Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

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.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|June 17, 2006
PubMed
Summary

This study introduces a new tool to visualize disease cluster data from SaTScan software. It simplifies interpreting large datasets, aiding early outbreak detection and public health surveillance.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Influence of correlated vaccination behaviors on estimates of COVID-19 vaccine effectiveness in older adults - VISION network, October 2023 - March 2024.

Vaccine·2026
Same author

An Interoperability Moonshot Proposal.

Applied clinical informatics·2026
Same author

Interim Estimated Effectiveness of 2025-2026 COVID-19 Vaccines in Adults Using a Test-Negative Design.

JAMA network open·2026
Same author

Influenza Activity and Estimated Vaccine Effectiveness During the 2025-2026 Influenza Season.

JAMA network open·2026
Same author

Estimated Effectiveness of 2024-2025 COVID-19 Vaccines in Adults.

JAMA internal medicine·2026
Same author

Influenza vaccine effectiveness against influenza-associated hospitalizations and emergency department or urgent care encounters among children and adults - United States, 2024-25 season.

medRxiv : the preprint server for health sciences·2026

Area of Science:

  • Epidemiology
  • Public Health
  • Data Science

Background:

  • SaTScan is a widely used free software for detecting disease clusters.
  • Analyzing large geographic and temporal surveillance datasets from SaTScan presents interpretation challenges.
  • Manual analysis of text-based SaTScan data for spatial-temporal disease patterns is cognitively demanding.

Purpose of the Study:

  • To develop an open-source tool for simplifying the interpretation of SaTScan analytic datasets.
  • To transform complex SaTScan data into user-friendly, navigable visualizations.
  • To enhance the early detection and understanding of disease outbreaks.

Main Methods:

  • Developed a Java-based open-source software tool.
  • The tool processes and transforms SaTScan analytic datasets.

Related Experiment Videos

  • Outputs easily navigable data visualizations for spatial-temporal analysis.

    • Main Results:

    • Successfully created a tool to convert SaTScan data into visual formats.
    • The visualizations simplify the interpretation of complex disease cluster patterns.
    • Facilitates easier identification of disease outbreaks through enhanced data exploration.

    Conclusions:

    • The developed tool significantly aids in understanding disease clusters identified by SaTScan.
    • Improved data visualization enhances public health surveillance and outbreak response capabilities.
    • Open-source visualization tools are valuable for epidemiological data analysis.