Surveillance Systems

Regional disease surveillance systems allow users the ability to view large amounts of population health information and examine automated alerts that suggest increased disease activity. These systems require users to view and interpret which of these alerts or data streams are epidemiologically important. This interpretation is valuable information that may benefit other users. In addition to the daily interpretation of data done by users, the ability to communicate local concerns and findings during a public health event to neighboring jurisdictions is of great public health importance. Public health officials also need constant situational awareness and a venue to share their concerns about increases in disease activity before a health emergency is declared. The Event Communications Component (ECC) was created to provide this venue. The ECC was developed for the National Capital Region (NCR) public health surveillance network to facilitate the need for users to communicate. The NCR system is an operational multi-jurisdictional biosurveillance system employed in the District of Columbia and in surrounding Maryland and Virginia counties. NCR users include epidemiologists and public health officials from different levels of government. The ECC has been in operation for a year in the NCR system. ECC 2.0 is being developed to improve on the original version’s capabilities and solve its shortcomings.

 

Objective

Identify areas of improvement and establish design goals of ECC 2.0. These design goals include: the incorporation of comment centric design versus event centric, automatic notification of new events/comments, the use of action oriented concern levels and user interface improvements. Focus design goals by utilizing prototyping and user group reviews. Develop ECC 2.0 and integrate it into the NCR system.

The Centre for Health Protection in Hong Kong has operated a sentinel surveillance system for infectious diseases at child care centre (CCC) since March 2004, among its multi-faceted disease surveillance systems. Forty-six CCCs have participated in the system and are contributing data weekly on absenteeism and common infectious disease symptoms such as fever, diarrhea, vomiting, and cough. The system was originally driven by a manual data collection mechanism via fax, followed by secondary data input and subsequent analysis. However, such mechanism might sometimes result in delayed data transmission and data loss. As an alternative to accommodate these limitations, a web-based platform is developed to increase the timeliness of data submission by the sentinel CCCs. The new platform not only speeds up data collection and eliminates the need for human data entry, but at the same time delivers summary statistics directly on the web through computer programmes on a real time basis, as soon as data is entered by the provider.

Objective

This paper describes the attempt to develop an internet-based community surveillance network to enhance timeliness and sensitivity in detecting community-wide infectious disease outbreaks among young children at CCCs in Hong Kong.

A large event such as the Super Bowl that attracts over 120,000 visitors to an area within a short period of time has the potential to increase the risk of communicable diseases and environmental hazards in a community in addition to the possibility of a bioterrorist attack. Though Miami-Dade County Health Department has in place a syndromic surveillance system, additional public health measures were implemented to ensure the health and safety of all residents and visitors in the weeks surrounding the February 4th event.

OBJECTIVE

To identify unusual patterns of communicable diseases, health events or bioterrorism-related activity in Miami-Dade County immediately before, during and after Super Bowl XLI.

In September 2004, Kingston, Frontenac and Lennox and Addington Public Health began a 2-year pilot project to develop and evaluate an Emergency Department Chief Complaint Syndromic Surveillance System in collaboration with the Ontario Ministry of Health and Long Term Care – Public Health Branch, Queen’s University, Public Health Agency of Canada, Kingston General Hospital and Hotel Dieu Hospital. At this time, the University of Pittsburgh’s Real-time Outbreak and Disease Surveillance (RODS, Version 3.0) was chosen as the surveillance tool best suited for the project and modifications were made to meet Canadian syndromic surveillance requirements.

Objective

This poster provides an overview of a RODS-based syndromic surveillance system as adapted for use at a Public Health unit in Kingston, Ontario Canada. The poster will provide a complete overview of the technical specifications, the capture, classification and management of the data streams, and the response protocols developed to respond to system alerts. It is hoped that the modifications described here, including the addition of unique data streams, will provide a benchmark for Canadian syndromic surveillance systems of the future.

