100+ datasets found
  1. C

    Death Profiles by County

    • data.chhs.ca.gov
    • data.ca.gov
    • +3more
    csv, zip
    Updated Nov 26, 2025
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    California Department of Public Health (2025). Death Profiles by County [Dataset]. https://data.chhs.ca.gov/dataset/death-profiles-by-county
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    csv(74351424), csv(75015194), csv(11738570), csv(1128641), csv(15127221), csv(60517511), csv(73906266), csv(60201673), csv(60676655), csv(28125832), csv(60023260), csv(51592721), csv(74689382), csv(52019564), csv(5095), csv(74043128), csv(24235858), csv(74497014), zip, csv(29775349)Available download formats
    Dataset updated
    Nov 26, 2025
    Dataset authored and provided by
    California Department of Public Health
    Description

    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.

  2. Mortality Statistics in US Cities

    • kaggle.com
    zip
    Updated Jan 23, 2023
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    The Devastator (2023). Mortality Statistics in US Cities [Dataset]. https://www.kaggle.com/datasets/thedevastator/mortality-statistics-in-us-cities
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    zip(96624 bytes)Available download formats
    Dataset updated
    Jan 23, 2023
    Authors
    The Devastator
    Area covered
    United States
    Description

    Mortality Statistics in US Cities

    Deaths by Age and Cause of Death in 2016

    By Health [source]

    About this dataset

    This dataset contains mortality statistics for 122 U.S. cities in 2016, providing detailed information about all deaths that occurred due to any cause, including pneumonia and influenza. The data is voluntarily reported from cities with populations of 100,000 or more, and it includes the place of death and the week during which the death certificate was filed. Data is provided broken down by age group and includes a flag indicating the reliability of each data set to help inform analysis. Each row also provides longitude and latitude information for each reporting area in order to make further analysis easier. These comprehensive mortality statistics are invaluable resources for tracking disease trends as well as making comparisons between different areas across the country in order to identify public health risks quickly and effectively

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    How to use the dataset

    This dataset contains mortality rates for 122 U.S. cities in 2016, including deaths by age group and cause of death. The data can be used to study various trends in mortality and contribute to the understanding of how different diseases impact different age groups across the country.

    In order to use the data, firstly one has to identify which variables they would like to use from this dataset. These include: reporting area; MMWR week; All causes by age greater than 65 years; All causes by age 45-64 years; All causes by age 25-44 years; All causes by age 1-24 years; All causes less than 1 year old; Pneumonia and Influenza total fatalities; Location (1 & 2); flag indicating reliability of data.

    Once you have identified the variables that you are interested in,you will need to filter the dataset so that it only includes relevant information for your analysis or research purposes. For example, if you are looking at trends between different ages, then all you would need is information on those 3 specific cause groups (greater than 65, 45-64 and 25-44). You can do this using a selection tool that allows you to pick only certain columns from your data set or an excel filter tool if your data is stored as a csv file type .

    Next step is preparing your data - it’s important for efficient analysis also helpful when there are too many variables/columns which can confuse our analysis process – eliminate unnecessary columns, rename column labels where needed etc ... In addition , make sure we clean up any missing values / outliers / incorrect entries before further investigation .Remember , outliers or corrupt entries may lead us into incorrect conclusions upon analyzing our set ! Once we complete the cleaning steps , now its safe enough transit into drawing insights !

    The last step involves using statistical methods such as linear regression with multiple predictors or descriptive statistical measures such as mean/median etc ..to draw key insights based on analysis done so far and generate some actionable points !

    With these steps taken care off , now its easier for anyone who decides dive into another project involving this particular dataset with added advantage formulated out of existing work done over our previous investigations!

    Research Ideas

    • Creating population health profiles for cities in the U.S.
    • Tracking public health trends across different age groups
    • Analyzing correlations between mortality and geographical locations

    Acknowledgements

    If you use this dataset in your research, please credit the original authors. Data Source

    License

    License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

    Columns

    File: rows.csv | Column name | Description | |:--------------------------------------------|:-----------------------------------...

