Many of the model input parameters allow the user to provide their forecasts in the form of ranges (80% prediction intervals) rather than point estimates. This enables users to quantify their uncertainty behind their input assumptions- the wider the range, the greater the uncertainty.
When the model is run, it performs hundreds of simulations based on these input ranges, generating a distribution of possible future healthcare demand scenarios. As such, the model outputs enable the user to explore the variation in the projected demand and plan accordingly.
For a technical overview of the probabilistic forecasting approach used in the model, please refer to the Overview of Methodology.