  We introduce a family of parsimonious network models that are intended to
generalize the configuration model to temporal settings. We present consistent
estimators for the model parameters and perform numerical simulations to
illustrate the properties of the estimators on finite samples. We also develop
analytical solutions for basic and effective reproductive numbers for the early
stage of discrete-time SIR spreading process. We apply three distinct temporal
configuration models to empirical student proximity networks and compare their
performance.
