Impacts of multitype interactions on epidemic spreading in temporal networks

Individuals have often been found to interact with each other with different intensity in a dynamical way due to their various types in real networks, which plays a fundamental role in dynamical process such as epidemic spreading. To understand the relationship between the network structure and the spreading process, we propose a kind of temporal network model which contains diverse types of individuals. Furthermore, we also assume that the transmission rate is also related to the individuals' types. Theoretical analysis and numerical results show that the epidemic threshold is affected by several factors, such as parameters described network structure and the ratio of intra-transmission rate to inter-transmission rate. Finally, we investigate immunization strategies for the network model and propose an immunization strategy by considering the mutual effect of individual's degree connected with the same type and those with different types. By comparing a kind of immunization strategies, we find that the proposed immunization strategy is able to suppress the outbreak with less observation time and that it is able to suppress the outbreak almost as efficient as the target immunization strategy with appropriate observation time.