Before revision:  We combine Bayesian parameter inference with a network-based epidemiological modelthat allows to interpolate between random and small-world transmission networks. Using epidemiological data from Germany, we show that NPIs reduced non-local contacts in the transmission network, resulting in a change from an exponential to a constant regime .
After revision:  We combine Bayesian parameter inference with a network-based epidemiological modelthat allows to interpolate between random and small-world network which allows to distinguish contacts within clustered cliques and unclustered, random contacts in the population, which have been shown to be crucial in sustaining the epidemic. In contrast to other works, which use coarse-grained network structures from anonymized data, like cell phone data, we consider the contacts of individual agents explicitly. We show that NPIs reduced non-local contacts in the transmission network, resulting in a change from an exponential to a constant regime .