Surveillance Systems

Within the syndromic surveillance literature there are acknowledged gaps with respect to penetration of syndromic surveillance systems and standard or promising practices for response. The lack of adequate data and evidence-based policy recommendations on response is especially concerning because syndromic surveillance systems are only as useful as the timely pubic health response launched after aberration detection. We undertook the first step of a multi-phase study, with the global objectives of describing existing infrastructure in responding to alerts generated by syndromic surveillance systems and creating response guidance materials for public health practitioners. The preliminary findings contained here describe syndromic surveillance systems in use throughout the United States, future plans related to the use of such systems, and basic information regarding how outbreak response is initiated. This cataloging of systems complements work currently underway by the International Society for Disease Surveillance directed towards developing a comprehensive registry of syndromic surveillance systems.

Objective

We aim to describe current syndromic surveillance systems in use throughout the U.S. and approaches to initiating an outbreak response as reported by survey participants.

Although syndromic surveillance cannot serve its intended purpose without the timely public health response launched after aberration detection, the literature is very limited with respect to response to syndromic surveillance systems alerts and related guidance for public health practitioners. Literature reviews reveal an absence of uniform approaches to developing and evaluating response protocols. The one published study that aimed to inform the development of written protocols was based on experience with a single system, ESSENCE, and concluded that careful development of an evaluation and response framework should be undertaken.

Objective

To develop a framework for public health departments to use for developing and enhancing response protocols to syndromic surveillance system alerts.

The Connecticut Department of Public Health (DPH), like all public health agencies, is constantly challenged by new health threats and emerging diseases. A major responsibility of these agencies is the rapid and effective communication of information on emerging threats to members of the public who may be potentially exposed. This responsibility for effective risk communication is critical when the public perception of risk is high. The September 11, 2001 terrorist attacks and subsequent anthrax mail attacks (Amerithrax) resulted in a new era of public risk perception and concern. Many new and advanced surveillance systems, developed in response to these events, have increased the need for effective risk communication. For example, the DPH developed its first syndromic surveillance system in September 2001 to monitor for possible bioterrorism events and emerging infections. This resulted in the implementation of a number of risk communication and response protocols. These and other protocols were tested in responding to the recent anthrax contamination of a drum maker’s residence and a multistate rash outbreak.

Objective

This paper describes various risk communications techniques used in Connecticut to provide health information to the public following surveillance signal alerts. The use of hotlines and contemporary social networking systems to quickly communicate with targeted populations are compared to the use of news releases and other traditional approaches.

Over the past seven years, the number of Lyme Disease (LD) cases in Anne Arundel County has more than doubled, from 84 in 2000 to 196 in 2007, which correlates to CDC findings. It is endemic in 10 states, including Maryland, and Anne Arundel County has the second highest number of LD cases in the state. Despite the increasing prevalence and growing public concern, there is no definitive evidence regarding efficacy of personal preventive measures and environmental interventions. Other county-level studies have investigated risk factors, but none have included the investigation as a part of routine surveillance or narrowed the study population to cases with a known exposure date range.

Objective

In order to respond to the increase of reports of LD to local health departments and the limited utility of routine LD surveillance, active surveillance activities were focused on collecting exposure data from LD cases with a reasonably narrow date range of exposure.

Emergency Department surveillance methods currently rely on identification of acute illness by tracking chief complaint or ICD9 discharge codes. Newer generation electronic medical records are now capturing additional  information such as vital signs. These data have the potential for identifying disease syndromes earlier than the traditional methods.

Objective

This paper describes the temporal relationship between numbers of cases of fever, recorded as discrete vital sign data in an electronic medical record, and ICD9 Influenza Like Illnesses in the Emergency Department at the University of Wisconsin Hospital.

The semantic web is an emerging technology for expressing rich descriptions of a problem domain in the form  of  ontologies.    An  ontology  provides  a  domain  specific  knowledge  base  for  the  communication  and  sharing  of  knowledge  between  various  human  and  computer agents [1].   Many  public  health  organizations  have  adopted  syndromic surveillance systems but criteria for the selection  of  appropriate  data  sources,  syndrome  definitions,   and   applicable   outbreak   detection   methods   have not been established [2].  Application of semantic web technology to the field of syndromic surveil-lance has been seen to be successful in an experimental  environment  through  the  BioSTORM  project  at  the  SMI  labs  at  the  Stanford  University  School  of  Medicine  [3].    The  semantic  web  shows  promise  for  providing  a  universal  problem  description  layer  that  will allow for easier integration between heterogeneous data sources and problem solving techniques. 

