Numerical Analysis and Applicable Mathematics
Title
Data-driven Analysis and Prediction of Fractional Order SIR Model for COVID-19
Authors
Michal Fečkan,*a Xu Wangb and JinRong Wanga
aDepartment of Mathematical Analysis and Numerical Mathematics, Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava, Mlynská dolina, 842 48 Bratislava, Slovakia, and Mathematical Institute, Slovak Academy of Sciences, Štefánikova 49, 814 73 Bratislava, Slovakia.
bDepartment of Mathematics, Guizhou University, Guiyang, Guizhou 550025, P.R. China
*Corresponding author E-mail address: Michal.Feckan@fmph.uniba.sk (Michal Fečkan)
Article History
Publication details: Received: 31st October 2020; Revised: 03rd April 2021; Accepted: 04th May 2021; Published: 14th May 2021
Cite this article
Fečkan M.; Wang X.; Wang JR. Data-driven Analysis and Prediction of Fractional Order SIR Model for COVID-19. Numer. Anal. Appl. Math., 2021, 2(3), 9-17.
Abstract
Coronavirus disease (COVID-19) broke out in Wuhan, Hubei province, China, in December 2019. Subsequently, various countries in the world also successively broke out the coronavirus disease. In this paper, we built a mathematical model to predict and analyze the change of COVID-19. Based on the fractional-order susceptible infected-recuperated (SIR) model with the real data from February 29 to March 30, 2020, and the predictor-correctors scheme is applied in this model. Then we use the fitting results and the integer-order (α = 1) comparison, the MAD, R2, BIC and absolute errors of fractional SIR model (α = 0:75) are smaller than those of integer model. We also predicted the situation of the new case in the next 400 days, the results indicate that the fractional order SIR model have a better fitting and forecasting of the data on the countries China, Italy, Spain, United Kingdom, United states, India and France.
Keywords
Fractional order; SIR epidemic model; Predictor-correctors scheme
