title: Visualizing results from infection transmission models: a case against "confidence intervals".
abstract: 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.
authors.affiliation: Department of Epidemiology, UNC Gillings School of Global Public Health, UNC Chapel Hill, Chapel Hill, NC, USA. elofgren@email.unc.edu
authors.forename: Eric T
authors.initials: ET
authors.lastname: Lofgren
mesh_terms: D003196:Computer Graphics; D003198:Computer Simulation; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D018562:Disease Transmission, Infectious / Q000706:statistics & numerical data*; D006801:Humans; D008954:Models, Biological; D013269:Stochastic Processes