Syndromic Surveillance

The Triple-S project (Syndromic Surveillance Systems in Europe, www.syndromicsurveillance.eu), co-financed by the European Commission and involving twenty four organizations from fourteen countries was launched in September 2010 with the following objectives 1) performing an inventory of existing or planned SyS systems in Europe both in animal and public health, 2) building a network of experts involved in SyS 3) producing guidelines to implement SyS systems, 4) developing synergies between human and animal health SyS systems. The project is based on a cooperation between human and animal health experts, as supported by the One Health initiative [1].

Objective: 

The objective of this study, based on the Triple-S project outputs, was to present the existing synergies between human and animal health syndromic surveillance (SyS) systems in Europe and a proposal to enhance this kind of collaboration.

 

Florida has implemented various surveillance methods to augment existing sources of surveillance data and enhance decision making with timely evidence based assessments to guide response efforts post-hurricanes. Historically, data collected from deployed federal assets have been an integral part of this effort. However, a number of factors have made this type of surveillance challenging: logistical is- sues of field work in a post-disaster environment, the resource inten- sive manual data collection process from DMAT sites, and delayed analysis and interpretation of these data to inform decision makers. The ESSENCE-FL system is an automated and secure web-based ap- plication accessed by FDOH epidemiologists and staff at participat- ing hospitals.

Objective

The Florida Department of Health (FDOH), Bureau of Epidemi- ology, partnered with the U.S. Department of Health and Human Services (HHS) Office of the Assistant Secretary for Preparedness and Response (ASPR) to improve surveillance methods in post dis- aster or response events. A new process was implemented for con- ducting surveillance to monitor injury and illness for those presenting for care to ASPR assets such as Disaster Medical Assistance Team (DMAT) sites when they are operational in the state. The purpose of the current work was to field test and document the operational ex- perience of the newly implemented ASPR data module in ESSENCE- FL (syndromic surveillance system) to receive near real-time automated data feeds when ASPR federal assets were deployed in Florida during the 2012 Republican National Convention (RNC).

MUse will make EHR data increasingly available for public health surveillance. For Stage 2, the Centers for Medicare & Medicaid Services (CMS) regulations will require hospitals and offer an option for eligible professionals to provide electronic syndromic surveillance data to public health. Together, these data can strengthen public health surveillance capabilities and population health outcomes (Figure 1). To facilitate the adoption and effective use of these data to advance population health, public health priorities and system capabilities must shape standards for data exchange. Input from all stakeholders is critical to ensure the feasibility, practicality, and, hence, adoption of any recommendations and data use guidelines.

Objective

To develop national Stage 2 Meaningful Use (MUse) recommendations for syndromic surveillance using hospital inpatient and ambulatory clinical care electronic health record (EHR) data

Lack of access to regular dental care often results in costly, oral health visits to EDs that could otherwise have been prevented or managed by a dentist (1). Most studies on oral health-related visits to EDs have used a wide range of classifications from different databases, but none have used syndromic surveillance data. The volume, frequency, and included details of syndromic data enabled timely burden estimates of nontraumatic oral health visits for NC EDs.

Objective:

To develop a nontraumatic oral health classification that could estimate the burden of oral health-related visits in North Carolina (NC) Emergency Departments (EDs) using syndromic surveillance system data.

 

Los Angeles County’s (LAC) early event detection system captures over 60% of total ED visits, as well as 800 to 1,000 emergency dispatch calls from Los Angeles City Fire (LACF) daily. Both ED visits and EDC calls are classified into syndrome categories, and then analyzed for aberrations in count and spatial distribution. During periods of high temperatures, a heat report is generated and sent to stakeholders upon request. We describe how syndromic surveillance serves as an important near real-time, population-based instrument for measuring the impact of heat waves on emergency service utilization in LAC.

Objective: 

To assess current indicators for situational awareness during heat waves derived from electronic emergency department (ED) and 911 emergency dispatch call (EDC) center data.

 

The incidence of and hospitalizations for SSTI have steadily increased over the last decade in the United States, primarily due to the emergence and spread of community acquired Methicillin resistant Staphylococcus aureus (CA-MRSA). The ED is a common site for SSTI treatment and serves populations not captured by traditional surveillance, including the homeless and uninsured. The use of near real-time syndromic surveillance within the ED to detect unusual activity for further public health investigation has been used to augment traditional infectious disease surveillance. However, the use of this approach for monitoring local epidemiologic trends in SSTI presentation where laboratory data are not available, has not previously been described.

Objective

We sought to describe the epidemiology of emergency department (ED) visits for skin and soft tissue infections (SSTI) in an urban area with diverse neighborhood populations using syndromic surveillance system data for the time period from 2007-2011. Our aims were threefold: to demonstrate a proof of concept using syndromic surveillance for SSTI surveillance in the absence of laboratory data, to estimate the burden of ED visits associated with SSTI, and to determine potential geographic “hotspots” for these infections.

