On the Stability Analysis of the Stochastic Infectious Model under Subclinical Infections

抄録

The stability of the stochastic infectious models under subclinical infection is considered in this paper. As we all know, the corona virus (COVID-19) has a great impact on economy and society since last December. Many people have still been suffering from COVID 19 infection. The control of COVID-19 infection is an emergent issue in epidemiology. One of characteristics of COVID-19 infection is the existence of subclinical infection. Hence, we analyze the stability of the infectious disease under subclinical infection in this paper. In the realistic spread of the infectious disease, environmental change and individual difference cause some kinds of random fluctuations in the model parameters. So, we introduce the random fluctuation into consideration in the model construction and we propose the stochastic infectious models with subclinical infection. Since the stability analysis of the infectious model is effective in the control of the spread of the infectious disease, we consider the stability analysis of the stochastic infectious model with subclinical infection. We show the efficacy of the stability theorems derived in this paper by numerical simulations.