100+ datasets found
  1. I

    India IN: Probability of Dying at Age 20-24 Years: per 1000

    • ceicdata.com
    Updated Feb 3, 2018
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    CEICdata.com (2018). India IN: Probability of Dying at Age 20-24 Years: per 1000 [Dataset]. https://www.ceicdata.com/en/india/health-statistics/in-probability-of-dying-at-age-2024-years-per-1000
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    Dataset updated
    Feb 3, 2018
    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, 2008 - Dec 1, 2019
    Area covered
    India
    Description

    India IN: Probability of Dying at Age 20-24 Years: per 1000 data was reported at 6.000 Ratio in 2019. This records a decrease from the previous number of 6.100 Ratio for 2018. India IN: Probability of Dying at Age 20-24 Years: per 1000 data is updated yearly, averaging 10.350 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 14.000 Ratio in 1990 and a record low of 6.000 Ratio in 2019. India IN: Probability of Dying at Age 20-24 Years: per 1000 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Health Statistics. Probability of dying between age 20-24 years of age expressed per 1,000 youths age 20, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

  2. d

    Demographics: Year-wise Number of Registered and Medically Certified Deaths...

    • dataful.in
    Updated Jul 29, 2025
    + more versions
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    Dataful (Factly) (2025). Demographics: Year-wise Number of Registered and Medically Certified Deaths in India, as per MCCD [Dataset]. https://dataful.in/datasets/168
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    application/x-parquet, xlsx, csvAvailable download formats
    Dataset updated
    Jul 29, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    India
    Variables measured
    Deaths
    Description

    The dataset contains year-wise data on the number of registered and medically certified deaths in India, compiled from Medical Certification of Cause of Death (MCCD) annual reports which contain registered deaths and other data obtained through the Civil Registration System (CRS) under the Registration of Births and Deaths Act, 1969

  3. T

    India Death Rate Crude Per 1 000 People

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 28, 2017
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    TRADING ECONOMICS (2017). India Death Rate Crude Per 1 000 People [Dataset]. https://tradingeconomics.com/india/death-rate-crude-per-1-000-people-wb-data.html
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    xml, json, csv, 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
    India
    Description

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

  4. d

    All India, Year wise Deaths due to Heatwaves as reported by NDMA, MoSPI,...

    • dataful.in
    Updated Jun 4, 2025
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    Dataful (Factly) (2025). All India, Year wise Deaths due to Heatwaves as reported by NDMA, MoSPI, NCRB, MoES, WMO and IMD [Dataset]. https://dataful.in/datasets/451/
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    xlsx, csv, application/x-parquetAvailable download formats
    Dataset updated
    Jun 4, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    India
    Variables measured
    Number of deaths
    Description

    This dataset consists of the number of deaths due to heatwaves reported by different agencies/organizations. These are listed below: 1. MoSPI or MoES: Ministry of Statistics and Programme Implementation (MoSPI) published data on heat wave deaths in its annual Envistats report until 2021. Since 2022, the data has been collated from the Ministry of Earth Sciences since in the Envistats report, the source is mentioned as the India Meteorological Department (IMD), Ministry of Earth Sciences. 2. National Disaster Management Authority (NDMA): The data reported by this organization in some of its reports and workshop content has been collated. Values shared by Ministry of Health in the Parliament , which started recording the figures since 2015, is same as this until 2022. 3. World Meteorological Organization (WMO) 4. National Crime Records Bureau (NCRB)'s Accidental Deaths and Suicides India report: Data on heat stroke deaths reported by police departments at state level is presented in the report, which has been collated in the dataset. 5. IMD: Data on heatwave deaths reported by the IMD in its annual reports has been collated separately since the figures are slightly different from that reported by MoSPI/MoES.

