Previous studies revealed that the susceptibility, contacting preference, and recovery probability markedly alter the epidemic outbreak size and threshold. The recovery probability of an infected node is closely related to its obtained resources. How to allocate limited resources to infected neighbors is extremely important for containing the epidemic spreading on complex networks. In this paper, we proposed an epidemic spreading model on complex networks, in which we assume that the node has heterogeneous susceptibility and contacting preference, and susceptible nodes are willing to share their resources to neighbors. Through a developed heterogeneous mean-field theory and a large number of numerical simulations, we find that the recovered nodes provide resources uniformly to their infected neighbor nodes, and the epidemic spreading can be suppressed optimally on homogeneous and heterogeneous networks. Besides, altering the susceptibility and contacting preference does not qualitatively change the results. The susceptibility of the node decreases, which makes the outbreak threshold of epidemic spreading increase, and the outbreak size decreases. Our theory agrees well with the numerical simulations.

中文翻译：

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在邻居资源支持下遏制网络上的流行病传播

先前的研究表明，易感性，接触偏好和恢复概率显着改变了流行病的爆发规模和阈值。受感染节点的恢复概率与其获得的资源密切相关。如何为感染的邻居分配有限的资源对于控制在复杂网络上传播的疫情极为重要。在本文中，我们提出了一种在复杂网络上的流行病传播模型，在该模型中，我们假设该节点具有异构的易感性和联系偏好，易受影响的节点愿意将其资源共享给邻居。通过发达的异构平均场理论和大量的数值模拟，我们发现恢复的节点向其被感染的邻居节点均匀地提供资源，并且可以在同质和异构网络上最佳地抑制流行病的传播。此外，改变易感性和接触偏好不会定性地改变结果。节点的敏感性降低，这使得流行病传播的爆发阈值增加，爆发规模减小。我们的理论与数值模拟非常吻合。