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PLoS One. 2011 Feb 15;6(2):e14683. doi: 10.1371/journal.pone.0014683.

Visual analytics for epidemiologists: understanding the interactions between age, time, and disease with multi-panel graphs.

Author information

1
Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, Massachusetts, United States of America. kenneth.chui@tufts.edu

Abstract

BACKGROUND:

Visual analytics, a technique aiding data analysis and decision making, is a novel tool that allows for a better understanding of the context of complex systems. Public health professionals can greatly benefit from this technique since context is integral in disease monitoring and biosurveillance. We propose a graphical tool that can reveal the distribution of an outcome by time and age simultaneously.

METHODOLOGY/PRINCIPAL FINDINGS:

We introduce and demonstrate multi-panel (MP) graphs applied in four different settings: U.S. national influenza-associated and salmonellosis-associated hospitalizations among the older adult population (≥65 years old), 1991-2004; confirmed salmonellosis cases reported to the Massachusetts Department of Public Health for the general population, 2004-2005; and asthma-associated hospital visits for children aged 0-18 at Milwaukee Children's Hospital of Wisconsin, 1997-2006. We illustrate trends and anomalies that otherwise would be obscured by traditional visualization techniques such as case pyramids and time-series plots.

CONCLUSION/SIGNIFICANCE:

MP graphs can weave together two vital dynamics--temporality and demographics--that play important roles in the distribution and spread of diseases, making these graphs a powerful tool for public health and disease biosurveillance efforts.

PMID:
21347221
PMCID:
PMC3039641
DOI:
10.1371/journal.pone.0014683
[Indexed for MEDLINE]
Free PMC Article

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