Brazil BR: Cause of Death: by Injury: % of Total data was reported at 11.554 % in 2019. This records a decrease from the previous number of 12.454 % for 2015. Brazil BR: Cause of Death: by Injury: % of Total data is updated yearly, averaging 12.652 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 13.157 % in 2010 and a record low of 11.554 % in 2019. Brazil BR: Cause of Death: by Injury: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Injuries include unintentional and intentional injuries.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;

Brazil BR: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data was reported at 13.709 % in 2019. This records a decrease from the previous number of 14.176 % for 2015. Brazil BR: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data is updated yearly, averaging 14.000 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 18.009 % in 2000 and a record low of 13.709 % in 2019. Brazil BR: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Communicable diseases and maternal, prenatal and nutrition conditions include infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;

Brazil BR: Number of Deaths Ages 15-19 Years data was reported at 19,053.000 Person in 2019. This records a decrease from the previous number of 19,914.000 Person for 2018. Brazil BR: Number of Deaths Ages 15-19 Years data is updated yearly, averaging 19,139.500 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 21,757.000 Person in 2014 and a record low of 15,994.000 Person in 1991. Brazil BR: Number of Deaths Ages 15-19 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Health Statistics. Number of deaths of adolescents ages 15-19 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

Context

The registry offices in Brazil decided to make available some charts about the registered deaths in Brazil since the coronavirus pandemic. Through the requests to visualize these charts is possible to obtain the raw data and make our own analysis or visualizations.

https://transparencia.registrocivil.org.br/especial-covid

Content

This data contain the number of registered deaths by day, state, gender, age, skin color and cause of death (mainly focused in covid-19 and cardiovascular diseases)[1] occurred between 01-01-2019 and 15-09-2020.

This data was collected between 14/09/2020 and 16/09/2020 and can be updated, since it can take some days until the death is registered by the family, by the registry office and then provided in the platform.

The data was also translated to English[2].

[1] The cause of death was selected following several rules that are listed in the end of their website.

[2] The skin color terms were translated based in this article.

Acknowledgements

The data is available at https://transparencia.registrocivil.org.br/ and was obtained by doing some web scraping.

In 2023, 208 homicides of indigenous people were recorded in Brazil. Compared to the previous year, there was an increase of 28 homicides.

The novel Coronavirus disease (COVID-19) is responsible for thousands of deaths worldwide, especially in Brazil, currently one of the leading countries in number of infections and deaths. The beginning of the COVID-19 epidemic in Brazil is uncertain due to the low number of tests done in the country. The excess number of deaths can suggest the beginning of the pandemic in this context. In this article, we used an autoregressive integrated moving average (ARIMA) model to investigate possible excesses in the number of deaths processed by the São Paulo Autopsy Service according to different causes of deaths: all-cause, cardiovascular, and pulmonary causes. We calculated the expected number of deaths using data from 2019 to 2020 (n=17,011), and investigated different seasonal patterns using harmonic dynamic regression with Fourier terms with residuals modeled by an ARIMA method. We did not find any abnormalities in the predicted number of deaths and the real values in the first months of 2020. We found an increase in the number of deaths only by March 20, 2020, right after the first COVID-19 confirmed case in the city of São Paulo, which occurred on March 16, 2020.

ABSTRACT Objective: To estimate the reporting rates of coronavirus disease 2019 (COVID-19) cases for Brazil as a whole and states. Methods: We estimated the actual number of COVID-19 cases using the reported number of deaths in Brazil and each state, and the expected case-fatality ratio from the World Health Organization. Brazil’s expected case-fatality ratio was also adjusted by the population’s age pyramid. Therefore, the notification rate can be defined as the number of confirmed cases (notified by the Ministry of Health) divided by the number of expected cases (estimated from the number of deaths). Results: The reporting rate for COVID-19 in Brazil was estimated at 9.2% (95%CI 8.8% - 9.5%), with all the states presenting rates below 30%. São Paulo and Rio de Janeiro, the most populated states in Brazil, showed small reporting rates (8.9% and 7.2%, respectively). The highest reporting rate occurred in Roraima (31.7%) and the lowest in Paraiba (3.4%). Conclusion: The results indicated that the reporting of confirmed cases in Brazil is much lower as compared to other countries we analyzed. Therefore, decision-makers, including the government, fail to know the actual dimension of the pandemic, which may interfere with the determination of control measures.

