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Evaluation of Syndromic Surveillance

Description

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.

Submitted by elamb on
Description

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.

Submitted by elamb on
Description

Events of recent years, particularly concern about a possible avian (H5N1) influenza pandemic, have focused increasing attention on the need for timely surveillance, with real time surveillance as the ultimate goal. In a previous study, we reported on the utility of monitoring clinical laboratory results as a means of estimating the incidence of influenza in the U.S. within 24 hours using the Quest Diagnostics Corporate Informatics Data Warehouse. We have now begun to explore the feasibility of near real time surveillance using an internal application capable of providing alerts on unusual conditions within minutes of their occurrence. Our first application of this technology to infectious disease is monitoring activity related to the possible emergence of avian (H5N1) influenza in the United States.

 

Objective

To explore the utility of a system monitoring program for infectious disease surveillance with real time proactive notification.

Submitted by elamb on
Description

Crude mortality could be valuable for infectious disease surveillance if available in a complete and timely fashion. Syndromic surveillance with weekly deaths has been demonstrated to be useful in France. Such data can be of use for detecting, and tracking the impact, of unusual health events (e.g. pandemic influenza) or other unexpected or unknown events of infectious nature. To evaluate whether these aims can be achieved with crude mortality monitoring in the Netherlands, we investigated trends in death notifications and we tested whether retrospective crude mortality trends, at different days of delay, reflect known trends in infectious pathogens that are associated with death (such as influenza).

 

Objective

To evaluate the potential of mortality data in the Netherlands for real-time surveillance of infectious events.

Submitted by elamb on
Description

Crude mortality could be valuable for infectious disease surveillance if available in a complete and timely fashion. Such data can be of used for detecting, and tracking the impact of unusual health events (e.g. pandemic influenza) or other unexpected or unknown events of infectious nature.

To evaluate whether these goals can be achieved with crude mortality monitoring in the Netherlands, a pilot study was set up in 2008 in which death counts were received from Statistics Netherlands. 

The aims of this pilot are: 1) Setting up communication and data transmission. 2) Calculating expected mortality counts (depending on the season) and a prediction interval. 3) Detecting deviations in mortality counts above the threshold. 4) Comparing such deviations (and lags hereof) with other public health information (such as sentinel influenza-like-illness surveillance, and web-based selfreported ILI). 4) Evaluating the additional value of such a system for infectious disease public health.

 

Objective

To evaluate the potential use of mortality data in the Netherlands for real-time surveillance of infectious disease events through a pilot study.

Submitted by elamb on
Description

With the recent emphasis on public health preparedness, health departments are identifying new ways to prepare for emergencies. There has been a significant increase in the number of syndromic surveillance systems operating in recent years. These systems are based on real-time information from hospital emergency departments that is transmitted and analyzed electronically for the purpose of early detection of public health emergencies. Like other states, Rhode Island sought to enhance its traditional surveillance activities through the implementation of such a system. Rhode Island implemented the Real-time Outbreak and Disease Surveillance (RODS) system, developed by the University of Pittsburgh’s Center for Biomedical Informatics. Data from three hospitals were collected as part of the pilot implementation of the Rhode Island RODS system. Personnel at both hospitals and the Department of Health, trained in surveillance-related areas such as infection control and epidemiology, received access to RI RODS. As part of the evaluation framework, Rhode Island desired to assess system user attitudes and opinions towards the new system.

 

Objective

This paper presents results of a survey assessing syndromic surveillance system initial user satisfaction and attitudes regarding syndromic surveillance.

Submitted by elamb on
Description

In the fall of 2001, the Bioterrorism Preparedness and Response (BT P&R) Unit initiated a syndromic surveillance system utilizing chief complaint data collected from Emergency Departments throughout Los Angeles County (LAC). Chief complaint data were organized into four syndromes (gastrointestinal, neurological, rash and respiratory) based on key words/phrases that appear in the patient’s record. Syndrome data are analyzed daily; counts for each syndrome are calculated and compared to a threshold to determine if a “signal” or aberration has occurred (EARS algorithm). A signal is defined as a case count elevated above threshold for a particular syndrome at an individual hospital.

 

Objective 

To describe the methods used by LAC, Department of Health Services, BT P&R Unit in determining the response to unusual disease/syndromic activity in LAC hospitals.

Submitted by elamb on
Description

In 2007-2008, the authors surveyed public health officials in 59 state, territorial, and selected large local jurisdictions in the United States regarding their conduct and use of syndromic surveillance. Fifty-two (88%) responded, representing areas comprising 94% of the United States population. Forty-three (83%) of the respondents reported conducting syndromic surveillance for a median of 3 years (range = 2 months to 13 years). Emergency department visits were the most common data source, used by 84%, followed by outpatient clinic visits (49%), over-the-counter medication sales (44%), calls to poison control centers (37%), and school absenteeism (35%). Among those who provided data on staffing and contract costs, the median number of staff dedicated to alert assessment was 1.0 (range 0.05 to 4), to technical system maintenance 0.6 (range zero to 3); and, among the two-thirds who reported using external contracts to support system maintenance, median annual contract costs were $95,000 (range = %5,500 to $1 million). Respondents rated syndromic surveillance as most useful for seasonal influenza monitoring, of intermediate usefulness for jurisdiction-wide trend monitoring and ad hoc analyses, and least useful for detecting typical community outbreaks. Nearly all plan to include syndromic surveillance as part of their surveillance strategy in the event of an influenza pandemic. Two thirds are either "highly" or "somewhat" likely to expand their use of syndromic surveillance within the next 2 years. Respondents from three state health departments who reported they did not conduct syndromic surveillance noted that local health departments in their states independently conducted syndromic surveillance. Syndromic surveillance is used widely throughout the United States. Although detection of outbreaks initially motivated investments in syndromic surveillance, other applications, notably influenza surveillance, are emerging as the main utility.

Submitted by elamb on
Description

Syndromic Surveillance utilizes health-related symptom data to monitor disease outbreaks. Its’ potential for prompt detection of disease outbreaks and strengthening of rapid public health response is anticipated. As a result, syndromic surveillance is widely employed by many local and regional health care agencies across the country in both routine monitoring of disease outbreaks as well as in special national events. However, the efficacy and effectiveness of syndromic surveillance are yet to be substantiated. In Florida many localized Syndromic Surveillance have been deployed by county health departments with little oversight or coordination of any state and federal agencies. Furthermore, many aspects including the design, operation, and funding characteristics of these systems are not well known and information and practice are not shared, hindering the potential for regional networks with shared data source, networked platform, expanded geographic coverage. This survey aims to establish an inventory of Syndromic Surveillance in the State of Florida and helps identify issues common among these systems.

 

Objective

To gather inventory information on syndromic surveillance deployment and utilization in the State of Florida; To identify issues in developing, operating, and sustaining local systems; To assess needs for system evaluation in order to establish efficacy and effectiveness of syndromic/disease surveillance in the state.

Submitted by elamb on