Analysis of COVID-19 using a modified SLIR model with nonlinear incidence

Results in Physics

Azizur Rahman¹  Md Abdul Kuddus² 

[1] Corresponding author.;Department of Mathematics, University of Rajshahi, Rajshahi 6205, Bangladesh;

关键词: Epidemic model;    Nonlinear incidence;    Stability analysis;    COVID-19;    Simulations;   

DOI  :  

来源: DOAJ

【 摘 要 】

Infectious diseases kill millions of people each year, and they are the major public health problem in the world. This paper presents a modified Susceptible-Latent-Infected-Removed (SLIR) compartmental model of disease transmission with nonlinear incidence. We have obtained a threshold value of basic reproduction number (R0) and shown that only a disease-free equilibrium exists when R0<1 and endemic equilibrium when R0>1. With the help of the Lyapunov-LaSalle Invariance Principle, we have shown that disease-free equilibrium and endemic equilibrium are both globally asymptotically stable. The study has also provided the model calibration to estimate parameters with month wise coronavirus (COVID-19) data, i.e. reported cases by worldometer from March 2020 to May 2021 and provides prediction until December 2021 in China. The Partial Rank Correlation Coefficient (PRCC) method was used to investigate how the model parameters’ variation impact the model outcomes. We observed that the most important parameter is transmission rate which had the most significant impact on COVID-19 cases. We also discuss the epidemiology of COVID-19 cases and several control policies and make recommendations for controlling this disease in China.

【 授权许可】

Unknown