMID:: 34477304
: Czasopismo naukowe

Pełny tekst

Background: Children are important in community-level influenza transmission. School-based monitoring may inform influenza surveillance.
Methods: We used reported weekly confirmed influenza in Allegheny County during the 2007 and 2010-2015 influenza seasons using Pennsylvania's Allegheny County Health Department all-age influenza cases from health facilities, and all-cause and influenza-like illness (ILI)-specific absences from nine county school districts. Negative binomial regression predicted influenza cases using all-cause and illness-specific absence rates, calendar week, average weekly temperature, and relative humidity, using four cross-validations.
Results: School districts reported 2 184 220 all-cause absences (2010-2015). Three one-season studies reported 19 577 all-cause and 3012 ILI-related absences (2007, 2012, 2015). Over seven seasons, 11 946 confirmed influenza cases were reported. Absences improved seasonal model fits and predictions. Multivariate models using elementary school absences outperformed middle and high school models (relative mean absolute error (relMAE) = 0.94, 0.98, 0.99). K-5 grade-specific absence models had lowest mean absolute errors (MAE) in cross-validations. ILI-specific absences performed marginally better than all-cause absences in two years, adjusting for other covariates, but markedly worse one year.
Conclusions: Our findings suggest seasonal models including K-5th grade absences predict all-age-confirmed influenza and may serve as a useful surveillance tool.
(© 2021 The Authors. Influenza and Other Respiratory Viruses published by John Wiley & Sons Ltd.)

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