当前位置:
X-MOL 学术
›
Phys. Rev. E
›
论文详情
Our official English website, www.x-mol.net, welcomes your
feedback! (Note: you will need to create a separate account there.)
Basic reproduction number of epidemic models on sparse networks
Physical Review E ( IF 2.2 ) Pub Date : 2022-09-22 , DOI: 10.1103/physreve.106.034318 Satoru Morita 1
Physical Review E ( IF 2.2 ) Pub Date : 2022-09-22 , DOI: 10.1103/physreve.106.034318 Satoru Morita 1
Affiliation
The basic reproduction number is a standard indicator of infection control in epidemiology. Although has been studied extensively for deterministic epidemic models, it has not been formulated accurately for models adopting network structures. Here, we extend a four-compartment model that includes commonly used epidemic models to a Markov process on networks. By examining the Markov process in detail, we derive a canonical formula for involving two probability values. Numerical calculations show that the derived formula is a better approximation than the conventional formula when the network is very sparse. We propose this as a standard formula for controlling infections that can only be transmitted through intimate contact, where contacts between individuals can be described as a sparse network.
中文翻译:
稀疏网络上流行病模型的基本复制数
基本再生数是流行病学中感染控制的标准指标。虽然已经针对确定性流行病模型进行了广泛的研究,但对于采用网络结构的模型还没有准确地制定。在这里,我们将包含常用流行病模型的四室模型扩展到网络上的马尔可夫过程。通过详细研究马尔可夫过程,我们推导出了一个典型公式涉及两个概率值。数值计算表明,当网络非常稀疏时,推导公式比传统公式更接近。我们建议将此作为控制只能通过亲密接触传播的感染的标准公式,其中个体之间的接触可以描述为稀疏网络。
更新日期:2022-09-22
中文翻译:
稀疏网络上流行病模型的基本复制数
基本再生数是流行病学中感染控制的标准指标。虽然已经针对确定性流行病模型进行了广泛的研究,但对于采用网络结构的模型还没有准确地制定。在这里,我们将包含常用流行病模型的四室模型扩展到网络上的马尔可夫过程。通过详细研究马尔可夫过程,我们推导出了一个典型公式涉及两个概率值。数值计算表明,当网络非常稀疏时,推导公式比传统公式更接近。我们建议将此作为控制只能通过亲密接触传播的感染的标准公式,其中个体之间的接触可以描述为稀疏网络。