COVID-19 rate of death, or the known deaths divided by confirmed cases, was over ten percent in Yemen, the only country that has 1,000 or more cases. This according to a calculation that combines coronavirus stats on both deaths and registered cases for 221 different countries. Note that death rates are not the same as the chance of dying from an infection or the number of deaths based on an at-risk population. By April 26, 2022, the virus had infected over 510.2 million people worldwide, and led to a loss of 6.2 million. 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.

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. Note that Statista aims to also provide domestic source material for a more complete picture, and not to just look at one particular source. Examples are these statistics on the confirmed coronavirus cases in Russia or the COVID-19 cases in Italy, both of which are from domestic sources. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

A word on the flaws of numbers like this

People are right to ask whether these numbers are at all representative or not for several reasons. First, countries worldwide decide differently on who gets tested for the virus, meaning that comparing case numbers or death rates could to some extent be misleading. Germany, for example, started testing relatively early once the country’s first case was confirmed in Bavaria in January 2020, whereas Italy tests for the coronavirus postmortem. Second, not all people go to see (or can see, due to testing capacity) a doctor when they have mild symptoms. Countries like Norway and the Netherlands, for example, recommend people with non-severe symptoms to just stay at home. This means not all cases are known all the time, which could significantly alter the death rate as it is presented here. Third and finally, numbers like this change very frequently depending on how the pandemic spreads or the national healthcare capacity. It is therefore recommended to look at other (freely accessible) content that dives more into specifics, such as the coronavirus testing capacity in India or the number of hospital beds in the UK. Only with additional pieces of information can you get the full picture, something that this statistic in its current state simply cannot provide.

The average for 2022 based on 196 countries was 8.24 deaths per 1000 people. The highest value was in the Central African Republic: 55.13 deaths per 1000 people and the lowest value was in Qatar: 0.93 deaths per 1000 people. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

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.

As of 2023, the countries with the highest death rates worldwide were Monaco, Bulgaria, and Latvia. In these countries, there were ** to ** deaths per 1,000 people. The country with the lowest death rate is Qatar, where there is just *** death per 1,000 people. Leading causes of death The leading causes of death worldwide are, by far, cardiovascular diseases, accounting for ** percent of all deaths in 2021. That year, there were **** million deaths worldwide from ischaemic heart disease and **** million from stroke. Interestingly, a worldwide survey from that year found that people greatly underestimate the proportion of deaths caused by cardiovascular disease, but overestimate the proportion of deaths caused by suicide, interpersonal violence, and substance use disorders. Death in the United States In 2023, there were around **** million deaths in the United States. The leading causes of death in the United States are currently heart disease and cancer, accounting for a combined ** percent of all deaths in 2023. Lung and bronchus cancer is the deadliest form of cancer worldwide, as well as in the United States. In the U.S. this form of cancer is predicted to cause around ****** deaths among men alone in the year 2025. Prostate cancer is the second-deadliest cancer for men in the U.S. while breast cancer is the second deadliest for women. In 2023, the tenth leading cause of death in the United States was COVID-19. Deaths due to COVID-19 resulted in a significant rise in the total number of deaths in the U.S. in 2020 and 2021 compared to 2019, and it was the third leading cause of death in the U.S. during those years.

The statistic shows the death rate in the MENA countries in 2023. MENA stands for Middle East and North Africa. In 2023, Libya had the highest death rate in the region, with **** deaths per 1,000 inhabitants. On the other hand, the United Arab Emirates and Qatar had the lowest death rate in the region as of the same period.

In 2020, the U.S. had the highest COVID-19 pandemic-related excess mortality rate among non-elderly people compared to other peer countries. “Excess deaths” represent the number of deaths beyond what is expected in a typical year. This measure illustrates the mortality directly or indirectly associated with the COVID-19 pandemic. This statistic presents the COVID-19 pandemic-related excess mortality rate in the U.S. and select countries in 2020, by age group (per 100,000 people in age group).

This dataset provides comprehensive information on maternal mortality rates across different countries and regions from 1751 to 2020. It offers researchers, policymakers, and health professionals a valuable resource for analyzing long-term trends in maternal health, evaluating the effectiveness of healthcare interventions, and identifying areas for improvement in maternal care worldwide.

