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Numerical solution and parameter estimation for uncertain SIR model with application to COVID-19

Developing algorithms for solving high-dimensional uncertain differential equations has been an exceedingly difficult task. This paper presents an [Formula: see text] -path-based approach that can handle the proposed high-dimensional uncertain SIR model. We apply the [Formula: see text] -path-based...

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Detalles Bibliográficos
Autores principales: Chen, Xiaowei, Li, Jing, Xiao, Chen, Yang, Peilin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7495411/
http://dx.doi.org/10.1007/s10700-020-09342-9
Descripción
Sumario:Developing algorithms for solving high-dimensional uncertain differential equations has been an exceedingly difficult task. This paper presents an [Formula: see text] -path-based approach that can handle the proposed high-dimensional uncertain SIR model. We apply the [Formula: see text] -path-based approach to calculating the uncertainty distributions and related expected values of the solutions. Furthermore, we employ the method of moments to estimate parameters and design a numerical algorithm to solve them. This model is applied to describing the development trend of COVID-19 using infected and recovered data of Hubei province. The results indicate that lockdown policy achieves almost 100% efficiency after February 13, 2020, which is consistent with the existing literatures. The high-dimensional [Formula: see text] -path-based approach opens up new possibilities in solving high-dimensional uncertain differential equations and new applications.