NBIC and DTRA, An Interagency Partnership to Integrate Analyst Capabilities

Wai-Ling Mui, Edward P. Argenta, Teresa Quitugua, Christopher Kiley

Abstract


ObjectiveThe National Biosurveillance Integration Center (NBIC) andthe Defense Threat Reduction Agency’s Chemical and BiologicalTechnologies Department (DTRA J9 CB) have partnered to co-develop the Biosurveillance Ecosystem (BSVE), an emergingcapability that aims to provide a virtual, customizable analystworkbench that integrates health and non-health data. This partnershippromotes engagement between diverse health surveillance entities toincrease awareness and improve decision-making capabilities.IntroductionNBIC collects, analyzes, and shares key biosurveillanceinformation to support the nation’s response to biological events ofconcern. Integration of this information enables early warning andshared situational awareness to inform critical decision making, anddirect response and recovery efforts.DTRA J9 CB leads DoD S&T to anticipate, defend, and safeguardagainst chemical and biological threats for the warfighter and thenation.These agencies have partnered to meet the evolving needs of thebiosurveillance community and address gaps in technology and datasharing capabilities. High-profile events such as the 2009 H1N1pandemic, the West African Ebola outbreak, and the recent emergenceof Zika virus disease have underscored the need for integration ofdisparate biosurveillance systems to provide a more functionalinfrastructure. This allows analysts and others in the communityto collect, analyze, and share relevant data across organizationssecurely and efficiently. Leveraging existing biosurveillance effortsprovides the federal public health community, and its partners, witha comprehensive interagency platform that enables engagement anddata sharing.MethodsNBIC and DTRA are leveraging existing biosurveillance projectsto share data feeds, work processes, resources, and lessons learned.A multi-stakeholder Agile process was implemented to representthe interests of NBIC, DTRA, and their respective partners. Systemrequirements generated by both agencies were combined to form asingle backlog of prioritized needs. Functional requirements fromNBIC support the development of the prototype by refining systemcapabilities and providing an operational perspective. DTRA’stechnical expertise and research and development (R&D) portfolioensures robust analytic applications are embedded within a secure,scalable system architecture.Integration of analyst validated data from the NBIC Biofeedssystem serves as a gold-standard to improve analytic developmentin machine learning and natural language processing. Additionally,working groups are formed using NBIC and DTRA extendedpartnerships with academia and private industry to expand R&Dpossibilities. These expansions include leveraging existing ontologyefforts for improved system functionality and integrating social mediaalgorithms for improved topic analysis output.ResultsThe combined efforts of these two agencies to develop theBSVE and improve overall biosurveillance processes across thefederal government has enhanced understanding of the needs ofthe community in a variety of mission spaces. To date, co-creation ofproducts, joint analysis, and sharing of data feeds has become a majorpriority for both partners to advance biosurveillance outcomes. Withinthe larger efforts of system development, possible coordination withother agencies such as the Department of Veterans Affairs (VA) andthe US Geological Survey (USGS) could expand reach of the systemto ensure fulfillment of health surveillance requirements as a whole.ConclusionsThe NBIC and DTRA partnership has demonstrated value inimproving biosurveillance capabilities for each agency and theirpartners. BSVE will provide NBIC analysts with a collaborativetool that can leverage use of applications that visualize near real-time global epidemic and outbreak data from a range of unique andtrusted sources. The continued collaboration means ongoing accessto new data streams and analytic processes for all analysts, as wellas advanced machine learning algorithms that increase capabilitiesfor joint analysis, rapid product creation, and continuous interagencycommunication.

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DOI: https://doi.org/10.5210/ojphi.v9i1.7624



Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org