Networked SIRS Epidemic Model With Opinion Evolutions: Stubborn Community and Maximum Infection Time

Autor: Li Ma, Junzhe Tang, Qingsong Liu
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: IEEE Access, Vol 12, Pp 43789-43795 (2024)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2024.3376705
Popis: This paper is concerned with the co-evolution problem of epidemic and opinion over social networks. A networked SIRS epidemic model with opinion dynamics is proposed to analyze the impact of the community’s opinion on the epidemic spreading. By introducing stubborn communities, we give a sufficient condition to guarantee the epidemics converging the healthy state. Furthermore, the explicit relationship between the maximum infection time and the opinion based reproduction number is presented. Based on the Italy interactive network and the dataset collects tweets and accounts about vaccines on Twitter from March 1 to August 31, 2021, our proposed discrete-time epidemic-opinion model is employed to analyze the influence of vaccination on the epidemic spreading. It is shown that the vaccination can delay the peak of infections and reduce the overall infection rate in these communities.
Databáze: Directory of Open Access Journals