  Epidemiological contact network models have emerged as an important tool in
understanding and predicting the spread of infectious disease, due to their
capacity to engage individual heterogeneity that may underlie essential
dynamics of a particular host-pathogen system. Just as fundamental are the
changes that real-world contact networks undergo over time, both independently
of and in response to pathogen spreading. These dynamics play a central role in
determining whether a disease will die out or become an epidemic within a
population, known as the epidemic threshold. In this paper, we provide an
overview of methods to predict the epidemic threshold for temporal contact
network models, and discuss areas that remain unexplored.
