Figure 1.
The proportion of the population with each given degree are different for a Poisson network (red histogram), urban network (blue histogram), and exponentially-scaled power law network (pink histogram).
Figure 2.
Probability that individual i adopts individual j's vaccination strategy. α represents the degree to which individuals respond to the differences of payoff.
Table 1.
Summary of the parameters used in simulations.
Figure 3.
Vaccination coverage as a function of the relative cost of vaccination (r) and the fraction of imitators (Θ) in a (A) homogenous Poisson network, (B) urban network, and (C) exponentially-scaled power law network.
Parameters: Population size N = 5000, recovery rate g = 0.25 d−1, α = 5.
Figure 4.
Frequency of vaccination as a function of the number of neighbors an individual has for the two extreme cases: fully payoff maximization (Θ = 0) and fully imitation (Θ = 1).
The homogeneous Poisson network is represented by (A,D), the urban network by (B,E), and the exponential-scaled power law network by (C,F). (A–C) the relative cost of vaccination r = 0.1; (D–E) r = 0.7. The solid line represents the average degree of the network, and the dashed line represents the average excess degree of the network. The average excess degree is a measure of the tendency to which individuals with high degree are connected to individuals with low degree, and vice versa [11].
Figure 5.
Vaccination coverage of imitators and payoff maximizers as a function of the relative cost of vaccination (r) for the portion of imitators equals to Θ = 0.2, Θ = 0.5, Θ = 0.8.
The homogeneous Poisson network is represented by (A,B,C), the urban network by (D,E,F), and the exponential-scaled power law network by (G,H,I).
Figure 6.
Epidemic size as a function of the relative cost of vaccination (r) and the fraction of imitators (Θ) in a (A) homogenous Poisson network, (B) urban network, and (C) exponentially-scaled power law network.
Figure 7.
Average number of contacts between non-vaccinators as a function of the fraction of imitators (Θ) and the relative cost of vaccination (r) in a (A) homogenous Poisson network, (B) urban network, and (C) exponentially-scaled power law network.
Figure 8.
Vaccination coverage under strong responsiveness to differences of payoff (α = 15) in a (A) homogenous Poisson network, (B) urban network, and (C) exponentially-scaled power law network.
Vaccine coverage is given as a function of r for the two extreme cases: fully payoff maximization (Θ = 0) and fully imitation (Θ = 1). Parameters are identical to Table 1, except α = 15.