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686. Use of an Influenza-Like Illness School Absenteeism Monitoring System to Identify Seasonal Influenza Outbreaks in the Community: ORCHARDS (Wisconsin, September 2014–June 2017)
Author(s) -
Jonathan L. Temte,
Yenlik Zheteyeva,
Shari Barlow,
Maureen Goss,
Emily Temte,
Amber Schemmel,
Brad Maerz,
Cristalyne Bell,
Erik Reisdorf,
Peter Shult,
Mary Wedig,
Thomas Haupt,
James H. Conway,
Ronald E. Gang,
Ashley Fowlkes,
Amra Uzicanin
Publication year - 2018
Publication title -
open forum infectious diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.546
H-Index - 35
ISSN - 2328-8957
DOI - 10.1093/ofid/ofy210.693
Subject(s) - medicine , absenteeism , poisson regression , outbreak , logistic regression , incidence (geometry) , influenza like illness , epidemiology , demography , environmental health , immunology , virology , virus , population , physics , management , sociology , optics , economics
Background Schools are purported to be primary venues of influenza transmission and amplification with secondary spread to communities. We assessed K—12 student absenteeism monitoring as a means for early detection of influenza activity in the community. Methods. We conducted a 3-year, prospective observational study of all-cause (a-TOT), illness-associated (a-I), and influenza-like illness-associated (a-ILI) absenteeism within the Oregon School District, Oregon, WI (OSD: enrollment = 3,900 students). Absenteeism reporting was facilitated by automated processes within OSD’s electronic student information system. Students were screened for ILI, and, if eligible, visited at home, where pharyngeal specimens were collected for influenza RT-PCR (IVD CDC Human Influenza Virus RT-PCR Diagnostic Panel) and multipathogen testing (Luminex NxTAG RPP). The study definition of a-ILI was validated for 700 children with acute respiratory infections using binomial logistic regression. Surveillance of medically attended laboratory-confirmed influenza (MAI) occurred in five primary care clinics in and adjoining OSD as part of the Wisconsin Influenza Incidence Surveillance Project using the same laboratory testing. Poisson general additive log linear regression models of daily counts of absenteeism and MAI were compared using correlation analysis. Results. Influenza A and B were detected in 54 and 51 of the 700 visited students, respectively. Influenza was significantly associated with a-ILI status (OR = 4.74; 95% CI: 2.78—8.18; P < 0.001). Of MAI patients, 371 had influenza A and 143 had influenza B. a-I was significantly correlated with MAI in the community (r = 0.472; P < 0.001) with a 15-day lead time. a-ILI was significantly correlated with MAI in the community (r = 0.480; P < 0.001) with a 1-day lead time. a-TOT performed poorly (r = 0.278; P < 0.001), following MAI by 9 days (Figure 1). Conclusion. Surveillance using cause-specific absenteeism was feasible to implement in OSD and performed well over a 3-year period marked by diverse presentations of seasonal influenza. Monitoring a-I and a-ILI can detect influenza outbreaks in the community, providing early warning in time for community mitigation efforts for seasonal and pandemic influenza. Disclosures All authors: No reported disclosures.

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