Data for deaths by leading cause of death categories are now available in the death profiles dataset for each geographic granularity.

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.

Cause of death categories for years 1999 and later are based on tenth revision of International Classification of Diseases (ICD-10) codes. Comparable categories are provided for years 1979 through 1998 based on ninth revision (ICD-9) codes. For more information on the comparability of cause of death classification between ICD revisions see Comparability of Cause-of-death Between ICD Revisions.

Cardiovascular diseases (CVDs) are the number 1 cause of death globally, taking an estimated 17.9 million lives each year, which accounts for 31% of all deaths worlwide. Heart failure is a common event caused by CVDs and this dataset contains 12 features that can be used to predict mortality by heart failure.

Most cardiovascular diseases can be prevented by addressing behavioural risk factors such as tobacco use, unhealthy diet and obesity, physical inactivity and harmful use of alcohol using population-wide strategies.

People with cardiovascular disease or who are at high cardiovascular risk (due to the presence of one or more risk factors such as hypertension, diabetes, hyperlipidaemia or already established disease) need early detection and management wherein a machine learning model can be of great help.

Attribute Information:

Thirteen (13) clinical features: - age: age of the patient (years) - anaemia: decrease of red blood cells or hemoglobin (boolean) - high blood pressure: if the patient has hypertension (boolean) - creatinine phosphokinase (CPK): level of the CPK enzyme in the blood (mcg/L) - diabetes: if the patient has diabetes (boolean) - ejection fraction: percentage of blood leaving the heart at each contraction (percentage) - platelets: platelets in the blood (kiloplatelets/mL) - sex: woman or man (binary) - serum creatinine: level of serum creatinine in the blood (mg/dL) - serum sodium: level of serum sodium in the blood (mEq/L) - smoking: if the patient smokes or not (boolean) - time: follow-up period (days) - [target] death event: if the patient deceased during the follow-up period (boolean)

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This Dataset contains state, district and disease-wise cases and death reported due to outbreaks of diseases as per weekly reports under the Integrated Disease Surveillance Programme (IDSP)

Note: 1. State and District names that were not mentioned in the source are left blank in the dataset 2. Several weeks where data is not provided in the source, were removed from the dataset 3. The datasets do not contain data for the 52nd (2011), 15th (2016), 13th, 38th and 39th (2020) weeks since their data is either not available or not provided fully

Effective September 27, 2023, this dataset will no longer be updated. Similar data are accessible from wonder.cdc.gov. This visualization provides weekly data on the number of deaths by jurisdiction of occurrence and cause of death. Counts of deaths in more recent weeks can be compared with counts from earlier years to determine if the number is higher than expected. Selected causes of death are shown, based on analyses of the most prevalent comorbid conditions reported on death certificates where COVID-19 was listed as a cause of death (see https://www.cdc.gov/nchs/nvss/vsrr/covid_weekly/index.htm#Comorbidities). Cause of death counts are based on the underlying cause of death, and presented for Respiratory diseases, Circulatory diseases, Malignant neoplasms, and Alzheimer disease and dementia. Estimated numbers of deaths due to these other causes of death could represent misclassified COVID-19 deaths, or potentially could be indirectly related to COVID-19 (e.g., deaths from other causes occurring in the context of health care shortages or overburdened health care systems). Deaths with an underlying cause of death of COVID-19 are not included in these estimates of deaths due to other causes. Deaths due to external causes (i.e. injuries) or unknown causes are excluded. For more detail, see the Technical Notes.

This table contains 5190 series, with data for years 1996 - 1996 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (173 items: Canada; Health and Community Services St. John's Region; Newfoundland and Labrador; Health and Community Services Eastern Region; Newfoundland and Labrador; Newfoundland and Labrador ...), Sex (3 items: Both sexes; Males; Females ...), Selected causes of death (ICD-9) (4 items: Bacterial infections; population aged 5 to 64;Cervical cancer; females aged 5 to 64;Pneumonia and unspecified bronchitis; population aged 5 to 49;Hypertensive diseases; population aged 5 to 64 ...), Characteristics (3 items: Deaths due to medically treatable diseases; High 95% confidence interval; deaths due to medically treatable diseases; Low 95% confidence interval; deaths due to medically treatable diseases ...).

This table contains 5010 series, with data for years 1997 - 1997 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (167 items: Canada; Health and Community Services St. John's Region; Newfoundland and Labrador; Health and Community Services Eastern Region; Newfoundland and Labrador; Newfoundland and Labrador ...), Sex (3 items: Both sexes; Females; Males ...), Selected causes of death (ICD-9) (4 items: Bacterial infections; population aged 5 to 64;Cervical cancer; females aged 15 to 64;Pneumonia and unspecified bronchitis; population aged 5 to 49;Hypertensive diseases; population aged 35 to 64 ...), Characteristics (3 items: Deaths due to medically treatable diseases; High 95% confidence interval; deaths due to medically treatable diseases; Low 95% confidence interval; deaths due to medically treatable diseases ...).

