An improved fractional-order transmission model of COVID-19 with vaccinated population in United States

Sun, Deshun1,2; Yuan, Kelei3; Yin, Guohua4

2024-08-01

10.1088/1402-4896/ad5ca5

PHYSICA SCRIPTA   影响因子和分区

0031-8949

1402-4896

In this paper, we propose a new fractional-order differential equation model with latent and vaccinated population to describe the dynamics of COVID-19. Firstly, the theoretical mathematical model is established based on the transmission mechanism of COVID-19 in the population. Then, the data of the infected, the recovered and the death are collected from big data report of Baidu's epidemic situation, and the parameters are estimated by piecewise fitting and nonlinear least square method based on collected data. The correlation coefficients between the infected and model simulation, between the recovered and model simulation, between the death and model simulation are 0.9868, 0.9948 and 0.9994, respectively and the accuracy of prediction are 96.05%, 99.33% and 99.88%, respectively. Additionally, the accuracy of prediction is compared between fractional-order differential equation model and integer-order differential equation model, and the results show fractional-order differential equation model can better predict the development trend of COVID-19. Finally, we analyze the sensitivity of the parameters through numerical simulations, and put forward the corresponding strategies to control the epidemic development according to the screened sensitive parameters.

COVID-19 integer-order model fractional-order model parameter estimation sensitivity analysis

SCI ; EI

英语

第一 ; 通讯

National Natural Science Foundation of China[62103287] ; Guangdong Provincial Natural Science Foundation General Project[2023A1515010518] ; Basic Research General Project of Shenzhen["JCYJ20210324103209026","RCBS20200714114856171"] ; President's Fund of Southern University of Science and Technology Hospital[2022-A3] ; Clinical Research Project of Shenzhen Second People's Hospital[20213357007] ; null[NSZD2023061]

Physics

Physics, Multidisciplinary

WOS:001268067400001

IOP Publishing Ltd

20242916722502

Differential equations ; Disease control ; Forecasting ; Least squares approximations ; Parameter estimation ; Sensitivity analysis ; Transmissions

Health Care:461.7 ; Mechanical Transmissions:602.2 ; Mathematics:921 ; Calculus:921.2 ; Numerical Methods:921.6

PHYSICS

Web of Science

1.Southern Univ Sci & Technol Hosp, Intelligent Med Innovat Inst, Shenzhen, Peoples R China
2.Shenzhen Univ, Shenzhen Peoples Hosp 2, Guangdong Prov Res Ctr Artificial Intelligence & D, Hlth Sci Ctr,Hosp 2,Shenzhen Key Lab Tissue Engn,S, Shenzhen, Peoples R China
3.USTC, Hefei, Peoples R China
4.Shenzhen Emergency Ctr, Shenzhen, Peoples R China

Sun, Deshun,Yuan, Kelei,Yin, Guohua. An improved fractional-order transmission model of COVID-19 with vaccinated population in United States[J]. PHYSICA SCRIPTA,2024,99(8).

Sun, Deshun,Yuan, Kelei,&Yin, Guohua.(2024).An improved fractional-order transmission model of COVID-19 with vaccinated population in United States.PHYSICA SCRIPTA,99(8).

Sun, Deshun,et al."An improved fractional-order transmission model of COVID-19 with vaccinated population in United States".PHYSICA SCRIPTA 99.8(2024).