We consider the edge-based compartmental models for infectious disease spreadintroduced in Part I. These models allow us to consider standard SIR diseasesspreading in random populations. In this paper we show how to handle deviationsof the disease or population from the simplistic assumptions of Part I. Weallow the population to have structure due to effects such as demographicdetail or multiple types of risk behavior the disease to have more complicatednatural history. We introduce these modifications in the static networkcontext, though it is straightforward to incorporate them into dynamicnetworks. We also consider serosorting, which requires using the dynamicnetwork models. The basic methods we use to derive these generalizations arewidely applicable, and so it is straightforward to introduce many othergeneralizations not considered here.
展开▼
