In 2019, the leading causes of death worldwide were ischemic heart disease, stroke, and chronic obstructive pulmonary disease (COPD). That year, ischemic heart disease and stroke accounted for a combined ** percent of all deaths worldwide. Although the leading causes of death worldwide vary by region and country, heart disease is a consistent leading cause of death regardless of income, development, size, or location. Heart disease In 2019, around **** million people worldwide died from ischemic heart disease. In comparison, around **** million people died from lung cancer that year, while *** million died from diabetes. The countries with the highest rates of death due to heart attack and other ischemic heart diseases are Lithuania, Russia, and Slovakia. Although some risk factors for heart disease, such as age and genetics, are unmodifiable, the likelihood of developing heart disease can be greatly reduced through a healthy lifestyle. The biggest modifiable risk factors for heart disease include smoking, an unhealthy diet, being overweight, and a lack of exercise. In 2019, it was estimated that around *** million deaths worldwide due to ischemic heart disease could be attributed to smoking. The leading causes of death in the United States Just as it is the leading cause of death worldwide, heart disease is also the leading cause of death in the United States. In 2023, heart disease accounted for ** percent of all deaths in the United States. Cancer was the second leading cause of death in the U.S. that year, followed by accidents. As of 2023, the odds that a person in the United States will die from heart disease is * in *. However, rates of death due to heart disease have actually declined in the U.S. over the past couple decades. From 2000 to 2022, there was a *** percent decline in heart disease deaths. On the other hand, deaths from Alzheimer’s disease saw an increase of *** percent over this period. Alzheimer’s disease is currently the sixth leading cause of death in the United States, accounting for **** deaths per 100,000 population in 2023.

In 2019, the leading causes of death globally included ischemic heart disease, stroke and chronic obstructive pulmonary disease (COPD). There were **** million deaths from ischemic heart disease at that time and about **** million deaths caused by stroke. In recent history, increases in life expectancy, increases in population and better standards of living have changed the leading causes of death over time. Non-Communicable Disease Deaths The number of deaths due to non-communicable diseases has remained relatively stable in recent years. A large majority of non-communicable or chronic disease deaths globally are caused by cardiovascular diseases, followed by cancer. Various lifestyle choices cause or exacerbate many of these chronic diseases. Drinking, smoking and lack of exercise can contribute to higher rates of non-communicable diseases and early death. It is estimated that the relative risk of death before the age of 65 was ** times greater among those that smoked and never quit. Infectious Disease Deaths Trends indicate that the number of deaths due to infectious diseases have decreased in recent years. However, infectious diseases still disproportionately impact low- and middle-income countries. In 2021, tuberculosis, malaria and HIV/AIDS were still among the leading causes of death in low-income countries. However, the leading causes of death in upper income countries are almost exclusively non-communicable, chronic conditions.

As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had spread to almost every country in the world, and more than 6.86 million people had died after contracting the respiratory virus. Over 1.16 million of these deaths occurred in the United States.

Waves of infections Almost every country and territory worldwide have been affected by the COVID-19 disease. At the end of 2021 the virus was once again circulating at very high rates, even in countries with relatively high vaccination rates such as the United States and Germany. As rates of new infections increased, some countries in Europe, like Germany and Austria, tightened restrictions once again, specifically targeting those who were not yet vaccinated. However, by spring 2022, rates of new infections had decreased in many countries and restrictions were once again lifted.

What are the symptoms of the virus? It can take up to 14 days for symptoms of the illness to start being noticed. The most commonly reported symptoms are a fever and a dry cough, leading to shortness of breath. The early symptoms are similar to other common viruses such as the common cold and flu. These illnesses spread more during cold months, but there is no conclusive evidence to suggest that temperature impacts the spread of the SARS-CoV-2 virus. Medical advice should be sought if you are experiencing any of these symptoms.

The World Health Organization reported 6932591 Coronavirus Deaths since the epidemic began. In addition, countries reported 766440796 Coronavirus Cases. This dataset provides - World Coronavirus Deaths- actual values, historical data, forecast, chart, statistics, economic calendar and news.

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.

In 2019, around 32.8 percent of all deaths globally were caused by cardiovascular diseases and almost 18 percent were caused by cancer. This statistic shows the distribution of causes of death worldwide in 2019.

This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool Data includes: * Date on which the death occurred * Age group * 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster ##Additional notes As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm. As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category. On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON. “Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.