  3. N

    New York City Leading Causes of Death

    • data.cityofnewyork.us
    • catalog.data.gov
    csv, xlsx, xml
    Updated Dec 9, 2024
    + more versions
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    Department of Health and Mental Hygiene (DOHMH) (2024). New York City Leading Causes of Death [Dataset]. https://data.cityofnewyork.us/Health/New-York-City-Leading-Causes-of-Death/jb7j-dtam
    Explore at:
    xml, xlsx, csvAvailable download formats
    Dataset updated
    Dec 9, 2024
    Dataset authored and provided by
    Department of Health and Mental Hygiene (DOHMH)
    Area covered
    New York
    Description

    The leading causes of death by sex and ethnicity in New York City in since 2007. Cause of death is derived from the NYC death certificate which is issued for every death that occurs in New York City.

    Report last ran: 09/24/2019
    Rates based on small numbers (RSE > 30) as well as aggregate counts less than 5 have been suppressed in downloaded data

    Source: Bureau of Vital Statistics and New York City Department of Health and Mental Hygiene

  4. Statewide Death Profiles

    • data.chhs.ca.gov
    • data.ca.gov
    • +3more
    csv, zip
    Updated Dec 2, 2025
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    California Department of Public Health (2025). Statewide Death Profiles [Dataset]. https://data.chhs.ca.gov/dataset/statewide-death-profiles
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    csv(4689434), csv(164006), csv(5034), csv(476576), csv(2026589), csv(5401561), csv(463460), csv(419332), csv(200270), csv(16301), zipAvailable download formats
    Dataset updated
    Dec 2, 2025
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    Description

    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.

  5. n

    Coronavirus (Covid-19) Data in the United States

    • nytimes.com
    • openicpsr.org
    • +4more
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    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html
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    Dataset provided by
    New York Times
    Description

    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.

  6. TABLE III. Deaths in 122 U.S. cities

    • catalog.data.gov
    • healthdata.gov
    • +6more
    Updated Jul 11, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). TABLE III. Deaths in 122 U.S. cities [Dataset]. https://catalog.data.gov/dataset/table-iii-deaths-in-122-u-s-cities
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    Dataset updated
    Jul 11, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Area covered
    United States
    Description

    TABLE III. Deaths in 122 U.S. cities – 2016. 122 Cities Mortality Reporting System — Each week, the vital statistics offices of 122 cities across the United States report the total number of death certificates processed and the number of those for which pneumonia or influenza was listed as the underlying or contributing cause of death by age group (Under 28 days, 28 days –1 year, 1-14 years, 15-24 years, 25-44 years, 45-64 years, 65-74 years, 75-84 years, and ≥ 85 years). FOOTNOTE: U: Unavailable. —: No reported cases. * Mortality data in this table are voluntarily reported from 122 cities in the United States, most of which have populations of 100,000 or more. A death is reported by the place of its occurrence and by the week that the death certificate was filed. Fetal deaths are not included. † Pneumonia and influenza. § Total includes unknown ages.

  7. Provisional COVID-19 death counts, rates, and percent of total deaths, by...

    • catalog.data.gov
    • data.virginia.gov
    • +2more
    Updated Sep 26, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). Provisional COVID-19 death counts, rates, and percent of total deaths, by jurisdiction of residence [Dataset]. https://catalog.data.gov/dataset/provisional-covid-19-death-counts-rates-and-percent-of-total-deaths-by-jurisdiction-of-res
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    Dataset updated
    Sep 26, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This file contains COVID-19 death counts, death rates, and percent of total deaths by jurisdiction of residence. The data is grouped by different time periods including 3-month period, weekly, and total (cumulative since January 1, 2020). United States death counts and rates include the 50 states, plus the District of Columbia and New York City. New York state estimates exclude New York City. Puerto Rico is included in HHS Region 2 estimates. 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 states. 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, New York City, Puerto Rico; 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). Rates are based on deaths occurring in the specified week/month 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/monthly 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/monthly) 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.).