Objective

A syndromic surveillance system which uses a semantic web description layer is more extensible than existing systems. This will be shown through the application of appropriate software metrics, as well as a case based review that targets three major system design components.

For syndromic and related public health surveillance systems to be effective, state and local health departments and the Centers for Disease Control and Prevention (CDC) need access to a variety of types of health data. Since the development and implementation of syndromic surveillance systems in recent years, health departments have gained varied levels of access to personal health information for inclusion in these systems. A variety of federal, state, and local laws enable, restrict, and otherwise infl uence the sharing of health information between health care providers and public health agencies for surveillance, as well as research, purposes. Some health care providers have expressed reluctance or refused to provide identifi able data for syndromic surveillance to health departments (1), citing state privacy laws or the Health Insurance Portability and Accountability Act of 1996 (HIPAA) Privacy Rule (2). Although the HIPAA Privacy Rule permits health care providers to disclose protected health information without patients’ consent to public health agencies for authorized purposes, it does not supersede state laws that provide greater protection of individual privacy (2,3). The use of individuals’ health information for syndromic surveillance poses challenging questions regarding the interpretation and future development of ethical and legal standards for public health practice and research. While the practice of syndromic surveillance extends the longstanding tradition of public health surveillance as an essential element of public health practice (4), it raises in a new light equally longstanding questions about governments’ authority to collect and use health information (5). As the practice of syndromic surveillance evolves, it is in the national interest to clarify the conditions under which health information can be shared, the ways that privacy and confi dentiality can be protected, and the ways that local, state, and federal public health agencies can legally, ethically, and effectively exercise their respective responsibilities to detect, monitor, and respond to public health threats.

 

The syndromic surveillance system in Scotland was implemented in response to Gleneagles hosting the G8 summit in July 2005. Part of this surveillance system used data from NHS24, a nurse led telephone help line that is the means of access to out of hours general practice services for the Scottish population. This data was processed by the ERS system and reports generated for 10 syndromes considered relevant to possible bio-terrorism or disease outbreaks. These syndromes are; colds and flu, difficulty breathing, fever, diarrhoea, coughs, double vision, eye problems, rash, lumps and vomiting. Following the G8 summit the ERS has been updated weekly using data pre-catagorised into syndromes at NHS24 (known as protocolled data). The proportion of calls processed by the protocol at NHS24 over this time has however fallen to around 40%. This change has given the impetus to create a free text searching algorithm which can classify all calls received by NHS 24 into one of the 10 syndromes or “other”. This therefore allows all calls to be analysed by the ERS.

Objective

Public Health consultants at Health Protection Scotland (HPS) monitor routine data from the NHS24 telephone helpline to provide information on possible epidemics of flu or other infectious diseases in Scotland. Within this paper the exception reporting system run at HPS is described and the adaptations made to the classification system as a response to the change of data recording patterns at NHS24 are described.

Facing public health threats of bioterrorism and emerging infectious diseases (EID), the traditional passive surveillance system is not efficient and outmoded. Evidences reveal that several newly developed syndromic surveillance system (SSS) in different countries can provide an active, powerful, timely, and effective epidemiological investigation. Using this SSS, we can find non-specific symptoms, and set up baseline clinical data and epidemic threshold. Due to English barriers and standardized language problem in the past, we initiated to develop an emergency department-based syndromic surveillance system (ED-SSS) using clinical data involving both check-list format chief complaints (CoCo) and International Classification of Diseases, Ninth Revision (ICD-9) that best fit the situations in Taiwan.

Objective

The aims of this study are to set up a SSS for detecting newly EID outbreaks early using more standardized information of triage CoCo of hospital emergency department in metropolitan Taipei City to (1) break through Chinese language barrier; (2) investigate its feasibility to detect influenza like illness (ILI) outbreaks using integrated clinical and epidemiological information installed within information technology system; and (3) compare the sensitivity, specificity, and kappa value of ILI between ICD-9 and CoCo.

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.