2019 Novel Coronavirus COVID-19 (2019-nCoV) Visual Dashboard and Map:
https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

• Confirmed Cases by Country/Region/Sovereignty
• Confirmed Cases by Province/State/Dependency
• Deaths
• Recovered

Downloadable data:
https://github.com/CSSEGISandData/COVID-19

Additional Information about the Visual Dashboard:
https://systems.jhu.edu/research/public-health/ncov

The COVID-19 pandemic increased the global death rate, reaching *** in 2021, but had little to no significant impact on birth rates, causing population growth to dip slightly. On a global level, population growth is determined by the difference between the birth and death rates, known as the rate of natural change. On a national or regional level, migration also affects population change. Ongoing trends Since the middle of the 20th century, the global birth rate has been well above the global death rate; however, the gap between these figures has grown closer in recent years. The death rate is projected to overtake the birth rate in the 2080s, which means that the world's population will then go into decline. In the future, death rates will increase due to ageing populations across the world and a plateau in life expectancy. Why does this change? There are many reasons for the decline in death and birth rates in recent decades. Falling death rates have been driven by a reduction in infant and child mortality, as well as increased life expectancy. Falling birth rates were also driven by the reduction in child mortality, whereby mothers would have fewer children as survival rates rose - other factors include the drop in child marriage, improved contraception access and efficacy, and women choosing to have children later in life.

Algeria DZ: Number of Deaths Ages 20-24 Years data was reported at 2,017.000 Person in 2019. This records a decrease from the previous number of 2,148.000 Person for 2018. Algeria DZ: Number of Deaths Ages 20-24 Years data is updated yearly, averaging 2,899.500 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 4,526.000 Person in 1998 and a record low of 2,017.000 Person in 2019. Algeria DZ: Number of Deaths Ages 20-24 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Algeria – Table DZ.World Bank.WDI: Health Statistics. Number of deaths of youths ages 20-24 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.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

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COVID-19 Worldwide Daily Data

Daily global COVID-19 data for all countries, provided by Johns Hopkins University (JHU) Center for Systems Science and Engineering (CSSE). If you want to use the update version of the data, you can use our daily updated data with the help of api key by entering it via Altadata.

Overview

In this data product, you may find the latest and historical global daily data on the COVID-19 pandemic for all countries.

The COVID‑19 pandemic, also known as the coronavirus pandemic, is an ongoing global pandemic of coronavirus disease 2019 (COVID‑19), caused by severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2). The outbreak was first identified in December 2019 in Wuhan, China. The World Health Organization declared the outbreak a Public Health Emergency of International Concern on 30 January 2020 and a pandemic on 11 March. As of 12 August 2020, more than 20.2 million cases of COVID‑19 have been reported in more than 188 countries and territories, resulting in more than 741,000 deaths; more than 12.5 million people have recovered.

The Johns Hopkins Coronavirus Resource Center is a continuously updated source of COVID-19 data and expert guidance. They aggregate and analyze the best data available on COVID-19 - including cases, as well as testing, contact tracing and vaccine efforts - to help the public, policymakers and healthcare professionals worldwide respond to the pandemic.

Methodology

• Cases and Death counts include confirmed and probable (where reported)
• Recovered cases are estimates based on local media reports, and state and local reporting when available, and therefore may be substantially lower than the true number. US state-level recovered cases are from COVID Tracking Project.
• Active cases = total cases - total recovered - total deaths
• Incidence Rate = cases per 100,000 persons
• Case-Fatality Ratio (%) = Number recorded deaths / Number cases
• Country Population represents 2019 projections by UN Population Division, integrated to the JHU CSSE's COVID-19 data by ALTADATA

Data Source

• Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE)
• United Nations Population Division

Related Data Products

• COVID-19 US Daily Data
• OECD, EU28, G20 Life Expectancy and Mortality Indicators

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Data Dictionary

• Reported Date (reported_date) : Covid-19 Report Date
• Country_Region (country_region) : Country, region or sovereignty name
• Population (population) : Country populations as per United Nations Population Division
• Confirmed Case (confirmed) : Confirmed cases include presumptive positive cases and probable cases
• Active cases (active) : Active cases = total confirmed - total recovered - total deaths
• Deaths (deaths) : Death cases counts
• Recovered (recovered) : Recovered cases counts
• Mortality Rate (mortality_rate) : Number of recorded deaths * 100 / Number of confirmed cases
• Incident Rate (incident_rate) : Confirmed cases per 100,000 persons

Germany DE: Number of Deaths Ages 20-24 Years data was reported at 1,391.000 Person in 2019. This records a decrease from the previous number of 1,398.000 Person for 2018. Germany DE: Number of Deaths Ages 20-24 Years data is updated yearly, averaging 2,215.500 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 4,715.000 Person in 1990 and a record low of 1,391.000 Person in 2019. Germany DE: Number of Deaths Ages 20-24 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Health Statistics. Number of deaths of youths ages 20-24 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.