  8. d

    Mass Killings in America, 2006 - present

    • data.world
    csv, zip
    Updated Dec 1, 2025
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    The Associated Press (2025). Mass Killings in America, 2006 - present [Dataset]. https://data.world/associatedpress/mass-killings-public
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    zip, csvAvailable download formats
    Dataset updated
    Dec 1, 2025
    Authors
    The Associated Press
    Time period covered
    Jan 1, 2006 - Nov 29, 2025
    Area covered
    Description

    THIS DATASET WAS LAST UPDATED AT 7:11 AM EASTERN ON DEC. 1

    OVERVIEW

    2019 had the most mass killings since at least the 1970s, according to the Associated Press/USA TODAY/Northeastern University Mass Killings Database.

    In all, there were 45 mass killings, defined as when four or more people are killed excluding the perpetrator. Of those, 33 were mass shootings . This summer was especially violent, with three high-profile public mass shootings occurring in the span of just four weeks, leaving 38 killed and 66 injured.

    A total of 229 people died in mass killings in 2019.

    The AP's analysis found that more than 50% of the incidents were family annihilations, which is similar to prior years. Although they are far less common, the 9 public mass shootings during the year were the most deadly type of mass murder, resulting in 73 people's deaths, not including the assailants.

    One-third of the offenders died at the scene of the killing or soon after, half from suicides.

    About this Dataset

    The Associated Press/USA TODAY/Northeastern University Mass Killings database tracks all U.S. homicides since 2006 involving four or more people killed (not including the offender) over a short period of time (24 hours) regardless of weapon, location, victim-offender relationship or motive. The database includes information on these and other characteristics concerning the incidents, offenders, and victims.

    The AP/USA TODAY/Northeastern database represents the most complete tracking of mass murders by the above definition currently available. Other efforts, such as the Gun Violence Archive or Everytown for Gun Safety may include events that do not meet our criteria, but a review of these sites and others indicates that this database contains every event that matches the definition, including some not tracked by other organizations.

    This data will be updated periodically and can be used as an ongoing resource to help cover these events.

    Using this Dataset

    To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:

    Mass killings by year

    Mass shootings by year

    To get these counts just for your state:

    Filter killings by state

    Definition of "mass murder"

    Mass murder is defined as the intentional killing of four or more victims by any means within a 24-hour period, excluding the deaths of unborn children and the offender(s). The standard of four or more dead was initially set by the FBI.

    This definition does not exclude cases based on method (e.g., shootings only), type or motivation (e.g., public only), victim-offender relationship (e.g., strangers only), or number of locations (e.g., one). The time frame of 24 hours was chosen to eliminate conflation with spree killers, who kill multiple victims in quick succession in different locations or incidents, and to satisfy the traditional requirement of occurring in a “single incident.”

    Offenders who commit mass murder during a spree (before or after committing additional homicides) are included in the database, and all victims within seven days of the mass murder are included in the victim count. Negligent homicides related to driving under the influence or accidental fires are excluded due to the lack of offender intent. Only incidents occurring within the 50 states and Washington D.C. are considered.

    Methodology

    Project researchers first identified potential incidents using the Federal Bureau of Investigation’s Supplementary Homicide Reports (SHR). Homicide incidents in the SHR were flagged as potential mass murder cases if four or more victims were reported on the same record, and the type of death was murder or non-negligent manslaughter.

    Cases were subsequently verified utilizing media accounts, court documents, academic journal articles, books, and local law enforcement records obtained through Freedom of Information Act (FOIA) requests. Each data point was corroborated by multiple sources, which were compiled into a single document to assess the quality of information.

    In case(s) of contradiction among sources, official law enforcement or court records were used, when available, followed by the most recent media or academic source.

    Case information was subsequently compared with every other known mass murder database to ensure reliability and validity. Incidents listed in the SHR that could not be independently verified were excluded from the database.

    Project researchers also conducted extensive searches for incidents not reported in the SHR during the time period, utilizing internet search engines, Lexis-Nexis, and Newspapers.com. Search terms include: [number] dead, [number] killed, [number] slain, [number] murdered, [number] homicide, mass murder, mass shooting, massacre, rampage, family killing, familicide, and arson murder. Offender, victim, and location names were also directly searched when available.

    This project started at USA TODAY in 2012.

    Contacts

    Contact AP Data Editor Justin Myers with questions, suggestions or comments about this dataset at jmyers@ap.org. The Northeastern University researcher working with AP and USA TODAY is Professor James Alan Fox, who can be reached at j.fox@northeastern.edu or 617-416-4400.

