4.7 Article

Impact of network assortativity on epidemic and vaccination behaviour

Journal

CHAOS SOLITONS & FRACTALS
Volume 140, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chaos.2020.110143

Keywords

Assortativity; Vaccination; Epidemic modelling; SIR Model; Scale-free networks

Funding

  1. Australian Research Council (ARC) [DP160102742, DP20 0103005]
  2. Australian Government Research Training Program (RTP) Scholarship
  3. Sydney Informatics Hub at the University of Sydney, through the use of High Performance Computing (HPC) services

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The resurgence of measles is largely attributed to the decline in vaccine adoption and the increase in mobility. Although the vaccine for measles is readily available and highly successful, its current adoption is not adequate to prevent epidemics. Vaccine adoption is directly affected by individual vaccination decisions, and has a complex interplay with the spatial spread of disease shaped by an underlying mobility (travelling) network. In this paper, we model the travelling connectivity as a scale-free network, and investigate dependencies between the network's assortativity and the resultant epidemic and vaccination dynamics. In doing so we extend an SIR-network model with game-theoretic components, capturing the imitation dynamics under a voluntary vaccination scheme. Our results show a correlation between the epidemic dynamics and the network's assortativity, highlighting that networks with high assortativity tend to suppress epidemics under certain conditions. In highly assortative networks, the suppression is sustained producing an early convergence to equilibrium. In highly disassortative networks, however, the suppression effect diminishes over time due to scattering of non-vaccinating nodes, and frequent switching between the predominantly vaccinating and non-vaccinating phases of the dynamics. (c) 2020 Elsevier Ltd. All rights reserved.

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