Literature DB >> 33212602

Effect of heterogeneous risk perception on information diffusion, behavior change, and disease transmission.

Yang Ye1, Qingpeng Zhang1, Zhongyuan Ruan2, Zhidong Cao3,4,5, Qi Xuan2, Daniel Dajun Zeng3,4,5.   

Abstract

Motivated by the importance of individual differences in risk perception and behavior change in people's responses to infectious disease outbreaks (particularly the ongoing COVID-19 pandemic), we propose a heterogeneous disease-behavior-information transmission model, in which people's risk of getting infected is influenced by information diffusion, behavior change, and disease transmission. We use both a mean-field approximation and Monte Carlo simulations to analyze the dynamics of the model. Information diffusion influences behavior change by allowing people to be aware of the disease and adopt self-protection and subsequently affects disease transmission by changing the actual infection rate. Results show that (a) awareness plays a central role in epidemic prevention, (b) a reasonable fraction of overreacting nodes are needed in epidemic prevention (c) the basic reproduction number R_{0} has different effects on epidemic outbreak for cases with and without asymptomatic infection, and (d) social influence on behavior change can remarkably decrease the epidemic outbreak size. This research indicates that the media and opinion leaders should not understate the transmissibility and severity of diseases to ensure that people become aware of the disease and adopt self-protection to protect themselves and the whole population.

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Year:  2020        PMID: 33212602     DOI: 10.1103/PhysRevE.102.042314

Source DB:  PubMed          Journal:  Phys Rev E        ISSN: 2470-0045            Impact factor:   2.529


  6 in total

1.  Development of a multivariable prediction model for severe COVID-19 disease: a population-based study from Hong Kong.

Authors:  Jiandong Zhou; Sharen Lee; Xiansong Wang; Yi Li; William Ka Kei Wu; Tong Liu; Zhidong Cao; Daniel Dajun Zeng; Keith Sai Kit Leung; Abraham Ka Chung Wai; Ian Chi Kei Wong; Bernard Man Yung Cheung; Qingpeng Zhang; Gary Tse
Journal:  NPJ Digit Med       Date:  2021-04-08

2.  Modeling COVID-19 Transmission Dynamics With Self-Learning Population Behavioral Change.

Authors:  Tsz-Lik Chan; Hsiang-Yu Yuan; Wing-Cheong Lo
Journal:  Front Public Health       Date:  2021-12-22

3.  Analyzing COVID-19 Vaccination Behavior Using an SEIRM/V Epidemic Model With Awareness Decay.

Authors:  Chao Zuo; Fenping Zhu; Yuting Ling
Journal:  Front Public Health       Date:  2022-01-27

4.  The effect of information literacy heterogeneity on epidemic spreading in information and epidemic coupled multiplex networks.

Authors:  Jiang Wu; Renxian Zuo; Chaocheng He; Hang Xiong; Kang Zhao; Zhongyi Hu
Journal:  Physica A       Date:  2022-03-03       Impact factor: 3.263

Review 5.  Data science approaches to confronting the COVID-19 pandemic: a narrative review.

Authors:  Qingpeng Zhang; Jianxi Gao; Joseph T Wu; Zhidong Cao; Daniel Dajun Zeng
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2021-11-22       Impact factor: 4.226

6.  Evolution and consequences of individual responses during the COVID-19 outbreak.

Authors:  Wasim Abbas; Masud M A; Anna Park; Sajida Parveen; Sangil Kim
Journal:  PLoS One       Date:  2022-09-01       Impact factor: 3.752

  6 in total

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