  9. Death Rates

    • kaggle.com
    zip
    Updated Jul 23, 2024
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    Melissa Monfared (2024). Death Rates [Dataset]. https://www.kaggle.com/datasets/melissamonfared/death-rates-united-states/code
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    zip(87422 bytes)Available download formats
    Dataset updated
    Jul 23, 2024
    Authors
    Melissa Monfared
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Description

    Context:

    This dataset provides data on death rates for suicide categorized by selected population characteristics including sex, race, Hispanic origin, and age in the United States. It includes critical information about measures, definitions, and changes over time.

    Source: - NCHS, National Vital Statistics System (NVSS) - Grove RD, Hetzel AM. Vital statistics rates in the United States, 1940–1960. National Center for Health Statistics. 1968 - Numerator data from NVSS annual public-use Mortality Files - Denominator data from U.S. Census Bureau national population estimates - Murphy SL, Xu JQ, Kochanek KD, Arias E, Tejada-Vera B. Deaths: Final data for 2018. National Vital Statistics Reports; vol 69 no 13. Hyattsville, MD: National Center for Health Statistics. 2021

    Source URLs:

    Death rates for suicide by sex, race, Hispanic origin, and age: United States - HUS 2019 Data Finder - National Vital Statistics Reports - NVSS Appendix Entry

    Dataset Details and Key Features

    The dataset consists of data collected from the National Vital Statistics System (NVSS) and the U.S. Census Bureau, providing a comprehensive overview of suicide death rates across different demographics in the United States from 1950 to 2001.

    Key Features:

    • Historical Coverage: Data spans from 1950 to 2001, providing long-term trends.
    • Demographic Breakdown: Includes data by sex, race, Hispanic origin, and age, facilitating targeted analysis.
    • Yearly Data: Provides annual death rate estimates, enabling year-over-year comparison.
    • Reliable Sources: Data collected from NVSS and U.S. Census Bureau, ensuring accuracy and reliability.

    Usage:

    Research and Analysis:

    • Trend Analysis: Study long-term trends in suicide rates across different demographic groups.
    • Impact Assessment: Analyze the impact of socio-economic factors on suicide rates over time.
    • Health Disparities: Identify disparities in suicide rates among different demographic segments.

    Policy Making:

    • Intervention Development: Inform the creation of targeted interventions for high-risk groups.
    • Resource Allocation: Aid in the effective allocation of resources to areas with higher suicide rates.
    • Policy Evaluation: Evaluate the effectiveness of past policies and programs aimed at reducing suicide rates.

    Public Health Initiatives:

    • Awareness Campaigns: Develop awareness campaigns tailored to specific demographic groups.
    • Prevention Programs: Design and implement suicide prevention programs based on demographic data.
    • Community Outreach: Facilitate community outreach efforts by identifying high-risk areas.

    Data Maintenance:

    Updates:

    • Periodic Updates: The dataset is periodically updated to incorporate the latest available data.
    • Version Control: Maintains previous versions for reference and longitudinal studies.

    Quality Assurance:

    • Data Validation: Ensures data accuracy through rigorous validation processes.
    • Consistency Checks: Regular consistency checks to maintain data integrity.

    Additional Notes:

    • For detailed definitions and explanations of measures, refer to the PDF or Excel version of this table in the HUS 2019 Data Finder.
    • Numerator data is derived from NVSS annual public-use Mortality Files, while denominator data comes from U.S. Census Bureau national population estimates.
    • The dataset also includes historical data, providing context and continuity for contemporary analysis.

