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Int J Environ Res Public Health. 2019 Jul 11;16(14). pii: E2477. doi: 10.3390/ijerph16142477.

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

Author information

1
Complex Systems Research Group, Faculty of Engineering, The University of Sydney, Sydney, NSW 2006, Australia. sheryl.chang@sydney.edu.au.
2
Complex Systems Research Group, Faculty of Engineering, The University of Sydney, Sydney, NSW 2006, Australia.
3
Charles Perkins Centre, The University of Sydney, John Hopkins Drive, Camperdown, NSW 2006, Australia.
4
Marie Bashir Institute for Infectious Diseases and Biosecurity, The University of Sydney, Westmead, NSW 2145, Australia.

Abstract

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.

KEYWORDS:

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

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