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The Oregon Child Absenteeism Due to Respiratory Disease Study (ORCHARDS): Rationale, objectives, and design

Temte, Jonathan L. ; Barlow, Shari ; Goss, Maureen ; [et al.]

Wiley ; 2022

In: Influenza and Other Respiratory Viruses Vol. 16, No. 2 ( 2022-03), p. 340-350

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In: Influenza and Other Respiratory Viruses, Wiley, Vol. 16, No. 2 ( 2022-03), p. 340-350

Abstract: Influenza viruses pose significant disease burdens through seasonal outbreaks and unpredictable pandemics. Existing surveillance programs rely heavily on reporting of medically attended influenza (MAI). Continuously monitoring cause‐specific school absenteeism may identify local acceleration of seasonal influenza activity. The Oregon Child Absenteeism Due to Respiratory Disease Study (ORCHARDS; Oregon, WI) implements daily school‐based monitoring of influenza‐like illness‐specific student absenteeism (a‐ILI) in kindergarten through Grade 12 schools and assesses this approach for early detection of accelerated influenza and other respiratory pathogen transmission in schools and surrounding communities. Methods Starting in September 2014, ORCHARDS combines automated reporting of daily absenteeism within six schools and home visits to school children with acute respiratory infection (ARI). Demographic, epidemiological, and symptom data are collected along with respiratory specimens. Specimens are tested for influenza and other respiratory viruses. Household members can opt into a supplementary household transmission study. Community comparisons are possible using a pre‐existing and highly effective influenza surveillance program, based on MAI at five family medicine clinics in the same geographical area. Results Over the first 5 years, a‐ILI occurred on 6634 (0.20%) of 3,260,461 student school days. Viral pathogens were detected in 64.5% of 1728 children with ARI who received a home visit. Influenza was the most commonly detected virus, noted in 23.3% of ill students. Conclusion ORCHARDS uses a community‐based design to detect influenza trends over multiple seasons and to evaluate the utility of absenteeism for early detection of accelerated influenza and other respiratory pathogen transmission in schools and surrounding communities.

Type of Medium: Online Resource

ISSN: 1750-2640 , 1750-2659

URL: Issue

URL: Article

DOI: 10.1111/irv.v16.2

DOI: 10.1111/irv.12920

Language: English

Publisher: Wiley

Publication Date: 2022

detail.hit.zdb_id: 2272349-3

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Cause-specific student absenteeism monitoring in K-12 schools for detection of increased influenza activity in the surrounding community—Dane County, Wisconsin, 2014–2020

Temte, Jonathan L. ; Barlow, Shari ; Goss, Maureen ; [et al.]

Public Library of Science (PLoS) ; 2022

In: PLOS ONE Vol. 17, No. 4 ( 2022-4-19), p. e0267111-

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In: PLOS ONE, Public Library of Science (PLoS), Vol. 17, No. 4 ( 2022-4-19), p. e0267111-

Abstract: Schools are primary venues of influenza 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. Materials and methods Between September 2014 and March 2020, we conducted a 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 (OSD), Dane County, Wisconsin. Absenteeism was reported through the electronic student information system. Students were visited at home where pharyngeal specimens were collected for influenza RT-PCR testing. Surveillance of medically-attended laboratory-confirmed influenza (MAI) occurred in five primary care clinics in and adjoining the OSD. Poisson general additive log linear regression models of daily counts of absenteeism and MAI were compared using correlation analysis. Findings Influenza was detected in 723 of 2,378 visited students, and in 1,327 of 4,903 MAI patients. Over six influenza seasons, a-ILI was significantly correlated with MAI in the community (r = 0.57; 95% CI: 0.53–0.63) with a one-day lead time and a-I was significantly correlated with MAI in the community (r = 0.49; 0.44–0.54) with a 10-day lead time, while a-TOT performed poorly (r = 0.27; 0.21–0.33), following MAI by six days. Discussion Surveillance using cause-specific absenteeism was feasible and performed well over a study period marked by diverse presentations of seasonal influenza. Monitoring a-I and a-ILI can provide early warning of seasonal influenza in time for community mitigation efforts.

Type of Medium: Online Resource

ISSN: 1932-6203

URL: Article

DOI: 10.1371/journal.pone.0267111

DOI: 10.1371/journal.pone.0267111.g001

DOI: 10.1371/journal.pone.0267111.g002

DOI: 10.1371/journal.pone.0267111.g003

DOI: 10.1371/journal.pone.0267111.g004

DOI: 10.1371/journal.pone.0267111.g005

DOI: 10.1371/journal.pone.0267111.t001

DOI: 10.1371/journal.pone.0267111.t002

DOI: 10.1371/journal.pone.0267111.t003

DOI: 10.1371/journal.pone.0267111.t004

DOI: 10.1371/journal.pone.0267111.t005

DOI: 10.1371/journal.pone.0267111.s001

DOI: 10.1371/journal.pone.0267111.s002

DOI: 10.1371/journal.pone.0267111.r001

DOI: 10.1371/journal.pone.0267111.r002

DOI: 10.1371/journal.pone.0267111.r003

DOI: 10.1371/journal.pone.0267111.r004

DOI: 10.1371/journal.pone.0267111.r005

DOI: 10.1371/journal.pone.0267111.r006

Language: English

Publisher: Public Library of Science (PLoS)

Publication Date: 2022

detail.hit.zdb_id: 2267670-3

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