基于复杂网络的不同路由策略下交通流驱动的流行病传播

2020年,随着新型冠状肺炎在全球范围的蔓延,交通流对流行病传播动力学的影响备受关注。虽然交通流与流行病传播动力学之间的相互作用已经开始受到关注,但路由策略对基于交通流的流行病传播动力学的影响还没有得到足够的重视,因此本文在SI模型上研究了最短路径、有效路径和概率路径三种路由策略对流行病传播动力学的影响。在BA无标度网络模型上进行了仿真实验,结果显示：在节点交付能力无限交通流无拥塞的情况下,相比于最短路径路由策略,概率路径路由策略能有效地抑制流行病的传播,而有效路径路由策略则加速了流行病的传播速度。此外,在上述三种路由策略下,交通流量和传染率的增加都会导致流行病传播阈值的降低,从而加快流行病的爆发。这些研究对控制流行病的传播具有一定指导意义。

Traffic-driven epidemic spread under different routing strategies based on complex networks

As COVID-19 spread globally in 2020, the impact of traffic flow on the epidemic spreading dynamics has attracted much attention. Although the interaction between traffic flow and epidemic spread dynamics has begun to receive attention, the impact of routing strategies on the traffic-driven epidemic spreading dynamics has not been paid enough attention. Therefore, this paper studied the impacts of the shortest path, efficient path and probability path three routing strategies on the dynamics of epidemic spreading on the SI model. Simulations in the BA scale-free network model show that, with unlimited node delivery capacity and free traffic flow, compared with the shortest path routing strategy, the probability path routing strategy can effectively control the spread of the epidemic and the efficient path routing strategy can accelerate the spread of the epidemic. In addition, under the three routing strategies described above, an increase in both traffic flow and infection rate will lead to a decrease in the epidemic threshold, thus accelerating the outbreak of the epidemic. These researches have significant implications for controlling the spread of the epidemic.