title: Reviewing and managing syndromic surveillance SaTScan datasets using an open source data visualization tool.
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.
authors.affiliation: Indiana University School of Medicine, Indianapolis, IN, USA.
authors.forename: Shaun J
authors.initials: SJ
authors.lastname: Grannis
authors.forename: James
authors.initials: J
authors.lastname: Egg
authors.forename: J Marc
authors.initials: JM
authors.lastname: Overhage
mesh_terms: D016000:Cluster Analysis; D003626:Data Display; D004196:Disease Outbreaks; D040362:Geographic Information Systems; D006801:Humans; D011159:Population Surveillance / Q000379:methods*; D040442:Public Health Informatics; D012984:Software