Standards

Cross-jurisdictional sharing of public health syndrome data is useful for many reasons, among them to provide a larger regional or national view of activity and to determine if unusual activity observed in one jurisdiction is atypical. Considerable barriers to sharing of public health data exist, including maintaining control of potentially sensitive data and having informatics systems available to take and view data. The Distribute project [1,2] has successfully enabled cross-jurisdictional sharing of ILI syndrome data through a community of practice approach to facilitate control and trust, and a distributed informatics solution. The Gossamer system [3] incorporates methods used in several UW projects including Distribute. Gossamer has been designed in a modular fashion to be hosted using virtual or physical machines, including inside cloud environments. Two modules of the Gossamer system are designed for aggregate data sharing, and provide a subset of the Distribute functionality. The Distribute and Gossamer systems have been used for ad-hoc sharing in three different contexts; sharing of common ILI data for research into syndrome standardization, sharing syndromic data for specific events (2010 Olympics) and for pilot regional sharing of respiratory lab results. Two additional projects are underway to share specific syndromes of recent interest: alcohol related and heat related ED visits.

Objective

To demonstrate how rapid adhoc sharing of surveillance data can be achieved through informatics methods developed for the Distribute project.

In the last decade, the scope of public health (PH) surveillance has grown, and biosurveillance capacity has expanded in Duval County. In 2004, the Duval County Health Department (DCHD) implemented a standalone syndromic surveillance (SS) system which required the manual classification and entry of emergency department (ED) chief complaints by hospital staff. At that time, this system, in conjunction with other external systems (e.g. CDC ILInet, FluStar, NRDM) were used to conduct surveillance for health events. Recommendations from a 2007 ISDS panel were used to strengthen surveillance within Duval County. Later that year, the Florida DOH moved to a statewide SS system and implemented ESSENCE which has been expanded to include 1) ED record data from 176 hospitals (8 within Duval County); 2) Reportable disease case records from Merlin; 3) Florida Poison Information Network consultations; and, 4) Florida Office of Vital Statistics death records (1). ESSENCE has subsequently become a platform for rapid data analysis, mapping, and visualization across several data sources (1). As a result, ESSENCE has improved business processes within DCHD well beyond the initial scope of event detection. These improvements have included 1) expansion of the ability to create visualizations (e.g. epi-curves, charts, and maps); 2) reduction in the time required to produce reports (e.g. newsletters, media responses); 3) reduction in staff training needs; and 4) augmentation of epidemiology processes (e.g. active case finding, emergency response, quality improvement (QI)), and closing the PH surveillance loop.

Objective

This paper reviews the evolution of biosurveillance in Duval County, FL and characterizes the subsequent improved execution of epidemiology functions as a result of the implementation of the Early Notification of Community-based Epidemics (ESSENCE) system.

Washoe County District Health Department (WCDHD) is a local health district serving nearly 400,000 residents in Washoe County including cities of Reno and Sparks, the second largest urban area in Nevada. To enhance overall public health surveillance capacities in the agency, WCDHD officially implemented National Retail Data Monitor (NRDM) in September 2004, Real-time Outbreak & Disease Surveillance (RODS) in July 2005, and FirstWatch in August 2005. These three systems monitor over-the-counter sales for medications and healthcare products, chief complaints at emergency room visits, and 911 calls, respectively. Preliminary evaluation of NRDM suggested the usefulness of system. The addition of RODS and FirstWatch also demonstrated the utility in assisting outbreak investigation during the past few months. Unfortunately no written protocols are in place to guide program staff to manage alerts in a standardized fashion and make appropriate responses. Such guidelines from federal or state level are not yet available as we are aware, however, such protocol is highly needed.

Objective

The objective of this paper is to describe the standard operation procedures for three existing syndromic surveillance systems in WCDHD, Nevada.

This paper describes the evaluation of an electronic disease surveillance system implemented in the Peruvian Army following the 2001 CDC surveillance evaluation guidelines.

There exists no standard set of syndromes for syndromic surveillance, and available syndromic case definitions demonstrate substantial heterogeneity of findings constituting the definition. Many syndromic case definitions require the presence of a syndromic finding (e.g., cough or diarrhea) and a fever.

 

Objective

Automated syndromic surveillance systems often use chief complaints as input. Our objective was to determine whether chief complaints accurately represent whether a patient has any of the following febrile syndromes: Febrile respiratory, febrile gastrointestinal, febrile rash, febrile neurological, or febrile hemorrhagic.

Within the syndromic surveillance literature there are acknowledged gaps with respect to penetration of syndromic surveillance systems and standard or promising practices for response. The lack of adequate data and evidence-based policy recommendations on response is especially concerning because syndromic surveillance systems are only as useful as the timely pubic health response launched after aberration detection. We undertook the first step of a multi-phase study, with the global objectives of describing existing infrastructure in responding to alerts generated by syndromic surveillance systems and creating response guidance materials for public health practitioners. The preliminary findings contained here describe syndromic surveillance systems in use throughout the United States, future plans related to the use of such systems, and basic information regarding how outbreak response is initiated. This cataloging of systems complements work currently underway by the International Society for Disease Surveillance directed towards developing a comprehensive registry of syndromic surveillance systems.

Objective

We aim to describe current syndromic surveillance systems in use throughout the U.S. and approaches to initiating an outbreak response as reported by survey participants.

After the SARS outbreak in 2003, Beijing established Fever Clinics in major hospitals for the early detection of potential respiratory disease outbreaks. The data collection in Fever Clinics contains the basic patient information, body temperature, cough, and breath condition, as well as a primary diagnosis. Since the symptoms and diagnosis are mainly recorded in free text format, it is very difficult to use for data analysis. Because of the problems in data processing, the data collection has decreased.

Objective

This paper describes the methodology in the development of an Integrated Surveillance System for Beijing, China.

The Los Angeles County (LAC) Bioterrorism Preparedness and Response Unit has made significant progress in automating the syndromic surveillance system. The surveillance system receives electronic data on a daily basis from different hospital information systems, then standardizes and generates analytical results.

OBJECTIVE

This article describes architecture, analytical method, and software applications used in automating the LAC syndromic surveillance system.

Integration of information from multiple disparate and heterogeneous sources is a labor and resource intensive task. Heterogeneity can come about in the way data is represented or in the meaning of data in different contexts. Semantic Web technologies have been proposed to address both representational and semantic heterogeneity in distributed and collaborative environments. We introduce an automated semantic information integration platform for public health surveillance using RDF and the Simple Knowledge Organization Standard developed by the Semantic Web community.

OBJECTIVE

This paper proposes the use of Semantic Web technologies to integrate heterogeneous data generated by disparate systems for public health use.