Analytic Biosurveillance Methods for Resource-Limited Settings

Authors

  • Howard Burkom Johns Hopkins Applied Physics Laboratory, Laurel, MD
  • Yevgeniy Elbert Johns Hopkins Applied Physics Laboratory, Laurel, MD
  • Erhan Guven Johns Hopkins Applied Physics Laboratory, Laurel, MD
  • Jacqueline Coberly Johns Hopkins Applied Physics Laboratory, Laurel, MD

DOI:

https://doi.org/10.5210/ojphi.v6i1.5037

Abstract

The authors describe the challenges of disease surveillance in settings lacking infrastructure and access to medical care. They address the role of analytic methods and evaluate open-source temporal alerting algorithms chosen for the Suite for Automated Global Electronic bioSurveillance (SAGES), collection of modular, freely-available software tools to enable electronic surveillance in these settings. An algorithm test-bed is described and used to compare algorithm alerting performance for both daily and weekly data streams. Multiple detection performance measures are defined, and a practical means of combining them is applied to recommend preferred alerting methods for common scenarios.

Author Biography

Howard Burkom, Johns Hopkins Applied Physics Laboratory, Laurel, MD

Howard Burkom is a project manager and researcher within the disease surveillance initiative of the Johns Hopkins Applied Physics Laboratory. He was previously a statistical consultant to the Biosense team at CDC, collaborating on system improvements and with health departments on public health applications. An elected member of the ISDS Board Of Directors for 7 years, he has worked exclusively in biosurveillance since 2000, adapting analytic methods from various scientific disciplines for disease monitoring systems.

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Published

2014-03-03

How to Cite

Burkom, H., Elbert, Y., Guven, E., & Coberly, J. (2014). Analytic Biosurveillance Methods for Resource-Limited Settings. Online Journal of Public Health Informatics, 6(1). https://doi.org/10.5210/ojphi.v6i1.5037

Issue

Vol. 6 No. 1 (2014)

Section

Lightning Talks

License

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