Effect of warning signs on the epidemic spreading of the COVID-19 pandemic

Author:

Xu Xin-Yun1,Zhang Hong-Bin1,Ma Yunhe1

Affiliation:

1. School of Computer Science & Technology, Soochow University, Suzhou, Jiangsu, 215006, China

Abstract

Early warning signs of the outbreak of pandemic disease become a high profile from the beginning and they remind more susceptible individuals to keep social distance on social occasions. However, these signs have no way to the Susceptible–Infected–Recovered (SIR) models which have been concerned by medical scientists. Warning signs imply the risk level of the pandemic disease evaluated by the government. The response of susceptible population ([Formula: see text]-population) to the warning signs is represented by a chicken game. In order to get a better payoff, the more beneficial behavior of the [Formula: see text]-population may be induced in the autonomous society based on the SIR model. We emphasize that participants can choose their strategies whether to follow the health rules or not without coercion in the chicken game while the warning signs released by the policy makers can encourage [Formula: see text]-population to choose beneficial behavior, instead of purely following the healthy rules or not. The agile policy helps [Formula: see text]-population to make a choice on the basis of risk interests but without losing to protect themselves in a serious pandemic situation. Comparing the classic SIR model with our signal-SIR model, the serious pandemic signal released by the policy makers and the disease awareness to it together play an important role in the outbreak period of the pandemic disease.

Publisher

World Scientific Pub Co Pte Ltd

Subject

Computational Theory and Mathematics,Computer Science Applications,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3