Innovative Uses for ESSENCE to Improve Standard Communicable Disease Reporting Practices in Miami-Dade County

To illustrate how ESSENCE can been utilized to collaborate with healthcare practitioners in order to improve communicable disease reporting

July 30, 2018

North Texas School Health Surveillance: First-Year Progress and Next Steps

Recognizing the threat of pandemic influenza and new or emerging disease such as SARS, the U.S.

July 30, 2018

Support Vector Machines for Syndromic Surveillance

Early and reliable detection of anomalies is a critical challenge in disease surveillance. Most surveillance systems collect data from multiple data streams but the majority of monitoring is performed at univariate time series level. Purely statistical methods used in disease surveillance look at each time series separately and tend to generate a large number of false alarms. Support Vector Machines can be used to develop rich multivariate models that allow detecting abnormal relationships between different time series leading to greatly reduced number of false alarms.


July 30, 2018

Using ESSENCE to Track a Gastrointestinal Outbreak in a Homeless Shelter in Miami-Dade County, 2008

Although Electronic Surveillance System for the Early Notification of Community Based Epidemics (ESSENCE) provides tools to detect a significant alert regarding an unusual public health event, combining that information with other surveillance data, such as 911 calls, school absenteeism and poison control records, has proved to be more sensitive in detecting an outbreak.

July 30, 2018

Components of Inter-Hospital Variability in Chief Complaints Assigned to a Gastrointestinal Syndrome

Patient’s chief complaint (CC) is often used for syndromic surveillance for bioterrorism and outbreak detection, but little is known about the inter-hospital variability in the sensitivity of this method. Objective: Our objective was to characterize the variability of a gastrointestinal (GI) CC text-matching algorithm.

July 30, 2018

Translational Research for Surveillance

Presented January 28, 2008

January 26, 2019

Dual Monitoring of ILI Syndrome Using the ESSENCE System

The threat of terrorism and high-profile disease outbreaks has drawn attention to public health syndromic surveillance systems for early detection of natural or man-made disease events. In this sense, the Miami-Dade County Health Department has implemented ESSENCE (Electronic Surveillance System for the Early Notification of Community-based Epidemics) in 2005; which has been developed and updated by the Johns Hopkins University.



July 30, 2018

GUARDIAN: Geographic Utilization of Artificial Intelligence in Real-Time for Disease Identification and Notification

Real-time disease surveillance is critical for early detection of the covert release of a biological threat agent (BTA). Numerous software applications have been developed to detect emerging disease clusters resulting from either naturally occurring phenomena or from occult acts of bioterrorism. However, these do not focus adequately on the diagnosis of BTA infection in proportion to the potential risk to public health.

July 30, 2018

Exercise Demonstrates Effective Syndromic Surveillance Response Process

Currently, Indiana monitors emergency department patient chief complaint data from 73 geographically dispersed hospitals. These data are analyzed using the Electronic Surveillance System for the Early Notification of Community-based Epidemics application. 

July 30, 2018

Use of Epidemiological Knowledge to Create Syndromic Surveillance Reports

Syndromic surveillance is an investigational approach used to monitor trends of illness in communities. It relies on pre-diagnostic health data rather than laboratory-confirmed clinical diagnoses. Its primary purpose is to detect disease outbreaks, incidents and unusual public health events earlier than possible with traditional public health surveillance methods.



July 30, 2018


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