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COVID-19 Model Based on Conformable Fractional Derivativeand Its Numerical Solution
Complex Systems and Complexity Science ; 19(3):27-32, 2022.
Article Dans Chinois | Scopus | ID: covidwho-20244500
ABSTRACT
After the outbreak of COVID-19, it is of great significance to find an appropriate dynamic model of COVID-19 epidemic in order to master its transmission law, predict its development trend, and provide corresponding prevention and control basis. In this paper, the SEIRV chamber model is adopted, and the dynamics model of infectious disease is established by combining the fractional derivative of Conformable. The fractional derivative differential equation of Conformable is discretized by numerical method and its numerical solution is obtained. In addition, numerical simulation was carried out on the confirmed data of Wuhan city from January 23, 2020 to February 11, 2020. At the same time, consider that the Wuhan municipal government revised the epidemic data on February 12, 2020, adding nearly 14,000 people. The order α value of SEIRV model is modified, and then the revised data is simulated. The simulation results are in good agreement with the published data. The results show that compared with the traditional integer order model, the fractional order model can simulate the modified data. This reflects the advantages of fractional infectious disease dynamics model, and can provide certain reference value for the prediction of COVID-19 model. © 2022 Editorial Borad of Complex Systems and Complexity Science. All rights reserved.
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Texte intégral: Disponible Collection: Bases de données des oragnisations internationales Base de données: Scopus Type d'étude: Étude pronostique langue: Chinois Revue: Complex Systems and Complexity Science Année: 2022 Type de document: Article

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Texte intégral: Disponible Collection: Bases de données des oragnisations internationales Base de données: Scopus Type d'étude: Étude pronostique langue: Chinois Revue: Complex Systems and Complexity Science Année: 2022 Type de document: Article