Key features of this dataset include:

• Historical data spanning over 250 years
• Coverage of multiple countries and regions
• Annual maternal mortality ratio estimates
• Consistent methodology for cross-country comparisons
• Data from reputable international organizations

This dataset is ideal for:

• Analyzing long-term trends in maternal health
• Comparing maternal mortality rates across different countries and regions
• Evaluating the impact of healthcare policies and interventions
• Developing predictive models for maternal health outcomes
• Creating visualizations to communicate global maternal health trends

Whether you're a public health researcher, data scientist, or policymaker, this dataset offers crucial insights into the progress and challenges in reducing maternal mortality worldwide.

The monthly excess mortality indicator is based on the exceptional data collection on weekly deaths that Eurostat and the National Statistical Institutes set up, in April 2020, in order to support the policy and research efforts related to the COVID-19 pandemic. With that data collection, Eurostat's target was to provide quickly statistics assessing the changing situation of the total number of deaths on a weekly basis, from early 2020 onwards.

The National Statistical Institutes transmit available data on total weekly deaths, classified by sex, 5-year age groups and NUTS3 regions (NUTS2021) over the last 20 years, on a voluntary basis. The resulting online tables, and complementary metadata, are available in the folder Weekly deaths - special data collection (demomwk).

Starting in 2025, the weekly deaths data collected on a quarterly basis. The database updated on the 16th of June 2025 (1st quarter), on the 16 th of September 2025 (2nd quarter), and next update will be in mid-December 2025 (3rd quarter), and mid-February 2026 (4th quarter).

In December 2020, Eurostat released the European Recovery Statistical Dashboard containing also indicators tracking economic and social developments, including health. In this context, “excess mortality” offers elements for monitoring and further analysing direct and indirect effects of the COVID-19 pandemic.

The monthly excess mortality indicator draws attention to the magnitude of the crisis by providing a comprehensive comparison of additional deaths amongst the European countries and allowing for further analysis of its causes. The number of deaths from all causes is compared with the expected number of deaths during a certain period in the past (baseline period, 2016-2019).

The reasons that excess mortality may vary according to different phenomena are that the indicator is comparing the total number of deaths from all causes with the expected number of deaths during a certain period in the past (baseline). While a substantial increase largely coincides with a COVID-19 outbreak in each country, the indicator does not make a distinction between causes of death. Similarly, it does not take into account changes over time and differences between countries in terms of the size and age/sex structure of the population Statistics on excess deaths provide information about the burden of mortality potentially related to the COVID-19 pandemic, thereby covering not only deaths that are directly attributed to the virus but also those indirectly related to or even due to another reason. For example, In July 2022, several countries recorded unusually high numbers of excess deaths compared to the same month of 2020 and 2021, a situation probably connected not only to COVID-19 but also to the heatwaves that affected parts of Europe during the reference period.

In addition to confirmed deaths, excess mortality captures COVID-19 deaths that were not correctly diagnosed and reported, as well as deaths from other causes that may be attributed to the overall crisis. It also accounts for the partial absence of deaths from other causes like accidents that did not occur due, for example, to the limitations in commuting or travel during the lockdown periods.

It is estimated that from 2020 to 2021, the mean rate of excess deaths associated with the COVID-19 pandemic from all-causes was highest in Peru. In 2020-2021, there were around 437 excess deaths due to the COVID-19 pandemic per 100,000 population in Peru. This statistic shows the mean number of excess deaths associated with the COVID-19 pandemic from all-causes in 2020-2021 in select countries worldwide, per 100,000 population.

