In this study, an epidemic model for spreading COVID-19 is presented. This model considers the birth and death rates in the dynamics of spreading COVID-19. The birth and death rates are assumed to be the same, so the population remains constant. The dynamics of the model are explained in two phases. The first is the epidemic phase, which spreads during a season based on the proposed SIR/V model and reaches a stable state at the end of the season. The other one is the “vaccination campaign”, which takes place between two seasons based on the rules of the vaccination game. In this stage, each individual in the population decides whether to be vaccinated or not. Investigating the dynamics of the studied model during a single epidemic season without consideration of the vaccination game shows waves in the model as experimental knowledge. In addition, the impact of the parameters is studied via the rules of the vaccination game using three update strategies. The result shows that the pandemic speeding can be changed by varying parameters such as efficiency and cost of vaccination, defense against contagious, and birth and death rates. The final epidemic size decreases when the vaccination coverage increases and the average social payoff is modified.

在这项研究中，提出了传播 COVID-19 的流行病模型。该模型考虑了 COVID-19 传播动态中的出生率和死亡率。假定出生率和死亡率相同，因此人口保持不变。模型的动力学分两个阶段进行解释。第一个是流行阶段，根据提出的 SIR/V 模型在一个季节内传播，并在季节结束时达到稳定状态。另一个是“疫苗接种运动”，根据疫苗接种游戏的规则在两个季节之间进行。在此阶段，种群中的每个人都决定是否接种疫苗。在不考虑疫苗接种游戏的情况下，在单个流行季节调查所研究模型的动态，将模型中的波浪显示为实验知识。此外，使用三种更新策略通过疫苗接种游戏规则研究参数的影响。结果表明，可以通过改变疫苗接种的效率和成本、对传染病的防御以及出生率和死亡率等参数来改变大流行的速度。当疫苗接种覆盖率增加并且平均社会收益被修改时，最终的流行病规模会减小。