Dynamics of two-strain disease transmission with negative vaccine information and vaccination on multiplex networks

During the disease transmission, the virus may mutate and novel strains appear. That causes the reduction of the immune effect of the vaccine against the original strain, and the vaccinated individuals may also be infected, which would lead to the generation and dissemination of negative vaccine information. However, the coupled dynamics of multi-strain disease and negative vaccine information has not yet been comprehensively investigated. In this paper, we consider both the original and mutant strains of the disease and introduce vaccination behavior in the propagation process to expand the classic susceptible-infectious-susceptible (SIS) model into five states: susceptible, vaccinated, infected by original strain, infected by mutant strain and recovered. Then, a two-layer network model is proposed to describe the coupled propagation dynamics of the negative vaccine information and the two-strain disease, and the epidemic outbreak thresholds of the two-strain disease are derived by using the Microscopic Markov Chain Approach (MMCA). Subsequently, the numerical results derived from the MMCA are compared with those from Monte-Carlo (MC) simulation to validate the correctness of the former. Finally, the phase diagrams and time history curves are presented to conduct parametric studies on the epidemic thresholds and information-disease transmission dynamics, such as the vaccination cost, vaccine effectiveness and the negative vaccine information. This research demonstrates that reducing the vaccination cost and enhancing the positive publicity of vaccine can effectively prevent the disease spreading when the infection rate of the mutant strain is low. If this infection rate is large, the effective measure is developing specific vaccines against the mutant strain to improve the vaccination efficacy. Those findings provide valuable strategies for the authorities to make appropriate disease prevention measures.