  5. I

    India IN: Number of Deaths Ages 20-24 Years

    • ceicdata.com
    Updated Sep 15, 2024
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    CEICdata.com (2024). India IN: Number of Deaths Ages 20-24 Years [Dataset]. https://www.ceicdata.com/en/india/health-statistics/in-number-of-deaths-ages-2024-years
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    Dataset updated
    Sep 15, 2024
    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, 2008 - Dec 1, 2019
    Area covered
    India
    Description

    India IN: Number of Deaths Ages 20-24 Years data was reported at 146,669.000 Person in 2019. This records a decrease from the previous number of 148,431.000 Person for 2018. India IN: Number of Deaths Ages 20-24 Years data is updated yearly, averaging 219,654.500 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 223,796.000 Person in 2003 and a record low of 146,669.000 Person in 2019. India IN: Number of Deaths Ages 20-24 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Health Statistics. Number of deaths of youths ages 20-24 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

  6. Deaths due to bubonic plague in India 1896-1904

    • statista.com
    Updated May 5, 2020
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    Statista (2020). Deaths due to bubonic plague in India 1896-1904 [Dataset]. https://www.statista.com/statistics/1115019/plague-deaths-india-circa-1900/
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    Dataset updated
    May 5, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    The Third Plague Epidemic began in the mid-1800s in Yunnan, China, (an area that is still a natural reservoir for the Yersinia pestis bacteria) and had a huge death toll across Asia in the next century. While plague was confined to the Yunnan region for some decades, the mass displacement and social upheaval caused by the Taiping Rebellion saw millions flee the area , bringing the disease to other parts of the country. A plague epidemic then emerged in British-controlled Hong Kong in 1894, where merchants then unknowingly transported infected rats to other parts of the empire along various trade routes. Arrival in Bombay The first Indian cases were reported in Bombay (present-day Mumbai), and the Bombay Presidency suffered more losses than any other region in India (although there were some individual years where the state of Punjab reported more deaths). As with most disease or famine outbreaks in the region, the British authorities were slow to react, and their eventual response was in many ways too late. In some cases authorities even facilitated the spread of the disease; with multiple accounts of the military forcing healthy people into quarantine camps, evicting and burning homes of the afflicted, or by using such excessive force that the public would refuse medical help. Spread in India Lack of understanding among the Indian public was also to their own detriment. Some religions in India forbid the killing of rats, while some people simply refused to acknowledge that they were sick. As the plague in Bombay spiraled out of control, many fled to other parts of the country, taking the plague with them. It is estimated that there were over one million deaths in India by 1902, and almost one million further deaths in 1903 alone. The first four months of 1904 also saw over half a million deaths, almost matching the entire total for 1902. Plague would remain endemic to India for the next few decades, and there are varying reports of up to 10 or 12 million total plague deaths in this time. The public health measures taken to combat the plague in the early 20th century would mark the beginnings of India's public health system, and some of the quarantine measures put in place by the colonial government were even used in 2020 during the outbreak of the COVID-19 pandemic.

  7. India - Demographics, Health and Infant Mortality Rates

    • data.unicef.org
    Updated Sep 29, 2016
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    UNICEF (2016). India - Demographics, Health and Infant Mortality Rates [Dataset]. https://data.unicef.org/country/ind/
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    Dataset updated
    Sep 29, 2016
    Dataset authored and provided by
    UNICEFhttp://www.unicef.org/
    Description

    UNICEF's country profile for India, including under-five mortality rates, child health, education and sanitation data.

  8. Prospective Study of One Million Deaths in India: Rationale, Design, and...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    doc
    Updated May 31, 2023
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    Prabhat Jha; Vendhan Gajalakshmi; Prakash C Gupta; Rajesh Kumar; Prem Mony; Neeraj Dhingra; Richard Peto (2023). Prospective Study of One Million Deaths in India: Rationale, Design, and Validation Results [Dataset]. http://doi.org/10.1371/journal.pmed.0030018
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    docAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Prabhat Jha; Vendhan Gajalakshmi; Prakash C Gupta; Rajesh Kumar; Prem Mony; Neeraj Dhingra; Richard Peto
    License

