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

被引:2
作者
Xu, Xin-Yun [1 ]
Zhang, Hong-Bin [1 ]
Ma, Yunhe [1 ]
机构
[1] Soochow Univ, Sch Comp Sci & Technol, Suzhou 215006, Jiangsu, Peoples R China
来源
INTERNATIONAL JOURNAL OF MODERN PHYSICS C | 2023年 / 34卷 / 07期
关键词
Pandemic information; SIR infectious disease model; policy evolution; chicken game; POPULATION BIOLOGY; DYNAMICS;
D O I
10.1142/S0129183123500973
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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 (S-population) to the warning signs is represented by a chicken game. In order to get a better payoff, the more beneficial behavior of the S-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 S-population to choose beneficial behavior, instead of purely following the healthy rules or not. The agile policy helps S-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.
引用
收藏
页数:15
相关论文
共 50 条
  • [21] A COVID-19 Epidemic Model Predicting the Effectiveness of Vaccination in the US
    Webb, Glenn
    INFECTIOUS DISEASE REPORTS, 2021, 13 (03) : 654 - 667
  • [22] Fractality of Borsa Istanbul during the COVID-19 Pandemic
    Balci, Mehmet Ali
    Batrancea, Larissa M.
    Akguller, Omer
    Gaban, Lucian
    Rus, Mircea-Iosif
    Tulai, Horia
    MATHEMATICS, 2022, 10 (14)
  • [23] Psychosocial determinants of anxiety about the COVID-19 pandemic
    Wright, Rachael N.
    Faul, Leonard
    Graner, John L.
    Stewart, Gregory W.
    LaBar, Kevin S.
    JOURNAL OF HEALTH PSYCHOLOGY, 2022, 27 (10) : 2344 - 2360
  • [24] Mathematical modeling of the COVID-19 pandemic with intervention strategies
    Khajanchi, Subhas
    Sarkar, Kankan
    Mondal, Jayanta
    Nisar, Kottakkaran Sooppy
    Abdelwahab, Sayed F.
    RESULTS IN PHYSICS, 2021, 25
  • [25] COVID-19 pandemic effect on trading and returns: Evidence from the Chinese stock market
    Bing, Tao
    Ma, Hongkun
    ECONOMIC ANALYSIS AND POLICY, 2021, 71 : 384 - 396
  • [26] COVID-19 pandemic in India: a mathematical model study
    Biswas, Sudhanshu Kumar
    Ghosh, Jayanta Kumar
    Sarkar, Susmita
    Ghosh, Uttam
    NONLINEAR DYNAMICS, 2020, 102 (01) : 537 - 553
  • [27] Mathematical Models for COVID-19 Pandemic: A Comparative Analysis
    Adiga, Aniruddha
    Dubhashi, Devdatt
    Lewis, Bryan
    Marathe, Madhav
    Venkatramanan, Srinivasan
    Vullikanti, Anil
    JOURNAL OF THE INDIAN INSTITUTE OF SCIENCE, 2020, 100 (04) : 793 - 807
  • [28] Modelling transmission and control of the COVID-19 pandemic in Australia
    Chang, Sheryl L.
    Harding, Nathan
    Zachreson, Cameron
    Cliff, Oliver M.
    Prokopenko, Mikhail
    NATURE COMMUNICATIONS, 2020, 11 (01)
  • [29] Implementation of a Vaccination Program Based on Epidemic Geospatial Attributes: COVID-19 Pandemic in Ohio as a Case Study and Proof of Concept
    Awad, Susanne F.
    Musuka, Godfrey
    Mukandavire, Zindoga
    Froass, Dillon
    MacKinnon, Neil J.
    Cuadros, Diego F.
    VACCINES, 2021, 9 (11)
  • [30] Prediction and control of COVID-19 spreading based on a hybrid intelligent model
    Zhang, Gengpei
    Liu, Xiongding
    PLOS ONE, 2021, 16 (02):