Effects of asymptomatic infection and self-initiated awareness on the coupled disease-awareness dynamics in multiplex networks

There has been growing interest in exploring the coupled epidemic-awareness dynamics within the multiplex network framework. Nevertheless, two important factors are not considered in the existing works, one is that the asymptomatic state is ignored in many epidemic dynamics, which can significantly affect the awareness and the epidemic dynamics simultaneously. The other is that the self-initiated awareness mechanism is omitted, which addresses that individuals can be altered spontaneously by the infected neighbors rather than just be informed by others. To this arm, we propose a novel coupled epidemic-awareness model in multiplex networks by incorporating these two factors and investigate their impacts on the dynamics of epidemic and awareness. Based on the microscopic Markov chain approach and Monte-Carlo simulation, our findings indicate that the asymptomatic state makes people underestimate the risk of disease, leading to insufficient diffusion of awareness and further inducing the outbreak of epidemic. On the contrary, even though the self-initiated mechanism plays a positive role on the control of epidemic, whose effect is also weakened by the existence of the asymptomatic state. More importantly, a fundamental quantity underlying the spreading dynamics–the epidemic threshold is analytically derived.