This dataset contains counts of deaths for California counties based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

The final data tables include both deaths that occurred in each California county regardless of the place of residence (by occurrence) and deaths to residents of each California county (by residence), whereas the provisional data table only includes deaths that occurred in each county regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

Effective June 28, 2023, this dataset will no longer be updated. Similar data are accessible from CDC WONDER (https://wonder.cdc.gov/mcd-icd10-provisional.html) Provisional count of deaths involving COVID-19 by county of occurrence, in the United States, 2020-2023.

Every year the CDC releases the country’s most detailed report on death in the United States under the National Vital Statistics Systems. This mortality dataset is a record of every death in the country for 2005 through 2015, including detailed information about causes of death and the demographic background of the deceased.

It's been said that "statistics are human beings with the tears wiped off." This is especially true with this dataset. Each death record represents somebody's loved one, often connected with a lifetime of memories and sometimes tragically too short.

Putting the sensitive nature of the topic aside, analyzing mortality data is essential to understanding the complex circumstances of death across the country. The US Government uses this data to determine life expectancy and understand how death in the U.S. differs from the rest of the world. Whether you’re looking for macro trends or analyzing unique circumstances, we challenge you to use this dataset to find your own answers to one of life’s great mysteries.

Overview

This dataset is a collection of CSV files each containing one year's worth of data and paired JSON files containing the code mappings, plus an ICD 10 code set. The CSVs were reformatted from their original fixed-width file formats using information extracted from the CDC's PDF manuals using this script. Please note that this process may have introduced errors as the text extracted from the pdf is not a perfect match. If you have any questions or find errors in the preparation process, please leave a note in the forums. We hope to publish additional years of data using this method soon.

A more detailed overview of the data can be found here. You'll find that the fields are consistent within this time window, but some of data codes change every few years. For example, the 113_cause_recode entry 069 only covers ICD codes (I10,I12) in 2005, but by 2015 it covers (I10,I12,I15). When I post data from years prior to 2005, expect some of the fields themselves to change as well.

All data comes from the CDC’s National Vital Statistics Systems, with the exception of the Icd10Code, which are sourced from the World Health Organization.

Project ideas

• The CDC's mortality data was the basis of a widely publicized paper, by Anne Case and Nobel prize winner Angus Deaton, arguing that middle-aged whites are dying at elevated rates. One of the criticisms against the paper is that it failed to properly account for the exact ages within the broad bins available through the CDC's WONDER tool. What do these results look like with exact/not-binned age data?
• Similarly, how sensitive are the mortality trends being discussed in the news to the choice of bin-widths?
• As noted above, the data preparation process could have introduced errors. Can you find any discrepancies compared to the aggregate metrics on WONDER? If so, please let me know in the forums!
• WONDER is cited in numerous economics, sociology, and public health research papers. Can you find any papers whose conclusions would be altered if they used the exact data available here rather than binned data from Wonder?

Differences from the first version of the dataset

• This version of the dataset was prepared in a completely different many. This has allowed us to provide a much larger volume of data and ensure that codes are available for every field.
• We've replaced the batch of sql files with a single JSON per year. Kaggle's platform currently offer's better support for JSON files, and this keeps the number of files manageable.
• A tutorial kernel providing a quick introduction to the new format is available here.
• Lastly, I apologize if the transition has interrupted anyone's work! If need be, you can still download v1.

This table provides Canadians and researchers with provisional data to monitor weekly death trends by age and sex in Canada. Given the delays in receiving the data from the provincial and territorial vital statistics offices, these data are considered provisional. Data in this table will be available by province and territory.

Death statistics (i) Number of Deaths for Different Sexes and Crude Death Rate for the Period from 1981 to 2023 (ii) Age-standardised Death Rate (Overall and by Sex) for the Period from 1981 to 2023 (iii) Age-specific Death Rate for Year 2013 and 2023 (iv) Death Rates by Leading Causes of Death for the Period from 2001 to 2023 (v) Number of Deaths by Leading Causes of Death for the Period from 2001 to 2023 (vi) Age-standardised Death Rates by Leading Causes of Death for the Period from 2001 to 2023 (vii) Late Foetal Mortality Rate for the Period from 1981 to 2023 (viii) Perinatal Mortality Rate for the Period from 1981 to 2023 (ix) Neonatal Mortality Rate for the Period from 1981 to 2023 (x) Infant Mortality Rate for the Period from 1981 to 2023 (xi) Number of Maternal Deaths for the Period from 1981 to 2023 (xii) Maternal Mortality Ratio for the Period from 1981 to 2023

In 2021, the death rate in the United States stood at **** deaths per 1,000 of the population. This is a slight increase from the previous year, when the death rate stood at **** deaths per 1,000 of the population.

