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)
Session: Poster Abstract Session: Public Health: Epidemiology and Outbreaks
Thursday, October 4, 2018
Room: S Poster Hall
Posters
  • IDWeek 2018 ORCHARDS.pdf (845.1 kB)
  • 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.

    Jonathan Temte, MD, PhD1, Yenlik Zheteyeva, MD, MPH2, Shari Barlow, BA1, Maureen Goss, MPH1, Emily Temte, BA1, Amber Schemmel, BS1, Brad Maerz, MS1, Cristalyne Bell, BA1, Erik Reisdorf, MPH3, Peter Shult, PhD3, Mary Wedig, BS3, Thomas Haupt, MS4, James Conway, MD FAAP5, Ronald Gangnon, PhD6, Ashley Fowlkes, MPH7 and Amra Uzicanin, MD, MPH8, (1)Family Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, (2)Centers for Disease Control and Prevention, Atlanta, GA, (3)Communicable Disease Division, Wisconsin State Laboratory of Hygiene, Madison, WI, (4)Bureau of Communicable Diseases, Wisconsin Division of Public Health, Madison, WI, (5)Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI, (6)Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin - Madison, Madison, WI, (7)Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, (8)CDC, Atlanta, GA

    Disclosures:

    J. Temte, None

    Y. Zheteyeva, None

    S. Barlow, None

    M. Goss, None

    E. Temte, None

    A. Schemmel, None

    B. Maerz, None

    C. Bell, None

    E. Reisdorf, None

    P. Shult, None

    M. Wedig, None

    T. Haupt, None

    J. Conway, None

    R. Gangnon, None

    A. Fowlkes, None

    A. Uzicanin, None

    Findings in the abstracts are embargoed until 12:01 a.m. PDT, Wednesday Oct. 3rd with the exception of research findings presented at the IDWeek press conferences.