2014.ISDS.Abstracts.Final.pdf


ISDS Annual Conference Proceedings 2014. This is an Open Access article distributed under the terms of the Creative Commons Attribution-
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ISDS 2014 Conference Abstracts

An Exploration of the H1N1 Outbreak in Champaign and 
Urbana Elementary Schools
Christopher Komisarz and Ian Brooks*

NCSA, University of Illinois, Urbana, IL, USA

Objective
The goal of this project is to examine the patterns of school 

absenteeism during the H1N1 pandemic of 2009 comparing two 
contiguous school districts with very different enrollment policies.

Introduction
Champaign and Urbana, Illinois are considered twin cities 

that share the University of Illinois. Due to different geographic 
recruitment procedures, Champaign and Urbana public elementary 
schools offer a particularly novel opportunity to examine the H1N1 
outbreak among students. Urbana schools recruit from specific 
geographic areas (neighborhoods) designated by the school district 
whereas Champaign schools are non-selective in their composition 
where students residing in Champaign can attend any school within 
the city.

Methods
Daily absence data from elementary schools in Champaign 

and Urbana school districts were obtained through the NCSA 
INDICATOR1 database. School population data were obtained from 
the Illinois State Board of Education annual school report cards2. Data 
were examined as a proportion of students within a school considered 
absent and mapped utilizing ArcMap 10.1 showing a time course 
of the percentage of students absent at each school for the period 
between September 8 and December 18 2009. Correlation analysis 
was used to examine relationships between specific demographics and 
absence patterns.

Results
In early October, both school districts showed an increase in 

overall absences with Urbana schools showing a quicker and more 
substantial increase in the beginning of the month then leveling off 
with a slight increase in later October. Champaign had a more gradual 
but substantial increase over the month of October peaking near the 
middle of the month and remained elevated for about two weeks. 
Both districts showed a drop in absences until late November when 
the Champaign schools saw another jump to nearly 8%. This was 
again followed by a decrease to pre-October absence percentages 
throughout the remainder of the semester. On an individual school 
level correlations between schools range from 0.692 to -.113 with 
a mean of 0.292 in Urbana indicating significant differences in the 
absence patterns. 9 of the 15 pairwise comparisons were significant 
at p<0.05. In Champaign the range was from to .817 to -.092 with a 
mean of 0.497. 51 of the 55 pairwise comparisons were significant 
at p<0.05.

Correlation analyses were used to determine trends among the 
variables. The only significant trends noted were among the student 
composition and the percentage of low income students. There were 
no significant correlations between the composition, number of 
students, or percent of low-income students and maximum or average 
absence proportion among the schools.

Conclusions
There is clear evidence from this small comparison that there 

is a difference in the pattern of disease spread depending on the 
geographic composition of the schools catchment area. In Urbana 
which uses traditional neighborhood schools only 60% of the pairwise 
epidemiological curves were significantly similar compared to 92.7% 
of the pairwise curves in Champaign. This shows that when students 
from the city are intermingled through a school district a disease 
epidemic spreads through the schools in a similar timeframe, whereas 
there is a greater temporal separation with neighborhood schools. The 
practical implication of this is that once an outbreak has been detected 
in a neighborhood school there may be time to prevent it spreading 
to other schools in the district, whereas with geographically mixed 
school an outbreak essentially hits all of the schools simultaneously.

Keywords
School absenteeism; H1N1 surveillance; Geographic analysis

Acknowledgments

The researchers would like to thank the Champaign and Urbana school 
districts; and Awais Vaid, MPH, MBBS.

References

1. W. Edwards, A. Vaid, and I. Brooks, “INDICATOR: An Open-
source Cyberenvironment for Biosurveillance,” in Defining Crisis
Management 3.0, Seattle, WA, 2010.

2. Illinois State Board of Education. (2010). 2010 Report Card Definitions
and Sources of Data (2010 ed.) [Brochure]

*Ian Brooks
E-mail: ian@ncsa.illinois.edu    

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * (1):e139, 201