Objective: This study examined cumulative excess mortality in European countries in the year of the Covid-19 pandemic and characterized the dynamics of the pandemic in different countries, focusing on Hungary and the Central and Eastern European region.Methods: Age-standardized cumulative excess mortality was calculated based on weekly mortality data from the EUROSTAT database, and was compared between 2020 and the 2016–2019 reference period in European countries.Results: Cumulate weekly excess mortality in Hungary was in the negative range until week 44. By week 52, it reached 9,998 excess deaths, corresponding to 7.73% cumulative excess mortality vs. 2016–2019 (p-value = 0.030 vs. 2016–2019). In Q1, only Spain and Italy reported excess mortality compared to the reference period. Significant increases in excess mortality were detected between weeks 13 and 26 in Spain, United Kingdom, Belgium, Netherland and Sweden. Romania and Portugal showed the largest increases in age-standardized cumulative excess mortality in the Q3. The majority of Central and Eastern European countries experienced an outstandingly high impact of the pandemic in Q4 in terms of excess deaths. Hungary ranked 11th in cumulative excess mortality based on the latest available data of from the EUROSTAT database.Conclusion: Hungary experienced a mortality deficit in the first half of 2020 compared to previous years, which was followed by an increase in mortality during the second wave of the COVID-19 pandemic, reaching 7.7% cumulative excess mortality by the end of 2020. The excess was lower than in neighboring countries with similar dynamics of the pandemic.

IntroductionBetween 2021 and 2023, a project was funded in order to explore the mortality burden (YLL–Years of Life Lost, excess mortality) of COVID-19 in Southern and Eastern Europe, and Central Asia.MethodsFor each national or sub-national region, data on COVID-19 deaths and population data were collected for the period March 2020 to December 2021. Unstandardized and age-standardised YLL rates were calculated according to standard burden of disease methodology. In addition, all-cause mortality data for the period 2015–2019 were collected and used as a baseline to estimate excess mortality in each national or sub-national region in the years 2020 and 2021.ResultsOn average, 15–30 years of life were lost per death in the various countries and regions. Generally, YLL rates per 100,000 were higher in countries and regions in Southern and Eastern Europe compared to Central Asia. However, there were differences in how countries and regions defined and counted COVID-19 deaths. In most countries and sub-national regions, YLL rates per 100,000 (both age-standardised and unstandardized) were higher in 2021 compared to 2020, and higher amongst men compared to women. Some countries showed high excess mortality rates, suggesting under-diagnosis or under-reporting of COVID-19 deaths, and/or relatively large numbers of deaths due to indirect effects of the pandemic.ConclusionOur results suggest that the COVID-19 mortality burden was greater in many countries and regions in Southern and Eastern Europe compared to Central Asia. However, heterogeneity in the data (differences in the definitions and counting of COVID-19 deaths) may have influenced our results. Understanding possible reasons for the differences was difficult, as many factors are likely to play a role (e.g., differences in the extent of public health and social measures to control the spread of COVID-19, differences in testing strategies and/or vaccination rates). Future cross-country analyses should try to develop structured approaches in an attempt to understand the relative importance of such factors. Furthermore, in order to improve the robustness and comparability of burden of disease indicators, efforts should be made to harmonise case definitions and reporting for COVID-19 deaths across countries.

For most of human history, pregnancy and childbirth were very risky; mothers would die in at least 1 in 100 pregnancies.1

Since the average woman would have at least four or five children, the lifetime risk of dying from maternal causes would be at least 1 in 25.2 This was true everywhere.

Thankfully, that’s no longer the case. We’ve made huge strides in not only protecting infants in childbirth and the early stages of their lives, but we’ve also made it much safer for women.

But we’re not done yet. There are still huge inequalities in the risks of pregnancy across the world. Pregnant women in countries like Sierra Leone and Kenya are around 100 times more likely to die during pregnancy or childbirth than those in countries like Norway, Sweden, or Germany.3 But it doesn’t have to be this way. We could save hundreds of thousands of lives a year by closing these gaps.

I’ve compared three scenarios in the chart below to clarify these points.

First, we can see that the situation today is awful. 286,000 women died from maternal causes in 2020.4 That’s 784 deaths per day on average, or one mother dying every two minutes.5

Second, we can consider the very high maternal mortality rates of the past. Particularly good long-term data is available for Finland or Sweden, which shows that in 1750, around 900 women died per 100,000 live births.6 Since there were 135 million births in 2020, I calculate that 1.2 million women would have died from maternal causes that year if these rates hadn’t improved.7 Things are much, much better than they used to be.

