  We propose a detailed discrete-time model of COVID-19 epidemics coming in two
flavours, mean-field and probabilistic. The main contribution lies in several
extensions of the basic model that capture i) user mobility - distinguishing
routing, i.e. change of residence, from commuting, i.e. daily mobility - and
ii) contact tracing procedures. We confront this model to public data on daily
hospitalizations, and discuss its application as well as underlying estimation
procedures.
