[Retracted] The Evolution Model of Public Risk Perception Based on Pandemic Spreading Theory under Perspective of COVID‐19

Abstract

After the occurrence of public health emergencies, due to the uncertainty of the evolution of events and the asymmetry of pandemic information, the public’s risk perception will fluctuate dramatically. Excessive risk perception often causes the public to overreact to emergencies, resulting in irrational behaviors, which have a negative impact on economic development and social order. However, low-risk perception will reduce individual awareness of prevention and control, which is not conducive to the implementation of government pandemic prevention and control measures. Therefore, it is of great significance to accurately evaluate public risk perception for improving government risk management. This paper took the evolution of public risk perception based on the COVID-19 region as the research object. First, we analyze the characteristics of infectious diseases in the evolution of public risk perception of public health emergencies. Second, we analyze the characteristics of risk perception transmission in social networks. Third, we establish the dynamic model of public risk perception evolution based on SEIR, and the evolution mechanism of the public risk perception network is revealed through simulation experiments. Finally, we provide policy suggestions for government departments to deal with public health emergencies based on the conclusions of this study.

Contrasting the COVID-19 Effects on Tourism Safety Perceptions and Coping Behavior among Young People during Two Pandemic Waves: Evidence from Egypt

“…Negative emotions, which express risk severity perceptions, may have a positive effect on coping beliefs and intentions [56], namely on the acceptance of restrictions and intentions to change behavior. On the contrary, lower severity risk perception may reduce youngsters' individual awareness of prevention and control, which is not conducive to the implementation of governmental containment measures [55]. Since young people are less affected by severe COVID-19 disease and are expected, during the course of the pandemic, to evolve regarding their adaptative coping beliefs and behavior given the lessened restrictions and their more confident self-efficacious behavior, we hypothesize the following significant differences contrasting the first and the second wave: Hypothesis 4 (H4).…”

“…In fact, in the tourism context, the higher the perceived susceptibility of potential risks is, the more people accept preventative actions [49]. Moreover, scholars generally believe that the public's perception of risk is affected by individual characteristics, as well as by time and event progress [55]. The reduced reported symptomatology related with COVID-19 can cause desensitization regarding the relevance of the problem [48].…”

Dataset Analysis of the Risks for Russian IT Companies Amid the COVID-19 Crisis

“…Published works (Cherry et al 2023;Villegas et al 2023) point to the evolution of business risks, which, in particular, were reflected in credit rankings during the COVID-19 pandemic. Multiple published works by Hadef et al (2022); Ouerfelli et al (2022); Yuan and Pang (2022) and Zhang et al (2022b) note that, during the COVID-19 crisis, especially at the early stage of the pandemic, revenues and competitiveness of businesses were largely predetermined by the situation in healthcare (Zhang et al 2021b), lockdowns that were imposed to fight the viral threat (Zhang et al 2021a) and the related socio-psychological situation in the society-ranging from emotional depression and social drama to euphoria, from the registration of first vaccines and the start of mass vaccination from the new coronavirus infection (Lu 2020).…”

The Credit Risk Contagion Mechanism of Financial Guarantee Network: An Application of the SEIR‐Epidemic Model

“…Hypothesis 1. Based on the research of Zhang et al [56], this study classifies the status of enterprises in the financing guarantee network into four categories: susceptible enterprise S, exposed enterprise E, infected enterprise I, and immune enterprise R. e total number of enterprises in the network is specified as N and remains unchanged without considering the entry of new enterprises and the bankruptcy of the original enterprises.…”