Global analysis of epidemic spreading with a general feedback mechanism on complex networks

This paper aims to investigate the effects of human behavior and contact heterogeneity on the spread of infectious diseases. For this purpose, a network-based SIRS epidemic model with a general feedback mechanism is proposed. In contrast to previous models, we consider the different fear degrees of individuals who have different potential number of contacts with others, when an epidemic prevails. The basic reproductive number that governs the global dynamics of the model is analytically derived. Accordingly, the permanence of the disease and stability conditions of the equilibria are studied in detail. It is shown that the general feedback mechanism cannot change the basic reproductive number, but theoretical and numerical results indicate that it plays an active role in reducing the disease damage. The obtained results generalize and improve some well-known ones.