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Modeling epidemic spread with awareness and heterogeneous transmission rates in networks

机译:利用网络中的意识和异构传输速率对流行病传播进行建模

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摘要

During an epidemic outbreak in a human population, susceptibility to infection can be reduced by raising awareness of the disease. In this paper, we investigate the effects of three forms of awareness (i.e.; contact, local, and global) on the spread of a disease in a random network. Connectivity-correlated transmission rates are assumed. By using the mean-field theory and numerical simulation, we show that both local and contact awareness can raise the epidemic thresholds while the global awareness cannot, which mirrors the recent results of Wu et al. The obtained results point out that individual behaviors in the presence of an infectious disease has a great influence on the epidemic dynamics. Our method enriches mean-field analysis in epidemic models.
机译:在人类的一次流行病暴发期间,可以通过提高对该疾病的认识来降低对感染的易感性。在本文中,我们研究了三种意识形式(即接触,局部和全局)对随机网络中疾病传播的影响。假设与连接性相关的传输速率。通过使用均值场理论和数值模拟,我们表明本地和接触意识都可以提高流行阈值,而整体意识却不能,这反映了Wu等人的最新结果。所得结果指出,在存在传染病的情况下,个人行为对流行趋势有很大影响。我们的方法丰富了流行病模型中的均值分析。

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