Surveillance Systems

The Automated Hospital Emergency Department Data System is designed to detect early indicators of bioterrorism events and naturally occurring public health threats. Four investigatory tools have been developed with drill-down detail reporting: 1. Syndromic Alerting, 2. Chief Complaint Data Mining, 3. ICD9 Code Disease, and 4. Influenza-Like-Illness Tracking.

All analysis processing runs on the server in seconds using ORACLE PL/SQL stored procedures and arrays.

Objective

This paper details the development of electronic surveillance tools by Communicable Disease Surveillance, which have increased detection and investigation capabilities.

Major challenges in syndromic surveillance today include lack of standardization in syndrome definitions and limited ability to detect outbreaks of specific and rare diseases. To generate situational awareness surveillance results across various regions must be comparable and epidemiologically well defined. In addition, the high cost of obtaining and maintaining powerful computing resources (e.g., parallel computers) needed for data processing and analysis, and absence of a protocol for data sharing, highlight some of the obstacles to achieving situational awareness.

Cloud computing is an enabling technology that can overcome these challenges and facilitate new and novel approaches to surveillance.

Objective

We present a Cloud Computing based approach to disease surveillance that facilitates efficient data collection, processing and storage, as well as new concepts for data sharing and data fusion, disease search and situational awareness.

In Connecticut, several syndromic surveillance systems have been established to detect and monitor potential public health threats: 1) the hospital admissions syndromic surveillance (HASS) system in 2001; and 2) the emergency department syndromic surveillance (EDSS) system in 2004. For the HASS, hospitals manually categorize unscheduled admissions into 11 syndrome categories and report these aggregate counts through an internet-based system daily to DPH; all 32 hospitals participate. For the EDSS, hospitals electronically report deidentified emergency department chief complaint data to DPH, and using a computerized algorithm, DPH categorizes this data into 8 syndrome categories; currently 17 hospitals participate. As part of pandemic influenza planning, there has been an increased focus on situational awareness at the state and national level; Connecticut would likely rely on these two systems for this purpose.

Objective

To evaluate the performance of the HASS and EDSS systems in reflecting seasonal influenza activity in Connecticut and, thus, their possible utility during a pandemic.

Every year the United States generates close to 300 million scrap tires. Due to their high energygenerating capacity, tires can be used as a fuel source (tire-derived fuel, or TDF). In 2006 a paper mill located less than 3 miles from the Vermont border received a permit to conduct a 2-week test burn of TDF to evaluate its potential to replace oil as a source of fuel. Simulations and data from other mills suggested that tires may release metal emissions and fine particulates when they are burned. The Vermont Department of Health (VDH) conducted surveillance in the population living closest to the paper mill because metal emissions and fine particulates have been associated with adverse health effects.

Objective

The VDH established a short term surveillance system to track health effects related to a test burn of tire-derived fuel.

The practice of real-time disease surveillance, sometimes called syndromic surveillance, is widespread at local, state, and national levels. Diseases ignore legal boundaries, so situations frequently arise where it is important to share surveillance information between public health jurisdictions. There are currently two fundamental ways for systems to share public health data and information related to disease outbreaks: sharing data, or sharing information. Data refers to patient level and aggregate counts of patients, and can be difficult to share legally because of privacy issues. Information refers to summaries, opinions or conclusions about data. There are few if any legal barriers to sharing information, and by definition it includes interpretation of data by knowledgeable local personnel which is vital during outbreak investigation. Currently most shared information is unstructured text, and this format makes it difficult for computers to use the information in any meaningful way. The only thing a system can do with this unstructured information is allow users to read each message.

Objectives

Alternate methods are needed to facilitate communication between jurisdictions during potential disease outbreaks. One alternative is to share structured information. Defined at the appropriate level, information sharing can avoid traditional data sharing barriers while capturing valuable local knowledge. The key is to identify the types of surveillance information that are neither so highly interpreted as to lose their value nor so loosely interpreted as to face traditional data sharing barriers. The objective of this work is to identify the level at which surveillance information sharing can be both feasible and beneficial, and to create a vocabulary standard that supports the exchange of structured information between diverse surveillance systems. 

