Syndromic Surveillance

The use of syndromic surveillance systems by state and local health departments for the detection of bioterrorist events and emerging infections has greatly increased since 2001. While these systems have proven useful for tracking influenza and identifying large outbreaks, the value of these systems in the early detection of bioterrorism events has been under constant evaluation [3,4].

Objective

The 2001 U.S. anthrax mailings, which followed a week after the tragic events of September 11th, highlighted the nation's vulnerability to bioterrorist attacks. This event, known by its FBI code name "Amerithrax," resulted in 22 known infections and five deaths in various east coast locations, including Connecticut [1]. These cases enforced the need for an effective, federal, state, and locally-integrated biosurveillance system network that can provide early warnings to reduce casualties, as called for in U.S. Homeland Security Presidential Directive-21 (HSPD-21) and emphasized in recent CDC reports [2]. This presentation reviews several post-2001 anthrax cases and the roles played by various biosurveillance systems in their identification. Recommendations for the use of modeling and the development of regional and national coordinated surveillance systems are also discussed.

CVD is one of the leading causes of death in the US, with 800,000 deaths being linked to CVD every year. Recently, the CDC reported that 1 in 4 of these deaths could be prevented by lifestyle changes, creating healthier living spaces, as well as managing high cholesterol, blood pressure and diabetes levels [1]. The report also stressed the importance of electronic health records (EHR) in identifying patients with CVD risk factors [1]. Surveillance is a critical component of national effort to prevent CVD [2]. The Nebraska Department of Health and Human Services (NDHHS) has traditionally tracked the burden of chronic diseases by retrospective analysis of hospital discharge data (HDD). However, HDD is limited by its lack of immediate availability and its limited amount of data. Timeliness of detection and analysis of CVD events could be improved with syndromic surveillance. To enhance CVD surveillance in Nebraska, NDHHS implemented a near-real_time IP surveillance system in 2011. This surveillance system facilitates near-real_time assessment of CVD risk factors, outcomes, and prevention program efficacy.

Objective

The main objective of this project is to expand inpatient syndromic surveillance in Nebraska to include indicators of Cardiovascular Disease (CVD).

The Louisiana Office of Public Health (OPH) conducts emergency department (ED) syndromic surveillance using the Louisiana Early Event Detection System (LEEDS). LEEDS automatically processes electronic chief complaint and diagnosis data to identify ED visits indicative of specific syndromes. The Infectious Disease Epidemiology section (IDEpi) of OPH uses LEEDS to monitor infectious disease and injury syndromes during natural or man-made disasters and high profile events. Past events monitored include hurricanes Katrina, Rita and Isaac, the Gulf Coast oil spill, yearly Mardi Gras festivities, marsh fires and chemical leaks. LEEDS has proven to be an invaluable tool in providing all-hazards public health situational awareness during these types of events by enabling near real-time monitoring of infectious disease and injury syndromes.

Objective

To demonstrate the value of syndromic surveillance as a tool to provide situational awareness during high profile events such as the Super Bowl and Mardi Gras in New Orleans, LA.

Syndromic surveillance of livestock animals at points of concentration, such as livestock markets, has the potential to provide early detection of endemic, zoonotic, transboundary, environmental, and newly emerging animal diseases and to identify animal health trends. In the United States, inspectors at livestock auction markets routinely observe animals for clinical signs of disease, but do not usually document the number of cattle or clinical signs observed. The purpose of this pilot program was to demonstrate the benefit and feasibility of utilizing inspectors at livestock markets to record the total number of animals observed and the number displaying body system-associated clinical signs/syndromes (BSAS). This project is a Federal and State partnership between the United States Department of Agriculture (USDA) Animal and Plant Health Inspection Service (APHIS) Veterinary Services (VS) and the Texas Animal Health Commission (TAHC). The livestock market syndromic surveillance pilot project is part of a broader effort in VS to develop and monitor non-traditional animal health surveillance data streams. These data streams include clinical sign information from private veterinary practitioners, veterinary diagnostic laboratory test requests, and livestock slaughter facility condemnations.

