Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD 21218, USA.
Department of Mathematics and Computer Science, College of the Holy Cross, Worcester, MA 01610, USA.
Math Biosci. 2023 Feb;356:108967. doi: 10.1016/j.mbs.2023.108967. Epub 2023 Jan 14.
As infectious diseases continue to threaten communities across the globe, people are faced with a choice to vaccinate, or not. Many factors influence this decision, such as the cost of the disease, the chance of contracting the disease, the population vaccination coverage, and the efficacy of the vaccine. While the vaccination games in which individuals decide whether to vaccinate or not based on their own interests are gaining in popularity in recent years, the vaccine imperfection has been an overlooked aspect so far. In this paper we investigate the effects of an imperfect vaccine on the outcomes of a vaccination game. We use a simple SIR compartmental model for the underlying model of disease transmission. We model the vaccine imperfection by adding vaccination at birth and maintain a possibility for the vaccinated individual to become infected. We derive explicit conditions for the existence of different Nash equilibria, the solutions of the vaccination game. The outcomes of the game depend on the complex interplay between disease transmission dynamics (the basic reproduction number), the relative cost of the infection, and the vaccine efficacy. We show that for diseases with relatively low basic reproduction numbers (smaller than about 2.62), there is a little difference between outcomes for perfect or imperfect vaccines and thus the simpler models assuming perfect vaccines are good enough. However, when the basic reproduction number is above 2.62, then, unlike in the case of a perfect vaccine, there can be multiple equilibria. Moreover, unless there is a mandatory vaccination policy in place that would push the vaccination coverage above the value of unstable Nash equilibrium, the population could eventually slip to the "do not vaccinate" state. Thus, for diseases that have relatively high basic reproduction numbers, the potential for the vaccine not being perfect should be explicitly considered in the models.
随着传染病继续在全球范围内威胁着各个社区,人们面临着是否接种疫苗的选择。许多因素影响着这个决定,例如疾病的成本、感染疾病的机会、人群疫苗接种覆盖率和疫苗的效力。虽然近年来,个人根据自己的利益决定是否接种疫苗的接种游戏越来越受欢迎,但疫苗的不完美性迄今为止一直被忽视。在本文中,我们研究了不完美疫苗对接种游戏结果的影响。我们使用简单的 SIR compartmental 模型作为疾病传播的基本模型。我们通过在出生时接种疫苗并保持接种个体感染的可能性来模拟疫苗的不完美性。我们推导出了不同纳什均衡(接种游戏的解)存在的显式条件。游戏的结果取决于疾病传播动态(基本再生数)、感染的相对成本和疫苗效力之间的复杂相互作用。我们表明,对于基本再生数相对较低(小于约 2.62)的疾病,完美或不完美疫苗的结果几乎没有差异,因此假设完美疫苗的更简单模型就足够了。然而,当基本再生数高于 2.62 时,与完美疫苗的情况不同,可能存在多个平衡点。此外,除非实施强制性疫苗接种政策,将疫苗接种覆盖率推高到不稳定纳什均衡值以上,否则人口最终可能会滑向“不接种”状态。因此,对于基本再生数相对较高的疾病,在模型中应明确考虑疫苗不完美的可能性。