Communicating uncertainty in epidemic models
Ruth McCabe, Mara D. Kont, Nora Schmit, Charles Whittaker, Alessandra Løchen, Patrick Walker, Azra C. Ghani, Neil M. Ferguson, Peter J White, Christl A. Donnelly, Oliver J. Watson
Abstract
While mathematical models of disease transmission are widely used to inform public health decision-makers globally, the uncertainty inherent in results are often poorly communicated. We outline some potential sources of uncertainty in epidemic models, present traditional methods used to illustrate uncertainty and discuss alternative presentation formats used by modelling groups throughout the COVID-19 pandemic. Then, by drawing on the experience of our own recent modelling, we seek to contribute to the ongoing discussion of how to improve upon traditional methods used to visualise uncertainty by providing a suggestion of how this can be presented in a clear and simple manner.