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.
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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.
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Correspondence: Eric Lofgren, 4501 Connecticut Ave. NW Apt. 411, Washington, DC 20008. E-mail: firstname.lastname@example.org