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基于风险感知和补贴政策的多信息源驱动的自愿疫苗接种。

Risk perception and subsidy policy-based voluntary vaccination driven by multiple information sources.

机构信息

School of Computer Engineering and Science, Shanghai University, Shanghai, P. R. China.

出版信息

PLoS One. 2022 Oct 13;17(10):e0276177. doi: 10.1371/journal.pone.0276177. eCollection 2022.

DOI:10.1371/journal.pone.0276177
PMID:36227953
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9560505/
Abstract

Exploring vaccination behavior is fundamental to understand the role of vaccine in suppressing the epidemic. Motivated by the efficient role of the risk perception and the subsidy policy in promoting vaccination, we propose the Risk Perception and the Risk Perception with Subsidy Policy voluntary vaccination strategies with imperfect vaccine. The risk perception is driven by multiple information sources based on global information (released by Public Health Bureau) and local information (from first-order neighbors). In time-varying networks, we use the mean-field approach and the Monte Carlo simulations to analyze the epidemic dynamics under vaccination behavior with imperfect vaccine. We find that vaccination with the incorporation of risk perception and subsidy policy can effectively control the epidemic. Moreover, information from different sources plays different roles. Global information is more helpful in promoting vaccination than local information. In addition, to further understand the influence of vaccination strategies, we calculate the social cost as the cost for the vaccine and treatment, and find that excess vaccination cost results in a higher social cost after the herd immunity. Thus, for balancing the epidemic control and social cost, providing individuals with more global information as well as local information would be helpful in vaccination. These results are expected to provide insightful guidance for designing the policy to promote vaccination.

摘要

探索疫苗接种行为对于理解疫苗在抑制疫情中的作用至关重要。鉴于风险感知和补贴政策在促进疫苗接种方面的高效作用,我们提出了带有不完善疫苗的风险感知和风险感知与补贴政策的自愿疫苗接种策略。风险感知受到基于全球信息(由公共卫生局发布)和本地信息(来自一阶邻居)的多种信息源的驱动。在时变网络中,我们使用平均场方法和蒙特卡罗模拟来分析在不完善疫苗接种行为下的疫情动力学。我们发现,结合风险感知和补贴政策的疫苗接种可以有效地控制疫情。此外,不同来源的信息发挥着不同的作用。全球信息比本地信息更有助于促进疫苗接种。此外,为了进一步了解疫苗接种策略的影响,我们将社会成本(疫苗和治疗的成本)计算在内,并发现群体免疫后过度的疫苗接种成本会导致更高的社会成本。因此,为了平衡疫情控制和社会成本,为个人提供更多的全球信息和本地信息将有助于疫苗接种。这些结果有望为设计促进疫苗接种的政策提供有见地的指导。

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