ESSENCE

Previously we used an “N-Gram” classifier for syndromic surveillance of emergency department (ED) chief complaints (CC) in English for bioterrorism. The classifier is trained on a set of ED visits for which both the ICD diagnosis code and CC are available by measuring the associations of text fragments within the CC (e.g. 3 characters for a “3-gram”) with a syndromic group of ICD codes. Because the ICD system is language independent, the technique has the potential advantage of rapid automated deployment in multiple languages. Our objective was to apply the N-Gram method to a training set of Turkish ED data to create a Turkish CC classifier for the respiratory syndrome (RESP) and determine its performance in a test set.

Objective

To determine how closely the performance of an ngram CC classifier for the RESP syndrome matched the performance of the ICD9 classifier.

Varied approaches have been used by syndromic surveillance systems for aberration detection. However, the performance of these methods has been evaluated only across a small range of epidemic characteristics.

Objective

We conducted a large simulation study to evaluate the detection properties of 6 different algorithms across a range of outbreak characteristics.

On October 24, 2005, Hurricane Wilma made landfall on the southwest coast of Florida as a category 3 storm. The storm moved toward the northeast and passed through Palm Beach and Broward Counties before entering the Atlantic Ocean. Hurricane force winds and rain caused extensive damage to electrical infrastructure and traffic lights, and temporarily displaced thousands of residents. Power outages in Broward County affected over 90% of its 1.8 million residents, with some outages lasting >2 weeks. Boil water notices were declared for much of the county. Acute care hospitals remained open during this time, although services provided by health care providers in other settings were interrupted due to structural damage and power outages.

Objective

We used the syndromic surveillance system ESSENCE to describe the morbidity after Hurricane Wilma in Broward County, Florida.

Syndromic surveillance is the surveillance of healthrelated data that precedes diagnosis to detect a disease outbreak or other health related event that warrants a public health response. Though syndromic surveillance is typically utilized to detect infectious disease outbreaks, its utility to detect bioterrorism events is increasingly being explored by public health agencies. Many agencies believe that syndromic surveillance holds great promise in enhancing our ability to detect both planned and unplanned outbreaks of disease and have made significant investments to develop syndromic surveillance capabilities.

For instance, the Centers for Disease Control and Prevention has invested in Biosense and the Department of Defense has invested in the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) which it has deployed in partnership with the Department of Veterans Affairs. The Department of Homeland Security has invested heavily in the National Bio-surveillance Integration System which integrates a broad spectrum of bio-surveillance information including data from Biosense and ESSENCE. The University of Pittsburgh has also developed a prominent tool and is considered a thought leader in this space.

Despite the significant investments in the area of syndromic surveillance, the technology is young and the relatively small field remains fragmented. As a result, there is limited public information that addresses the field as a whole.

Objective

The objective of this assessment is to research, develop and maintain a national syndromic surveillance registry that describes each system’s configuration. By collecting current information on the leading systems we will gain a greater understanding of the syndromic surveillance landscape and capabilities.

When the Chicago Bears met the Indianapolis Colts for Super Bowl XLI in Miami in January, 2007, fans from multiple regions visited South Florida for the game. In the past, public health departments have instituted heightened local surveillance during mass gatherings due to concerns about increased risk of disease outbreaks. For the first time, in 2007, health departments in all three Super Bowl-related regions already practiced daily disease surveillance using biosurveillance information systems (separate installations of the ESSENCE system, developed at JHUAPL). The situation provided an opportunity to explore ways in which separate surveillance systems could be coordinated for effective, short-term, multijurisdictional surveillance.

Objective

This paper describes an inter-jurisdictional surveillance data sharing effort carried out by public health departments in Miami, Chicago, and Indianapolis in conjunction with Super Bowl XLI.

The 2005 Youth Risk Behavior Survey of 9th to 12th graders in Miami-Dade County public schools found that 69.7% of students tried alcohol, 28.3% tried marijuana, and 6.3% tried cocaine in their lifetime. Results also showed that Hispanics had a higher percentage of usage when compared to Blacks or Whites. The 2007 White House Office of National Drug Control Policy special report entitled “Hispanic Teens and Drugs” also concluded that Hispanics were at the highest risk for substance abuse. With the county’s 60% Hispanic population, this issue is of concern for the community. This is the first study to compare multiple sources of data to describe substance abuse among youth from areas such as healthcare utilization to criminal charges.

In 2004, the Indiana State Department of Health (ISDH) partnered with the Regenstrief Institute to begin collecting syndromic data from 14 ED’s to monitor bioterrorism-related events and other public health emergencies. Today, Indiana’s public health emergency surveillance system (PHESS) receives approximately 5,000 daily ED visits as real-time HL7 formatted surveillance data from 55 hospitals. The ISDH analyzes these data using ESSENCE and initiates field investigations when human review deems necessary.1 The Marion County Health Department, located in the state’s capitol and most populous county, is the first local health department in Indiana using ESSENCE.

Objective

This paper describes how local and state stakeholders interact with Indiana’s operational PHESS, including resources allocated to syndromic surveillance activities and methods for managing surveillance data flow. We also describe early successes of the system.

This paper describes lessons learned from a regional tabletop exercise (TTX) of the National Capital Region (NCR) Syndromic Surveillance Network, from the perspective of the Maryland Department of Health and Mental Hygiene (DHMH).

Since October 2004, the Indiana State Health Department and the Marion County Health Department have been developing and using a syndromic surveillance system based on emergency department admission data. The system currently receives standards-based HL7 emergency department visit data, including free-text chief complaints from 72 hospitals throughout the state. Fourteen of these hospitals are in Marion County, which serves the Indianapolis metropolitan region (population 865,000).

Objective

This paper describes how a syndromic surveillance system based on emergency department data may be leveraged for other public health uses.

In the spring of 2005, the ISDH began using Electronic Surveillance System for the Early Notification of Community-based Epidemics  (ESSENCE) application to analyze emergency department (ED) chief complaint data for syndromic surveillance purposes.  While granting hospitals and local health departments access to their data through ESSENCE has been desirable since the start of the PHESS project, an aggressive timeline made it necessary to direct all resource capacity toward first establishing hospital ED data connections.  The Marion County Health Department (Indianapolis) was the only LHD in the state with access to its 14 hospitals through ESSENCE.

However, because hospitals and local health departments (except Marion County) did not have access to their data through ESSENCE, any syndromic alert follow-up conducted by the ISDH was accomplished primarily by telephone.   This method, while feasible, was inefficient.  The ISDH felt that alert data follow-up could be greatly facilitated if hospitals and LHDs could view these data through ESSENCE just as the ISDH was doing.

Objective

This paper describes how the Indiana State Department of Health (ISDH) improved response capability by increasing local health department (LHD) and hospital access to syndromic surveillance data as part of the stateís evolving Public Health Emergency Surveillance System (PHESS).