Infectious Diseases

While traditional means of surveillance by governments, multi-national agencies, and institutional networks assist in reporting and confirming infectious disease outbreaks, these formal sources of information are limited by their geographic coverage and timeliness of information flow. In contrast, rapid global reach of electronic communication has resulted in the advent of informal sources of information on outbreaks. Informal resources include discussion sites, online news media, individual and organization reports and even individual search records. The earliest descriptions of the severe acute respiratory syndrome outbreak in Guangdon Province, south China came from informal reports. However, system development to date has been geared toward knowledge management and strategies for interpreting these data are underdeveloped. There is a need to move from simple knowledge reorganization to an analytic approach for disseminating timely yet specific signals.

Objective

Internet-based resources such as discussion sites and online news sources have become invaluable sources for a new wave of surveillance systems. The WHO relies on these informal sources for about 65% of their outbreak investigations. Despite widespread use of unstructured information there has been little, if any, data evaluation.

Capital Health is a regional health care organization, which provides services for over one million inhabitants in the Edmonton area of Alberta, Canada. Traditionally, disease surveillance under its jurisdiction has been paper-based and records maintained by different departments in several locations. Before the Alberta Real Time Syndromic Surveillance Net (ARTSSN), there was no centralized database or unified approach to surveillance and automated reporting despite rich electronic health data in the region. The existing labor-intensive manual surveillance process is inefficient and inherently susceptible to human error. Its effectiveness is sub-optimal in detecting outbreaks of emerging infectious diseases, and clusters of injuries or toxic exposures. The ultimate objective of ARTSSN is to enhance public health surveillance through earlier and more sensitive detection of clusters and trends, with subsequent tracking and response through an integrated, automated surveillance and reporting system.

Objective

ARTSSN is a pilot public health surveillance project developed for the Capital Health region of Alberta, Canada and funded by Alberta Health and Wellness. This paper describes the advantages of using ARTSSN and comparing information derived from multiple electronic data sources simultaneously for real time syndromic surveillance.

The Centre for Health Protection in Hong Kong has operated a sentinel surveillance system for infectious diseases at child care centre (CCC) since March 2004, among its multi-faceted disease surveillance systems. Forty-six CCCs have participated in the system and are contributing data weekly on absenteeism and common infectious disease symptoms such as fever, diarrhea, vomiting, and cough. The system was originally driven by a manual data collection mechanism via fax, followed by secondary data input and subsequent analysis. However, such mechanism might sometimes result in delayed data transmission and data loss. As an alternative to accommodate these limitations, a web-based platform is developed to increase the timeliness of data submission by the sentinel CCCs. The new platform not only speeds up data collection and eliminates the need for human data entry, but at the same time delivers summary statistics directly on the web through computer programmes on a real time basis, as soon as data is entered by the provider.

Objective

This paper describes the attempt to develop an internet-based community surveillance network to enhance timeliness and sensitivity in detecting community-wide infectious disease outbreaks among young children at CCCs in Hong Kong.

Evidence suggests that transmission within the workplace contributes significantly to the magnitude of a pandemic flu epidemic. A significant number of large organizations have a pandemic plan in place which may help in controlling this manner of transmission. These plans typically include telecommuting and other measures to reduce the need to physically commute to the workplace. Good data are needed in order to obtain valid results from simulation models and to be able to assess the effect of reductions in commuting.

Objective

The objective in this study was to explore data on employment and commuting from different sources, using statistical analytic techniques together with geographical experts to obtain information to be provided to modelers in order to help them improve the employment and commuting component of their models, determine potential issues related to these data, and identify problem areas where further investigation is needed.

