Social Communications Assisted Epidemic Disease Influence Minimization

This work explores the use of social communications for epidemic disease control. Since the most infectious diseases spread through human contacts, we focus on modeling the diffusion of diseases by analyzing the social relationship among individuals. In other words, we try to capture the interaction pattern among human beings using the social contact information, and investigate its impact on the spread of diseases. Particularly, we investigate the problem of minimizing the expected number of infected persons by treating a small fraction of the population with vaccines. We prove that this problem is NP-hard, and propose an approximate algorithm representing a preventive disease control strategy based on the social patterns. Simulation results confirm the superiority of our strategy over existing ones.