Inferring COVID-19 spreading rates and potential change points for case number forecasts

Jonas Dehning; Johannes Zierenberg; Frank Paul Spitzner; Michael Wibral; Joao Pinheiro Neto; Michael Wilczek; Viola Priesemann

Priors for the full model (Table IV) : In order to constrain our full model, an SIR model with change points in the spreading rate, we chose the same priors as for the simple model but added the required priors associated with the change points. In general, we assume that each set of governmental interventions (together with the increasing awareness) leads to a reduction (and not an increase) of λ at a change point. As we cannot know yet the precise reduction factor, we adhere to assume a reduction by 50%, but always with a fairly wide uncertainty, so that in principle even an increase at the change point would be possible. We model the time dependence of λ as change points, and not as continuous changes, because the policy changes were implemented in three discrete steps, which were All rights reserved. No reuse allowed without permission. author/funder, who has granted medRxiv a license to display the preprint in perpetuity.