In 2023, about **** million deaths were reported in the United States. This figure is an increase from **** million deaths reported in 1990, and from **** in 2019. This sudden increase can be attributed to the COVID-19 pandemic.

This dataset contains counts of deaths for California as a whole based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

The final data tables include both deaths that occurred in California regardless of the place of residence (by occurrence) and deaths to California residents (by residence), whereas the provisional data table only includes deaths that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

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.

This file contains COVID-19 death counts and rates by month and year of death, jurisdiction of residence (U.S., HHS Region) and demographic characteristics (sex, age, race and Hispanic origin, and age/race and Hispanic origin). United States death counts and rates include the 50 states, plus the District of Columbia. Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file. Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death. Death counts should not be compared across jurisdictions. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly. The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington. Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf). Rate are based on deaths occurring in the specified week and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly) rate prevailed for a full year. Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

Death rate, crude (per 1,000 people) in United States was reported at 9.2 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Death rate, crude - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

In 2023, there were approximately 750.5 deaths by all causes per 100,000 inhabitants in the United States. This statistic shows the death rate for all causes in the United States between 1950 and 2023. Causes of death in the U.S. Over the past decades, chronic conditions and non-communicable diseases have come to the forefront of health concerns and have contributed to major causes of death all over the globe. In 2022, the leading cause of death in the U.S. was heart disease, followed by cancer. However, the death rates for both heart disease and cancer have decreased in the U.S. over the past two decades. On the other hand, the number of deaths due to Alzheimer’s disease – which is strongly linked to cardiovascular disease- has increased by almost 141 percent between 2000 and 2021. Risk and lifestyle factors Lifestyle factors play a major role in cardiovascular health and the development of various diseases and conditions. Modifiable lifestyle factors that are known to reduce risk of both cancer and cardiovascular disease among people of all ages include smoking cessation, maintaining a healthy diet, and exercising regularly. An estimated two million new cases of cancer in the U.S. are expected in 2025.

Estimates of excess deaths can provide information about the burden of mortality potentially related to the COVID-19 pandemic, including deaths that are directly or indirectly attributed to COVID-19. Excess deaths are typically defined as the difference between the observed numbers of deaths in specific time periods and expected numbers of deaths in the same time periods. This visualization provides weekly estimates of excess deaths by the jurisdiction in which the death occurred. Weekly counts of deaths are compared with historical trends to determine whether the number of deaths is significantly higher than expected.Counts of deaths from all causes of death, including COVID-19, are presented. As some deaths due to COVID-19 may be assigned to other causes of deaths (for example, if COVID-19 was not diagnosed or not mentioned on the death certificate), tracking all-cause mortality can provide information about whether an excess number of deaths is observed, even when COVID-19 mortality may be undercounted. Additionally, deaths from all causes excluding COVID-19 were also estimated. Comparing these two sets of estimates — excess deaths with and without COVID-19 — can provide insight about how many excess deaths are identified as due to COVID-19, and how many excess deaths are reported as due to other causes of death. These deaths could represent misclassified COVID-19 deaths, or potentially could be indirectly related to the COVID-19 pandemic (e.g., deaths from other causes occurring in the context of health care shortages or overburdened health care systems).Estimates of excess deaths can be calculated in a variety of ways, and will vary depending on the methodology and assumptions about how many deaths are expected to occur. Estimates of excess deaths presented in this webpage were calculated using Farrington surveillance algorithms (1). A range of values for the number of excess deaths was calculated as the difference between the observed count and one of two thresholds (either the average expected count or the upper bound of the 95% prediction interval), by week and jurisdiction.Provisional death counts are weighted to account for incomplete data. However, data for the most recent week(s) are still likely to be incomplete. Weights are based on completeness of provisional data in prior years, but the timeliness of data may have changed in 2020 relative to prior years, so the resulting weighted estimates may be too high in some jurisdictions and too low in others. As more information about the accuracy of the weighted estimates is obtained, further refinements to the weights may be made, which will impact the estimates. Any changes to the methods or weighting algorithm will be noted in the Technical Notes when they occur. More detail about the methods, weighting, data, and limitations can be found in the Technical Notes.This visualization includes several different estimates:Number of excess deaths: A range of estimates for the number of excess deaths was calculated as the difference between the observed count and one of two thresholds (either the average expected count or the upper bound threshold), by week and jurisdiction. Negative values, where the observed count fell below the threshold, were set to zero.Percent excess: The percent excess was defined as the number of excess deaths divided by the threshold.Total number of excess deaths: The total number of excess deaths in each jurisdiction was calculated by summing the excess deaths in each week, from February 1, 2020 to present. Similarly, the total number of excess deaths for the US overall was computed as a sum of jurisdiction-specific numbers of excess deaths (with negative values set to zero), and not directly estimated using the Farrington surveillance algorithms.Select a dashboard from the menu, then click on “Update Dashboard” to navigate through the different graphics.The first dashboard shows the weekly predicted counts of deaths from all causes, and the threshold for the expected number of deaths. Select a jurisdiction from the drop-down menu to show data for that jurisdiction.The second dashboard shows the weekly predicted counts of deaths from all causes and the weekly count of deaths from all causes excluding COVID-19. Select a jurisdiction from the drop-down menu to show data for that jurisdiction.The th

