Before revision:  In this paper, we apply the recent massively parallelizable Bayesian uncertainty quantification framework  to a model of a disease spreading on a network of communities , showing that the method can accurately and tractably recover system parameters and select optimal models in this setting .
After revision:  In this paper, we apply the recent massively parallelizable Bayesian uncertainty quantification framework  to infer model parameters for a disease spreading on a network of communities , showing that the method can accurately and tractably recover system parameters and select optimal models in this setting .