The Bioterrorism Surveillance Unit of the Los Angeles County (LAC) Department of Public Health, Acute Communicable Disease Control (ACDC) program analyzes Emergency Department (ED) data daily. Currently capturing over 40% of the ED visits in LAC, the system categorizes visits into syndrome groups and analyzes the data for aberrations in count and spatial distribution. Typical usage of the system may be extended for various enhanced surveillance activities by creating additional syndrome categories tailored to specific illnesses or conditions. This report describes how ED data was utilized for enhanced surveillance regarding: (1) a sustained heat wave in California that broke temperature and duration records, (2) a 30,000 gallon raw sewage spill that prompted the closure of two miles of beach, and (3) an alert to ACDC of a high school student who attended school while symptomatic for meningitis.

Objective

To describe enhanced surveillance provided by the LAC Department of Public Health’s syndromic surveillance system for monitoring health events in 2006.

Data quality for syndromic surveillance extends beyond validating and evaluating syndrome results. Data aggregators and data providers can take additional steps to monitor and ensure the accuracy of the data. In North Carolina, hospitals are mandated to transmit electronic emergency department data to the North Carolina Disease Event Tracking and Epidemiologic Tool (NC DETECT) system at least every 24 hours. Protocols have been established to ensure the highest level of data quality possible. These protocols involve multiple levels of data validity and reliability checks by NC DETECT staff as well as feedback from end-users concerning data quality. Hospitals also participate in the data quality processes by providing metadata including historical trends at each facility.

Objective

The purpose of this project is to describe the initiatives used by the NC DETECT to ensure the quality of ED data for surveillance.

The Threat Agent Detection and (TADR) Network currently supports the U.S. Government’s (USG) strategy for strengthening Biological Weapons Convention (BWC) compliance through focus on disease surveillance and investigations of suspicious outbreaks of disease in the Republics of Kazakhstan, Uzbekistan, Georgia and Azerbaijan. TADR is a comprehensive approach to achieving the USG’s overall BWC compliance, and consists of

several components.

Objective

This paper describes the Electronic Integrated Disease Surveillance System being deployed in Uzbekistan, Kazakhstan, Georgia, and Azerbaijan under the Biological Threat Reduction Program (BTRP) as part of the TADR Network.

On June 7, 2008, federal food protection and public health agencies alerted consumers of a nationwide outbreak of Salmonella Saintpaul infections. As of June 30, 2008, 851 persons infected with Salmonella Saintpaul with the same genetic fingerprint had been identified in 36 states and the District of Columbia since April 20081. On June 13, 2008, Maryland confirmed its first case of Salmonella Saintpaul infection matching the national outbreak strain and as of June 30, 2008, 29 cases of Salmonella related to the outbreak have been identified.

Objective 

The purpose of this paper is to describe the use of syndromic surveillance emergency department data as a tool for enhanced case finding of outbreak-related illnesses.

The 2003/04 influenza season included a more pathogenetic organism and had an earlier onset. There were noticeably more deaths in otherwise healthy children than in previous seasons. Following this season, States were asked by the Centers for Disease Control and Prevention to increase their surveillance efforts for influenza illness.

Objective 

This paper describes data that was available in Ohio for analysis and considered valuable to determine the occurrence of influenza-like illness (ILI). These data sources were studied to determine their value to ILI surveillance and to develop an improved method of establishing influenza activity levels.

Current syndromic surveillance systems run multiple simultaneous univariate procedures, each focused on detecting an outbreak in a single data stream. Multivariate procedures have the potential to better detect some types of outbreaks, but most of the existing methods are directionally invariant and are thus less relevant to the problem of syndromic surveillance. This article develops two directionally sensitive multivariate procedures and compares the performance of these procedures both with the original directionally invariant procedures and with the application of multiple univariate procedures using both simulated and real syndromic surveillance data. The performance comparison is conducted using metrics and terminology from the statistical process control (SPC) literature with the intention of helping to bridge the SPC and syndromic surveillance literatures. This article also introduces a new metric, the average overlapping run length, developed to compare the performance of various procedures on limited actual syndromic surveillance data. Among the procedures compared, in the simulations the directionally sensitive multivariate cumulative sum (MCUSUM) procedure was preferred, whereas in the real data the multiple univariate CUSUMs and the MCUSUM performed similarly. This article concludes with a brief discussion of the choice of performance metrics used herein versus the metrics more commonly used in the syndromic surveillance literature (sensitivity, specificity, and timeliness), as well as some recommendations for future research.