Disclosure of information with far right's ideas, negationism of science and anti-vaccine attitude x Risk of COVID-19

The electoral preference by Bolsonaro in the first round of Brazil presidential election 2018 per state, shows a relation with the amount of deaths by Covid-19 per 100000, excess death per 100,000, increased P-score and intensity in reducing Brazilian population growth in the 1st quarter 2021

Content

In the period from January to April (1st Quadrimester Q1) from 2021 and 2019 per state (UF)

Main variables for each of the 27 Brazilian states and 4 States groups

1. The main population rates: - Number deaths, excess deaths, births, birth rate, mortality rate, vegetative growth, p-score, total population, population> 70A., Demographic density

2. The main rates of Pandemic by Coronavirus - Covid-19:

   • No. Total cases, cases Q1, Nº Total deaths, Nº Q1 deaths, Total deaths / 100000 hab, mortality rate, cases / 100000 hab

3. The main metrics of the 2018 presidential election:

   • Voters, voting paragraphs, nº of votes in Bolsonararo 1st turn, nº of abstinences.

Groups of Brazilian UFS (Federation States)

1. States that Bolsonaro received more than 50% of the votes in the 1st turn
2. States that Bolsonaro received less than 50% of the votes in the 1st turn and more than 50% in the 2nd turn
3. States that Bolsonaro received less than 50% of the votes in the 1st and 2nd shifts
4. Sum of the 27 Brazilian states

PT(BR) - version

Divulgação de informações com idéias da extrema direita, negacionismo da ciência e atitude anti-vacina x risco de Covid-19

A preferência eleitoral por Bolsonaro no 1º turno de 2018 por estado, mostra-se relacionada com a quantidade de mortes por COVID-19, excesso de mortes por 100000, aumento do P-score e intensidade na redução do crescimento populacional brasileiro no 1ºquadrimestre de 2021.

No período de Janeiro a Abril(1º Quadrimestre Q1) de 2021 e 2019 por estado (UF)

Principais variáveis

1. As principais taxas populacionais: - nº mortes, excesso de mortes, nº nascimentos, taxa de natalidade, taxa de mortalidade, crescimento vegetativo, P-score, população total, população > 70a., densidade demográfica

2. As principais taxas da pandemia por Coronavirus - COVID-19:

   • nº casos totais, nº casos Q1, nº mortes totais, nº mortes Q1, mortes totais/100000 hab, taxa de Mortalidade, casos/100000 hab

3. As principais métricas da eleição presidencial de 2018:

   • nº eleitores, nº votantes, nº de votos em Bolsonaro 1º turno, nº de abstinências.

Grupos de UFs (Estados da Federação)

1.Estados que Bolsonaro recebeu mais de 50% dos votos no 1º turno 2.Estados que Bolsonaro recebeu menos que 50% dos votos no 1º turno e mais de 50% no 2º turno 3.Estados que Bolsonaro recebeu menos que 50% dos votos no 1º e 2º turnos 4.Soma dos 27 Estados Brasileiros

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

Peru is the country with the highest mortality rate due to the coronavirus disease (COVID-19) in Latin America. As of November 13, 2023, the country registered over 672 deaths per 100,000 inhabitants. It was followed by Brazil, with around 331.5 fatal cases per 100,000 population. In total, over 1.76 million people have died due to COVID-19 in Latin America and the Caribbean.

Are these figures accurate? Although countries like Brazil already rank among the countries most affected by the coronavirus disease (COVID-19), there is still room to believe that the number of cases and deaths in Latin American countries are underreported. The main reason is the relatively low number of tests performed in the region. For example, Brazil, one of the most impacted countries in the world, has performed approximately 63.7 million tests as of December 22, 2022. This compared with over one billion tests performed in the United States, approximately 909 million tests completed in India, or around 522 million tests carried out in the United Kingdom.

Capacity to deal with the outbreak With the spread of the Omicron variant, the COVID-19 pandemic is putting health systems around the world under serious pressure. The lack of equipment to treat acute cases, for instance, is one of the problems affecting Latin American countries. In 2019, the number of ventilators in hospitals in the most affected countries ranged from 25.23 per 100,000 inhabitants in Brazil to 5.12 per 100,000 people in Peru.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

How did Brazil become a global epicenter of the outbreak? After seeming to ease, is the virus making a comeback?

A world leader in infections and deaths.

Latin America became an epicenter of the coronavirus pandemic in May, driven by Brazil’s ballooning caseload. Ten months after its first known case, Brazil has had more than 7.9 million cases and over 200,000 deaths.