    Columns:

    Column NameDescription
    INDICATORIndicator for the data type, e.g., Death rate
    UNITUnit of measurement, e.g., Deaths per 100,000 population
    UNIT_NUNumerical value representing the unit
    STUB_NAStub name for category, e.g., Total
    STUB_LALabel for the stub category, e.g., All persons
    STUB_LA_1Additional label information for the stub category
    YEARThe year the data was recorded
    YEAR_NUMNumerical value representing the year
    AGEAge group category, e.g., All ages
    AGE_NUMNumerical value representing the age group
    ESTIMATEEstimated death rate
  10. T

    United States Death Rate Crude Per 1 000 People

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 28, 2017
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    TRADING ECONOMICS (2017). United States Death Rate Crude Per 1 000 People [Dataset]. https://tradingeconomics.com/united-states/death-rate-crude-per-1-000-people-wb-data.html
    Explore at:
    json, csv, xml, excelAvailable download formats
    Dataset updated
    May 28, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    Actual value and historical data chart for United States Death Rate Crude Per 1 000 People

  11. Data from: Cause of death statistics

    • kaggle.com
    zip
    Updated Nov 19, 2022
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    The Devastator (2022). Cause of death statistics [Dataset]. https://www.kaggle.com/datasets/thedevastator/us-death-rates-by-age-and-cause-2014
    Explore at:
    zip(6580 bytes)Available download formats
    Dataset updated
    Nov 19, 2022
    Authors
    The Devastator
    Description

    US Death Rates by Age and Cause

    Study why are people dying

    About this dataset

    Data on death rates in the United States in by age and cause of death. At the bottom of the table, some of the columns are a little out of whack but if you download the file, you should be able to make out all the numbers and information

    How to use the dataset

    Looking at death rates in the United States can be a sobering experience, but it can also be a helpful way to see where our country needs to focus its efforts in terms of public health. This dataset contains information on death rates in the United States in 2014, by age and cause of death. This can be used to help identify which age groups are most at risk for certain causes of death, and what factors may contribute to those risks

    Research Ideas

    • Find out what age group is dying the most and why.
    • Compare death rates from different causes of death.
    • Find out which states have the highest death rates

    Acknowledgements

    License

    Unknown License - Please check the dataset description for more information.

    Columns

    File: 2014 Death Rates by Age & Cause.csv | Column name | Description | |:-------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------| | Cause of death (based on ICD–10) | The cause of death that the row represents. This is given as a code based on the International Classification of Diseases (ICD). (String) | | All ages1 | The number of deaths due to the given cause in the given age group.(Integer) | | Under 1 year2 | The number of deaths due to the given cause in the given age group.(Integer) | | 1–4 | The number of deaths due to the given cause in the given age group.(Integer) | | 5–14 | The number of deaths due to the given cause in the given age group.(Integer) | | 15–24 | The number of deaths due to the given cause in the given age group.(Integer) | | 25–34 | The number of deaths due to the given cause in the given age group.(Integer) | | 35–44 | The number of deaths due to the given cause in the given age group.(Integer) | | 45–54 | The number of deaths due to the given cause in the given age group.(Integer) | | 55–64 | The number of deaths due to the given cause in the given age group.(Integer) | | 65–74 | The number of deaths due to the given cause in the given age group.(Integer) | | 75–84 | The number of deaths due to the given cause in the given age group.(Integer) | | 85 and over | The number of deaths due to the given cause in the given age group.(Integer) |

  12. National Death Index

    • healthdata.gov
    • odgavaprod.ogopendata.com
    • +2more
    csv, xlsx, xml
    Updated Feb 13, 2021
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    (2021). National Death Index [Dataset]. https://healthdata.gov/w/ta9n-3c8q/default?cur=fn4FBRcgpkA
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    csv, xml, xlsxAvailable download formats
    Dataset updated
    Feb 13, 2021
    Description

    The National Death Index (NDI) is a centralized database of death record information on file in state vital statistics offices. Working with these state offices, the National Center for Health Statistics (NCHS) established the NDI as a resource to aid epidemiologists and other health and medical investigators with their mortality ascertainment activities.

    Assists investigators in determining whether persons in their studies have died and, if so, provide the names of the states in which those deaths occurred, the dates of death, and the corresponding death certificate numbers. Investigators can then make arrangements with the appropriate state offices to obtain copies of death certificates or specific statistical information such as manner of death or educational level. Cause of death codes may also be obtained using the NDI Plus service.

    Records from 1979 through 2011 are currently available and contain a standard set of identifying information on each death. Death records are added to the NDI file annually, approximately 12 months after the end of a particular calendar year. 2012 should be available summer 2014. Early Release Program for 2013 is now available.

