In this study, we construct a network-based SAIS model that accounts for the interplay of human mobility and asymptomatic infected individuals. The stability analysis of equilibrium points is performed by constructing suitable Lyapunov functions. Based on the next generation matrix method, the basic reproduction number \(\mathscr {R}_0\) is attained in a form similar to the results derived in the two-strain epidemic model. Numerical results demonstrate the impact of \(\mathscr {R}_0\) on the final steady state of disease transmission and inspire us that the role of asymptomatic cases cannot be overlooked in the course of a disease. Further simulations reveal the influence mechanism of human mobility on disease spreading in population with heterogeneous contact modes, which will undergo four different stages as the degree of nodes increases. It is concluded that the optimal movement rate should be determined on the basis of human contact patterns, and that controlling population flow with this rate could significantly reduce the peak density of infected individuals.
