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Effect of heterogeneous risk perception on information diffusion, behavior change, and disease transmission.
Ye, Yang; Zhang, Qingpeng; Ruan, Zhongyuan; Cao, Zhidong; Xuan, Qi; Zeng, Daniel Dajun.
  • Ye Y; School of Data Science, City University of Hong Kong, Hong Kong SAR, China.
  • Zhang Q; School of Data Science, City University of Hong Kong, Hong Kong SAR, China.
  • Ruan Z; Institute of Cyberspace Security, Zhejiang University of Technology, Hangzhou, Zhejiang, China.
  • Cao Z; State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
  • Xuan Q; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China.
  • Zeng DD; Shenzhen Artificial Intelligence and Data Science Institute, Shenzhen, Guangdong, China.
Phys Rev E ; 102(4-1): 042314, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-920840
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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Full text: Available Collection: International databases Database: MEDLINE Main subject: Behavior / Disease Transmission, Infectious / Models, Theoretical Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: Phys Rev E Year: 2020 Document Type: Article Affiliation country: PhysRevE.102.042314

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Behavior / Disease Transmission, Infectious / Models, Theoretical Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: Phys Rev E Year: 2020 Document Type: Article Affiliation country: PhysRevE.102.042314