title: Advancing a framework to enable characterization and evaluation of data streams useful for biosurveillance.
abstract: In recent years, biosurveillance has become the buzzword under which a diverse set of ideas and activities regarding detecting and mitigating biological threats are incorporated depending on context and perspective. Increasingly, biosurveillance practice has become global and interdisciplinary, requiring information and resources across public health, One Health, and biothreat domains. Even within the scope of infectious disease surveillance, multiple systems, data sources, and tools are used with varying and often unknown effectiveness. Evaluating the impact and utility of state-of-the-art biosurveillance is, in part, confounded by the complexity of the systems and the information derived from them. We present a novel approach conceptualizing biosurveillance from the perspective of the fundamental data streams that have been or could be used for biosurveillance and to systematically structure a framework that can be universally applicable for use in evaluating and understanding a wide range of biosurveillance activities. Moreover, the Biosurveillance Data Stream Framework and associated definitions are proposed as a starting point to facilitate the development of a standardized lexicon for biosurveillance and characterization of currently used and newly emerging data streams. Criteria for building the data stream framework were developed from an examination of the literature, analysis of information on operational infectious disease biosurveillance systems, and consultation with experts in the area of biosurveillance. To demonstrate utility, the framework and definitions were used as the basis for a schema of a relational database for biosurveillance resources and in the development and use of a decision support tool for data stream evaluation.
authors.affiliation: Defense Systems and Analysis Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
authors.forename: Kristen J
authors.initials: KJ
authors.lastname: Margevicius
authors.affiliation: Defense Systems and Analysis Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Generous
authors.affiliation: Biosciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
authors.forename: Kirsten J
authors.initials: KJ
authors.lastname: Taylor-McCabe
authors.affiliation: Defense Systems and Analysis Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
authors.forename: Mac
authors.initials: M
authors.lastname: Brown
authors.affiliation: Defense Systems and Analysis Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
authors.forename: W Brent
authors.initials: WB
authors.lastname: Daniel
authors.affiliation: Defense Systems and Analysis Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
authors.forename: Lauren
authors.initials: L
authors.lastname: Castro
authors.affiliation: Defense Systems and Analysis Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
authors.forename: Andrea
authors.initials: A
authors.lastname: Hengartner
authors.affiliation: Defense Systems and Analysis Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
authors.forename: Alina
authors.initials: A
authors.lastname: Deshpande
mesh_terms: D000818:Animals; D055877:Biosurveillance / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D006801:Humans; D016247:Information Storage and Retrieval; D009938:Organizations; D062486:Public Health Surveillance