In early June, Brazil began averaging about 1,000 deaths per day from Covid-19, joining the United States — and later India — as the countries with the world’s largest death tolls.

This dataset contains information about COVID-19 in Brazil extracted on the date 16/06/2021. It is the most updated dataset available about Covid in Brazil

Features:

🔍 date: date that the data was collected. format YYYY-MM-DD.
🔍 state: Abbreviation for States. Example: SP
🔍 city: Name of the city (if the value is NaN, they are referring to the State, not the city)
🔍 place_type: Can be City or State
🔍 order_for_place: Number that identifies the registering order for this location. The line that refers to the first log is going to be shown as 1, and the following information will start the count as an index.
🔍 is_last: Show if the line was the last update from that place, can be True or False
🔍 city_ibge_code: IBGE Code from the location
🔍confirmed: Number of confirmed cases.
🔍deaths: Number of deaths.
🔍estimated_population: Estimated population for this city/state in 2020. Data from IBGE
🔍estimated_population_2019: Estimated population for this city/state in 2019. Data from IBGE.
🔍confirmed_per_100k_inhabitants: Number of confirmed cases per 100.000 habitants (based on estimated_population).
🔍death_rate: Death rate (deaths / confirmed cases).

Acknowledgements

This dataset was downloaded from the URL bello. Thanks, Brasil.IO! Their main goal is to make all Brazilian data available to the public DATASET URL: https://brasil.io/dataset/covid19/files/ Cities map file https://geoftp.ibge.gov.br/organizacao_do_territorio/malhas_territoriais/malhas_municipais/municipio_2020/Brasil/BR/

Similar Datasets

COVID-19 - https://www.kaggle.com/rafaelherrero/covid19-brazil-full-cases-17062021 COVID-19 - https://www.kaggle.com/imdevskp/corona-virus-report MERS - https://www.kaggle.com/imdevskp/mers-outbreak-dataset-20122019 Ebola Western Africa 2014 Outbreak - https://www.kaggle.com/imdevskp/ebola-outbreak-20142016-complete-dataset H1N1 | Swine Flu 2009 Pandemic Dataset - https://www.kaggle.com/imdevskp/h1n1-swine-flu-2009-pandemic-dataset SARS 2003 Pandemic - https://www.kaggle.com/imdevskp/sars-outbreak-2003-complete-dataset HIV AIDS - https://www.kaggle.com/imdevskp/hiv-aids-dataset

WHO: COVID-2019: Number of Patients: Death: New: Brazil data was reported at 0.000 Person in 24 Dec 2023. This stayed constant from the previous number of 0.000 Person for 23 Dec 2023. WHO: COVID-2019: Number of Patients: Death: New: Brazil data is updated daily, averaging 204.000 Person from Feb 2020 (Median) to 24 Dec 2023, with 1398 observations. The data reached an all-time high of 4,249.000 Person in 10 Apr 2021 and a record low of 0.000 Person in 24 Dec 2023. WHO: COVID-2019: Number of Patients: Death: New: Brazil data remains active status in CEIC and is reported by World Health Organization. The data is categorized under High Frequency Database’s Disease Outbreaks – Table WHO.D002: World Health Organization: Coronavirus Disease 2019 (COVID-2019): by Country and Region (Discontinued).

In 2020, the south region of Brazil had the highest number of deaths due to Dengue fever, with *** confirmed fatal cases. The Brazilian southeast followed with *** confirmed deaths that year. This region was also the most affected in 2019, when the number of deaths due to Dengue fever amounted to *** fatal cases.

In the second half of the past decade, the number of deaths attributed to ambient particulate matter air pollution (PM2.5) in Brazil increased continuously. In 2019, approximately **** thousand deaths were attributed to this type or air pollution, up from ** thousand deaths in 2015. Brazil was the Latin American country with the largest number of deaths due to air pollution in 2019.

Brazil BR: Mortality Caused by Road Traffic Injury: per 100,000 People data was reported at 16.000 Number in 2019. This records a decrease from the previous number of 17.100 Number for 2018. Brazil BR: Mortality Caused by Road Traffic Injury: per 100,000 People data is updated yearly, averaging 22.000 Number from Dec 2000 (Median) to 2019, with 20 observations. The data reached an all-time high of 24.800 Number in 2012 and a record low of 16.000 Number in 2019. Brazil BR: Mortality Caused by Road Traffic Injury: per 100,000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Social: Health Statistics. Mortality caused by road traffic injury is estimated road traffic fatal injury deaths per 100,000 population.;World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).;Weighted average;This is the Sustainable Development Goal indicator 3.6.1 [https://unstats.un.org/sdgs/metadata/].