Predictors of death within 30 Days after COVID-19 test.

United States Excess Deaths excl COVID: Predicted: No. of Deaths: Utah data was reported at 406.000 Number in 16 Sep 2023. This records an increase from the previous number of 399.000 Number for 09 Sep 2023. United States Excess Deaths excl COVID: Predicted: No. of Deaths: Utah data is updated weekly, averaging 386.000 Number from Jan 2017 (Median) to 16 Sep 2023, with 350 observations. The data reached an all-time high of 482.000 Number in 17 Dec 2022 and a record low of 317.000 Number in 10 Aug 2019. United States Excess Deaths excl COVID: Predicted: No. of Deaths: Utah data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under Global Database’s United States – Table US.G012: Number of Excess Deaths: by States: All Causes excluding COVID-19: Predicted (Discontinued).

United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Maine data was reported at 313.000 Number in 08 Jan 2022. This stayed constant from the previous number of 313.000 Number for 01 Jan 2022. United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Maine data is updated weekly, averaging 291.500 Number from Jan 2017 to 08 Jan 2022, with 262 observations. The data reached an all-time high of 317.000 Number in 16 Mar 2019 and a record low of 266.000 Number in 18 Aug 2018. United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Maine data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under Global Database’s United States – Table US.G014: Number of Excess Deaths: by States: All Causes excluding COVID-19: Predicted.

Data Overview

This repository contains spatiotemporal data from many official sources for 2019-Novel Coronavirus beginning 2019 in Hubei, China ("nCoV_2019") You may not use this data for commercial purposes. If there is a need for commercial use of the data, please contact Ginkgo Biosecurity, the biosecurity and public health unit of Ginkgo Bioworks at help-epi-modeling@ginkgobioworks.com to obtain a commercial use license.

The incidence data are in a CSV file format. One row in an incidence file contains a piece of epidemiological data extracted from the specified source.

The file contains data from multiple sources at multiple spatial resolutions in cumulative and non-cumulative formats by confirmation status. To select a single time series of case or death data, filter the incidence dataset by source, spatial resolution, location, confirmation status, and cumulative flag.

Data are collected, structured, and validated by Ginkgo's digital surveillance experts. The data structuring process is designed to produce the most reliable estimates of reported cases and deaths over space and time. The data are cleaned and provided in a uniform format such that information can be compared across multiple sources. Data are collected at the time of publication in the highest geographic and temporal resolutions available in the original report.

This repository is intended to provide a single access point for data from a wide range of data sources. Data will be updated periodically with the latest epidemiological data. Ginkgo Biosecurity maintains a database of epidemiological information for over three thousand high-priority infectious disease events (please note: this database was previously maintained by Metabiota; the team responsible joined Ginkgo Biosecurity in August 2022. When using the database, please cite Ginkgo Biosecurity and refer to this repository). Please contact us (help-epi-modeling@ginkgobioworks.com) if you are interested in licensing the complete dataset.

Cumulative vs. Non-Cumulative Incidence

Reporting sources provide either cumulative incidence, non-cumulative incidence, or both. If the source only provides a non-cumulative incidence value, the cumulative values are inferred using prior reports from the same source. Use the CUMULATIVE FLAG variable to subset the data to cumulative (TRUE) or non-cumulative (FALSE) values.

Case Confirmation Status

The incidence datasets include the confirmation status of cases and deaths when this information is provided by the reporting source. Subset the data by the CONFIRMATION_STATUS variable to either TOTAL, CONFIRMED, SUSPECTED, or PROBABLE to obtain the data of your choice.

Total incidence values include confirmed, suspected, and probable incidence values. If a source only provides suspected, probable, or confirmed incidence, the total incidence is inferred to be the sum of the provided values. If the report does not specify confirmation status, the value is included in the "total" confirmation status value.

The data provided under the "Multisource Fusion" often does not include suspected incidence due to inconsistencies in reporting cases and deaths with this confirmation status.

