On the effect of COVID-19 pandemic in the excess of human mortality. The case of Brazil and Spain

Abstract

Excess of deaths is a technique used in epidemiology to assess the deaths caused by an unexpected event. For the present COVID–19 pandemic, we discuss the performance of some linear and nonlinear time series forecasting techniques widely used for modeling the actual pandemic and provide estimates for this metric from January 2020 to April 2021. We apply the results obtained to evaluate the evolution of the present pandemic in Brazil and Spain, which allows in particular to compare how well (or bad) these countries have managed the pandemic. For Brazil, our calculations refute the claim made by some officials that the present pandemic is “a little flu”. Some studies suggest that the virus could be lying dormant across the world before been detected for the first time. In that regard, our results show that there is no evidence of deaths by the virus in 2019.

Infodemiological study on the impact of the COVID-19 pandemic on increased headache incidences at the world level

“…In particular, excess mortality is defined as the surge of all-cause mortality over the level that would have been expected based on historic trends 44 . Consequently, an increasing strand of literature estimates excess death rates 43 , 45 – 54 , etc.) or assesses and predicts the spread of COVID-19 as reflected in hospitalization rates 55 during the ongoing global health crisis.…”

“…Some authors estimate multiple models in an attempt to improve inference and forecasting ability. For example, Borrego–Morell et al 45 use three statistical methods (i.e. GLM, ETS, and ARIMA) to model the historical evolution and produce estimates of excess mortality rates in Brazil and Spain, and identify ARIMA as overperforming in out-of-sample prediction.…”

Assessing COVID-19 pandemic excess deaths in Brazil: years 2020 and 2021

“…wherein pan refers to the pandemic period. For obtaining ỹpan 6 | b6 in (10) we substitute ε 6pan by its best predictor available, i.e the null vector, and the distinction between predictions formulae ( 9) and ( 10) is with respect to their variances. The variance-covariance matrix of the complete predicted vector ỹ6 |b 6 is…”

“…In a countrywide survey, Horta et al [9], found that about 25% of the interviewees reported failing to seek care due to a health problem or missed a routine examination during the first six months of the pandemic. Additionally, mitigation measures imposed to control transmission can impact mortality downwards by lowering the risk of accidents, homicides and exposure to other infectious diseases [3,4,10].…”

“…Pandemic excess death in Brazil's mortality has been studied by several authors, using different data sources, locations and periods [4,[10][11][12][13][14][15][16][17][18]. Santos et al [4] presented an account on excess deaths for the year 2020 by using the Negative Binomial regression model.…”