The dataset contains year-, state- and gender-wise number of medically certified deaths from the total registered deaths with Medical Certification of Cause of Death (MCCD). The MCCD is a system that medically certifies the registered deaths, under the Registration of Births and Deaths Act, 1969.

The major groups of diseases covered in the dataset include Pregnancy, Childbirth and the Puerperium, Certain Infectious and Parasitic Diseases, Injury, Poisoning and Certain Other Consequences of External Causes, Codes for Special Purposes, Neoplasms, Mental and Behavioural Disorders, Diseases of Blood and Blood Forming Organs and Certain Disorders Involving the Immune Mechanism, Endocrine, Nutritional and Metabolic Diseases, Symptoms, Signs and Abnormal Clinical and Laboratory Findings, Certain Conditions Originating in the Perinatal Period, Congenital Malformations, Deformations and Chromosomal Abnormalities, Diseases of the Digestive System, Skin and Subcutaneous Tissue, Musculoskeletal System and Connective Tissue, Genitourinary System, Nervous System, Eye and Adnexa, Ear and Mastoid, Circulatory System, Respiratory System

Death rate due to chronic diseases

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.

Chronic diseases impose a tremendous global health problem of the 21st century. Epidemiological and public health models help to gain insight into the distribution and burden of chronic diseases. Moreover, the models may help to plan appropriate interventions against risk factors. To provide accurate results, models often need to take into account three different time-scales: calendar time, age, and duration since the onset of the disease. Incidence and mortality often change with age and calendar time. In many diseases such as, for example, diabetes and dementia, the mortality of the diseased persons additionally depends on the duration of the disease. The aim of this work is to describe an algorithm and a flexible software framework for the simulation of populations moving in an illness-death model that describes the epidemiology of a chronic disease in the face of the different times-scales. We set up a discrete event simulation in continuous time involving competing risks using the freely available statistical software R. Relevant events are birth, the onset (or diagnosis) of the disease and death with or without the disease. The Lexis diagram keeps track of the different time-scales. Input data are birth rates, incidence and mortality rates, which can be given as numerical values on a grid. The algorithm manages the complex interplay between the rates and the different time-scales. As a result, for each subject in the simulated population, the algorithm provides the calendar time of birth, the age of onset of the disease (if the subject contracts the disease) and the age at death. By this means, the impact of interventions may be estimated and compared.

This dataset includes Respiratory Viruses,COVID-19, Influenza, and RSV, associated statewide death counts by MMWR week. This dataset corresponds to the data on https://www.vdh.virginia.gov/epidemiology/respiratory-diseases-in-virginia/data/.

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.

This dataset contains Emergency Medical Services (EMS) information for reported emergency response incidents in Virginia that involve heat-related illness (HRI), as defined using heat-related protocols; heat-related ICD-10-CM codes in the cause of injury, primary impression, and secondary impressions fields; and key terms in the patient complaint and narrative text fields. The full case definition is available on this Virginia Department of Health Office of EMS data requests webpage under ‘Case Definitions’: https://www.vdh.virginia.gov/emergency-medical-services/ems-trauma-data/data-requests/. These data only represent HRI patients who interacted with the EMS system and do not represent HRI patients who reported directly to an emergency room or did not seek medical care. Therefore, these data should not be interpreted as the total number of HRI incidents in a community.

Data in this dataset have been provided by ESO on behalf of the Office of EMS. Please be advised that the accuracy of the data within the EMS patient care reporting system is limited by system performance and the accuracy of data submissions received from EMS agencies.

Counts of less than 5 have been suppressed, denoted by an asterisk, to prevent individual identification and protect patient confidentiality. This dataset has been classified as a Tier 0 asset by the Commonwealth Data Trust. Tier 0 classifies a data resource as information that is neither sensitive nor proprietary and is intended for public access.

This data shows premature deaths (Age under 75) from Respiratory Disease, numbers and rates by gender, as 3-year range. Smoking is the major cause of chronic obstructive pulmonary disease (COPD), one of the major Respiratory diseases. COPD (which includes chronic bronchitis and emphysema) results in many hospital admissions. Respiratory diseases can also be caused by environmental factors (such as pollution, or housing conditions) and influenza. Respiratory disease mortality rates show a socio-economic gradient. Directly Age-Standardised Rates (DASR) are shown in the data, where numbers are sufficient, so that death rates can be directly compared between areas. The DASR calculation applies Age-specific rates to a Standard (European) population to cancel out possible effects on crude rates due to different age structures among populations, thus enabling direct comparisons of rates. A limitation on using mortalities as a proxy for prevalence of health conditions is that mortalities may give an incomplete view of health conditions in an area, as ill-health might not lead to premature death. Data source: Office for Health Improvement and Disparities (OHID) Public Health Outcomes Framework (PHOF) indicator 4.07i. This data is updated annually.

Note: Reporting of new COVID-19 Case Surveillance data will be discontinued July 1, 2024, to align with the process of removing SARS-CoV-2 infections (COVID-19 cases) from the list of nationally notifiable diseases. Although these data will continue to be publicly available, the dataset will no longer be updated.

