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认知对随机网络上流行病传播的影响。

The influence of awareness on epidemic spreading on random networks.

作者信息

Li Meili, Wang Manting, Xue Shuyang, Ma Junling

机构信息

School of Science, Donghua University, Shanghai 201620, China.

School of Information Science and Technology, Donghua University, Shanghai 201620, China.

出版信息

J Theor Biol. 2020 Feb 7;486:110090. doi: 10.1016/j.jtbi.2019.110090. Epub 2019 Nov 22.

Abstract

During an outbreak, the perceived infection risk of an individual affects his/her behavior during an epidemic to lower the risk. We incorporate the awareness of infection risk into the Volz-Miller SIR epidemic model, to study the effect of awareness on disease dynamics. We consider two levels of awareness, the local one represented by the prevalence among the contacts of an individual, and the global one represented by the prevalence in the population. We also consider two possible effects of awareness: reducing infection rate or breaking infectious edges. We use the next generation matrix method to obtain the basic reproduction number of our models, and show that awareness acquired during an epidemic does not affect the basic reproduction number. However, awareness acquired from outbreaks in other regions before the start of the local epidemic reduces the basic reproduction number. Awareness always reduces the final size of an epidemic. Breaking infectious edges causes a larger reduction than reducing the infection rate. If awareness reduces the infection rate, the reduction increases with both local and global awareness. However, if it breaks infectious edges, the reduction may not be monotonic. For the same awareness, the reduction may reach a maximum on some intermediate infection rates. Whether local or global awareness has a larger effect on reducing the final size depends on the network degree distribution and the infection rate.

摘要

在疫情爆发期间,个体感知到的感染风险会影响其在疫情期间的行为,以降低风险。我们将感染风险意识纳入Volz - Miller SIR疫情模型,以研究意识对疾病动态的影响。我们考虑两种意识水平,一种是由个体接触者中的患病率所代表的局部意识,另一种是由人群中的患病率所代表的全局意识。我们还考虑了意识的两种可能影响:降低感染率或切断感染联系。我们使用下一代矩阵方法来获得模型的基本再生数,并表明疫情期间获得的意识不会影响基本再生数。然而,在本地疫情开始之前从其他地区的疫情爆发中获得的意识会降低基本再生数。意识总是会降低疫情的最终规模。切断感染联系比降低感染率导致的规模减小更大。如果意识降低感染率,这种降低会随着局部和全局意识的增加而增大。然而,如果意识切断感染联系,这种降低可能不是单调的。对于相同的意识,在某些中间感染率下,降低幅度可能会达到最大值。局部意识还是全局意识对降低最终规模的影响更大,这取决于网络度分布和感染率。

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