Modeling of the COVID-19 Epidemic Outbreak in Real-World Social Networks
In this paper, the features of real-world social graphs are considered and a generalization of the classical infection spread model called SIR is applied to graphs that meet the “social network” criteria. For the SIR model coefficient of the characteristic virus transmission rate, the dependence on time and the social graph structure is introduced. The individual condition is determined by three groups of the SIR model: susceptible, infected and recovered. The decrease in the infection intensity is taken into account when modeling the mask and self-isolation measures introduced in many countries in order to reduce the COVID-19 incidence. The results of modeling the COVID-19 infection spread are represented in the example of the “Social circles: Facebook” graph from Stanford University.