Uncertainty quantification for the modeling of the Covid-19 outbreak

We carry out a Bayesian uncertainty quantification analysis of SEIR-type models applied to Covid-19 outbreak. We determine the critical parameters of the models that are responsible for the uncertainties of the predictions. We identify the types of data that should be collected to reduce the uncertainties. We will discuss some strategies under progress to implement the data collection.