The Effects of Imitation Dynamics on Vaccination Behaviours in SIR-Network Model.

Erdös-Rényi random networks SIR model epidemic modelling greater Sydney commuting network herd immunity strategy imitation vaccination

Journal

International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455

Informations de publication

Date de publication:
11 07 2019
Historique:
received: 07 05 2019
revised: 08 07 2019
accepted: 09 07 2019
entrez: 25 7 2019
pubmed: 25 7 2019
medline: 3 1 2020
Statut: epublish

Résumé

We present a series of SIR-network models, extended with a game-theoretic treatment of imitation dynamics which result from regular population mobility across residential and work areas and the ensuing interactions. Each considered SIR-network model captures a class of vaccination behaviours influenced by epidemic characteristics, interaction topology, and imitation dynamics. Our focus is the resultant vaccination coverage, produced under voluntary vaccination schemes, in response to these varying factors. Using the next generation matrix method, we analytically derive and compare expressions for the basic reproduction number R 0 for the proposed SIR-network models. Furthermore, we simulate the epidemic dynamics over time for the considered models, and show that if individuals are sufficiently responsive towards the changes in the disease prevalence, then the more expansive travelling patterns encourage convergence to the endemic, mixed equilibria. On the contrary, if individuals are insensitive to changes in the disease prevalence, we find that they tend to remain unvaccinated. Our results concur with earlier studies in showing that residents from highly connected residential areas are more likely to get vaccinated. We also show that the existence of the individuals committed to receiving vaccination reduces R 0 and delays the disease prevalence, and thus is essential to containing epidemics.

Identifiants

pubmed: 31336761
pii: ijerph16142477
doi: 10.3390/ijerph16142477
pmc: PMC6678199
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

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Auteurs

Sheryl Le Chang (SL)

Complex Systems Research Group, Faculty of Engineering, The University of Sydney, Sydney, NSW 2006, Australia. sheryl.chang@sydney.edu.au.

Mahendra Piraveenan (M)

Complex Systems Research Group, Faculty of Engineering, The University of Sydney, Sydney, NSW 2006, Australia.
Charles Perkins Centre, The University of Sydney, John Hopkins Drive, Camperdown, NSW 2006, Australia.

Mikhail Prokopenko (M)

Complex Systems Research Group, Faculty of Engineering, The University of Sydney, Sydney, NSW 2006, Australia.
Marie Bashir Institute for Infectious Diseases and Biosecurity, The University of Sydney, Westmead, NSW 2145, Australia.

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Classifications MeSH