ISDS Conference

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.

One of the challenges facing developers and users of automated disease surveillance systems is being able to accurately evaluate the performance of their systems for the wide variety of public health threats that are possible. A variety of methods have been used in the past to create data sets for use in testing algorithm performance. Synthetic data has been created using agent-based simulations where data is created based on the hypothesized activity of individuals with contagious diseases. This data is only as accurate as the social models and variety of assumptions which must be made permit. Real data containing elevated levels of respiratory and gastrointestinal activity have been used to evaluate the ability of algorithms to detect the elevated levels. Routine unvalidated outbreaks are typically not public health emergencies and may not represent signals of interest. Another approach is to use real background data and inject a variety of different types of synthetic cases representing various types of outbreaks on top of that background.

With the introduction of the American Health Information Community (AHIC) Minimum Data Set (MDS), the public health surveillance community should have the potential to obtain greater specificity for alerts generated in automated systems. The introduction of these additional data elements increases the complexity of algorithms using linked data elements. Creating synthetic data sets that accurately estimate relationships among chief complaint, pharmacy, laboratory and radiology is an added complexity in creating synthetic outbreaks for performance evaluation.

Objective

The objectives of this presentation are to describe the need for synthetic data containing the elements of the AHIC MDS. Approaches for creating synthetic data with MDS data elements will be presented and methods for insuring maintenance of confidentiality will be discussed.

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.

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.

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.

Infection Control Law in Japan has asked doctors to cooperate in syndromic surveillance for pandemic flu and smallpox since 2007. However, doctors have to report by typing the number of patients on the web site, or by sending a fax to local public health centers. It imposes the heavy burden of reporting, and thus it has not worked well yet. Therefore, we need an automatic system for routine syndromic surveillance.

Objective

We performed some syndromic surveillance system for the Hokkaido Toyako G8 summit meeting in July 2008 in Japan as a counter-measure to bioterrorism attack or other health emergency. This presentation shows the workable syndromic surveillance systems in Japan.

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.

CDC is building a public health information grid to enable controlled distribution of data, services and applications for researchers, Federal authorities, local and state health departments nationwide, enabling efficient controlled sharing of data and analytical tools. Federated aggregate analysis of distributed data sources may detect clusters that might be invisible to smaller, isolated systems. Success of the public health grid is contingent upon the number of participating agencies and the quantity, quality, and utility of data and applications available for sharing. Grid protocols allow data owners to control data access, but requires a model to control the level of identifiability of depending upon the user’s permissions. Here, we describe a work currently in progress involving the design and implementation of an ambulatory syndromic surveillance data stream generator for the public health grid. The project is intended to broadly disseminate aggregate syndrome counts for general use by the public health community, to develop a model for sharing varying levels of identifiable data on cases depending upon the user, and to facilitate ongoing development of the grid.

Objective

To implement a syndromic surveillance system on CDC’s public health information grid, capable of securely distributing syndromic data streams ranging from aggregate case counts to individual case details, to appropriate personnel.

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.

Syndromic surveillance had been implemented in Dongcheng District with a view to probing into the feasibility of establishing a syndromic surveillance system in major Chinese cities, sieving syndromic surveillance indicators applicable to the eruption of infectious respiratory tract and digestive tract diseases, and attempting the operating method of data collection in different locations such as hospital and drug stores in Dongcheng of Beijing China.

Objective

The project has fund donated by World Bank under joint management of WHO and Ministry of Health of P.R.China , The target was try to build up a syndromic surveillance system in Beijing.