The Surveillance Window - Contextualizing Data Streams

Authors

  • Kirsten McCabe Los Alamos National Laboratory, Los Alamos, NM
  • Lauren Castro Los Alamos National Laboratory, Los Alamos, NM
  • Mac Brown Los Alamos National Laboratory, Los Alamos, NM
  • William Daniel Los Alamos National Laboratory, Los Alamos, NM
  • Eric Nick Generous Los Alamos National Laboratory, Los Alamos, NM
  • Kristen Margevicius Los Alamos National Laboratory, Los Alamos, NM
  • Alina Deshpande Los Alamos National Laboratory, Los Alamos, NM

DOI:

https://doi.org/10.5210/ojphi.v5i1.4404

Abstract

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. In this presentation application of this methodology to Foot and Mouth Disease, Ebola and Influenza and E.coli related gastrointestinal disease surveillance will be demonstrated.

Author Biography

Kirsten McCabe, Los Alamos National Laboratory, Los Alamos, NM

Kirsten J Taylor-McCabe, Ph.D., is a Scientist and Interim BSL3 Director in the Biosecurity and Public Health Group in Bioscience Division at Los Alamos National Laboratory. Kirsten received a B.A in Biochemistry and Molecular, Cellular and Developmental Biology from the University of Colorado at Boulder. She also holds a Masters in Biochemistry from Kent State University and Ph.D in Molecular Biochemistry from Loyola University Stritch School of Medicine.

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Published

2013-03-23

How to Cite

McCabe, K., Castro, L., Brown, M., Daniel, W., Generous, E. N., Margevicius, K., & Deshpande, A. (2013). The Surveillance Window - Contextualizing Data Streams. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4404

Issue

Section

Poster Presentations