Modeling and forecasting the early evolution of the Covid-19 pandemic in Brazil

Abstract

We model and forecast the early evolution of the COVID-19 pandemic in Brazil using Brazilian recent data from February 25, 2020 to March 30, 2020. This early period accounts for unawareness of the epidemiological characteristics of the disease in a new territory, sub-notification of the real numbers of infected people and the timely introduction of social distancing policies to flatten the spread of the disease. We use two variations of the SIR model and we include a parameter that comprises the effects of social distancing measures. Short and long term forecasts show that the social distancing policy imposed by the government is able to flatten the pattern of infection of the COVID-19. However, our results also show that if this policy does not last enough time, it is only able to shift the peak of infection into the future keeping the value of the peak in almost the same value. Furthermore, our long term simulations forecast the optimal date to end the policy. Finally, we show that the proportion of asymptomatic individuals affects the amplitude of the peak of symptomatic infected, suggesting that it is important to test the population.

Which COVID policies are most effective? A Bayesian analysis of COVID-19 by jurisdiction

“…Many modeling approaches have been adopted to estimate infection rates, death rates, and disease spread. A well-established class of models relies on differential equations to analyze disease dynamics within susceptible, exposed, infected, and recovered (SEIR) "compartments" of populations [6][7][8][9][10][11]. The SEIR model and its variants (e.g., the SIR and SEIRS models) assume that the flow rates between compartments in the population are reflected in the history of the disease [9,10].…”

“…The SEIR model and its variants (e.g., the SIR and SEIRS models) assume that the flow rates between compartments in the population are reflected in the history of the disease [9,10]. The SEIR framework has been used to study past COVID transmission and forecast future evolution [6,7,11,12]. Its variants have also produced insight on the importance of accounting for presymptomatic and asymptomatic individuals in order to curb COVID spread [13,14].…”

A model for COVID-19 with isolation, quarantine and testing as control measures

“… Par. Value–Range Reference Remark [0.62,2] Alimohamadi et al, 2020 , Bastos and Cajueiro, 2020 , Flaxman et al, 2020 , Shen et al, 2020 1. Liang and Yuan (2020) 2.…”

An optimal lockdown relaxation strategy for minimizing the economic effects of covid–19 outbreak

“…Several researchers have used the SIR model to forecast the covid-19 incidence (Atkeson, 2020;Bastos & Cajueiro, 2020;Roda et al, 2020). The SIR model in its original form is however not very helpful for our purpose.…”