Authorizations to collect certain public health data expired at the end of the U.S. public health emergency declaration on May 11, 2023. The following jurisdictions discontinued COVID-19 case notifications to CDC: Iowa (11/8/21), Kansas (5/12/23), Kentucky (1/1/24), Louisiana (10/31/23), New Hampshire (5/23/23), and Oklahoma (5/2/23). Please note that these jurisdictions will not routinely send new case data after the dates indicated. As of 7/13/23, case notifications from Oregon will only include pediatric cases resulting in death.

This case surveillance public use dataset has 19 elements for all COVID-19 cases shared with CDC and includes demographics, geography (county and state of residence), any exposure history, disease severity indicators and outcomes, and presence of any underlying medical conditions and risk behaviors.

Currently, CDC provides the public with three versions of COVID-19 case surveillance line-listed data: this 19 data element dataset with geography, a 12 data element public use dataset, and a 33 data element restricted access dataset.

The following apply to the public use datasets and the restricted access dataset:

• Data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf.
• Data are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers.
• Some data are suppressed to protect individual privacy.
• Datasets will include all cases with the earliest date available in each record (date received by CDC or date related to illness/specimen collection) at least 14 days prior to the creation of the current datasets. This 14-day lag allows case reporting to be stabilized and ensure that time-dependent outcome data are accurately captured.
• Datasets are updated monthly.
• Datasets are created using CDC’s Policy on Public Health Research and Nonresearch Data Management and Access and include protections designed to protect individual privacy.
• For more information about data collection and reporting, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/about-us-cases-deaths.html.
• For more information about the COVID-19 case surveillance data, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html
  

Overview

The COVID-19 case surveillance database includes individual-level data reported to U.S. states and autonomous reporting entities, including New York City and the District of Columbia (D.C.), as well as U.S. territories and affiliates. On April 5, 2020, COVID-19 was added to the Nationally Notifiable Condition List and classified as “immediately notifiable, urgent (within 24 hours)” by a Council of State and Territorial Epidemiologists (CSTE) Interim Position Statement (<a href="https://cdn.ymaws.com/www.cste.org/resource/resmgr/ps/positionstatement2020/Interim-20-ID-01_COVID

Number of deaths caused by diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism, by age group and sex, 2000 to most recent year.

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.

Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').

The Occupational Safety and Health Administration (OSHA) collected work-related injury and illness data from employers within specific industry and employment size specifications from 2002 through 2011. This data collection is called the OSHA Data Initiative or ODI. The data provided is used by OSHA to calculate establishment specific injury and illness incidence rates. This searchable database contains a table with the name, address, industry, and associated Total Case Rate (TCR), Days Away, Restricted, and Transfer (DART) case rate, and the Days Away From Work (DAFWII) case rate for the establishments that provided OSHA with valid data for calendar years 2002 through 2011. This data has been sampled down from its original size to 4%. In addition, the original dataset only has data from a small portion of all private sector establishments in the United States (80,000 out of 7.5 million total establishments). Therefore, these data are not representative of all businesses and general conclusions pertaining to all US business should not be overdrawn. Data quality: While OSHA takes multiple steps to ensure the data collected is accurate, problems and errors invariably exist for a small percentage of establishments. OSHA does not believe the data for the establishments with the highest rates on this file are accurate in absolute terms. Efforts were made during the collection cycle to correct submission errors, however some remain unresolved. It would be a mistake to say establishments with the highest rates on this file are the ‘most dangerous’ or ‘worst’ establishments in the Nation. Rate Calculation: An incidence rate of injuries and illnesses is computed from the following formula: (Number of injuries and illnesses X 200,000) / Employee hours worked = Incidence rate. The Total Case Rate includes all cases recorded on the OSHA Form 300 (Column G + Column H + Column I + Column J). The Days Away/Restriced/Transfer includes cases recorded in Column H + Column I. The Days Away includes cases recorded in Column H. For further information on injury and illness incidence rates, please visit the Bureau of Labor Statistics’ webpage at http://www.bls.gov/iif/osheval.htm State Participation: Not all state plan states participate in the ODI. The following states did not participate in the 2010 ODI (collection of CY 2009 data), establishment data is not available for these states: Alaska; Oregon; Puerto Rico; South Carolina; Washington; Wyoming.

Data Dictionary

Acknowlegement

Original Data

CORGIS Dataset Project

Foto von National Cancer Institute auf Unsplash

The dataset contains year-wise data on share of groups of diseases in medically certified deaths, compiled from Medical Certification of Cause of Death (MCCD) annual reports which contain registered deaths and other data obtained through the Civil Registration System under the Registration of Births and Deaths Act, 1969. The annual reports on MCCD contain data of total registered deaths and the number of deaths that are medically certified within the registered deaths. Within this medically certified deaths, the data is categorised by share of groups of diseases, such as Diseases of the Circulatory System, Diseases of the Respiratory System, etc. The dataset contains this data