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A class of anomalous diffusion epidemic models based on CTRW and distributed delay
International Journal of Biomathematics ; 2022.
Article in English | Web of Science | ID: covidwho-2194046
ABSTRACT
In recent years, the epidemic model with anomalous diffusion has gained popularity in the literature. However, when introducing anomalous diffusion into epidemic models, they frequently lack physical explanation, in contrast to the traditional reaction-diffusion epidemic models. The point of this paper is to guarantee that anomalous diffusion systems on infectious disease spreading remain physically reasonable. Specifically, based on the continuous-time random walk (CTRW), starting from two stochastic processes of the waiting time and the step length, time-fractional space-fractional diffusion, time-fractional reaction-diffusion and fractional-order diffusion can all be naturally introduced into the SIR (S susceptible, I infectious and R recovered) epidemic models, respectively. The three models mentioned above can also be applied to create SIR epidemic models with generalized distributed time delays. Distributed time delay systems can also be reduced to existing models, such as the standard SIR model, the fractional infectivity model and others, within the proper bounds. Meanwhile, as an application of the above stochastic modeling method, the physical meaning of anomalous diffusion is also considered by taking the SEIR (E exposed) epidemic model as an example. Similar methods can be used to build other types of epidemic models, including SIVRS (V vaccine), SIQRS (Q quarantined) and others. Finally, this paper describes the transmission of infectious disease in space using the real data of COVID-19.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: International Journal of Biomathematics Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: International Journal of Biomathematics Year: 2022 Document Type: Article