Facultad de Ciencias, Universidad de Colima, Apdo. Postal 25, Colima, Colima, Mexico.
Math Biosci Eng. 2010 Oct;7(4):809-23. doi: 10.3934/mbe.2010.7.809.
In this work we consider every individual of a population to be a server whose state can be either busy (infected) or idle (susceptible). This server approach allows to consider a general distribution for the duration of the infectious state, instead of being restricted to exponential distributions. In order to achieve this we first derive new approximations to quasistationary distribution (QSD) of SIS (Susceptible- Infected- Susceptible) and SEIS (Susceptible- Latent- Infected- Susceptible) stochastic epidemic models. We give an expression that relates the basic reproductive number, R0 and the server utilization,p.
在这项工作中，我们将群体中的每个个体视为一个服务器，其状态可以是忙碌（感染）或空闲（易感染）。这种服务器方法允许考虑传染病状态持续时间的一般分布，而不受限于指数分布。为了实现这一点，我们首先推导出 SIS（易感-感染-易感）和 SEIS（易感-潜伏-感染-易感）随机传染病模型的准静态分布（QSD）的新近似值。我们给出了一个表达式，将基本繁殖数 R0 和服务器利用率 p 联系起来。