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

    Area covered
    India
    Description

    BackgroundOver 75% of the annual estimated 9.5 million deaths in India occur in the home, and the large majority of these do not have a certified cause. India and other developing countries urgently need reliable quantification of the causes of death. They also need better epidemiological evidence about the relevance of physical (such as blood pressure and obesity), behavioral (such as smoking, alcohol, HIV-1 risk taking, and immunization history), and biological (such as blood lipids and gene polymorphisms) measurements to the development of disease in individuals or disease rates in populations. We report here on the rationale, design, and implementation of the world's largest prospective study of the causes and correlates of mortality. Methods and FindingsWe will monitor nearly 14 million people in 2.4 million nationally representative Indian households (6.3 million people in 1.1 million households in the 1998–2003 sample frame and 7.6 million people in 1.3 million households in the 2004–2014 sample frame) for vital status and, if dead, the causes of death through a well-validated verbal autopsy (VA) instrument. About 300,000 deaths from 1998–2003 and some 700,000 deaths from 2004–2014 are expected; of these about 850,000 will be coded by two physicians to provide causes of death by gender, age, socioeconomic status, and geographical region. Pilot studies will evaluate the addition of physical and biological measurements, specifically dried blood spots. Preliminary results from over 35,000 deaths suggest that VA can ascertain the leading causes of death, reduce the misclassification of causes, and derive the probable underlying cause of death when it has not been reported. VA yields broad classification of the underlying causes in about 90% of deaths before age 70. In old age, however, the proportion of classifiable deaths is lower. By tracking underlying demographic denominators, the study permits quantification of absolute mortality rates. Household case-control, proportional mortality, and nested case-control methods permit quantification of risk factors. ConclusionsThis study will reliably document not only the underlying cause of child and adult deaths but also key risk factors (behavioral, physical, environmental, and eventually, genetic). It offers a globally replicable model for reliably estimating cause-specific mortality using VA and strengthens India's flagship mortality monitoring system. Despite the misclassification that is still expected, the new cause-of-death data will be substantially better than that available previously.

  9. I

    India IN: Number of Deaths Ages 10-14 Years

    • ceicdata.com
    Updated Aug 19, 2020
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    CEICdata.com (2020). India IN: Number of Deaths Ages 10-14 Years [Dataset]. https://www.ceicdata.com/en/india/health-statistics/in-number-of-deaths-ages-1014-years
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    Dataset updated
    Aug 19, 2020
    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, 2008 - Dec 1, 2019
    Area covered
    India
    Description

    India IN: Number of Deaths Ages 10-14 Years data was reported at 68,681.000 Person in 2019. This records a decrease from the previous number of 71,179.000 Person for 2018. India IN: Number of Deaths Ages 10-14 Years data is updated yearly, averaging 119,467.500 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 140,520.000 Person in 1995 and a record low of 68,681.000 Person in 2019. India IN: Number of Deaths Ages 10-14 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Health Statistics. Number of deaths of adolescents ages 10-14 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

  10. T

    India Coronavirus COVID-19 Cases

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Dec 15, 2017
    + more versions
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    TRADING ECONOMICS (2017). India Coronavirus COVID-19 Cases [Dataset]. https://tradingeconomics.com/india/coronavirus-cases
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    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    Dec 15, 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 4, 2020 - May 17, 2023
    Area covered
    India
    Description

    India recorded 44983152 Coronavirus Cases since the epidemic began, according to the World Health Organization (WHO). In addition, India reported 531794 Coronavirus Deaths. This dataset includes a chart with historical data for India Coronavirus Cases.

  11. COVID-19 India

    • kaggle.com
    Updated Feb 4, 2023
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    swaptr (2023). COVID-19 India [Dataset]. https://www.kaggle.com/datasets/swaptr/covid19-state-data
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 4, 2023
    Dataset provided by
    Kaggle
    Authors
    swaptr
    License

    http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/

    Area covered
    India
    Description

    This dataset is a comprehensive collection of data related to the spread of COVID-19 in India. It captures the number of confirmed cases and deaths in each state and union territory of India from the first reported case in January 2020 to the present day. The dataset was created to provide an understanding of the extent of the COVID-19 pandemic in India. It is important because it allows researchers, policy-makers and citizens to gain insights into the various factors that may be driving the spread of the virus in different states and regions of India. It also provides valuable information for researchers trying to understand the dynamics of the pandemic in India.

