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Reviewing and managing syndromic surveillance SaTScan datasets using an open source data visualization tool
Shaun J Grannis1, James Egg, J Marc Overhage
1Indiana University School of Medicine, Indianapolis, IN, USA.
Abstract:
SaTScan is a popular, free software tool used to identify disease clusters early in the course of an outbreak. Using geographic and time-based surveillance data, SaTScan can generate large datasets that are difficult for humans to interpret. Tracing disease clusters through space and time using text tables is a challenging cognitive task. To simplify this process, we developed a Java-based open-source tool to transform SaTScan analytic datasets into easily navigable data visualizations.
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