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Edge-based compartmental modelling of an SIR epidemic on a dual-layer static-dynamic multiplex network with tunable clustering

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Version 2 2023-06-12, 07:25
Version 1 2023-06-09, 14:45
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posted on 2023-06-12, 07:25 authored by Rosanna Barnard, Istvan Kiss, Luc BerthouzeLuc Berthouze, Joel C Miller
The duration, type and structure of connections between individuals in real-world populations play a crucial role in how diseases invade and spread. Here, we incorporate the aforementioned heterogeneities into a model by considering a dual-layer static-dynamic multiplex network. The static network layer affords tunable clustering and describes an individual’s permanent community structure. The dynamic network layer describes the transient connections an individual makes with members of the wider population by imposing constant edge rewiring. We follow the edge-based compartmental modelling approach to derive equations describing the evolution of a susceptible - infected - recovered (SIR) epidemic spreading through this multiplex network of individuals. We derive the basic reproduction number, measuring the expected number of new infectious cases caused by a single infectious individual in an otherwise susceptible population. We validate model equations by showing convergence to pre-existing edge-based compartmental model equations in limiting cases and by comparison with stochastically simulated epidemics. We explore the effects of altering model parameters and multiplex network attributes on resultant epidemic dynamics. We validate the basic reproduction number by plotting its value against associated final epidemic sizes measured from simulation and predicted by model equations for a number of setups. Further, we explore the effect of varying individual model parameters on the basic reproduction number. We conclude with a discussion of the significance and interpretation of the model and its relation to existing research literature. We highlight intrinsic limitations and potential extensions of the present model and outline future research considerations, both experimental and theoretical.

Funding

Institute of Disease Modeling

Global Good Fund

Engineering and Physical Sciences esearch Council

History

Publication status

  • Published

File Version

  • Published version

Journal

Bulletin of Mathematical Biology

ISSN

0092-8240

Publisher

Elsevier

Issue

10

Volume

80

Page range

2698-2733

Department affiliated with

  • Engineering and Design Publications

Research groups affiliated with

  • Centre for Computational Neuroscience and Robotics Publications
  • Mathematics Applied to Biology Research Group Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2018-08-24

First Open Access (FOA) Date

2018-08-24

First Compliant Deposit (FCD) Date

2018-08-23

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