Surveillance Systems

The resources available in most public health departments are limited. Access to trained technical personnel and stateof-the-art computing resources are also lacking. Customizable off-the-shelf systems contribute only to creation of information silos, are expensive, and not affordable by the limited budget available to the departments of health (only growing worse with the recession). The one thing that has increased is the need for surveillance in more areas, from diseases to environmental exposures to unexpected disasters. One solution would be an adaptable system able to cope with changing requirements while reusing or eliminating infrastructure from both computing hardware and technical personnel.2 We report in this paper an instance of such system as used to perform disease surveillance across the Harris County school system. The system is designed to be customizable for surveillance of any disease, while simultaneously accommodating other use cases like disaster response and registries.

Objective

This paper describes use of semantic technologies in combination with Services Oriented Architecture (SOA) to construct dynamic public health surveillance systems1 used for just-in-time monitoring of emerging infectious disease outbreaks. The system was used for surveillance of schools in the third largest population center, Harris County.

The primary goal of the Electronic Syndromic Surveillance system (ESSS) is to monitor trends in non-specific symptoms of illness at the community level in real time. The ESSS includes emergency department chief complaint data that are categorized into eight syndromes: respiratory, gastrointestinal, fever, asthma, neurological, rash, carbon monoxide, and hypothermia. Since the onset of H1N1, fever syndrome has been used to monitor flu activity. As H1N1 spread nationwide, the need of visualizing flu activity geographically became clear, and urgent.

Objective

The objective of this paper is to describe a map application added to the New York state Electronic Syndromic Surveillance system (ESSS). The application allows system users to display the geographic distributions, and trends of fever syndrome that was used to monitor seasonal and H1N1 influenza activities.

Medically unexplained syndromes (MUS) are conditions that are diagnosed on the basis of symptom constellations and are characterized by a lack of well-defined pathogenic pathways. The three most common MUS are chronic fatigue syndrome, irritable bowel syndrome, and fibromyalgia. Different types of persistent symptoms, originating from different organ systems, characterize these syndromes. Patients often meet the criteria for more than one MUS.

Objectives

We sought to develop a guideline and annotation schema that can be consistently applied to identify MUS found in VA clinical documents. These efforts will support building a reference standard used for training and evaluation of a Natural Language Processing system developed for automated symptom extraction. Our overarching goal is to characterize the occurrence of MUS in Operation Enduring Freedom/Operation Iraqi Freedom veterans.

The Centers for Disease Control and Prevention (CDC) launched the BioSense program in 2003 to establish an integrated system of nationwide public health surveillance for the early detection and assessment of potential bioterrorism-related illness. Over the ensuing years, the original aims of BioSense were broadened to meet evolving public health surveillance needs and priorities.

In 2009, CDC embarked on a redesign of the BioSense system that would retain the original purpose of early event (or threat) detection and characterization, but enhance the capacity for situation awareness, event response, and routine public health practice. The BioSense redesign will be accomplished through continuous involvement of state and local users, and technical experts in the planning, design, development, and testing phases of the new BioSense system.

Objective

The objective of this poster presentation is to provide information on the efforts and results of the user requirements gathering process, pursued in the redesign of the BioSense system employing a User-Centered Design (UCD) approach. A UCD system development approach studies the people that the system will serve, and involves them through the planning, design, and development processes.

On 24 December 2009, a female New Hampshire resident was confirmed to have gastrointestinal anthrax on the basis of clinical findings and laboratory testing. Her source of anthrax was not immediately known, so the New Hampshire Department of Health and Human Services, in conjunction with several other state and federal agencies, conducted a comprehensive epidemiologic investigation, which included active surveillance to identify any additional anthrax cases from a similar exposure. It was determined that the index patient participated in a drumming event with animal-hide drums on 4 December, one day before the onset of symptoms. Two drums used at the event were later found to be contaminated with Bacillus anthracis.

Objective

This paper describes the use of customizable tools to query electronic emergency department data, as part of case finding, during the response to a community anthrax exposure in New Hampshire.

