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Evaluation of sliding baseline methods for spatial estimation for cluster detection in the biosurveillance system |
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| Authors: | Jian Xing Howard Burkom Linda Moniz James Edgerton Michael Leuze Jerome Tokars |
| Institution: | (1) Centers for Disease Control and Prevention, 1600 Clifton Road NE, Atlanta, GA 30333, USA;(2) The Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, MD 20723, USA;(3) Edge Space Systems, Inc, PO Box 310, Glenelg, MD 21737, USA;(4) Oak Ridge National Laboratory Oak Ridge National Laboratory, PO Box 2008, MS 6367, Oak Ridge, TN 37831, USA |
| Abstract: | BackgroundThe Centers for Disease Control and Prevention's (CDC's) BioSense system provides near-real time situational awareness for public health monitoring through analysis of electronic health data. Determination of anomalous spatial and temporal disease clusters is a crucial part of the daily disease monitoring task. Our study focused on finding useful anomalies at manageable alert rates according to available BioSense data history. |
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