WHO: COVID-2019: No of Patients: Death: To-Date: Brazil data was reported at 702,116.000 Person in 24 Dec 2023. This stayed constant from the previous number of 702,116.000 Person for 23 Dec 2023. WHO: COVID-2019: No of Patients: Death: To-Date: Brazil data is updated daily, averaging 622,949.000 Person from Feb 2020 (Median) to 24 Dec 2023, with 1398 observations. The data reached an all-time high of 702,116.000 Person in 24 Dec 2023 and a record low of 0.000 Person in 18 Mar 2020. WHO: COVID-2019: No of Patients: Death: To-Date: Brazil data remains active status in CEIC and is reported by World Health Organization. The data is categorized under High Frequency Database’s Disease Outbreaks – Table WHO.D002: World Health Organization: Coronavirus Disease 2019 (COVID-2019): by Country and Region (Discontinued).

Brazil is the Latin American and Caribbean country with the highest number of deaths that can be attributed to household air pollution from fossil fuels. In 2019, approximately ****** deaths were caused by this type of household air pollution in Brazil. Haiti was the second country in the region with the highest number of estimated casualties, with ******, followed by Mexico with almost 10,000.

Abstract Background Chronic noncommunicable diseases (CNCDs) caused more than 734,000 deaths (55% of all deaths) in Brazil in 2019, with an important socioeconomic impact. Objectives To analyze the mortality rates from CNCDs in Brazil from 1980 to 2019 and their association with socioeconomic indicators. Method This was a descriptive, time-series study of deaths from CNCDs in Brazil from 1980 to 2019. Data on the annual frequencies of deaths and on population were obtained from the Department of Informatics of the Brazilian Unified Health System. Crude and standardized mortality rates per 100,000 inhabitants were estimated using the direct method (Brazilian population in 2000). The quartiles of each CNCD were calculated, where a quartile change, due to an increase in mortality rate, was represented by a chromatic gradient. The Municipal Human Development Index (MHDI) of each Brazilian federative unit was extracted from the Atlas Brasil website and correlated with the rates of CNCD mortality. Results There was a reduction in mortality rates due to diseases of the circulatory system during the period, except in the Northeast Region. There was also an increase in mortality from neoplasia and diabetes, while the rates of chronic respiratory diseases showed little variation. There was an inverse correlation between the federative units with greater reduction in CNCD mortality rates and the MHDI. Conclusions The observed decrease in mortality due to diseases of the circulatory system may reflect an improvement in socioeconomic indicators in Brazil during the period. The increase in mortality rates due to neoplasms is probably related to the aging of the population. The higher mortality rates of diabetes seem to be associated with an increase in the prevalence of obesity in Brazilian women.

Time series data for the statistic Cause of death, by non-communicable diseases, ages 15-59 (% of population ages 15-59) and country Brazil. Indicator Definition:Number of deaths ages 15-59 due to non-communicable diseases divided by number of all deaths ages 15-59 expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.

ABSTRACT Background: Syphilis is a chronic infectious disease that has created challenging situations for humanity for centuries. Transmission can occur sexually or vertically, with great repercussions on populations, particularly among women and children. The present study presents information on the main burden imposed by syphilis generated by the Global Burden of Disease (GBD) Study 2019 for Brazil and its 27 federated units. Methods: We described the metrics of incidence, deaths, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs), standardized by age and per 100,000 inhabitants, from 1990 to 2019, and we compared the disease burden between the years 1990 and 2019. Results: In Brazil, the disease burden increased between 2005 and 2019 for all metrics. Although a higher incidence of syphilis was found among women in 2019, DALYs [YLLs (males: 15.9%; females: 21.8%), YLDs (males: 25.0%; females: 50.0%), and DALYs (males: 16.2%; females: 22.4%)] were higher among men. In 2019, the highest DALY rate per 100,000 inhabitants was observed in individuals aged above 50 years. The State of Maranhão presented the highest values of DALYs {1990: 165.2 [95% uncertainty interval (UI) 96.2-264.4]; 2005: 43.8 [95% UI 30.3-62.4]; 2019: 29.1 [95% UI 19.8-41.1]} per 100,000 inhabitants in the three years analyzed. Conclusions: The burden of syphilis has increased in recent years. Men presented higher DALYs, although the incidence of the disease was higher in women. Syphilis affects a large number of people across all age groups, causing different degrees of disability and premature death (DALYs).