Reviewing and managing syndromic surveillance SaTScan datasets using an open source data visualization tool.

Shaun J. Grannis, James Egg, J. Marc Overhage

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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.

Original languageEnglish (US)
Number of pages1
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
StatePublished - 2005

ASJC Scopus subject areas

  • Medicine(all)

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