Theoretical and numerical analysis of COVID-19 pandemic model with non-local and non-singular kernels

被引:3
|
作者
Cui, Ting [1 ]
Liu, Peijiang [2 ]
Din, Anwarud [3 ]
Ali, Fawad [4 ]
机构
[1] Guangdong Univ Finance & Econ, Sch Econ, Guangzhou 510320, Peoples R China
[2] Guangdong Univ Finance & Econ, Sch Stat & Math, Big Data & Educ Stat Applicat Lab, Guangzhou 510320, Peoples R China
[3] Sun Yat Sen Univ, Dept Math, Guangzhou 510275, Peoples R China
[4] Kohat Univ Sci & Technol, Inst Numer Sci, Kohat 26000, Kpk, Pakistan
关键词
CORONAVIRUS;
D O I
10.1038/s41598-022-21372-4
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The global consequences of Coronavirus (COVID-19) have been evident by several hundreds of demises of human beings; hence such plagues are significantly imperative to predict. For this purpose, the mathematical formulation has been proved to be one of the best tools for the assessment of present circumstances and future predictions. In this article, we propose a fractional epidemic model of coronavirus (COVID-19) with vaccination effects. An arbitrary order model of COVID-19 is analyzed through three different fractional operators namely, Caputo, Atangana-Baleanu-Caputo (ABC), and Caputo-Fabrizio (CF), respectively. The fractional dynamics are composed of the interaction among the human population and the external environmental factors of infected peoples. It gives an extra description of the situation of the epidemic. Both the classical and modern approaches have been tested for the proposed model. The qualitative analysis has been checked through the Banach fixed point theory in the sense of a fractional operator. The stability concept of Hyers-Ulam idea is derived. The Newton interpolation scheme is applied for numerical solutions and by assigning values to different parameters. The numerical works in this research verified the analytical results. Finally, some important conclusions are drawn that might provide further basis for in-depth studies of such epidemics.
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页数:21
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