    The NDI service is available to investigators solely for statistical purposes in medical and health research. The service is not accessible to organizations or the general public for legal, administrative, or genealogy purposes.

  13. U

    United States US: Death Rate: Crude: per 1000 People

    • ceicdata.com
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    CEICdata.com, United States US: Death Rate: Crude: per 1000 People [Dataset]. https://www.ceicdata.com/en/united-states/population-and-urbanization-statistics/us-death-rate-crude-per-1000-people
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    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    United States
    Variables measured
    Population
    Description

    United States US: Death Rate: Crude: per 1000 People data was reported at 8.400 Ratio in 2016. This records a decrease from the previous number of 8.440 Ratio for 2015. United States US: Death Rate: Crude: per 1000 People data is updated yearly, averaging 8.700 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 9.800 Ratio in 1968 and a record low of 7.900 Ratio in 2009. United States US: Death Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Population and Urbanization Statistics. Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

  14. O

    COVID-19 Cases and Deaths by Race/Ethnicity - ARCHIVE

    • data.ct.gov
    • s.cnmilf.com
    • +2more
    csv, xlsx, xml
    Updated Jun 24, 2022
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    Department of Public Health (2022). COVID-19 Cases and Deaths by Race/Ethnicity - ARCHIVE [Dataset]. https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-and-Deaths-by-Race-Ethnicity-ARCHIV/7rne-efic
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    xlsx, csv, xmlAvailable download formats
    Dataset updated
    Jun 24, 2022
    Dataset authored and provided by
    Department of Public Health
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve.

    The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj.

    The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 .

    The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 .

    The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed.

    COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update.

    The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates.

    The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used.

    Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf

    Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic.

    Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics

    Data are subject to future revision as reporting changes.

    Starting in July 2020, this dataset will be updated every weekday.

    Additional notes: A delay in the data pull schedule occurred on 06/23/2020. Data from 06/22/2020 was processed on 06/23/2020 at 3:30 PM. The normal data cycle resumed with the data for 06/23/2020.

    A network outage on 05/19/2020 resulted in a change in the data pull schedule. Data from 5/19/2020 was processed on 05/20/2020 at 12:00 PM. Data from 5/20/2020 was processed on 5/20/2020 8:30 PM. The normal data cycle resumed on 05/20/2020 with the 8:30 PM data pull. As a result of the network outage, the timestamp on the datasets on the Open Data Portal differ from the timestamp in DPH's daily PDF reports.

    Starting 5/10/2021, the date field will represent the date this data was updated on data.ct.gov. Previously the date the data was pulled by DPH was listed, which typically coincided with the date before the data was published on data.ct.gov. This change was made to standardize the COVID-19 data sets on data.ct.gov.

  15. Provisional COVID-19 death counts and rates by month, jurisdiction of...

    • data.virginia.gov
    • healthdata.gov
    • +3more
    csv, json, rdf, xsl
    Updated Sep 25, 2025
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    Centers for Disease Control and Prevention (2025). Provisional COVID-19 death counts and rates by month, jurisdiction of residence, and demographic characteristics [Dataset]. https://data.virginia.gov/dataset/provisional-covid-19-death-counts-and-rates-by-month-jurisdiction-of-residence-and-demographic-
    Explore at:
    rdf, csv, json, xslAvailable download formats
    Dataset updated
    Sep 25, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    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.).

  16. d

    Maryland and Jurisdictions Total Deaths: 2020-2024

    • catalog.data.gov
    • opendata.maryland.gov
    • +1more
    Updated May 31, 2025
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    opendata.maryland.gov (2025). Maryland and Jurisdictions Total Deaths: 2020-2024 [Dataset]. https://catalog.data.gov/dataset/maryland-total-deaths-by-year-2000-2016
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    Dataset updated
    May 31, 2025
    Dataset provided by
    opendata.maryland.gov
    Area covered
    Maryland
    Description

    Total deaths for Maryland and its jurisdictions are derived from the U.S. Census Bureau’s Population Estimates Program. These estimates reflect revisions to the entire time series, beginning with the estimate base of April 1, 2020, through July 1 of the current year (referred to as the 'vintage year,' or V2024). Each time series incorporates updated administrative records, geographic boundary changes, and methodological improvements. The data is updated annually. Source: U.S. Census Bureau, Population Estimates Program, March 2025.

