In this paper we model the spreading of the SARS-CoV-2 in Mexico by introducing a new stochastic approximation constructed from first principles, structured on the basis of a Latent-Infectious- (Recovered or Deceased) (LI(RD)) compartmental approximation, where the number of new infected individuals caused by a single infectious individual per unit time (a day), is a random variable of a Poisson distribution and whose parameter is modulated through a weight-like time-dependent function. The weight function serves to introduce a time dependence to the average number of new infections and as we will show, this information can be extracted from empirical data, giving to the model self-consistency and provides a tool to study information about periodic patterns encoded in the epidemiological dynamics
翻译:在本文中,我们以墨西哥SARS-COV-2的扩展为模型,采用了一种根据第一原则构建的新的随机近似值,这种近似值基于一种基于隐性传染(恢复或死亡)(LI(RD)(LI)(LI(RD)))的条状近似值,即每个单位时间(一天)由单一感染个人造成的新感染者人数是Poisson分布的一个随机变数,其参数通过一个与体重相似的时间依赖功能来调节。重量函数的作用是给新感染的平均数带来时间依赖性,正如我们将显示的那样,这一信息可以从实验数据中提取,给模型自我一致性,并提供一个工具,用于研究流行病学动态中编码的定期模式的信息。