  We consider the edge-based compartmental models for infectious disease spread
introduced in Part I. These models allow us to consider standard SIR diseases
spreading in random populations. In this paper we show how to handle deviations
of the disease or population from the simplistic assumptions of Part I. We
allow the population to have structure due to effects such as demographic
detail or multiple types of risk behavior the disease to have more complicated
natural history. We introduce these modifications in the static network
context, though it is straightforward to incorporate them into dynamic
networks. We also consider serosorting, which requires using the dynamic
network models. The basic methods we use to derive these generalizations are
widely applicable, and so it is straightforward to introduce many other
generalizations not considered here.
