Localized Cluster Detection Applied to Joint and Separate Military and Veteran Subpopulations

Authors

  • Howard Burkom Johns Hopkins Applied Physics Laboratory, Laurel, MD
  • Yevgeniy Elbert Johns Hopkins Applied Physics Laboratory, Laurel, MD
  • Carla Winston Office of Public Health Surveillance Research, Veterans Health Administration, Palo Alto, CA
  • Julie Pavlin Armed Forces Health Surveillance Center, Silver Spring, MD
  • Cynthia Lucero-Obusan Office of Public Health Surveillance Research, Veterans Health Administration, Palo Alto, CA
  • Mark Holodniy Office of Public Health Surveillance Research, Veterans Health Administration, Palo Alto, CA

DOI:

https://doi.org/10.5210/ojphi.v5i1.4414

Abstract

The study investigated combining Department of Defense (DoD) and Veterans Administration (VA) outpatient datasets for disease cluster detection. Results of retrospective scan statistics over 4 years were compared using both separate and joined data. Combining data sources increased the background alert rate by a manageable 1-10% across run sets. Clustering evidence of known outbreaks found in separate DoD and VA runs persisted when data sets were combined. Some clusters found only when the data were combined persisted over several days and may have indicated small events not reported in either system.

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 is also 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

2013-03-23

How to Cite

Burkom, H., Elbert, Y., Winston, C., Pavlin, J., Lucero-Obusan, C., & Holodniy, M. (2013). Localized Cluster Detection Applied to Joint and Separate Military and Veteran Subpopulations. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4414

Issue

Section

Oral Presentations: Cluster Detection