    This dataset is important because it allows us to understand the current situation of the pandemic in India and to monitor the progress of the virus in each state. It can also be used to measure the effectiveness of the strategies implemented by the Indian Government to contain the spread of the virus. The dataset is applicable to anyone interested in understanding the dynamics of the COVID-19 pandemic in India, such as policy-makers, researchers, citizens, NGOs and media. It can be used to gain insights into the current situation and to track the progress of the virus in each state. It can also be used to monitor the effectiveness of the strategies implemented by the Indian Government to contain the spread of the virus.

    Overall, this dataset provides a comprehensive view of the COVID-19 pandemic in India. It is updated on a daily basis, and provides essential information that is useful for researchers, policy-makers and citizens. It is an invaluable resource that can be used to understand the dynamics of the virus and to monitor the progress of the virus in each state.

  12. India Female child mortality rate

    • knoema.com
    csv, json, sdmx, xls
    Updated Oct 2, 2025
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    Knoema (2025). India Female child mortality rate [Dataset]. https://knoema.com/atlas/India/topics/Health/Health-Status/Female-child-mortality-rate
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    sdmx, xls, json, csvAvailable download formats
    Dataset updated
    Oct 2, 2025
    Dataset authored and provided by
    Knoemahttp://knoema.com/
    Time period covered
    2012 - 2023
    Area covered
    India
    Variables measured
    Female child mortality rate
    Description

    Female child mortality rate of India declined by 4.79% from 29.2 deaths per thousand live births in 2022 to 27.8 deaths per thousand live births in 2023. Since the 5.90% slump in 2013, female child mortality rate plummeted by 45.49% in 2023. Child mortality rate is the probability of dying between the exact ages of one and five, if subject to current age-specific mortality rates. The probability is expressed as a rate per 1,000.

  13. COVID-19 cases and deaths per million in 210 countries as of July 13, 2022

    • statista.com
    Updated Jul 13, 2022
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    Statista (2022). COVID-19 cases and deaths per million in 210 countries as of July 13, 2022 [Dataset]. https://www.statista.com/statistics/1104709/coronavirus-deaths-worldwide-per-million-inhabitants/
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    Dataset updated
    Jul 13, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

    The difficulties of death figures

    This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

    Where are these numbers coming from?

    The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

  14. d

    State, Age, Gender and Tiger Reserve-wise Date of Deaths of Tigers in India

    • dataful.in
    Updated Nov 20, 2025
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    Dataful (Factly) (2025). State, Age, Gender and Tiger Reserve-wise Date of Deaths of Tigers in India [Dataset]. https://dataful.in/datasets/19646
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    application/x-parquet, csv, xlsxAvailable download formats
    Dataset updated
    Nov 20, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    Tiger Reserves of India, States of India
    Variables measured
    Tiger Deaths, Area
    Description

    This Dataset contains date of death, state, gender, age and tiger reserve location wise deaths of Tigers. The dataset also includes core area and buffer area of each tiger reserve

    Note: Adult Age Group: 3 to 10 Years Sub-Adult Age Group: 1 to 3 Years Cub Age Group: less than 1 Year

  15. T

    CORONAVIRUS DEATHS by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 4, 2020
    + more versions
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    TRADING ECONOMICS (2020). CORONAVIRUS DEATHS by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/coronavirus-deaths
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    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Mar 4, 2020
    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
    2025
    Area covered
    World
    Description

    This dataset provides values for CORONAVIRUS DEATHS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  16. I

