Investigating the trade-off between infections and social interactions using a compact model of endemic infections on networks

This paper is part of a special issue on Behavioural Epidemiology.In many epidemiological and ecological contexts, there is a trade-off between infections and interactions. This arises because the links between individuals capable of spreading infections are also often associated with beneficial activities. Here, we consider how the presence of explicit network structure changes the optimal solution of a class of infection-interaction trade-offs. In order to do this, we develop and analyse a low-dimensional dynamical system approximating the network SIS epidemic. We find that network structure in the form of heterogeneous numbers of contacts can have a significant impact on the optimal number of contacts that comes out of a trade-off model.

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Publication Details

Journal
Mathematics in Medical and Life Sciences
Published
2025-03-27
DOI
https://doi.org/10.1080/29937574.2025.2468221
Primary Topic
Evolutionary Game Theory and Cooperation
Type
article
Field-Weighted Citation Impact
0.00

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article

Investigating the trade-off between infections and social interactions using a compact model of endemic infections on networks

Thomas House, Christopher E. Overton, Bunlang Thatchai
Mathematics in Medical and Life Sciences
Evolutionary Game Theory and Cooperation
article

Investigating the trade-off between infections and social interactions using a compact model of endemic infections on networks

Thomas House, Christopher E. Overton, Bunlang Thatchai
article en

Abstract

This paper is part of a special issue on Behavioural Epidemiology.In many epidemiological and ecological contexts, there is a trade-off between infections and interactions. This arises because the links between individuals capable of spreading infections are also often associated with beneficial activities. Here, we consider how the presence of explicit network structure changes the optimal solution of a class of infection-interaction trade-offs. In order to do this, we develop and analyse a low-dimensional dynamical system approximating the network SIS epidemic. We find that network structure in the form of heterogeneous numbers of contacts can have a significant impact on the optimal number of contacts that comes out of a trade-off model.

Mathematics in Medical and Life SciencesVol. 2(1)
University of Liverpool (GB), University of Manchester (GB)
Wellcome, Royal Golden Jubilee (RGJ) Ph.D. Programme
Openalex Percentile: Top 92%
Evolutionary Game Theory and Cooperation
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