LAUSR

Human settlements are embedded in the traffic networks with hierarchical structure. In order to understand the spreading mechanism of infectious disease and deploy control measures, the susceptible-infected-removed spreading process is studied with agents moving globally on the hierarchical geographic network, taking into account agents' preference for node layers and memory of initial nodes. We investigate the spreading behavior in the case of global infection under different scenarios, including different directions of human flow, different locations of infection source, and different moving behaviors of agents between each layer. Based on the analysis above, we propose screening strategies based on layer rank and moving distance, and compare their effects on delaying epidemic spreading. We find that in the case of global infection, infection spreads faster in high layers than in low layers, and early infection in high layers and moving to high layers both accelerate epidemic spreading. Travel of high-layer and low-layer residents have different effects on accelerating epidemic spreading, and moving between high and low layers increases the peak value of new infected cases more than moving in the same layer or between adjacent layers. Infection in intermediate nodes enhances the effects of the moving of low-layer residents more than the moving of high-layer residents on accelerating epidemic spreading. For screening measures, improving the success rate is more effective on delaying epidemic spreading than expanding the screening range. With the same number of moves screened, screening moves into or out of high-layer nodes combined with screening moves between subnetworks has better results than only screening moves into or out of high-layer nodes, and screening long-distance moves has the worst results when the screening range is small, but it achieves the best results in reducing the peak value of new infected cases when the screening range is large enough. This paper probes into the spreading process and control measures under different scenarios on the hierarchical geographical network, and is of great significance for epidemic control in the real world.