Edge-Based Compartmental Modeling for Infectious Disease Spread Part III: Disease and Population Structure

Abstract

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.

References in corpus (4)

• Edge-Based Compartmental Modeling for Infectious Disease Spread Part I: An Overview
• Predicting the size and probability of epidemics in a population with heterogeneous infectiousness and susceptibility
• Large graph limit for an SIR process in random network with heterogeneous connectivity
• Edge-based compartmental modeling for epidemic spread Part II: Model Selection and Hierarchies

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