Julie A. Pavlin

Implementing Syndromic Surveillance: A Practical Guide Informed by the Early Experience

Syndromic surveillance refers to methods relying on detection of individual and population health indicators that are discernible before confirmed diagnoses are made. In particular, prior to the laboratory confirmation of an infectious disease, ill persons may exhibit behavioral patterns, symptoms, signs, or laboratory findings that can be tracked through a variety of data sources. Syndromic surveillance systems are being developed locally, regionally, and nationally. The efforts have been largely directed at facilitating the early detection of a covert bioterrorist attack, but the technology may also be useful for general public health, clinical medicine, quality improvement, patient safety, and research. This report, authored by developers and methodologists involved in the design and deployment of the first wave of syndromic surveillance systems, is intended to serve as a guide for informaticians, public health managers, and practitioners who are currently planning deployment of such systems in their regions.

A systems overview of the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE II)

The Electronic Surveillance System for the Early Notification of Community-Based Epidemics, or ESSENCE II, uses syndromic and nontraditional health information to provide very early warning of abnormal health conditions in the National Capital Area (NCA). ESSENCE II is being developed for the Department of Defense Global Emerging Infections System and is the only known system to combine both military and civilian health care information for daily outbreak surveillance. The National Capital Area has a complicated, multijurisdictional structure that makes data sharing and integrated regional surveillance challenging. However, the strong military presence in all jurisdictions facilitates the collection of health care information across the region. ESSENCE II integrates clinical and nonclinical human behavior indicators as a means of identifying the abnormality as close to the time of onset of symptoms as possible. Clinical data sets include emergency room syndromes, private practice billing codes grouped into syndromes, and veterinary syndromes. Nonclinical data include absenteeism, nurse hotline calls, prescription medications, and over-the-counter self-medications. Correctly using information marked by varying degrees of uncertainty is one of the more challenging as pects of this program. The data (without personal identifiers) are captured in an electronic format, encrypted, archived, and processed at a secure facility. Aggregated information is then provided to users on secure Web sites. When completed, the system will provide automated capture, archiving, processing, and notification of abnormalities to epidemiologists and analysts. Outbreak detection methods currently include temporal and spatial variations of odds ratios, autoregressive modeling, cumulative summation, matched filter, and scan statistics. Integration of nonuniform data is needed to increase sensitivity and thus enable the earliest notification possible. The performance of various detection techniques was compared using results obtained from the ESSENCE II system.

Code-based syndromic surveillance for influenzalike illness by International Classification of Diseases, Ninth Revision.

ICD-9 codes collected automatically in a syndromic system are sensitive and specific in detecting outbreaks caused by respiratory viruses.

Beyond traditional surveillance: applying syndromic surveillance to developing settings - opportunities and challenges.

BackgroundAll countries need effective disease surveillance systems for early detection of outbreaks. The revised International Health Regulations [IHR], which entered into force for all 194 World Health Organization member states in 2007, have expanded traditional infectious disease notification to include surveillance for public health events of potential international importance, even if the causative agent is not yet known. However, there are no clearly established guidelines for how countries should conduct this surveillance, which types of emerging disease syndromes should be reported, nor any means for enforcement.DiscussionThe commonly established concept of syndromic surveillance in developed regions encompasses the use of pre-diagnostic information in a near real time fashion for further investigation for public health action. Syndromic surveillance is widely used in North America and Europe, and is typically thought of as a highly complex, technology driven automated tool for early detection of outbreaks. Nonetheless, low technology applications of syndromic surveillance are being used worldwide to augment traditional surveillance.SummaryIn this paper, we review examples of these novel applications in the detection of vector-borne diseases, foodborne illness, and sexually transmitted infections. We hope to demonstrate that syndromic surveillance in its basic version is a feasible and effective tool for surveillance in developing countries and may facilitate compliance with the new IHR guidelines.

The AFHSC-Division of GEIS Operations Predictive Surveillance Program: a multidisciplinary approach for the early detection and response to disease outbreaks

The Armed Forces Health Surveillance Center, Division of Global Emerging Infections Surveillance and Response System Operations (AFHSC-GEIS) initiated a coordinated, multidisciplinary program to link data sets and information derived from eco-climatic remote sensing activities, ecologic niche modeling, arthropod vector, animal disease-host/reservoir, and human disease surveillance for febrile illnesses, into a predictive surveillance program that generates advisories and alerts on emerging infectious disease outbreaks. The program’s ultimate goal is pro-active public health practice through pre-event preparedness, prevention and control, and response decision-making and prioritization. This multidisciplinary program is rooted in over 10 years experience in predictive surveillance for Rift Valley fever outbreaks in Eastern Africa. The AFHSC-GEIS Rift Valley fever project is based on the identification and use of disease-emergence critical detection points as reliable signals for increased outbreak risk. The AFHSC-GEIS predictive surveillance program has formalized the Rift Valley fever project into a structured template for extending predictive surveillance capability to other Department of Defense (DoD)-priority vector- and water-borne, and zoonotic diseases and geographic areas. These include leishmaniasis, malaria, and Crimea-Congo and other viral hemorrhagic fevers in Central Asia and Africa, dengue fever in Asia and the Americas, Japanese encephalitis (JE) and chikungunya fever in Asia, and rickettsial and other tick-borne infections in the U.S., Africa and Asia.

