6th Annual Public Health Information Network Conference: Evaluation of Syndrome-Specific School Absenteeism Data for Public Health Surveillance

Sunday, August 24, 2008

South/West Halls

Shuying Shen, Master, of, Statistics , Division of Epidemiology, COE Public Health Informatics, University of Utah, Salt Lake City, UT

Nicole Stone, MPH , Davis County Health Department, Farmington, UT

Brian Hatch, MPH , Davis County Health Department, Farmington, UT

Lisa Wyman, MPH , Bureau of Epidemiology, Utah Department of Health, Salt Lake City, UT

Robert T. Rolfs, MD, MPH , Utah Department of Health, Salt Lake City, UT

Brett R. South, MS , Division of Epidemiology, COE Public Health Informatics, University of Utah, Salt Lake City, UT

Adi Gundlapalli, MD, PhD, MS , Internal Medicine, University of Utah, Salt Lake City, UT

Catherine Staes, BSN, MPH, PhD , Dept of Biomedical Informatics, University of Utah, Salt Lake City, UT

Matthew Samore, MD , Internal Medicine, University of Utah, Salt Lake City, UT

Slides

BACKGROUND

School absenteeism data could be used as an early indicator for disease outbreaks. The increase in absences, however, may be driven by non-sickness related factors. Reason for absence combined with syndrome-specific information might improve the utility of absenteeism data for early outbreak detection. A collaborative project was initiated under the Utah COE in Public Health Informatics to evaluate and improve an information system collecting syndrome-specific school absenteeism. The present study is a pilot evaluation to determine the usefulness of the system for public health surveillance.

METHODS

Ten public elementary schools in Davis County in Utah were selected as sentinel schools to collect syndrome-specific school absenteeism in addition to reason for absence. Reasons for absence include sick, other, and unknown. Syndromes include respiratory, GI, rash, other, and unknown. Clerks entered daily absences through a web-based information system and these data were available in real-time to the county surveillance coordinators. Data from September 1, 2007 to March 14, 2008 were extracted to generate descriptive statistics.

RESULTS

Average daily absence per 100 enrolled students was 4.02 for total absences, and 0.9 for sick absences. The most common reason for absence was unknown (59%), followed by sick (23%) and other (18%). Other sickness-related absences accounted for 38% of the sick absences, followed by unknown (26%), GI (18%), respiratory (16%), and rash (0.6%). There was a seasonal trend of decreasing GI-related absences, and increasing respiratory-related absences going from the fall to the winter (Figure 1).

CONCLUSION

The enhanced school absenteeism data from Davis County provided timely information about the reason for absences at the syndrome level, which would be useful for targeted surveillance. Longer follow-up is required to evaluate the impact of non-sickness related factors such as school holidays on reason for absenteeism. Specificity of data could be improved by encouraging reports from parents.

Winter Recess