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

Shaun Grannis, James Egg, J. Marc Overhage

Research output: Contribution to journalArticle

2 Citations (Scopus)

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
Pages (from-to)967
Number of pages1
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
StatePublished - 2005

Fingerprint

Information Storage and Retrieval
Disease Outbreaks
Software
Datasets

ASJC Scopus subject areas

  • Medicine(all)

Cite this

@article{e2fe0353b5be4eb0a276286c36765230,
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.",
author = "Shaun Grannis and James Egg and Overhage, {J. Marc}",
year = "2005",
language = "English",
pages = "967",
journal = "AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium",
issn = "1559-4076",
publisher = "American Medical Informatics Association",

}

TY - JOUR

T1 - Reviewing and managing syndromic surveillance SaTScan datasets using an open source data visualization tool.

AU - Grannis, Shaun

AU - Egg, James

AU - Overhage, J. Marc

PY - 2005

Y1 - 2005

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=36048935269&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=36048935269&partnerID=8YFLogxK

M3 - Article

SP - 967

JO - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium

JF - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium

SN - 1559-4076

ER -