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arXiv 2501.04463cond-mat.stat-mech
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在感染人群连接中具有缓解措施的易感-感染-易感动力学

Susceptible-Infected-Susceptible dynamics with mitigation in connection of infected population

K. M. Kim, C. Dias, M. O. Hase

AI总结:

提出在SIS模型的边感染概率中加入缓解因子以表征感染者隔离或住院,并在Barabási-Albert网络上用度平均场方法解析比较新旧模型。

摘要:

本文通过基于度的平均场方法分析了易感-感染-易感流行病模型。在这项工作中,在沿一条边发现感染个体的概率中引入了一个缓解因子。这一修正模拟了感染人群减少其参与疾病传播动力学的情况,例如感染个体的隔离或住院可能发生的情形。在Barabási-Albert网络上对这一新模型及其与原始模型(无缓解因子)的比较进行了详细研究,其中一些重要结果可通过解析方式获得。

英文摘要:

The susceptible-infected-susceptible epidemic model is analyzed through a degree-based mean-field approach. In this work, a mitigation factor is introduced in the probability of finding an infected individual following an edge. This modification simulates situations where the infected population reduces its participation in the dynamics of disease propagation, as may happen with the seclusion or hospitalization of infected individuals. A detailed investigation of this new model and its comparison to the original one (without the mitigation factor) was performed on the Barabási-Albert network, where some important results were analytically accessible.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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