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Impact of co-evolution of negative vaccine-related information, vaccination behavior and epidemic spreading in multilayer networks
Communications in Nonlinear Science and Numerical Simulation ; : 106312, 2022.
Article in English | ScienceDirect | ID: covidwho-1663465
ABSTRACT
In this paper, we establish a three-layer coupled network model to analyze the co-evolution of negative vaccine-related information, vaccination behavior, and epidemic spread. The three layers are used to represent negative vaccine-related information dissemination, vaccination behavior diffusion and epidemic propagation, respectively. The comprehensive impact of vaccination costs and herd mentality are firstly considered in the diffusion of vaccination behavior. Then, we use the micro-Markov chain (MMC) method to derive the system dynamics equations and the epidemic threshold. The analytical results show that the proportion of efficaciously vaccinated individuals and the topology of the epidemic spread layer both determine the epidemic threshold. Finally, a large number of simulation experiments are conducted to investigate the impact of various factors on the epidemic spread, which include negative vaccine-related information diffusion, rational judgment and herd mentality during the process of vaccination decision, and cost of vaccine. The results demonstrate the role of negative vaccine-related information diffusion and vaccination behavior spread in epidemic control, and may provide some valuable clues for policymakers to formulate appropriate measures to prevent and control epidemics.
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Full text: Available Collection: Databases of international organizations Database: ScienceDirect Type of study: Experimental Studies Topics: Vaccines Language: English Journal: Communications in Nonlinear Science and Numerical Simulation Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: ScienceDirect Type of study: Experimental Studies Topics: Vaccines Language: English Journal: Communications in Nonlinear Science and Numerical Simulation Year: 2022 Document Type: Article