Contextualizing Data Streams for Infectious Disease Surveillance

Kirsten Taylor-McCabe, Lauren Castro, Nicholas Generous, Kristen Margevicius, Mac Brown, Alina Deshpande


To aid in developing a global biosurveillance program, it is critical to develop a framework to capture and understand the myriad of data streams and evaluate them in context of surveillance goals.  Toward this goal, Los Alamos National Laboratory has developed a new method of evaluating the effectiveness of data stream types through the use of a novel concept called the surveillance window, a technique that integrates operational systems analysis, surveillance system analysis and epidemiological analysis. This study provides a simple, yet elegant methodology for which to ground truth known and emerging data streams for utility in integrated biosurveillance efforts.

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Online Journal of Public Health Informatics * ISSN 1947-2579 *