Epidemic predictability in meta-population models with heterogeneous couplings:: The impact of disease parameter values

We study the predictability of epidemic forecasts in a data-driven meta-population model considering the complete air transportation system and the associated urban areas. We de. ne the predictability as the robustness of the system evolution with respect to the stochastic fluctuations. As a quantitative measure of predictability we consider the information similarity of the time series characterizing different epidemic outbreaks with the same initial conditions. We study the predictability as a function of the parameters describing the basic susceptible-latent-infected and recovered disease dynamics. We find that the overall predictability is determined by the level of sampling of the underlying travel pattern by infected and latent individuals.