Finally, things can still be much better. We know this because some countries have maternal mortality rates that are far lower than the global average. And they all used to be in a similar position to the worst-off countries today. In Europe, the maternal mortality rate was 8 deaths per 100,000 live births in 2020. That’s around 25 times lower than the global average.8 If all countries could achieve the same outcomes as Europe, 11,000 women would have died from maternal causes in 2020 — a small fraction of the 286,000 deaths that occurred.9

Providing the best conditions for women everywhere would reduce the global death toll by 275,000 maternal deaths a year.

Covid-19 death rates in France and South Africa (per 1000).

Dataset Description

This dataset serves as a comprehensive repository of global development metrics, consolidating data from multiple international organizations into a single, unified structure. It provides a granular view of the state of health, economy, and nutrition across 193 countries over a 30-year period (1990–2019).

The data is organized by Country, Year, and Gender (Male, Female, and Both Sexes), making it a valuable resource for longitudinal studies, demographic analysis, and socio-economic research. It combines high-level economic indicators (like GDP) with granular health metrics (specific mortality rates) and detailed nutritional breakdowns (diet composition by food group).

Content Overview

The dataset covers a wide spectrum of categories:

• Demographics & Economy: Population stats, GNI, GDP, and poverty rates.
• Mortality & Life Expectancy: Survival rates at various ages, maternal mortality, and life expectancy.
• Public Health: Incidence of infectious diseases (Malaria, Tuberculosis, Hepatitis B) and prevalence of health risks (Tobacco, road traffic accidents).
• Environmental Health: Mortality attributed to air pollution, sanitation access, and clean fuel availability.
• Nutrition: Detailed caloric and quantity breakdown of food consumption (fruits, vegetables, cereals, meats, etc.).
• Healthcare Infrastructure: Coverage of essential health services and density of medical professionals.

Sources

The data was extracted and unified via an ETL process from the following organizations:

• World Bank: World Development Indicators
• WHO: Global Health Observatory Data
• UNICEF: Data Warehouse
• Our World In Data: Statistics and Research
• FAOSTAT: Food and Agriculture Data
• Kaggle: WHO World Health Statistics 2020 Complete

Data Dictionary

Index Columns

• Country: Name of the country.
• Year: The calendar year of the recorded data.
• Gender: The gender category for the data (Female, Male, or Both sexes).

Demographics & Health Metrics

• Life Expectancy: The average number of years a newborn is expected to live.
• Infant Mortality Rate: Number of infants dying before reaching one year of age, per 1,000 live births.
  • Includes Low/High Confidence Interval (CI) columns.
• Under 5 Mortality Rate: Probability of a child dying before reaching age 5, per 1,000 live births.
  • Includes Low/High CI columns.
• Neonatal Mortality Rate: Number of deaths during the first 28 days of life per 1,000 live births.
  • Includes Low/High CI columns.
• Maternal Mortality Ratio: Number of maternal deaths due to childbirth per 100,000 live births.
  • Includes Low/High CI columns.
• Birth Rate: Number of births per 1,000 inhabitants.
• Death Rate: Number of deaths per 1,000 inhabitants.
• Adolescent Birth Rate: Number of births by women aged 15 to 19 per 1,000 women in that age range.
• % Population Aged 0-14 / 15-64 / 65+: Percentage of the total population falling into these specific age brackets.
• % Population Aged 65-69 / 70-74 / 75-79 / 80+: Granular breakdown of the elderly population percentages.
• Total Population: Total number of inhabitants.

Causes of Death & Disease

• % Death Cardiovascular: Probability of dying from cardiovascular diseases, cancer, diabetes, or chronic respiratory diseases between ages 30 and 70.
  • Includes Low/High CI columns.
• Incidence of Malaria: Number of malaria cases per 1,000 inhabitants at risk per year.
• Incidence of Tuberculosis: Estimated cases of tuberculosis per 100,000 inhabitants.
  • Includes Low/High CI columns.
• Hepatitis B Surface Antigen: Prevalence of hepatitis B surface antigen.
  • Includes Low/High CI columns.
• Road Traffic Deaths: Number of deaths due to traffic accidents per 100,000 people.
• Poisoning Mortality Rate: Deaths attributed to unintentional poisoning per 100,000 people.
• Conflict and Terrorism Deaths: Number of deaths due to armed conflicts and terrorism.
• Battle Related Deaths: Number of deaths related to battles in an armed conflict.
• % Injury Deaths: Percentage of deaths caused by injuries.
• Suicides Rate: Number of deliberate deaths per 100,000 inhabitants.
• Homicide Rate: Number of homicides per 100,000 inhabitants.