The use of syndromic surveillance systems to detect illness and outbreaks in the mid 1990s in New York City resulted in recommendations for increased use of these systems for detection of bioterrorist agents, and tracking influenza throughout the region. Discussions on approaches to best respond to surveillance system signals led to initial efforts to organize a coordinating group of various public health agencies throughout the New York City region. These efforts were strengthened after the events of September 11, 2001, and resulted in the development of a regional workgroup consisting of epidemiologists and other staff from all state, county, and municipal health departments who operate, respond to, or oversee public health preparedness surveillance systems throughout the greater New York City metropolitan area.

Objective

The rapid and effective coordination of the multi-jurisdictional communications and response to a surveillance system signal are an important goal of public health preparedness planning. This goal is particularly challenging if the signal indicates a possible risk that could adversely affect populations in multiple states and municipalities. This paper examines the value of a regional workgroup in the activation, integration, and coordination of multiple surveillance systems along with efforts to coordinate risk communication messaging. Recommendations for the development of similar groups in other regions are discussed.

The novel strain of H1N1 Influenza A virus, which first caused localized outbreaks in parts of Mexico, was declared a pandemic in June 2009. The Centers for Disease Control and Prevention’s (CDC) Countermeasure and Response Administration System (CRA) was used to track the H1N1 vaccine uptake across population age groups during the first eight weeks of the event (3 October to 21 November 2009). The CRA application was utilized to track vaccine doses administered in the initial period of H1N1 vaccine campaign, as there was no other method available to inform how well the vaccine was reaching target age groups.

Objective

The objective of this paper is to report the use of the CDC CRA to track and monitor H1N1 doses administered during the initial weeks of the 2009–2010 H1N1 Vaccine Program when supplies of the vaccines were limited, and before population-based surveys like Behavioral Risk Factor Surveillance Systems, and National H1N1 Flu Survey could effectively monitor vaccine coverage.

From January to March 2010, thirteen outbreaks of Norovirus infection were reported to the Epidemiology, Disease Control and Immunization Service (EDC-IS), up from four outbreaks in the entire 2008 and same number during 2009. Individual cases of Norovirus are not reportable in the State of Florida. That makes it difficult to track the onset, rise, peak, and fading of epidemics of this disease.

Objective

To demonstrate how the EDC-IS at the Miami-Dade County Health Department used ESSENCE to track gastrointestinal symptoms during a Norovirus epidemic.

Hospital discharge data received by public health agencies has a reporting lag time of greater than six months. This data is often used retrospectively to conduct surveillance to assess severity of illness and outcome, and for evaluating performance of public health surveillance systems. 

With the emergence of Health Information Exchanges and Regional Health Information Organizations (RHIOs), inpatient data can be available to public health in near real-time. However, there currently are no established public health practices or information systems for conducting routine surveillance in the inpatient setting. 

Through a contract with the Centers for Disease Control and Prevention, New York State Department of Health

initiated the development of a statewide public–health Health Information Exchanges with New York RHIOs. Daily

minimum biosurveillance data set data-exchange implementation, and evaluation efforts were focused on one RHIO (RHIO A) and one participating hospital system composed of five acute-care facilities.

Objective

The objective of this paper is to assess the potential utility of inpatient minimum biosurveillance data set data obtained from RHIOs for pneumonia and influenza surveillance.

Biosurveillance systems commonly use emergency department (ED) patient chief complaint data (CC) for surveillance of influenza-like illness (ILI). Daily volumes are tracked using a computerized patient CC classifier for fever (CC Fever) to identify febrile patients. Limitations in this method have led to efforts to identify other sources of ED data. At many EDs the triage nurse measures the patient’s temperature on arrival and records it in the electronic medical record. This makes it possible to directly identify patients who meet the CDC temperature criteria for ILI: temperature greater than 100 degrees F (T>100F).

Objective

To evaluate whether a classifier based on temperature >100F would perform similarly to CC Fever and might identify additional patients.