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Published on: January 2, 2011
Visual analytics for epidemiologists: understanding the interactions between age, time, and disease with multi-panel
Kenneth K H Chui1, Julia B Wenger, Steven A Cohen
1Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, Massachusetts, United States of America. kenneth.chui@tufts.edu
Plos One
|February 25, 2011
Summary
Multi-panel (MP) graphs enhance disease monitoring and public health surveillance by visualizing temporal and demographic disease patterns. These novel tools reveal trends and anomalies for better understanding of complex health systems.
Area of Science:
- Public health
- Biostatistics
- Data visualization
Background:
- Visual analytics aids data analysis and decision-making by improving understanding of complex systems.
- Context is crucial for effective disease monitoring and public health surveillance.
- Visual analytics offers novel tools for public health professionals.
Purpose of the Study:
- To introduce a graphical tool for simultaneously revealing outcome distribution by time and age.
- To demonstrate the utility of multi-panel (MP) graphs in public health and biosurveillance.
Main Methods:
- Application of multi-panel (MP) graphs in four distinct public health settings.
- Analysis of U.S. national influenza and salmonellosis hospitalizations (older adults, 1991-2004).
- Examination of Massachusetts salmonellosis cases (general population, 2004-2005).
- Review of asthma-associated hospital visits (children, 1997-2006).
Main Results:
- MP graphs illustrate trends and anomalies in disease data.
- These patterns were previously obscured by traditional visualization methods like case pyramids and time-series plots.
- Demonstrated effectiveness across diverse populations and health outcomes.
Conclusions:
- MP graphs integrate temporality and demographics for disease analysis.
- These graphs are powerful tools for public health and disease biosurveillance.
- MP graphs improve the understanding of disease distribution and spread.
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