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

Xiaowei Chen (), Jing Li (), Chen Xiao () and Peilin Yang ()
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Xiaowei Chen: Nankai University
Jing Li: Nankai University
Chen Xiao: Nankai University
Peilin Yang: Nankai University

Fuzzy Optimization and Decision Making, 2021, vol. 20, issue 2, No 3, 189-208

Abstract: Abstract Developing algorithms for solving high-dimensional uncertain differential equations has been an exceedingly difficult task. This paper presents an $$\alpha $$ α -path-based approach that can handle the proposed high-dimensional uncertain SIR model. We apply the $$\alpha $$ α -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 $$\alpha $$ α -path-based approach opens up new possibilities in solving high-dimensional uncertain differential equations and new applications.

Keywords: Uncertainty theory; Uncertain differential equation; SIR model; COVID-19 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (12)

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DOI: 10.1007/s10700-020-09342-9

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