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Newborn vaccination game model with potentially periodic behavior

接种疫苗 流行病模型 数学 应用数学 计算机科学 医学 病毒学 环境卫生 人口
作者
K. M. Ariful Kabir
出处
期刊:Applied Mathematics and Computation [Elsevier]
卷期号:475: 128757-128757
标识
DOI:10.1016/j.amc.2024.128757
摘要

We explore the complex dynamics of epidemics, considering the significant effects of disease transmission, newborn individuals, and mortality rate. Employing an evolutionary game theory approach, we model the vaccination aspect for newborns, incorporating potential periodic behavior. The goal is to create an engaging simulation that underscores the criticality of timely infant vaccinations. By introducing periodic elements, the game adds complexity, fostering player participation and awareness of vaccination schedules. In contrast to traditional intervention game models focused on adult vaccine behavior, our approach recognizes the unique challenges posed by newborn vaccination. We address the limitations of existing models by developing a generalized compartmental model, accommodating infection duration distribution, and accurately capturing both periodic and non-periodic disease trajectories. The results show that higher efficacy in a newborn vaccine program can potentially eradicate the disease, but higher effectiveness and cost may deter vaccination. Increased motivation cost boosts vaccination rates without impacting epidemic size, whereas lower costs stabilize vaccination rates. Lower vaccine costs call for increased government investment to counter hesitancy. However, reduced efficacy and lower motivation lead to higher Vaccine Fear Scores, discouraging participation. Our work also offers a unique perspective on the dilemma of newborn vaccination, providing solutions with closed-form expressions that may exhibit periodic or non-periodic behavior. This approach facilitates disease modelers in exploring the potential periodicity of newborn vaccination programs, aiding efforts to prevent recurrent outbreaks.

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