Suppressing Epidemic Spreading by Imitating Hub Nodes' Strategy
Suppressing Epidemic Spreading by Imitating Hub Nodes' Strategy
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DOI：
10.1109/tcsii.2019.2938775
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发表时间：
2020-10-01
影响因子：
4.4
通讯作者：
Wang, Zhen
中科院分区：
文献类型：
--
作者：
Zhang, Hai-Feng;Wang, Zhen
在这篇文章中，我们将优先模仿规则的影响引入到社交网络上基于疫苗接种博弈的流行病传播模型中，其中每个个体选择其邻居之一作为模仿参考，其概率与邻居的程度成正比。我们的研究结果表明，疫苗接种覆盖率可以显着增加，如果枢纽节点的优先模仿，导致疫情规模显着减少。我们解释了这一点，表明中心节点的疫苗接种意愿是非常高的自愿接种机制时，假设，谁可以吸引更多的个人接种疫苗，如果他们优先模仿。此外，一个平均场理论的方法来进一步验证我们的研究结果。这份简报表明，人类的行为反应是传播动力学的一个重要因素。
In this brief, we incorporate the impact of preferential imitation rule into a vaccination game based epidemic spreading model on social networks, where each individual chooses one of its neighbors as an imitation reference with a probability proportional to the neighbor's degree. Our results indicate that the vaccination coverage can be remarkably increased if hub nodes are preferentially imitated, leading to the dramatic reduction of the epidemic size. We explain this by suggesting that the vaccination willingness of hub nodes is very high when voluntary vaccination mechanism is assumed, who can attract more individuals to take vaccination if they are preferentially imitated. Moreover, a mean-field theoretical approach is developed to further verify our findings. This brief suggests that the human behavioral response is an important factor for spreading dynamics.