接种疫苗
群体免疫
透视图(图形)
疾病
博弈论
复制因子方程
进化博弈论
社会心理学
心理学
医学
认知心理学
免疫学
计算机科学
微观经济学
经济
环境卫生
人工智能
病理
人口
作者
K. M. Ariful Kabir,Jun Tanimoto
标识
DOI:10.1016/j.chaos.2019.04.010
摘要
To avoid the infection, the epidemic outburst plays a significant role that encourages people to take vaccination and induce behavioral changes. The interplay between disease incidence, vaccine uptake and the behavior of individuals are taking place on the local time scale. Here, we analyze the individual's behavior in disease-vaccination interaction model based on the evolutionary game approach that captures the idea of vaccination decisions on disease prevalence that also include social learning. The effect of herd immunity is partly important when the individuals are deciding whether to take the vaccine or not. The possibility that an individual taking a vaccination or becoming infected depends upon how many other people are vaccinated. To apprehend this interplay, four strategy updating rules: individual based risk assessment (IB-RA), society based risk assessment (SB-RA), direct commitment (DC) and modified replicator dynamics (MRD) are contemplated for game theoretical approach by how one individual can learn from society or neighbors. The theory and findings of this paper provide a new perspective for vaccination taking policy in daily basis that provision of prompt learning with the collective information reliefs to reduce infection, which gives a new ‘vaccination game’ from other previous models.
科研通智能强力驱动
Strongly Powered by AbleSci AI