Washoe County District Health Department (WCDHD) is a local health district serving nearly 400,000 residents in Washoe County including cities of Reno and Sparks, the second largest urban area in Nevada. To enhance overall public health surveillance capacities in the agency, WCDHD officially implemented National Retail Data Monitor (NRDM) in September 2004, Real-time Outbreak & Disease Surveillance (RODS) in July 2005, and FirstWatch in August 2005. These three systems monitor over-the-counter sales for medications and healthcare products, chief complaints at emergency room visits, and 911 calls, respectively. Preliminary evaluation of NRDM suggested the usefulness of system. The addition of RODS and FirstWatch also demonstrated the utility in assisting outbreak investigation during the past few months. Unfortunately no written protocols are in place to guide program staff to manage alerts in a standardized fashion and make appropriate responses. Such guidelines from federal or state level are not yet available as we are aware, however, such protocol is highly needed.

Objective

The objective of this paper is to describe the standard operation procedures for three existing syndromic surveillance systems in WCDHD, Nevada.

For more than a decade, biosurveillance systems (and more recently BioSense) have been employed in the United States. Efforts to drastically expand these surveillance capacities have been a national priority given concerns about national security. However, there has been little emphasis on value or increasing value to communities or agencies contributing and analyzing data. This qualitative analysis focused on all biosurveillance stakeholders and the opportunity to enhance interoperability and reuse of data and systems.

Objective

To understand the perspective of biosurveillance stakeholders and how their participation creates value for them as well as public health departments.

As the Georgia Division of Public Health began constructing a systems interface for its syndromic surveillance program, the nature and intended use of these data inspired new approaches to interface design. With the temporal and spatial components of these data serving as fundamental determinants within common aberration detection methods (e.g., Early Aberration Reporting System, SaTScan™), it became apparent that an interface technique that could present a synthesis of the two might better facilitate the visualization, interpretation and analysis of these data.

Typical presentations of data spatially oriented at the zip code level use a color gradient applied to a zip code polygon to represent the differences in magnitude of events within a given region across a particular time span. Typical presentations of temporally oriented data use time series graphs and tabular formats. Visualizations that present both aspects of spatially and temporally rich datasets within a single visualization are noticeably absent.

Objective

This paper describes an approach to the visualization of disease surveillance data through the use of animation techniques applied to datasets with both temporal and geospatial components.

Visitors from areas outside Miami-Dade County have the potential to introduce diseases and/or strains of microorganisms circulating in their regions of residence. Immunocompromised and immunonaive travelers are at higher risk of contagion by locally transmitted pathogens. The first encounter with a local health care facility for many of these visitors is often an Emergency Departments (ED). Little is known about this group of patients with regard to socio-demographic and temporal patterns. This knowledge is essential to further characterize their syndromic patterns as well as to integrate this knowledge to the growing use of syndromic surveillance as an early-warning public health tool.

Objective

To describe socio-demographic and temporal patterns of patients who reside outside Miami-Dade and who visited EDs of hospitals located in this County during 2007.

While early event detection systems aim to detect disease outbreaks before traditional means, following up on the many alerts generated by these systems can be time-consuming and a drain on limited resources.

Authorized users at local, regional and state levels in North Carolina rely on the North Carolina Disease Event Tracking and Epidemiologic Collection Tool's (NC DETECT) Java-based Web application to monitor and follow-up on signals based on the CDC’s EARS CUSUM algorithms. The application provides users with access to aggregate syndrome-based reports as well as to patient-specific line listing reports for three data sources: emergency departments, ambulance runs and the statewide poison control center. All NC DETECT Web functionality is developed in a user-centered, iterative process with user feedback guiding enhancements and new development. This feedback, along with the need for improved situational awareness and the desire to improve communication among users drove the development of the Annotation Reports and the Custom Event Report.

Objective

We describe the addition of two reports to NC DETECT designed to improve NC public health situational awareness capability.