File:In-silico-Surveillance-evaluating-outbreak-detection-with-simulation-models-1472-6947-13-12-S4.ogv

In-silico-Surveillance-evaluating-outbreak-detection-with-simulation-models-1472-6947-13-12-S4.ogv(Ogg Theora video file, length 37 s, 640 × 512 pixels, 604 kbps, file size: 2.63 MB)


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Summary

Description
English: Animation of the “Uniform” surveillance system with 6% coverage detecting, missing, and signaling false positives over the course of a year. The counts per day per location are visualized as epicurves centered on each location. Locations that are identified as part of a cluster are filled in with a color ranging from red to pale yellow denoting the statistical significance of the identified cluster (red = p-value of 0.001 and pale yellow = p-value of 0.03333). Inserted artificial outbreaks are shown as red triangles in the epicurves and the locations are also outlined in red. False-positive outbreaks are outlined with bold borders in black.
Date
Source Lewis B, Eubank S, Abrams A, Kleinman K (2013). "in silico Surveillance: evaluating outbreak detection with simulation models". BMC Medical Informatics and Decision Making. DOI:10.1186/1472-6947-13-12. PMID 23343523. PMC: 3691709.
Author Lewis B, Eubank S, Abrams A, Kleinman K
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Date/TimeThumbnailDimensionsUserComment
current21:57, 29 June 201337 s, 640 × 512 (2.63 MB)Open Access Media Importer BotAutomatically uploaded media file from Open Access source. Please report problems or suggestions here.

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