Subsidy policies have been a common way for governments and health organizations to encourage individuals’ voluntary vaccination behaviors. However, subsidy policies are often used in combination with punishment policies in reality. So far, few researchers have studied the combination of vaccination subsidy policies and punishment policies. In this study, a new subsidy policy with the punishment mechanism (P-TAR) is first introduced in the vaccination game to explore its impact on voluntary vaccination behaviors. P-TAR selects to subsidize punishers of the last season based on the degree, which is similar to targeted subsidy policy (S-TAR). We first adjust fines and punishment costs to explore how the punishment mechanism of P-TAR influences vaccination coverage and epidemic dynamics. The results show that vaccination coverage can be significantly improved when the fine is high and the punishment cost is low. By comparing P-TAR with S-TAR, we find that P-TAR can more effectively increase the number of vaccinated individuals to control the epidemic size. However, the P-TAR has a higher social cost than S-TAR. Through micro-analyzing the evolution of vaccination behaviors, the P-TAR effectively improves the voluntary vaccination behaviors of non-hub nodes, which is the main reason for P-TAR has more vaccinated individuals than S-TAR. To analyze the model robustness, experiments are conducted with larger network sizes. In addition, we compare the results of unvaccinated individuals who are sequentially punished by their surrounding punishers, as well as those who are punished only once. Finally, we perform the sensitivity analysis on the effectiveness of imperfect vaccine. Current results conclude that implementing strict policies usually incurs significant social costs, while effectively preventing epidemic spreading. We anticipate that this study can offer policymakers valuable insights into the balance between social costs and benefits when formulating vaccination policies.
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