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

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

The CR(t) data for the accumulated reported infectious in Brasil, from February 25 th , when the first infected individual was reported, up to March 29 th , is presented in the Appendix. First, the exponential phase of the evolution was fitted, taking the data from day 10 to 25, yielding the estimates of the three parameters, 1 For instance, in the analysis of the Italy epidemic evolution reported in [6] , with data from January 31 st to March 8 th , a comparable low attenuation factor of = 0.032 was identified. It is also possible to observe the lower value of the parameter 0 , in comparison to the value obtained for the China dataset, which represents that only around 30% of the infected symptomatic individuals become in fact reported cases. This result could reflect an initial protocol of not thoroughly testing the mildly symptomatic individuals or just a lack of enough testing kits. This fact shall be discussed again further ahead when the impact of public health measures is analysed. Figure 6 illustrates the good agreement of Brasil's full dataset (period from February 25th till March 29th) with the mathematical model predictions, after adopting the estimated values for the parameters in Table 4 . The theoretical CR(t) curve is plotted together with the 95% confidence interval bounds for this simulated evolution. It should be recalled that non-informative priors were adopted for the three parameters, as in the China example, and except for the transmission rate, All rights reserved. No reuse allowed without permission.