Excess deaths from all causes and by COVID-19 in Brazil in 2020
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Abstract
OBJECTIVE To estimate the 2020 all-cause and COVID-19 excess mortality according to sex, age, race/color, and state, and to compare mortality rates by selected causes with that of the five previous years in Brazil. METHODS Data from the Mortality Information System were used. Expected deaths for 2020 were estimated from 2015 to 2019 data using a negative binomial log-linear model. RESULTS Excess deaths in Brazil in 2020 amounted to 13.7%, and the ratio of excess deaths to COVID-19 deaths was 0.90. Reductions in deaths from cardiovascular diseases (CVD), respiratory diseases, and external causes, and an increase in ill-defined causes were all noted. Excess deaths were also found to be heterogeneous, being higher in the Northern, Center-Western, and Northeastern states. In some states, the number of COVID-19 deaths was lower than that of excess deaths, whereas the opposite occurred in others. Moreover, excess deaths were higher in men aged 20 to 59, and in black, yellow, or indigenous individuals. Meanwhile, excess mortality was lower in women, in individuals aged 80 years or older, and in whites. Additionally, deaths among those aged 0 to 19 were 7.2% lower than expected, with reduction in mortality from respiratory diseases and external causes. There was also a drop in mortality due to external causes in men and in those aged 20 to 39 years. Moreover, reductions in deaths from CVD and neoplasms were noted in some states and groups. CONCLUSION There is evidence of underreporting of COVID-19 deaths and of the possible impact of restrictive measures in the reduction of deaths from external causes and respiratory diseases. The impacts of COVID-19 on mortality were heterogeneous among the states and groups, revealing that regional, demographic, socioeconomic, and racial differences expose individuals in distinct ways to the risk of death from both COVID-19 and other causes.
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SciScore for 10.1101/2021.08.13.21261939: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Field Sample Permit: To estimate the Brazilian population by race/color in 2020, we used the median proportions of each category in the quarterly continuous national surveys taken via household sampling conducted over the past six years16 and multiplied them by the Brazilian population of each year.
IRB: The scripts can be accessed at the following website: https://github.com/aamouradasilva/excess_mortality.git. Ethical aspects: Since the present study used public and unidentified secondary data, approval from the Ethics Committee on Research in Human Beings was waived (Resolution no. 510/2016 of the National Health Council).Sex as a biological variable Deaths were then analyzed by … SciScore for 10.1101/2021.08.13.21261939: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Field Sample Permit: To estimate the Brazilian population by race/color in 2020, we used the median proportions of each category in the quarterly continuous national surveys taken via household sampling conducted over the past six years16 and multiplied them by the Brazilian population of each year.
IRB: The scripts can be accessed at the following website: https://github.com/aamouradasilva/excess_mortality.git. Ethical aspects: Since the present study used public and unidentified secondary data, approval from the Ethics Committee on Research in Human Beings was waived (Resolution no. 510/2016 of the National Health Council).Sex as a biological variable Deaths were then analyzed by epidemiological week and stratified according to sex (male and female), age groups (0-19, 20-39, 40-59, 60-79, and ≥ 80 years), race/color (white, black, brown and others), and state. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources All analyses in this study were performed in the R software (version 4.1.0) and RStudio (version 1.4.1717). RStudiosuggested: (RStudio, RRID:SCR_000432)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Despite the findings of this study, certain limitations were noted. For one, SIM data for the year 2020 were preliminary and may not represent all deaths that occurred in the period, as it is subject to corrections, especially in the underlying cause of death. However, these changes in data are expected to be minimal in the future since most of 2020 deaths have already been recorded. Nevertheless, we highlight some strengths in this study. First, the use of the SIM database made it possible to process detailed information on the basic cause of death and perform analysis by place of residence. Another strong point was the inclusion of deaths from external causes, which allowed the identification of an accentuated drop in violent deaths among men, those under 19 years of age, and those between 20 and 39 years of age. In conclusion, the impacts of COVID-19 on mortality were heterogeneous among Brazilian states and in sex, age, and race/color groups, as well as modified the mortality structure in 2020 relative to the previous five years. These different impacts of COVID-19 on mortality in certain states and groups revealed geographic, demographic, socioeconomic, and racial inequalities that expose individuals in different ways to the risk of infection and mortality from COVID-19 or other causes. Furthermore, the underreporting of COVID-19 deaths and the increase of mortality from ill-defined causes reflect the shortcomings of the death surveillance system, reinforcing the need fo...
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Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
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Results from scite Reference Check: We found no unreliable references.
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