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ISDS 2016 Conference Abstracts

Using Syndromic Surveillance Alert Protocols for 
Epidemiologic Response in Georgia
Rene Borroto*1, Bill Williamson1, Patrick Pitcher1, Lance Ballester2, Wendy Smith1, 
Karl Soetebier1 and Cherie Drenzek1
1Georgia Department of Public Health, Atlanta, GA, USA; 2Emory University, Atlanta, GA, USA

Objective
Describe how the Georgia Department of Public Health (DPH) uses 

syndromic surveillance to initiate review by District Epidemiologists 
(DEs) to events that may warrant a public health response (1).

Introduction
DPH uses its State Electronic Notifiable Disease Surveillance 

System (SendSS) Syndromic Surveillance (SS) Module to collect, 
analyze and display results of emergency department patient chief 
complaint data from hospitals throughout Georgia.

Methods
DPH prepares a daily SS report, based upon the analysis of 

daily visits to 112 Emergency Department (EDs). The visits are 
classified in 33 syndromes. Queries of chief complaint and discharge 
diagnosis are done using the internal query capability of SendSS-SS 
and programming in SAS/BASE. Charting of the absolute counts 
or percentage of ED visits by syndromes is done using the internal 
charting capability of SendSS-SS. A daily SS report includes the 
following sections: Statewide Emergency Department Visits 
by Priority Syndromes (Bioterrorism, BloodyRespiratory, 
FeverRespiratory, FeverChest, FeverFluAdmit, FeverFluDeaths, 
VeryIll, and PoxRashFever, Botulism, Poison, BloodyDiarrhea, 
BloodyVomit, FeverGI, ILI, FeverFlu, RashFever, Diarrhea, 
Vomit). Statewide Flag Analysis: Is intended to detect statewide 
flags, by using the Charts capability in SendSS SS. Possible cases 
with presumptive diagnosis of potentially notifiable diseases: Is 
intended to provide early-warning to the DEs of possible cases that 
are reportable to public health immediately or within 7 days using 
queries in the Chief Complaint and Preliminary Diagnosis fields of 
SendSS-SS. Possible clusters of illness: Since any cluster of illness 
must be reported immediately to DPH, this analysis is aimed at 
querying and identifying possible clusters of patients with similar 
symptoms (2). Possible travel-related illness: Is intended to identify 
patients with symptoms and recent travel history. Other events of 
interest: Exposures to ill patients in institutional settings (e.g. chief 
complaint indicates that other children in the daycare have similar 
symptoms). Trend Analysis: Weekly analysis of seasonality and 
trends of 14 syndromes. Finally, specific events are notified to and 
reviewed by the 18 DEs, who follow up by contacting the Infection 
Preventionists of the hospitals to identify the patients using medical 
records or other hospital-specific identification numbers and follow 
up on the laboratory test results.

Results
Since 05/15/2016, 12 travel-related illnesses, 29 vaccine-

preventable diseases, 14 clusters, and 3 chemical exposures have 
been notified to DEs. For instance, a cluster of chickenpox in children 
was identified after the DE contacted the Infection Preventionist of 
a hospital, who provided the DE with the laboratory results and the 
physician notes about the symptoms of the patients. These actions 
have resulted in earlier awareness of single cases or cluster of illness, 
prompt reporting of notifiable diseases, and successful interaction 

between DEs and health care providers. In addition, SS continues to 
track the onset, peak, and decline of seasonal illnesses.

Conclusions
The implementation of SS in the State of Georgia is helping with 

the timely detection and early responses to disease events and could 
prove useful in reducing the disease burden caused by a bioterrorist 
attack.

Keywords
syndromic; reports; queries; charts

References
1. W Cameron, A Neu, E Murray, K Soetebier, S Cookson. Responding

to Syndromic Surveillance Alerts: An Adaptable Protocol for 
Georgia Health Districts. In: https://www.researchgate.net/
publication/266093117_Responding_to_Syndromic_Surveillance_
Alerts_An_Adaptable_Protocol_for_Georgia_Health_Districts

2. G Zhang, A Llau, J Suarez, E O’Connell, E Rico, R Borroto, 
F Leguen. Using ESSENCE to Track a Gastrointestinal Outbreak in a 
Homeless Shelter in Miami-Dade County, 2008. Advances in Disease 
Surveillance. 2008; 5:139.

*Rene Borroto
E-mail: rene.borroto@dph.ga.gov

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 9(1):e123, 2017