Dynamical analysis on symptom-based SEMIR compartmental model with age groups

This paper proposes the symptom-based SEMIR compartmental model with age groups and fluctuations from the perspective of the managers of the local government. The basic reproduction number of the total population is given by the next generation matrix method, the group-based basic reproduction number are then followed. The unique global positive solution is derived by using the Lyapunov function. Furthermore, the sufficient conditions of the stochastic extinction and the stochastic persistence of the SEMIR model are studied. When Fuzhou COVID-19 epidemic is chosen from the surveillance data for the further numerical investigation, the data fittings of the SEMIR model reveal that age groups are profitable to control the infection scale of intensive cases, and that the susceptibility to infection of age groups are higher than those within the total population. Alternatively, the scenario investigations show that the prompt treatments are conducive to the reduction of infection scale for intensive cases.