The Bioterrorism Surveillance Unit of the Los Angeles County (LAC) Department of Public Health, Acute Communicable Disease Control (ACDC) program analyzes Emergency Department (ED) data daily. Currently capturing over 40% of the ED visits in LAC, the system categorizes visits into syndrome groups and analyzes the data for aberrations in count and spatial distribution. Typical usage of the system may be extended for various enhanced surveillance activities by creating additional syndrome categories tailored to specific illnesses or conditions. This report describes how ED data was utilized for enhanced surveillance regarding: (1) a sustained heat wave in California that broke temperature and duration records, (2) a 30,000 gallon raw sewage spill that prompted the closure of two miles of beach, and (3) an alert to ACDC of a high school student who attended school while symptomatic for meningitis.

Objective

To describe enhanced surveillance provided by the LAC Department of Public Health’s syndromic surveillance system for monitoring health events in 2006.

 Syndromic surveillance systems often classify patients into syndromic categories based on emergency department (ED) chief complaints. There exists no standard set of syndromes for syndromic surveillance, and the available syndromic case definitions demonstrate substantial heterogeneity of findings constituting the definition. The use of fever in the definition of syndromic categories is arbitrary and unsystematic. We determined whether chief complaints accurately represent whether a patient has any of five febrile syndromes: febrile respiratory, febrile gastrointestinal, febrile rash, febrile neurological, or febrile hemorrhagic.

In the past, the media has served a source of data for syndromic surveillance of infectious disease, whether it is outbreaks of disease in animals or humans resulting in illness or death.  More often than not, the reverse is true; data based on analyses of   syndromic surveillance often flows from hospital to local health departments and federal governmental agencies such as the CDC to the media which then relays it to the public. In both instances, the media may serve as a purveyor of vital information.  But, sometimes the media reports are less than ideal; the public may become fearful and panic at the news of a potential outbreak of an emerging infectious disease such as bird flu for which there is a high fatality case rate and no proven available vaccine, or curative therapy. Moreover, supplies of vaccine may be limited, and news of a shortage of antiviral medications such as Tamiflu may lead to stockpiling similar to what occurred with Cipro during the anthrax  ‘scare.’  

Objective:

This paper explores how the mass media covered bird flu outbreaks overseas in the Fall of 2005, and the nationís preparations for a possible bird flu pandemic, and how this period of intense media activity affected sales of antivirals in New City and New York State as monitored by syndromic surveillance techniques.

BioSense is a national Centers for Disease Control and Prevention (CDC) initiative to improve the nation's capabilities for early event detection and situational awareness. BioSense data includes Department of Defense and Veterans Affairs ambulatory care diagnoses and procedures, as well as Laboratory Corporation of America lab test orders.  The data are collected, assigned to syndromes based upon definitions developed by a multi-agency working group, analyzed using several detection algorithms, and displayed in various visualizations [2,3].  BioIntelligence Center (BIC) staff at CDC monitors BioSense national data on a daily basis and are available to support state and local public health officials’ monitoring and investigations [3]. As part of its ongoing bioterrorism surveillance, the New Jersey Department of Health and Senior Services (NJDHSS) reviews the BioSense application for syndrome activity and disease alerts of potential public health importance.  In November, 2004, staff noted a Sentinel Infection Alert for Smallpox two days before the Thanksgiving holiday.  The investigation of this Sentinel Alert by NJDHSS was the first Sentinel Alert follow-up investigation by a state health department and helped state and CDC colleagues identify ways to enhance BioSense.

Objective:

This paper describes a situation in November, 2004, regarding a Sentinel Infection Alert for Smallpox that appeared in the BioSense application.

Syndromic surveillance has been used to detect variation in seasonal viral illnesses such as influenza and norovirus infection (1). Limited information is available on the use of a comprehensive bio-surveillance system, including syndromic surveillance, for detection and situational awareness during a sustained outbreak.  

Objective:

To report on surveillance and response activities during the 2006-2007 norovirus season in Boston.

This paper describes a methodology for applying natural language parsing (NLP) technologies, originally developed for analyzing biomedical journal articles, to the monitoring of emergency department patient charts for infectious diseases of interest.