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进化博弈论建模,以呈现新冠疫情中经济封锁和屏蔽免疫的行为动态。

Evolutionary game theory modelling to represent the behavioural dynamics of economic shutdowns and shield immunity in the COVID-19 pandemic.

作者信息

Kabir K M Ariful, Tanimoto Jun

机构信息

Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-koen, Kasuga-shi, Fukuoka 816-8580, Japan.

Department of Mathematics, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh.

出版信息

R Soc Open Sci. 2020 Sep 30;7(9):201095. doi: 10.1098/rsos.201095. eCollection 2020 Sep.

Abstract

The unprecedented global spread of COVID-19 has prompted dramatic public-health measures like strict stay-at-home orders and economic shutdowns. Some governments have resisted such measures in the hope that naturally acquired shield immunity could slow the spread of the virus. In the absence of empirical data about the effectiveness of these measures, policymakers must turn to epidemiological modelling to evaluate options for responding to the pandemic. This paper combines compartmental epidemiological models with the concept of behavioural dynamics from evolutionary game theory (EGT). This innovation allows us to model how compliance with an economic lockdown might wane over time, as individuals weigh the risk of infection against the certainty of the economic cost of staying at home. Governments can, however, increase spending on social programmes to mitigate the cost of a shutdown. Numerical analysis of our model suggests that emergency-relief funds spent at the individual level are effective in reducing the duration and overall economic cost of a pandemic. We also find that shield immunity takes hold in a population most easily when a lockdown is enacted with relatively low costs to the individual. Our qualitative analysis of a complex model provides evidence that the effects of shield immunity and economic shutdowns are complementary, such that governments should pursue them in tandem.

摘要

新冠病毒在全球前所未有的传播态势促使各国采取了严格的居家令和经济封锁等重大公共卫生措施。一些政府抵制这些措施,希望自然获得的屏障免疫能够减缓病毒传播。在缺乏关于这些措施有效性的实证数据的情况下,政策制定者必须借助流行病学建模来评估应对疫情的各种选项。本文将 compartments 流行病学模型与进化博弈论(EGT)中的行为动力学概念相结合。这一创新使我们能够模拟随着个人权衡感染风险与居家经济成本的确定性,对经济封锁的遵守程度如何随时间减弱。然而,政府可以增加社会项目支出以减轻封锁成本。我们模型的数值分析表明,在个人层面支出的紧急救济资金在减少疫情持续时间和总体经济成本方面是有效的。我们还发现,当实施封锁对个人成本相对较低时,屏障免疫最容易在人群中形成。我们对一个复杂模型的定性分析提供了证据,表明屏障免疫和经济封锁的效果是互补的,因此政府应同时推行这两项措施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f49/7540740/f528ca4ed0bf/rsos201095-g1.jpg

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