Impact of population size on epidemic spreading in a bipartite metapopulation network with recurrent mobility

Abstract

The mobility pattern of a population plays a key role in the spread of epidemics. Despite extensive work on epidemic spreading, little attention has been paid to the impact of subpopulation size. This paper investigates the spread of epidemics on a bipartite metapopulation network considering recurrent mobility patterns and different sizes of subpopulations. With the Markovian process approach, the epidemic threshold can be predicted as a function of subpopulation size and epidemic parameters. Simulation and theoretical results indicate that there exists a critical mobility intensity below which the epidemic will be eliminated, while limiting the size of the subpopulation can suppress the epidemic. Additionally, the epidemic threshold will approach zero when the size of the public area is large. The results can help the prevention of epidemic spreading under recurrent crowd mobility.