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LHDs are operating in a changing data environment. As household telephone use declines, national surveys are not sampling large enough populations to report representative local health statistics. As a result, reliable indicators from surveys such as the Behavioral Risk Factors Surveillance... Read more

Content type: Abstract

The UNC Department of Emergency Medicine (UNC DEM) conducted an online survey to better understand the surveillance needs of Infection Control Practitioners (ICPs) in North Carolina and solicit feedback on the utility of the North Carolina Disease Event Tracking and Epidemiologic Collection Tool... Read more

Content type: Abstract

Syndromic surveillance data have been widely shown to be useful to large health departments. Use at smaller local health departments (LHDs) has rarely been described, and the effectiveness of various methods of delivering syndromic surveillance data and information to smaller health departments ... Read more

Content type: Abstract

Typical approaches to monitoring ED data classify cases into pre-defined syndromes and then monitor syndrome counts for anomalies. However, syndromes cannot be created to identify every possible cluster of cases of relevance to public health. To address this limitation, NC DETECT’s approach... Read more

Content type: Abstract

NC DETECT receives data on at least a daily basis from five data sources: emergency departments (ED), the statewide poison center (CPC), the statewide EMS data collection system, a regional wildlife center and laboratories from the NC State College of Veterinary Medicine.  A Web portal is... Read more

Content type: Abstract

Despite considerable effort since the turn of the century to develop Natural Language Processing (NLP) methods and tools for detecting negated terms in chief complaints, few standardised methods have emerged. Those methods that have emerged (e.g. the NegEx algorithm) are confined to local... Read more

Content type: Abstract

Materials associated with the Analytic Solutions for Real-Time Surveillance: Asyndromic Cluster Detection consultancy held June 9-10, 2015 at the University of North Carolina, Chapel Hill.

Problem Summary

A syndrome cannot be created to identify every possible cluster of potential... Read more

Content type: Report

A retrospective analysis of emergency department data in NC for drug and opioid overdoses has been explained previously [1]. We built on this initial work to develop new poisoning and surveillance reports to facilitate near real time surveillance by health department and hospital users. In North... Read more

Content type: Abstract

NC BEIPS is a system designed and developed by the NC Division of Public Health (DPH) for early detection of disease and bioterrorism outbreaks or events. It analyzes emergency department (ED) data on a daily basis from 33 (29%) EDs in North Carolina. With a new mandate requiring the submission... Read more

Content type: Abstract

Over the last few decades, the United States has made considerable progress in decreasing the incidence of motor vehicle occupants injured and killed in traffic collisions.1 However, there is still a need for continued motor vehicle crash (MVC) injury surveillance, particularly for vulnerable... Read more

Content type: Abstract

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National Syndromic
Surveillance Program

Email:nssp@cdc.gov

The National Syndromic Surveillance Program (NSSP) is a collaboration among states and public health jurisdictions that contribute data to the BioSense Platform, public health practitioners who use local syndromic surveillance systems, Center for Disease Control and Prevention programs, other federal agencies, partner organizations, hospitals, healthcare professionals, and academic institutions.

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