Surveillance Systems

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.

Timely surveillance of disease outbreak events of public health concern currently requires detailed and time consuming manual analysis by experts. Recently in addition to traditional information sources, the World Wide Web has offered a new modality in surveillance, but the massive collection of multilingual texts which must be processed in real time presents an enormous challenge.

Objective

In this paper we present a summary of the BioCaster system architecture for Web rumour surveillance, the rationale for the choices made in the system design and an empirical evaluation of topic classification accuracy for a gold-standard of English and Vietnamese news.

To design detectability evaluation software that interfaces with the Realtime Outbreak and Disease Surveillance (RODS) System.

This presentation introduces the U.S. Department of Homeland Security (DHS) National Bio-Surveillance Integration System (NBIS) and the analytics functionality within the NBIS that integrates and analyzes structured and unstructured data streams across domains to provide inter-agency analysts with an integrated view of threat scenarios. The integration of Human and Animal incidences of Avian Influenza will be used to demonstrate initial capability.

The objectives of the two day International Society for Disease Surveillance (ISDS) funded consultation were to develop expert, consensus-based recommendations that address specific, unanswered questions that hinder advances in cross border syndromic surveillance. The consultation included a discussion of the details of existing Canadian (Can) and United States (US) syndromic surveillance systems and the opportunities and challenges for new developments. Particular focus was placed on the ability to detect and respond to a bioterrorism event or infectious disease outbreak across borders.

This panel member consultation is an International Society of Disease Surveillance (ISDS) sponsored project. It involved expert personnel in their respective area to address specific, priority questions confronting researchers, developers, and public health practioners in the field of syndromic surveillance (SS). The objective of this consultation will be to develop expert, consensus-based recommendations that address specific, unsettled problems or unanswered questions that hinder advances in utilization of syndromic surveillance data in combination with other data sources. Recommendations arising from the consultation should facilitate efforts by researchers, developers, or practitioners to be able to stride ahead and make progress.

Objective The objective of this study was to determine which chief complaints and ICD-9-CM coded diagnoses from real-time BioSense hospital data correlate well with data from conventional influenza surveillance systems.

The 2003 outbreak of severe acute respiratory syndrome (SARS) in Taiwan provided accelerated us to develop the most timely surveillance system1. Taipei, a metropolitan with many travelers annually, requires the earliest warningand immediate responses once novel agents would attack. Considering international exchanges of epidemiological information for travelers and possible cross-country spread of EID,we initiated an ED-SSS using clinical data involving checklist CoCo and ICD-9 plus IT internally installed mechanism integrated with epidemiological information to increase the sensitivity and timeliness to detect unusual outbreaks. Objective: To face challenges of emerging infectious diseases (EID) and bioterrorism and to prepare for international collaboration without language barriers, we established a timely hospital emergency department-based syndromic surveillance system (ED-SSS) using both triage predefined check-list chief complaints (CoCo) and International Classification of Diseases, 9th Revision (ICD-9) in Taipei. The aims of this study are: (1) to monitor the patterns and trends of Taiwan’s important infectious diseases using different syndrome groups [gastrointestinal (GI), respiratory, enteroviral infections, etc.]; (2) to integrate epidemiological attributes, syndrome groups and lab. findings for improving the sensitivity, specificity and timeliness of ED-SSS in detecting outbreaks; and (3) to compare the sensitivity, specificity, and kappa value of GI, respiratory, enteroviral and central nervous system (CNS) infections between CoCo and ICD-9.

The University of Washington's Center for Public Health Informatics, in collaboration with the Kitsap County Health District and the UW Clinical Informatics Research Group, has developed the Peninsula Syndromic Surveillance Information Collection System (SSIC), a complex second-generation [1,2] distributed database system which collects heterogeneous data from three emergency department / urgent care facilities computerized electronic admission and discharge diagnosis data. We transform heterogeneous institution-specific data to a standardized XML (eXtensible Markup Language) format, which is then transmitted to and integrated into a central database. Aberration detection algorithms are used to analyze this data so that public health officials can detect higher-than-usual incidences of the clinical syndromes under surveillance.

This paper will use CDCís EARS-X to examine Tele-healthís potential as an early warning system specifically for influenza-like illness compared to NACRS, as well as qualitatively comparing the resultant EARS flags to peaks in influenza activity identified by the Public Health Agency of Canadaís (PHAC) Federal Influenza surveillance system (Fluwatch).