Dynamic Modeling Of Zoonotic SARS-CoV-2

COVID-19 caused by the novel coronavirus（SARS-Co V-2）has been occured in various parts of the world since the end of 2019.The outbreaks of SARS-Co V-2 has not only led to serious economic losses and human loss,but also caused a huge impact on the public health of the world.At present,we have evidence that COVID-19 can infect both humans and animals,which is a new zoonotic disease.In this thesis,deterministic models are established to explore the risk of co-infection between humans and animals and the influence of risk factors such as exposure to infection under different initial conditions on the transmission of SARS-Co V-2.It is a prospective study and risk assessment of zoonotic novel coronavirus.Based on the study of the epidemic mechanism of the novel coronavirus,a human-animal-environment model of SARS-Co V-2 transmission is established.The forward invariant set and the basic reproduction number R₀of system is calculated.Then,we prove the global asymptotic stability of the disease-free equilibrium of the model and the existence,uniqueness and uniform persistence of the endemic equilibrium.Sensitivity analysis is applied to explore the parameters that have a great impact on the system.Numerical simulation results reveal the influence of several key parameters on the transmission of zoonotic novel coronavirus.According to the transmission characteristics of zoonotic novel coronavirus,an 11-dimensi-onal epidemic dynamics model with low risk population,high risk population,domestic ani-mals and wild animals is proposed.We considered the different impacts of high-risk and low-risk populations on the the transmission of SARS-Co V-2.Moreover,the maximum likelihood function is used to estimate the parameters,and the parameter values are given under 95%con-fidence interval.And the numerical results are carried out to analyze the risk of transmission under different initial values.