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

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 (hDBI) 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 "over-reacting" nodes are needed in epidemic prevention; (c) R0 has different effects on epidemic outbreak for cases with and without asymptomatic infection; (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 could become aware of the disease and adopt self-protection to protect themselves and the whole population.

References in corpus (10)

• Multilayer Networks
• Mean-field theory for scale-free random networks
• Dynamical interplay between awareness and epidemic spreading in multiplex networks
• Epidemic dynamics on an adaptive network
• Activity driven modeling of time varying networks
• Competing spreading processes on multiplex networks: awareness and epidemics
• Layered Complex Networks
• Towards a characterization of behavior-disease models
• Universal Masking is Urgent in the COVID-19 Pandemic: SEIR and Agent Based Models, Empirical Validation, Policy Recommendations
• The limitations of discrete-time approaches to continuous-time contagion dynamics

Cited by in corpus (4)

• Transitions between polarization and radicalization in a temporal bilayer echo chambers model
• Coexistence of positive and negative information in information-epidemic dynamics on multiplex networks
• A geometric analysis of the SIRS compartmental model with fast information and misinformation spreading
• A high-frequency mobility big-data reveals how COVID-19 spread across professions, locations and age groups