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. © 2011 Chui et al.
CITATION STYLE
Chui, K. K. H., Wenger, J. B., Cohen, S. A., & Naumova, E. N. (2011). Visual analytics for epidemiologists: Understanding the interactions between age, time, and disease with multi-panel graphs. PLoS ONE, 6(2). https://doi.org/10.1371/journal.pone.0014683
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