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Visualizing Results From Infection Transmission Models: A Case Against “Confidence Intervals”

Lofgren, Eric T.

doi: 10.1097/EDE.0b013e318258369b

Stochastic transmission models are highly important in infectious disease epidemiology. The quantity of data produced by these models is challenging to display and communicate. A common approach is to display the model results in the familiar form of a mean or median and 95% interval, plotted over time. This approach has drawbacks, however, including the potential for ambiguity and misinterpretation of model results. Instead, we propose 2 alternative approaches for visualizing results from stochastic models. These proposed approaches convey the information provided by the median and 95% interval, as well as information about unexpected outcomes that may be of particular interest for stochastic epidemic models.

Supplemental Digital Content is available in the text.

From the Department of Epidemiology, UNC Gillings School of Global Public Health, UNC Chapel Hill, Chapel Hill, NC.

Submitted 4 November 2011; accepted 28 February 2012; posted 18 May 2012.

Supported by NIH Training Grant 2T32AI070114. The author reported no other financial interests related to this research.

Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article ( This content is not peer-reviewed or copy-edited; it is the sole responsibility of the author.

Correspondence: Eric Lofgren, 4501 Connecticut Ave. NW Apt. 411, Washington, DC 20008. E-mail:

© 2012 Lippincott Williams & Wilkins, Inc.