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首页> 外文期刊>Chaos, Solitons and Fractals: Applications in Science and Engineering: An Interdisciplinary Journal of Nonlinear Science >Evolutionary vaccination game approach in metapopulation migration model with information spreading on different graphs
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Evolutionary vaccination game approach in metapopulation migration model with information spreading on different graphs

机译:不同图中的信息传播信息中的进化疫苗方法

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The two layer SIR/V-UA epidemic diffusion model is incorporated in metapopulation migration model for random walkers to study the impact of awareness (rumor) for evolutionary vaccination game approach. In metapopulation, each node denoted a sub-population where the individuals migrate from one node to another by random walk following different graphs; star, cycle, wheel and complete. The framework of epidemic migration model in vaccination game with information spreading effect is observed in one single season as well as generation by some strategy update rules for an individual either taking vaccination or not. Furthermore, individuals in each node are divided into seven situations as; unaware susceptible, aware susceptible, unaware vaccinated, aware vaccinated, unaware infected, aware infected and recovered in a single season. Two strategy updating rules: individual based risk assessment (IB-RA) and strategy based risk assessment (SB-RA) are discussed for game theoretical approach for four new states; healthy vaccinated, infected vaccinated, successfully free rider and failed free rider at the end of each season to explore how different graphs of an underlying social network giving impact on the final epidemic size through the effect of information spreading in the complex population network with various number of nodes. Accordingly, the information spreading with migration in metapopulation model can enhance the epidemic threshold effectiveness and help to overcome on controlling disease diffusion. (C) 2019 Elsevier Ltd. All rights reserved.
机译:两层SIR / V-UA流行病扩散模型纳入了随机步行者的Metapupulation迁移模型中,以研究进化疫苗接种游戏方法的感知(谣言)的影响。在Metapopulation中,每个节点表示一个子群,其中各个通过随机散步从一个节点迁移到不同的图形;星,循环,轮和完整。在一个单一季节中观察到具有信息传播效果的疫苗接种游戏中的流行病迁移模型以及由某种策略更新规则,为个人提供疫苗接种。此外,每个节点中的个体分为七种情况。不知道易感,意识到敏感,不知道接种疫苗,意识到疫苗,不知道感染,意识到感染并在一个季节中恢复。两个策略更新规则:为四个新州的游戏理论方法讨论了基于个人的风险评估(IB-RA)和基于战略的风险评估(SB-RA);健康接种疫苗,感染疫苗的疫苗,成功的骑手,在每个赛季结束时获得的自由骑手失败,以探索潜在的社交网络的不同图表通过在复杂人口网络中的信息传播中的信息传播的影响,潜在的社交网络对最终的疫情大小进行了各种数量的影响节点。因此,通过在比例模型中迁移的信息传播可以增强流行病阈值效果,并有助于克服控制疾病扩散。 (c)2019年elestvier有限公司保留所有权利。

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