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Turing instability in the fractional-order system with random network
International Journal of Modern Physics B ; 2022.
Article in English | Web of Science | ID: covidwho-2020346
ABSTRACT
The epidemic often spreads along social networks and shows the effect of memorability on the outbreak. But the dynamic mechanism remains to be illustrated in the fractional-order epidemic system with a network. In this paper, Turing instability induced by the network and the memorability of the epidemic are investigated in a fractional-order epidemic model. A method is proposed to analyze the stability of the fractional-order model with a network through the Laplace transform. Meanwhile, the conditions of Turing instability and Hopf bifurcation are obtained to discuss the role of fractional order in the pattern selection and the Hopf bifurcation point. These results prove the fractional-order epidemic model may describe dynamical behavior more accurately than the integer epidemic model, which provides the bridge between Turing instability and the outbreak of infectious diseases. Also, the early warning area is discussed, which can be treated as a controlled area to avoid the spread of infectious diseases. Finally, the numerical simulation of the fractional-order system verifies the academic results is qualitatively consistent with the instances of COVID-19.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Randomized controlled trials Language: English Journal: International Journal of Modern Physics B Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Randomized controlled trials Language: English Journal: International Journal of Modern Physics B Year: 2022 Document Type: Article