Objective

To describe the design and implementation of a syndromic surveillance program in selected cattle markets in Texas, USA.

A goal of biosurveillance is to identify incidents that require a public health response. The challenge is creating specific definitions of such incidents so they can be detected. In syndromic surveillance, this is accomplished by classifying emergency department chief complaints, nurse triage calls, and other prediagnostic data into categories, and then looking for increases in visits related to those categories. This approach can only find incidents that match those predefined categories. It is well-suited to handle common diseases; data from prior years provides information not only on which symptoms correlate with the disease, but also on how patients report them and how they appear in prediagnostic data streams. For unique or rare events, it is hard to know in advance how they will be described or recorded. Another approach is to look for similarities in the time of the healthcare encounters alone. This method can detect events which are missed by syndrome-oriented surveillance, but healthcare encounters that only have time of occurrence aren't necessarily related. To address this limitation, we propose a set of similarity criteria which incorporates both timing and reason.

Objective

Develop a method for detecting groups of related healthcare encounters without having to specify details of the reasons for those encounters in advance.

Co-financed by the European Commission through the Executive Agency for Health and Consumers, the European Triple-S project (Syndromic Surveillance Survey, Assessment towards Guidelines for Europe) was launched in 2010 for a 3-year period [1]. It involves 24 organisations from 13 countries. The project's final purpose is to increase the European capacity for real-time surveillance and monitoring of the health burden of expected and unexpected health-related events. Based on inventories of European SyS systems [2;3], eight country visits [4] and experts advice, the project has developed scientific guidelines that aim at providing scientific and technical guidance for the development and implementation of SyS systems for both human and animal health.

Objective

To present the Guidelines for implementing syndromic surveillance (SyS) systems at a national, regional or local level.

The NYC syndromic surveillance system has been monitoring syndromes from NYC emergency department (ED) visits for over a decade. We applied several aberration detection methodologies to a time series of ED visits in NYC spiked with synthetic outbreaks. This effort is part of a larger evaluation of the NYC syndromic system, funded by a grant from the Alfred P. Sloan Foundation.

Objective

To critically evaluate temporal aberration detection methodologies using New York City (NYC) syndromic surveillance data.

The monitoring of whole or partial carcass condemnations can constitute a valuable indirect indicator of herd health (1). Nevertheless, systematic collection and use of such data for epidemiological surveillance is scarce within the European Union (2).

Objective

We evaluate Swiss abattoir data for integration in a national syndromic surveillance system for production animals. More specifically, we identify gaps in the current federal meat inspection database and provide suggestions for its improvement.

Extreme heat events over the past 30 years have resulted in unprecedented increase in the numbers of heat-related morbidity and mortality across the world (1-3). During the same time frame, Houston residents has experienced three of the hottest summers on record since 1889, with 2011 being the hottest summer on record (4). Therefore, preparing for extreme heat events and monitoring their effects on public health is a vital role for the Houston Department of Health and Human Services (HDHHS). Since heat-related illnesses are not a reportable condition in the state of Texas, HDHHS authorities rely on other sources to provide information on the impact of heat on the population. HDHHS is currently able to monitor emergency departments (ED) visits across the Houston metropolitan area, Harris County, and the surrounding jurisdictions by using a syndromic surveillance system called Real-time Outbreak Disease Surveillance (RODS). The RODS system collects de-identified patient data that consists of their chief complaint and basic demographics (e.g. age, sex, zip code). This study is aimed at evaluating the ability of RODS to detect heat-related illnesses during heat event of the years 2009-2012 as well as identifying the areas of Houston that had the highest incidence of heat-related morbidity.

Objective

To evaluate the ability of a syndromic surveillance system to detect heat-related illnesses during a heat wave in Houston and to identify areas in Houston that requires additional resources to prevent heat-related illnesses.