  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 eventual 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 in all the studied models. 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.
