  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