Air Pollution Mortality

• Air Pollution Death Rate Total: Probability of dying fr...

Sex-ratio of Covid-19 death rates in France and South Africa (Male/Female).

In April 2020 Eurostat set up an exceptional data collection on total weekly deaths, in order to support the policy and research efforts related to Covid-19. With this data collection, Eurostat's target was to provide quickly statistics that show the changing situation of the total number of weekly deaths from early 2020 onwards.

The available data on the total weekly deaths are transmitted by the National Statistical Institutes to Eurostat on voluntary basis. Data are collected cross classified by sex, 5-year age-groups and NUTS3 region (NUTS2021). The age breakdown by 5-year age group is the most significant and should be considered by the reporting countries as the main option; when that is not possible, data may be provided with less granularity. Similar with the regional structure, data granularity varies with the country.

Eurostat requested from the National Statistical Institutes the transmission of a back time series of weekly deaths for as many year as possible, recommending as starting point the year 2000. Shorter time series, imposed by data availability, are transmitted by some countries. A long enough time series is necessary for temporal comparisons and statistical modelling.

A note on Ireland: Data from Ireland were not included in the first phase of the weekly deaths data collection: official timely data were not available because deaths can be registered up to three months after the date of death. Because of the COVID-19 pandemic, the Central Statistics Office of Ireland began to explore experimental ways of obtaining up-to-date mortality data, finding a strong correlation between death notices published on RIP.ie and official mortality statistics. Recently, CSO Ireland started publishing a time series covering the period from October 2019 until the most recent weeks, using death notices (see CSO website). For the purpose of this release, Eurostat compared the new 2020-2021 web-scraped series with a 2016-2019 baseline established using official data. CSO is periodically assessing the quality of these data.

The purpose of Eurostat’s online tables in the folder Weekly deaths - special data collection (demomwk) is to make available to users information on the weekly number of deaths disaggregated by sex, 5 years age group and NUTS3 regions over the last 20 years, depending on the availability in each country covered in Eurostat demographic statistics data collections. In order to ensure the highest timeliness possible, data are made available as reported by the countries, and work is ongoing in order to improve data quality and user friendliness.

Starting in 2025, the weekly deaths data is collected on a quarterly basis. The database updates are expected by mid-June (release of monthly data for 1st quarter of the year), mid-September (2nd quarter), mid-December (3rd quarter), and mid-February (4th quarter).

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.

As of May 25, 2020, there were around 295 deaths due to COVID-19 in the United States per million population. Among long-term care residents in the U.S. there were around 91 deaths from COVID-19 per million population. This statistic shows the total rate of COVID-19 deaths compared to deaths among long-term care residents in select countries worldwide as of May 2020.

United States - Infant Mortality Rate for High Income Countries was 4.10000 Number per 1,000 Live Births in January of 2023, according to the United States Federal Reserve. Historically, United States - Infant Mortality Rate for High Income Countries reached a record high of 36.40000 in January of 1960 and a record low of 4.10000 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Infant Mortality Rate for High Income Countries - last updated from the United States Federal Reserve on November of 2025.

Mexico Establishment Death Rate: Sinaloa data was reported at 37.110 % in 2021. This records an increase from the previous number of 27.704 % for 2020. Mexico Establishment Death Rate: Sinaloa data is updated yearly, averaging 27.704 % from Dec 2020 (Median) to 2021, with 2 observations. The data reached an all-time high of 37.110 % in 2021 and a record low of 27.704 % in 2020. Mexico Establishment Death Rate: Sinaloa data remains active status in CEIC and is reported by National Institute of Statistics and Geography. The data is categorized under Global Database’s Mexico – Table MX.O: Establishment Death Rate: by State.