A time-dependent SEIRS model for COVID-19 in China (mainland)

Abstract

In the spring of 2022, two years after the onset of the coronavirus pandemic, a second worldwide outbreak is underway, with the number of patients infected with COVID-19 much higher than the peak during the first outbreak. Moreover, the second outbreak was not prevented in mainland China by a series of management measures with few local infections and mandatory quarantine of incoming persons. In this paper, we construct a compartmental model that includes exposed and isolated individuals to address the fact that the COVID-19 virus cannot be permanently immunized and to consider the isolation and treatment process in China. The model is used to analyze which factors have an impact on secondary outbreaks and uses the basic reproduction number to represent the outbreak. We obtained the expression for the basic reproduction number by calculating the basic reproduction number of the model. We used MATLAB to perform sensitivity analysis on each variable included in the expression for the basic reproduction number. In the sensitivity analysis, the increase in the basic reproduction number indicates that the rate of virus transmission and the rate of antibody failure are more critical to the pandemic. Reducing these rates can be effective in mitigating the epidemic. Also, the sensitivity analysis showed that increasing the vaccination rate does not help to reduce the basic reproduction number effectively. Therefore, the Chinese government should urge people to continue wearing masks to reduce the route and likelihood of the COVID-19 virus transmission and could appropriately reduce funding for vaccine promotion until a long-term effective vaccine is invented.