Department of Defense influenza and other respiratory disease surveillance during the 2009 pandemic

The Armed Forces Health Surveillance Center’s Division of Global Emerging Infections Surveillance and Response System (AFHSC-GEIS) supports and oversees surveillance for emerging infectious diseases, including respiratory diseases, of importance to the U.S. Department of Defense (DoD). AFHSC-GEIS accomplishes this mission by providing funding and oversight to a global network of partners for respiratory disease surveillance. This report details the system’s surveillance activities during 2009, with a focus on efforts in responding to the novel H1N1 Influenza A (A/H1N1) pandemic and contributions to global public health. Active surveillance networks established by AFHSC-GEIS partners resulted in the initial detection of novel A/H1N1 influenza in the U.S. and several other countries, and viruses isolated from these activities were used as seed strains for the 2009 pandemic influenza vaccine. Partners also provided diagnostic laboratory training and capacity building to host nations to assist with the novel A/H1N1 pandemic global response, adapted a Food and Drug Administration-approved assay for use on a ruggedized polymerase chain reaction platform for diagnosing novel A/H1N1 in remote settings, and provided estimates of seasonal vaccine effectiveness against novel A/H1N1 illness. Regular reporting of the system’s worldwide surveillance findings to the global public health community enabled leaders to make informed decisions on disease mitigation measures and controls for the 2009 A/H1N1 influenza pandemic. AFHSC-GEIS’s support of a global network contributes to DoD’s force health protection, while supporting global public health.

Enhancing Time-Series Detection Algorithms for Automated Biosurveillance

BioSense is a US national system that uses data from health information systems for automated disease surveillance. We studied 4 time-series algorithm modifications designed to improve sensitivity for detecting artificially added data. To test these modified algorithms, we used reports of daily syndrome visits from 308 Department of Defense (DoD) facilities and 340 hospital emergency departments (EDs). At a constant alert rate of 1%, sensitivity was improved for both datasets by using a minimum standard deviation (SD) of 1.0, a 14-28 day baseline duration for calculating mean and SD, and an adjustment for total clinic visits as a surrogate denominator. Stratifying baseline days into weekdays versus weekends to account for day-of-week effects increased sensitivity for the DoD data but not for the ED data. These enhanced methods may increase sensitivity without increasing the alert rate and may improve the ability to detect outbreaks by using automated surveillance system data.

Investigation of disease outbreaks detected by “syndromic” surveillance systems

Syndromic surveillance systems can detect potential disease outbreaks quickly and can provide useful tools to assist in outbreak investigation. The steps used to investigate diseases detected through these newer methods are not that different from traditional investigative measures, but the differences and limitations of the systems must be understood. With syndromic surveillance systems, there is often readily available electronic demographic information that can help define the epidemic and direct disease control measures. The diagnosis needs to be confirmed as quickly as possible, however, as specific diagnostic information will be missing with early detection from nonspecific data. It is also important not to disregard smaller, nonsevere rises in disease incidence as they might be a harbinger of a worsening outbreak. The rapidity of most syndromic surveillance systems also requires an equally rapid response, and planning must be done to prioritize alert categories and the response sequence to best utilize the information available in these new systems.

Innovative Surveillance Methods for Rapid Detection of Disease Outbreaks and Bioterrorism: Results of an Interagency Workshop on Health Indicator Surveillance

A system designed to rapidly identify an infectious disease outbreak or bioterrorism attack and provide important demographic and geographic information is lacking in most health departments nationwide. The Department of Defense Global Emerging Infections System sponsored a meeting and workshop in May 2000 in which participants discussed prototype systems and developed recommendations for new surveillance systems. The authors provide a summary of the groups findings, including expectations and recommendations for new surveillance systems. The consensus of the group was that a nationally led effort in developing health indicator surveillance methods is needed to promote effective, innovative systems.

Malaria and other vector-borne infection surveillance in the U.S. Department of Defense Armed Forces Health Surveillance Center-Global Emerging Infections Surveillance program: review of 2009 accomplishments

Vector-borne infections (VBI) are defined as infectious diseases transmitted by the bite or mechanical transfer of arthropod vectors. They constitute a significant proportion of the global infectious disease burden. United States (U.S.) Department of Defense (DoD) personnel are especially vulnerable to VBIs due to occupational contact with arthropod vectors, immunological naiveté to previously unencountered pathogens, and limited diagnostic and treatment options available in the austere and unstable environments sometimes associated with military operations. In addition to the risk uniquely encountered by military populations, other factors have driven the worldwide emergence of VBIs. Unprecedented levels of global travel, tourism and trade, and blurred lines of demarcation between zoonotic VBI reservoirs and human populations increase vector exposure. Urban growth in previously undeveloped regions and perturbations in global weather patterns also contribute to the rise of VBIs. The Armed Forces Health Surveillance Center-Global Emerging Infections Surveillance and Response System (AFHSC-GEIS) and its partners at DoD overseas laboratories form a network to better characterize the nature, emergence and growth of VBIs globally. In 2009 the network tested 19,730 specimens from 25 sites for Plasmodium species and malaria drug resistance phenotypes and nearly another 10,000 samples to determine the etiologies of non-Plasmodium species VBIs from regions spanning from Oceania to Africa, South America, and northeast, south and Southeast Asia. This review describes recent VBI-related epidemiological studies conducted by AFHSC-GEIS partner laboratories within the OCONUS DoD laboratory network emphasizing their impact on human populations.