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

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

The copyright holder for this preprint (which was not peer-reviewed) is . https://doi.org/10.1101/2020.03.31.20049130 doi: medRxiv preprint a simultaneous estimation of the five parameters. Then, employing the dataset for Brasil, the parametrized time variation of the transmission rate ( 0 and ) and the fraction of asymptomatic infectious that become reported ( 0 ), initially assumed constant, are estimated. In addition, due to the behaviour of the estimated CR(t) curve in this case, it is also attempted to estimate a possible time variation for the fraction of asymptomatic infectious that become reported, ( ), by parametrization of an abrupt variation that requires just the estimation of and . The statistical inversion approach here implemented falls within the Bayesian statistical framework [8] [9] [10] [11] [12] , in which (probability distribution) models for the measurements and the unknowns are constructed separately and explicitly, as shall be briefly reviewed in what follows.