Outcome - Cases vs. Deaths

The incidence datasets include cases and deaths. Subset the data to either CASE or DEATH using the OUTCOME variable. It should be noted that deaths are included in case counts.

Spatial Resolution

Data are provided at multiple spatial resolutions. Data should be subset to a single spatial resolution of interest using the SPATIAL_RESOLUTION variable.

Information is included at the finest spatial resolution provided to the original epidemic report. We also aggregate incidence to coarser geographic resolutions. For example, if a source only provides data at the province-level, then province-level data are included in the dataset as well as country-level totals. Users should avoid summing all cases or deaths in a given country for a given date without specifying the SPATIAL_RESOLUTION value. For example, subset the data to SPATIAL_RESOLUTION equal to "AL0” in order to view only the aggregated country level data.

There are differences in administrative division naming practices by country. Administrative levels in this dataset are defined using the Google Geolocation API (https://developers.google.com/maps/documentation/geolocation/). For example, the data for the 2019-nCoV from one source provides information for the city of Beijing, which Google Geolocations indicates is a "locality.” Beijing is also the name of the municipality where the city Beijing is located. Thus, the 2019-nCoV dataset includes rows of data for both the city Beijing, as well as the municipality of the same name. If additional cities in the Beijing municipality reported data, those data would be aggregated with the city Beijing data to form the municipality Beijing data.

Sources

Data sources in this repository were selected to provide comprehensive spatiotemporal data for each outbreak. Data from a specific source can be selected using the SOURCE variable.

In addition to the original reporting sources, Ginkgo Biosecurity compiles multiple sources to generate the most comprehensive view of an outbreak. This compilation is stored in the database under the source name "Multisource Fusion". The purpose of generating this new view of the outbreak is to provide the most accurate and precise spatiotemporal data for the outbreak. At this time, Ginkgo Biosecurity does not incorporate unofficial - including media - sources into the "Multisource Fusion" dataset.

Quality Assurance

Data are collected by a team of digital surveillance experts and undergo many quality assurance tests. After data are collected, they are independently verified by at least one additional analyst. The data also pass an automated validation program to ensure data consistency and integrity.

NonCommercial Use License

• Creative Commons License Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)

• This is a human-readable summary of the Legal Code.

• You are free:

  to Share — to copy, distribute and transmit the work to Remix — to adapt the work

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  Attribution — You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work).

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• With the understanding that:

  Waiver — Any of the above conditions can be waived if you get permission from the copyright holder.

  Public Domain — Where the work or any of its elements is in the public domain under applicable law, that status is in no way affected by the license.

  Other Rights — In no way are any of the following rights affected by the license: Your fair dealing or fair use rights, or other applicable copyright exceptions and limitations; The author's moral rights; Rights other persons may have either in the work itself or in how the work is used, such as publicity or privacy rights. Notice — For any reuse or distribution, you must make clear to others the license terms of this work. The best way to do this is with a link to this web page.

For details and the full license text, see http://creativecommons.org/licenses/by-nc-sa/3.0/

Liability

The information is provided “AS IS” and Concentric makes no representations or warranties, express or implied, of any type whatsoever including, without limitation, title, noninfringement, accuracy, completeness, merchantability, or fitness for any particular purpose. Use of proprietary information shall be at the user’s own risk, and Concentric assumes no liability or obligation to the user as a result of use.

Ginkgo Biosecurity shall in no event be liable for any decision taken by the user based on the data made available. Under no circumstances, shall Ginkgo Biosecurity be liable for any damages (whatsoever) arising out of the use or inability to use the database. The entire risk arising out of the use of the database remains with the user.

According to the findings of a survey by IPSOS, worldwide people generally underestimate the proportion of deaths from cardiovascular diseases and cancer, two of the leading causes of death worldwide. It was found that on average respondents thought cardiovascular diseases accounted for just 11 percent of deaths worldwide, when in reality cardiovascular diseases account for 32 percent of deaths. This statistic shows the actual vs public estimates for causes of death worldwide as of 2019.

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

Germany DE: Cause of Death: by Injury: % of Total data was reported at 4.642 % in 2019. This records an increase from the previous number of 3.947 % for 2015. Germany DE: Cause of Death: by Injury: % of Total data is updated yearly, averaging 4.032 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 4.642 % in 2019 and a record low of 3.868 % in 2010. Germany DE: 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 Germany – Table DE.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;