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.

The graph displays the number of deaths per year in the United States from 1950 to 2025. The x-axis represents the years, abbreviated from '50 to '25, while the y-axis indicates the annual number of deaths. Over this 75-year period, the number of deaths ranges from a low of 1,479,684 in 1950 to a high of 3,492,879 in 2021. Notable figures include 2,430,923 deaths in 2001 and 3,090,000 projected deaths in 2024. The data exhibits a general upward trend in annual deaths over the decades, with significant increases in recent years. This information is presented in a line graph format, effectively highlighting the long-term trends and yearly variations in deaths across the United States.

Deaths counts for influenza, pneumonia, and COVID-19 reported to NCHS by week ending date, by state and HHS region, and age group.

This data presents national-level provisional maternal mortality rates based on a current flow of mortality and natality data in the National Vital Statistics System. Provisional rates which are an early estimate of the number of maternal deaths per 100,000 live births, are shown as of the date specified and may not include all deaths and births that occurred during a given time period (see Technical Notes). A maternal death is the death of a woman while pregnant or within 42 days of termination of pregnancy irrespective of the duration and the site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management, but not from accidental or incidental causes. In this data visualization, maternal deaths are those deaths with an underlying cause of death assigned to International Statistical Classification of Diseases, 10th Revision (ICD-10) code numbers A34, O00–O95, and O98–O99. The provisional data include reported 12 month-ending provisional maternal mortality rates overall, by age, and by race and Hispanic origin. Provisional maternal mortality rates presented in this data visualization are for “12-month ending periods,” defined as the number of maternal deaths per 100,000 live births occurring in the 12-month period ending in the month indicated. For example, the 12-month ending period in June 2020 would include deaths and births occurring from July 1, 2019, through June 30, 2020. Evaluation of trends over time should compare estimates from year to year (June 2020 and June 2021), rather than month to month, to avoid overlapping time periods. In the visualization and in the accompanying data file, rates based on death counts less than 20 are suppressed in accordance with current NCHS standards of reliability for rates. Death counts between 1-9 in the data file are suppressed in accordance with National Center for Health Statistics (NCHS) confidentiality standards. Provisional data presented on this page will be updated on a quarterly basis as additional records are received. Previously released estimates are revised to include data and record updates received since the previous release. As a result, the reliability of estimates for a 12-month period ending with a specific month will improve with each quarterly release and estimates for previous time periods may change as new data and updates are received.

Death rate, crude (per 1,000 people) in World was reported at 7.5788 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Death rate, crude - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

Number and percentage of deaths, by month and place of residence, 1991 to most recent year.

In 2024, the Italian region with the highest death rate was Liguria. By contrast, Trentino-South Tyrol was the area where the lowest death rate was registered in the whole country. In the period between 2010 and 2019, the annual death rate in Italy remained rather stable. In 2020, instead, the death rate increased compared to previous years. Coronavirus deaths In Italy, the first cases of coronavirus (COVID-19) were registered at the end of January 2020. Then, since the end of February, the virus started to spread among the Italian population. As of October 2021, Italy recorded 4.7 million cases of coronavirus (COVID-19) and over 130,000 deaths. Death rates in other European countries In 2019, Italy was the European country which registered the second-highest number of deaths. The state with the highest number of deceased was Germany, which is also the most populous country on the continent. On the contrary, Italy ranked only fourth, considering the size of the population.