  17. Coronavirus (COVID-19) deaths per day compared to all causes U.S. 2022

    • statista.com
    Updated Jan 7, 2022
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    Statista (2022). Coronavirus (COVID-19) deaths per day compared to all causes U.S. 2022 [Dataset]. https://www.statista.com/statistics/1109281/covid-19-daily-deaths-compared-to-all-causes/
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    Dataset updated
    Jan 7, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of January 6, 2022, an average of 1,192 people per day have died from COVID-19 in the U.S. since the first case was confirmed in the country on January 20th the year before. On an average day, nearly 8,000 people die from all causes in the United States, based on data from 2019. Based on the latest information, roughly one in seven deaths each day were related to COVID-19 between January 2020 and January 2022. However, there were even days when more than every second death in the U.S. was connected to COVID-19. The daily death toll from the seasonal flu, using preliminary maximum estimates from the 2019-2020 influenza season, stood at an average of around 332 people. We have to keep in mind that a comparison of influenza and COVID-19 is somewhat difficult. COVID-19 cases and deaths are counted continuously since the begin of the pandemic, whereas flue counts are seasonal and often less accurate. Furthermore, during the last two years, COVID-19 more or less 'replaced' the flu, with COVID-19 absorbing potential flu cases. Many countries reported a very weak seasonal flu activity during the COVID-19 pandemic. But it has yet to be seen how the two infectious diseases will develop side by side during the winter season 2021/2022 and in the years to come.

    Symptoms and self-isolation COVID-19 and influenza share similar symptoms – a cough, runny nose, and tiredness – and telling the difference between the two can be difficult. If you have minor symptoms, there is no need to seek urgent medical care, but it is recommended that you self-isolate, whereas rules vary from country to country. Additionally, rules depend on someone's vaccination status and infection history. However, if you think you have the disease, a diagnostic test can show if you have an active infection.

    Scientists alert to coronavirus mutations The genetic material of the novel coronavirus is RNA, not DNA. Other notable human diseases caused by RNA viruses include SARS, Ebola, and influenza. A continual problem that vaccine developers encounter is that viruses can mutate, and a treatment developed against a certain virus type may not work on a mutated form. The seasonal flu vaccine, for example, is different each year because influenza viruses are frequently mutating, and it is critical that those genetic changes continue to be tracked.

  18. Death rate by age and sex in the U.S. 2021

    • statista.com
    • akomarchitects.com
    Updated Oct 25, 2024
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    Statista (2024). Death rate by age and sex in the U.S. 2021 [Dataset]. https://www.statista.com/statistics/241572/death-rate-by-age-and-sex-in-the-us/
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    Dataset updated
    Oct 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    United States
    Description

    In the United States in 2021, the death rate was highest among those aged 85 and over, with about 17,190.5 men and 14,914.5 women per 100,000 of the population passing away. For all ages, the death rate was at 1,118.2 per 100,000 of the population for males, and 970.8 per 100,000 of the population for women. The death rate Death rates generally are counted as the number of deaths per 1,000 or 100,000 of the population and include both deaths of natural and unnatural causes. The death rate in the United States had pretty much held steady since 1990 until it started to increase over the last decade, with the highest death rates recorded in recent years. While the birth rate in the United States has been decreasing, it is still currently higher than the death rate. Causes of death There are a myriad number of causes of death in the United States, but the most recent data shows the top three leading causes of death to be heart disease, cancers, and accidents. Heart disease was also the leading cause of death worldwide.

  19. NCHS - Drug Poisoning Mortality by County: United States

    • data.virginia.gov
    • healthdata.gov
    • +4more
    csv, json, rdf, xsl
    Updated Apr 21, 2025
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    Centers for Disease Control and Prevention (2025). NCHS - Drug Poisoning Mortality by County: United States [Dataset]. https://data.virginia.gov/dataset/nchs-drug-poisoning-mortality-by-county-united-states
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    json, rdf, xsl, csvAvailable download formats
    Dataset updated
    Apr 21, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Area covered
    United States
    Description

    This dataset contains model-based county estimates for drug-poisoning mortality.

    Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent).

    Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2016 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published.

    Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Drug poisoning death rates may be underestimated in those instances.

    Smoothed county age-adjusted death rates (deaths per 100,000 population) were obtained according to methods described elsewhere (3–5). Briefly, two-stage hierarchical models were used to generate empirical Bayes estimates of county age-adjusted death rates due to drug poisoning for each year. These annual county-level estimates “borrow strength” across counties to generate stable estimates of death rates where data are sparse due to small population size (3,5). Estimates for 1999-2015 have been updated, and may differ slightly from previously published estimates. Differences are expected to be minimal, and may result from different county boundaries used in this release (see below) and from the inclusion of an additional year of data. Previously published estimates can be found here for comparison.(6) Estimates are unavailable for Broomfield County, Colorado, and Denali County, Alaska, before 2003 (7,8). Additionally, Clifton Forge County, Virginia only appears on the mortality files prior to 2003, while Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. These counties were therefore merged with adjacent counties where necessary to create a consistent set of geographic units across the time period. County boundaries are largely consistent with the vintage 2005-2007 bridged-race population file geographies, with the modifications noted previously (7,8).

    REFERENCES 1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm.

    1. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html.

    2. Rossen LM, Khan D, Warner M. Trends and geographic patterns in drug-poisoning death rates in the U.S., 1999–2009. Am J Prev Med 45(6):e19–25. 2013.

    3. Rossen LM, Khan D, Warner M. Hot spots in mortality from drug poisoning in the United States, 2007–2009. Health Place 26:14–20. 2014.

    4. Rossen LM, Khan D, Hamilton B, Warner M. Spatiotemporal variation in selected health outcomes from the National Vital Statistics System. Presented at: 2015 National Conference on Health Statistics, August 25, 2015, Bethesda, MD. Available from: http://www.cdc.gov/nchs/ppt/nchs2015/Rossen_Tuesday_WhiteOak_BB3.pdf.

    5. Rossen LM, Bastian B, Warner M, and Khan D. NCHS – Drug Poisoning Mortality by County: United States, 1999-2015. Available from: https://data.cdc.gov/NCHS/NCHS-Drug-Poisoning-Mortality-by-County-United-Sta/pbkm-d27e.

    6. National Center for Health Statistics. County geog

  20. NCHS - Leading Causes of Death: United States

    • catalog.data.gov
    • healthdata.gov
    • +5more
    Updated Apr 23, 2025
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    Centers for Disease Control and Prevention (2025). NCHS - Leading Causes of Death: United States [Dataset]. https://catalog.data.gov/dataset/nchs-leading-causes-of-death-united-states
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    Dataset updated
    Apr 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Area covered
    United States
    Description

    This dataset presents the age-adjusted death rates for the 10 leading causes of death in the United States beginning in 1999. Data are based on information from all resident death certificates filed in the 50 states and the District of Columbia using demographic and medical characteristics. Age-adjusted death rates (per 100,000 population) are based on the 2000 U.S. standard population. Populations used for computing death rates after 2010 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for non-census years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Causes of death classified by the International Classification of Diseases, Tenth Revision (ICD–10) are ranked according to the number of deaths assigned to rankable causes. Cause of death statistics are based on the underlying cause of death. SOURCES CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. Murphy SL, Xu JQ, Kochanek KD, Curtin SC, and Arias E. Deaths: Final data for 2015. National vital statistics reports; vol 66. no. 6. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_06.pdf.

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California Department of Public Health (2025). Death Profiles by County [Dataset]. https://data.chhs.ca.gov/dataset/death-profiles-by-county

Death Profiles by County

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3 scholarly articles cite this dataset (View in Google Scholar)
csv(74351424), csv(75015194), csv(11738570), csv(1128641), csv(15127221), csv(60517511), csv(73906266), csv(60201673), csv(60676655), csv(28125832), csv(60023260), csv(51592721), csv(74689382), csv(52019564), csv(5095), csv(74043128), csv(24235858), csv(74497014), zip, csv(29775349)Available download formats
Dataset updated
Nov 26, 2025
Dataset authored and provided by
California Department of Public Health
Description

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.

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