Coupling media coverage and susceptibility for modeling epidemic dynamics: An application to COVID-19

Abstract

During an epidemic outbreak, social media is highly influential on human behavior and hence affects the spread of the epidemic course. In order to examine the impact of social media on disease transmission, a qualitative SIS-M type model with media-induced susceptibility is established, dealing with the amount of media coverage as an independent variable. The dynamic analysis of the proposed model is conducted theoretically and numerically. It is found that the growth rate of media coverage as well as the dissemination rate among the susceptible population may destabilize the endemic equilibrium under certain conditions, and consequently results in the existence of Hopf bifurcation. Moreover, the proposed model is applied to fit the daily confirmed cases of COVID-19 as well as the related news items for two cities in mainland China, and the estimated variation in daily confirmed cases triggered by the change of concerned parameters is investigated, revealing the effectiveness of our model and the performance of social media on mitigating the disease spread.