2014.ISDS.Abstracts.Final.pdf


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ISDS 2014 Conference Abstracts

Creating a Local Geographic Influenza-like Illness 
Activity Report

Dino Rumoro1, Shital Shah1, Gordon Trenholme1, Gillian Gibbs*1, Marilyn Hallock1 and 
Michael J. Waddell2

1Emergency Medicine, Rush University Medical Center, Chicago, IL, USA; 2Pangaea Information Technologies, Chicago, IL, USA

Objective
To create a local geographic influenza-like illness (ILI) activity 

report.

Introduction
Mapping ILI surveillance data can be useful in identifying the 

direction and speed of an outbreak and for focusing control measures 
for an efficient public health response. The Centers for Disease 
Control and Prevention’s (CDC) ILINet currently displays weekly 
ILI geographic data at a national/regional/state level, but this visual 
data could also be useful at the local level.

Methods
The data elements that were included in this study were: daily 

emergency department (ED) ILI rate, 7 day moving average ED ILI 
rate, zip code, and date from October 1, 2013 to March 31, 2014. The 
data region was the catchment area of an urban academic medical 
center (AMC). The data were processed using the GUARDIAN 
(Geographic Utilization of Artificial Intelligence in Real-Time for 
Disease Identification and Alert Notification) surveillance system. 
We created the following derived variables in percentages:

• ILI within a zip code = ILI positive ED visits within zip code/total 
ED visits within zip code

• Proportion of zip code ILI with regional ILI = ILI positive ED
visits within zip code/ total ILI positive ED visits within the AMC 
region

• Zip code representation = total ED visits within zip code/total ED 
visits within the AMC region

These three variables provide information on the relative 
importance of the ILI rate within a zip code compared to the overall 
ILI rate within the AMC region. These trends were utilized to generate 
rules for the development of a color coded zip code map, as follows:

• White represents no data available or 0% of total ED visits within 
the AMC region are in the zip code

• Gray represents insufficient data or <10% and > 0% of total ED
visits within the AMC region are in the zip code

• Green represents within normal limits and requires 10% of total 
ED visits within the AMC region are in the zip code AND ILI rate is 
below 10% within the zip code

• Yellow represents more than 2 standard deviations above the
mean and requires  10% of total ED visits within the AMC region 
are in the zip code AND ILI rate is between 10% and 12.5% within 
the zip code

• Orange  represents more than 20% of all positive ILI cases come 
from that zip code within the AMC region

• Red represents more than 3 standard deviations above the mean
and requires 10% of total ED visits within the AMC region are in the 
zip code AND ILI rate is above 12.5% within the zip code

The thresholds utilized in the rules were either generated through 
historical statistical analysis or based on the need for an adequate 
sample size. The rules were translated into the GUARDIAN system, 
which auto-generates daily reports of geographic ILI activity at the 
AMC.

Results
Each morning, the GUARDIAN reporting module generates a map 

for the AMC’s current 7-day moving average ILI rate by zip code 
(Figure 1). The resulting map and a summary table are combined 
into a PDF document and emailed out to the response team at the 
AMC. In addition, an interactive web-based version of the map is 
made available through the GUARDIAN user interface, which allows 
clinicians to review individual patient’s charts.

Conclusions
The ILI activity report provides zip code level geographic analysis 

of ILI prevalence using the developed color scheme. With additional 
data, such as multiple ED sites and temporal information, the ILI 
activity maps could be further enhanced to capture spatial/temporal 
changes in ILI rates within the broader region (e.g., metropolitan area, 
state level, or CDC region). These daily auto-generated geographic 
reports can be utilized by clinical and public health personnel for 
monitoring ILI activity within their regions, as well as initiating 
appropriate emergency management protocols.

Figure 1: Map of the seven day moving average ILI rate by zip code on January 
14, 2014.

Keywords
Influenza-like illness surveillance; GUARDIAN; GIS

Acknowledgments

GUARDIAN is funded by the US Department of Defense, Telemedicine 
and Advanced Technology Research Center, Award numbers 
W81XWH-09-1-0662 and W81XWH-11-1-0711.

*Gillian Gibbs

E-mail: Gillian_Gibbs@rush.edu    

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 7(1):e155, 2015