Modelling the COVID-19 epidemics in Brasil: Parametric identification and public health measures influence

Renato Machado Cotta; Carolina Palma Naveira-Cotta; pierre magal

The classical susceptible-infectious-recovered (SIR) model describes the transmission of diseases between susceptible and infective individuals and provides the basic framework for almost all later epidemic models. At the onset of the coronavirus epidemy in China, there were some initial studies for the prediction of its evolution and and France [5] [6] [7] . Besides identifying unreported cases, this simple and robust model also allows for introducing a latency period and a time variable transmission rate, which can simulate a public health orientation change such as in a general isolation measure. In addition, an analytical exponential behaviour is assumed for the accumulated reported cases evolution along a second phase just following the onset of the epidemy, which, upon fitting of the available data, allows for the explicit analytical estimation of the transmission rate and the associated initial conditions required by the model.