Social distancing measures may have reduced the estimated deaths related to Covid-19 in Brazil

Abstract

Social distancing was planned as a preventive measure to control the extensive spread of COVID-19. COVID-19-related deaths in Brazil were analyzed during the period of social distancing measures. Mortality data for COVID-19 was obtained from the Worldometer website. Deaths were estimated up to the 31st day after the occurrence of the 5th COVID-19-related death in Brazil. Social distance was measured using Google's community mobility reports. The Brazilian epidemic curves were interconnected, and mathematical models were evaluated to fit the mortality estimation curves. The optimistic model was defined in the opening period of social distancing and, therefore, in the lower mobility (40-60%). The realistic model was calculated according to relaxed social distance measures (<40%) and the pessimistic model was calculated based on the transmission rate between 2-3. Thus, the equations of the mathematical models provided the outcomes for the date of June 9, 2020, as follows: realistic model with 40,623 deaths, pessimistic model with 64,310 deaths and the optimistic model with a projection of 31,384 deaths. As a result of these analyzes, on May 24, 2020, there were a total of 22,965 deaths related to COVID-19, and those deaths included within the proposed mathematical models were 17,452 for the optimistic model, 22,623 for the realistic model and 32,825 for the pessimistic model. Thus, it is concluded that social distancing measures promoted by the Brazilian public managers contributes to the reduction in approximately ten thousand deaths related to COVID-19 in the current pandemic scenario.

Community movement and COVID-19: a global study using Google's Community Mobility Reports

“…For example, 'social distancing' has been widely promoted as a Epidemiology and Infection measure to reduce the transmission of COVID-19 [53]. Valenti et al [54] used CMR data as an estimate of social distancing in the modelling of deaths in Brazil. However, CMR data indicate only general activity at specific location types, and provide no direct indication of adherence to such rules.…”

“…Valenti et al . [54] used CMR data as an estimate of social distancing in the modelling of deaths in Brazil. However, CMR data indicate only general activity at specific location types, and provide no direct indication of adherence to such rules.…”

The Path of Humanity in the Pandemic of Covid-19: The Choice of the Realistic, Optimist or Pessimist Scenario

“…The implementation of non-pharmacological measures is urgent. Valenti et al, 5 demonstrated that social distance is an effective measure to control the extensive dissemination of COVID-19.…”

Intelligent computing with Levenberg–Marquardt artificial neural networks for nonlinear system of COVID-19 epidemic model for future generation disease control

“…Nowadays, the dynamics of COVID-19 models have been growing interest in the research community and may mathematical models are designed for the better interest of people around the world, such as the model of eight classes based on susceptible, infected, diagnosed, ailing, recognized, threatened, healed and extinct (SIDARTHE) [6], five classes based on SEIAR represented with 5 number of ordinary differential equations [7], a new θ -SEIHRD model represented with nine classes [8], modified SEIRS model system with five classes [9], four class modified SIR model [10], SAIR system based COVID-19 model for complex networks [11]. Beside, these variety of COVID-19 model are introduced by the researchers [8,[12][13][14][15][16][17][18][19][20][21][22]. However, in the current scenarios, we have taken a complex 8 classes model based on Susceptible (S), exposed (E), symptomatic and infectious (I), super propagation (P), infection but asymptomatic (A), hospitalized (H), recovery (R) and fatality (F) classes, i.e., SEIPAHRF for numerical investigations [23].…”