Covid modeling through delay equations

For try to describe the behavior of progress of the Coronavirus in Chile we based our analysis in a typical SEIR Model. SEIR is an epidemiological model used to predict infectious disease dynamics by compartmentalizing the population into four possible states: Susceptible [S], Exposed or latent [E], Infectious [I] or Removed [R]. A simply SEIR model considers a specific recovery time’s for all infected, but take in count the  behavior of disease populations in function of symptoms developed, we divide the infected population in asymptomatics and symptomatics (mild, seriously and critical condition), so that each population of symptomatics has a different recovery time, evidently these datas are considered in our set of SEIR equations. Finally, we divide the population of exposed in age gaps considers the typical features of each gap as the contagious susceptibility of age. For to compare with a real situation, like Santiago, and to determinate what could be the right measures for reduce the contagions, we apply two kinds of “interventions”, the first one is a quarantine where reduces the contagious because decrease the amount of peoples that circuls for the city, and the second is an intervention of trasability that retires infected people of the system through sanitaries residences or isolated quarantines. In our model we investigated the dynamic of these modified SEIR equations and his response a differents interventions.