Data is collected daily by the DOHMH from 49 of the 52 NYC EDs, representing approximately 95% of all ED visits in NYC. Variability in data fields between and within EDs has been noticed for some time. Differences in chief complaint (CC) characteristics and inconsistent availability of data elements, such as disposition and diagnosis, suggest that procedures, coding practices and health information systems (HIS) are not standardized across all NYC EDs, and may change within EDs. These differences may have an unapparent effect on the DOHMH’s ability to consistently categorize ED visits into syndrome groupings, which may alter how syndromic trends are analyzed. Prior to this project, the DOHMH had no method in place to regularly capture, evaluate or utilize this level of ED-specific information.

Objective

To describe the development, implementation, and analysis of a hospital based emergency department (ED) survey and site visit project conducted by the New York City (NYC) Department of Health and Mental Hygiene (DOHMH).

Early detection of rarely occurring but potentially harmful diseases such as bio-threat agents (e.g., anthrax), chemical agents (e.g., sarin), and naturally occurring diseases (e.g., meningitis) is critical for rapid initiation of treatment, infection control measures, and emergency response plans. To facilitate clinicians’ ability to detect these diseases, various syndrome definitions have been developed. Due to the rarity of these diseases, standard statistical methodologies for validating syndrome definitions are not applicable.

Objective

To develop and test a novel syndrome definition validation approach for rarely occurring diseases.

Preface

Effective public health surveillance is essential for detecting and responding to emerging public health threats, including terrorism and emerging infectious diseases. New surveillance methods are being developed and tested to improve the timeliness and completeness of detection of disease outbreaks. One promising set of approaches is syndromic surveillance, in which information about health events that precede a firm clinical diagnosis is captured early and rapidly from existing, usually electronic, data sources, and analyzed frequently to detect signals that might indicate an outbreak requiring investigation.

To provide a forum for scientists and practitioners to report on progress in developing and evaluating syndromic surveillance systems, the New York City Department of Health and Mental Hygiene, the New York Academy of Medicine, and CDC convened the second annual National Syndromic Surveillance Conference in New York City during October 23--24, 2003. The conference, supported by the Alfred P. Sloan Foundation, was attended by more than 460 public health practitioners and researchers, who had the opportunity to hear 41 oral presentations and view 50 poster presentations.

The original papers and posters for this conference were chosen by a scientific program committee after a review of submitted abstracts. Senior researchers in the field were also invited to address key concerns in surveillance for early detection of outbreaks. All participants who presented papers or posters at either the conference or at a preconference workshop were invited to submit manuscripts based on their presentations for publication in this Morbidity and Mortality Weekly Report Supplement. Each manuscript was then reviewed by at least two peer reviewers and final publication decisions were made by an editorial committee. Many of the articles are considerably different from the material originally presented at the conference. Certain authors updated their findings, and others were asked to revise their papers into descriptions of syndromic surveillance systems. Other presenters chose to submit only abstracts. Papers are presented here in the following order: system descriptions, research methods, evaluation, and public health practice.

In addition to these reports, other resources on syndromic surveillance are available. The proceedings of the 2002 National Syndromic Surveillance Conference were published in the Journal of Urban Health (accessible at http://jurban.oup journals.org/content/suppl_1/index.shtml). In May 2004, a revisedFramework for Evaluating Public Health Surveillance Systems for Early Detection of Outbreaks was published (MMWR 2004;53[No. RR-5]). An annotated bibliography of published papers and other Internet-accessible materials has been developed and is maintained monthly on a CDC website (http://www.cdc.gov/epo/dphsi/syndromic/index.htm). An Internet-based forum (http://syndromic.forum.cdc.gov) was established for discussion of topics related to syndromic surveillance and was used to distribute answers to audience questions raised at the conference. A related forum (http://surveval.forum.cdc. gov) has been maintained for discussion of topics related to surveillance system evaluation. Finally, the website of the Annual Syndromic Surveillance Conferences (http://www. syndromic.org) includes links to recent news and scientific articles about syndromic surveillance, oral and poster presentations and workshop materials from past conferences, and notices of upcoming conferences. The third National Syndromic Surveillance Conference is planned for November 3--4, 2004, in Boston, Massachusetts.

The editorial committee acknowledges the work of the scientific planning committee: Dennis Cochrane, Christine Hahn, Patrick Kelley, Martin Kulldorff, John Loonsk, David Madigan, Richard Platt, and Don Weiss. The committee is also grateful for the support and efforts of the following staff members in conducting this conference and developing this Supplement: Alan Fleischman, Irv Gertner, and Jessica Hartman, New York Academy of Medicine; Rick Heffernan, New York Department of Health and Mental Hygiene; and Alan Davis, Division of Public Health Surveillance and Informatics, Epidemiology Program Office, CDC; Valerie Kokor, Division of International Health, Epidemiology Program Office; and Stephanie Malloy, Jeffrey Sokolow, and Malbea LaPete, MMWR, Epidemiology Program Office, CDC. Special thanks are given to JoEllen DeThomasis, Division of Applied Public Health Training and Division of Public Health Surveillance and Informatics, Epidemiology Program Office, CDC, who coordinated the preparation of these reports.

--- The Editorial Committee