Threshold dynamics of a stochastic epidemic model incorporating emotional influence under three-tier media alerts

During the outbreak of emerging infectious diseases, a complex interplay of random events, media messages and human emotions inevitably affects disease transmission. In this paper, we propose a new stochastic epidemic model incorporating emotional influence under three-tier media alerts. Itô’s formula, Lyapunov function method and ergodicity of Markov chain are employed to research the extinction–persistence behavior of diseases. Our findings show that early detection and reporting contribute to effective prevention. However, the intensity of reporting rates and warning thresholds will need to be chosen according to the characteristic of each epidemic. Otherwise, media coverage may have a negative impact on the human psychology of disease prevention and control. A biological paradox emerges: high reporting rate and premature activation of the third-tier media warning may increase the number of infected individuals.