A Review of Evaluations of Electronic Event-based Biosurveillance Systems

Gajewski, Kimberly; Chrétien, Dominique; Peterson, Amy E.; Pavlin, Julie A.; Chitale, Rohit A.

doi:10.5210/ojphi.v5i1.4444

Cited by 2 publications

(2 citation statements)

References 19 publications

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“…33 Internet news media, social networking services, and government as well as nongovernment reports have been suggested as resources because they can be used to detect any kind of threat. 34,35 Advantages of the BSP compared with other biosurveillance systems are the capabilities to integrate the military and civilian surveillance efforts of the ROK and the United States; to leverage other existing biosurveillance systems, incorporating them into the BSP; and to expand the user interface and analytic tools through an agile development process involving user feedback and implementation of functional exercises.…”

Section: Discussionmentioning

confidence: 99%

Syndromic Surveillance System for Korea–US Joint Biosurveillance Portal: Design and Lessons Learned

Rhee¹,

Burkom²,

Yoon³

et al. 2016

Health Security

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Driven by the growing importance of situational awareness of bioterrorism threats, the Republic of Korea (ROK) and the United States have constructed a joint military capability, called the Biosurveillance Portal (BSP), to enhance biosecurity. As one component of the BSP, we developed the Military Active Real-time Syndromic Surveillance (MARSS) system to detect and track natural and deliberate disease outbreaks. This article describes the ROK military health data infrastructure and explains how syndromic data are derived and made available to epidemiologists. Queries corresponding to 8 syndromes, based on published clinical effects of weaponized pathogens, were used to classify military hospital patient records to form aggregated daily syndromic counts. A set of ICD-10 codes for each syndrome was defined through literature review and expert panel discussion. A study set of time series of national daily counts for each syndrome was extracted from the Defense Medical Statistical Information System between January 1, 2011, and May 31, 2014. A stratified, adjusted cumulative summation algorithm was implemented for each syndrome group to signal alerts prompting investigation. The algorithm was developed by calculating sensitivity to sets of 1,000 artificial outbreak signals randomly injected in the dataset, with each signal injected in a separate trial. Queries and visualizations were adapted from the Suite for Automated Global bioSurveillance. Findings indicated that early warning of outbreaks affecting fewer than 50 patients will require analysis at subnational levels, especially for common syndrome groups. Developing MARSS to improve sensitivity will require modification of underlying syndromic diagnosis codes, engineering to coordinate alerts among subdivisions, and enhanced algorithms. The bioterrorist threat in the Korean peninsula mandates these efforts.

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Section: Discussionmentioning

confidence: 99%

Syndromic Surveillance System for Korea–US Joint Biosurveillance Portal: Design and Lessons Learned

Rhee¹,

Burkom²,

Yoon³

et al. 2016

Health Security

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“…[32][33][34] As systems that provide early but nonspecific indicators of an outbreak-such as Google Flu Trends, 35 HealthMap, 36 and others 37 -mature, they will provide valuable inputs into the inference engines used for national surveillance.…”

Section: Specialized Biosurveillance Nodesmentioning

confidence: 99%

A Conceptual Architecture for National Biosurveillance: Moving Beyond Situational Awareness to Enable Digital Detection of Emerging Threats

Velsko¹,

Bates²

2016

Health Security

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Despite numerous calls for improvement, the US biosurveillance enterprise remains a patchwork of uncoordinated systems that fail to take advantage of the rapid progress in information processing, communication, and analytics made in the past decade. By synthesizing components from the extensive biosurveillance literature, we propose a conceptual framework for a national biosurveillance architecture and provide suggestions for implementation. The framework differs from the current federal biosurveillance development pathway in that it is not focused on systems useful for "situational awareness" but is instead focused on the long-term goal of having true warning capabilities. Therefore, a guiding design objective is the ability to digitally detect emerging threats that span jurisdictional boundaries, because attempting to solve the most challenging biosurveillance problem first provides the strongest foundation to meet simpler surveillance objectives. Core components of the vision are: (1) a whole-of-government approach to support currently disparate federal surveillance efforts that have a common data need, including those for food safety, vaccine and medical product safety, and infectious disease surveillance; (2) an information architecture that enables secure national access to electronic health records, yet does not require that data be sent to a centralized location for surveillance analysis; (3) an inference architecture that leverages advances in "big data" analytics and learning inference engines-a significant departure from the statistical process control paradigm that underpins nearly all current syndromic surveillance systems; and (4) an organizational architecture with a governance model aimed at establishing national biosurveillance as a critical part of the US national infrastructure. Although it will take many years to implement, and a national campaign of education and debate to acquire public buy-in for such a comprehensive system, the potential benefits warrant increased consideration by the US government.

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A Review of Evaluations of Electronic Event-based Biosurveillance Systems

Cited by 2 publications

References 19 publications

Syndromic Surveillance System for Korea–US Joint Biosurveillance Portal: Design and Lessons Learned

Syndromic Surveillance System for Korea–US Joint Biosurveillance Portal: Design and Lessons Learned

A Conceptual Architecture for National Biosurveillance: Moving Beyond Situational Awareness to Enable Digital Detection of Emerging Threats

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