Author: Chen, Xiaowei; Li, Jing; Xiao, Chen; Yang, Peilin
Title: Numerical solution and parameter estimation for uncertain SIR model with application to COVID-19 Cord-id: 2znhvzkf Document date: 2020_9_17
ID: 2znhvzkf
Snippet: 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
Document: 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.
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