Cooperative coinfection dynamics on clustered networks

TL;DR

This paper investigates how contact clustering in networks influences the spread and coexistence of two pathogens during coinfection, revealing that contact topology details significantly affect coinfection levels.

Contribution

It introduces a generating function approach to analyze coinfection dynamics on clustered networks, highlighting the impact of contact topology on disease spread.

Findings

Clustering affects coinfection levels based on contact topology.

Threshold conditions for pathogen coexistence depend on network structure.

Contact clustering can either facilitate or hinder coinfection.

Abstract

Coinfection is the process by which a host that is infected with a pathogen becomes infected by a second pathogen at a later point in time. An immunosuppressant host response to a primary disease can facilitate spreading of a subsequent emergent pathogen among the population. Social contact patterns within the substrate populace can be modelled using complex networks and it has been shown that contact patterns vastly influence the emergent disease dynamics. In this paper, we consider the effect of contact clustering on the coinfection dynamics of two pathogens spreading over a network. We use the generating function formulation to describe the expected outbreak sizes of each pathogen and numerically study the threshold criteria that permit the coexistence of each strain among the network. We find that the effects of clustering on the levels of coinfection are governed by the details of the contact topology.