School of Mathematical and Statistical Sciences Faculty Publications and Presentations
Document Type
Article
Publication Date
12-11-2021
Abstract
During the COVID-19 pandemic, conflicting opinions on physical distancing swept across social media, affecting both human behavior and the spread of COVID-19. Inspired by such phenomena, we construct a two-layer multiplex network for the coupled spread of a disease and conflicting opinions. We model each process as a contagion. On one layer, we consider the concurrent evolution of two opinions — pro-physical-distancing and anti-physical-distancing — that compete with each other and have mutual immunity to each other. The disease evolves on the other layer, and individuals are less likely (respectively, more likely) to become infected when they adopt the pro-physical-distancing (respectively, anti-physical-distancing) opinion. We develop approximations of mean-field type by generalizing monolayer pair approximations to multilayer networks; these approximations agree well with Monte Carlo simulations for a broad range of parameters and several network structures. Through numerical simulations, we illustrate the influence of opinion dynamics on the spread of the disease from complex interactions both between the two conflicting opinions and between the opinions and the disease. We find that lengthening the duration that individuals hold an opinion may help suppress disease transmission, and we demonstrate that increasing the cross-layer correlations or intra-layer correlations of node degrees may lead to fewer individuals becoming infected with the disease.
Recommended Citation
Peng, Kaiyan; Lu, Zheng; Lin, Vanessa; Lindstrom, Michael R.; Parkinson, Christian; Wang, Chuntian; Bertozzi, Andrea L.; and Porter, Mason A., "A multilayer network model of the coevolution of the spread of a disease and competing opinions" (2021). School of Mathematical and Statistical Sciences Faculty Publications and Presentations. 518.
https://scholarworks.utrgv.edu/mss_fac/518
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Publication Title
Mathematical Models and Methods in Applied Sciences
DOI
10.1142/S0218202521500536
Comments
© The Author(s)
This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 (CC BY-NC-ND) License which permits use, distribution and reproduction, provided that the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.