    India IN: Number of Deaths Ages 5-9 Years

    • ceicdata.com
    Updated Aug 19, 2020
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    CEICdata.com (2020). India IN: Number of Deaths Ages 5-9 Years [Dataset]. https://www.ceicdata.com/en/india/health-statistics/in-number-of-deaths-ages-59-years
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    Dataset updated
    Aug 19, 2020
    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, 2008 - Dec 1, 2019
    Area covered
    India
    Description

    India IN: Number of Deaths Ages 5-9 Years data was reported at 67,196.000 Person in 2019. This records a decrease from the previous number of 72,012.000 Person for 2018. India IN: Number of Deaths Ages 5-9 Years data is updated yearly, averaging 180,128.000 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 310,340.000 Person in 1990 and a record low of 67,196.000 Person in 2019. India IN: Number of Deaths Ages 5-9 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Health Statistics. Number of deaths of children ages 5-9 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

  17. H

    Dataset for Economic Burden of Suicide Deaths in India in 2019

    • datasetcatalog.nlm.nih.gov
    • dataverse.harvard.edu
    • +1more
    Updated Feb 18, 2024
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    Nigam, Anukrati; Zadey, Siddhesh; Vuddemarry, Madhurima (2024). Dataset for Economic Burden of Suicide Deaths in India in 2019 [Dataset]. http://doi.org/10.7910/DVN/EVZCQV
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    Dataset updated
    Feb 18, 2024
    Authors
    Nigam, Anukrati; Zadey, Siddhesh; Vuddemarry, Madhurima
    Area covered
    India
    Description

    This dataset provides underlying data and calculated novel estimates for Economic Burden of Suicide Deaths in India in 2019. Dataset and data dictionaries are provided with a technical protocol detailing updates and corrections.

  18. I

    India WHO: Influenza A (H1N1): No of Deaths: India

    • ceicdata.com
    Updated Nov 30, 2025
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    CEICdata.com (2025). India WHO: Influenza A (H1N1): No of Deaths: India [Dataset]. https://www.ceicdata.com/en/india/world-heath-organization-influenza-a-h1n1-by-countries/who-influenza-a-h1n1-no-of-deaths-india
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    Dataset updated
    Nov 30, 2025
    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
    Jun 25, 2009 - Jul 6, 2009
    Area covered
    India
    Description

    WHO: Influenza A (H1N1): Number of Deaths: India data was reported at 0.000 Person in 06 Jul 2009. This stayed constant from the previous number of 0.000 Person for 05 Jul 2009. WHO: Influenza A (H1N1): Number of Deaths: India data is updated daily, averaging 0.000 Person from Apr 2009 (Median) to 06 Jul 2009, with 74 observations. The data reached an all-time high of 0.000 Person in 06 Jul 2009 and a record low of 0.000 Person in 06 Jul 2009. WHO: Influenza A (H1N1): Number of Deaths: India data remains active status in CEIC and is reported by World Health Organization. The data is categorized under High Frequency Database’s Disease Outbreaks – Table WHO.D002: World Heath Organization: Influenza A (H1N1): By Countries.

  19. STATE WISE DEATH OF INDIA

    • kaggle.com
    zip
    Updated Jul 16, 2024
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    Harinkl (2024). STATE WISE DEATH OF INDIA [Dataset]. https://www.kaggle.com/datasets/harinkl/state-wise-death-of-india/code
    Explore at:
    zip(266202 bytes)Available download formats
    Dataset updated
    Jul 16, 2024
    Authors
    Harinkl
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    India
    Description

    This dataset provides a comprehensive state-wise report of deaths in India from the year 2009 to 2020. This data is crucial for conducting in-depth analysis, identifying trends, making predictions, and developing technologies aimed at health improvement and prevention strategies. By examining this dataset, researchers can uncover the underlying factors contributing to mortality rates and address the challenges in public health.

    Dataset Summary Time Period: 2009-2020 Geographical Coverage: All Indian states and Union Territories Data Sources: Official government records, public health databases, and verified statistical reports. Features State/UT: The name of the state or union territory. Year: The reporting year ranging from 2009 to 2020. Total Deaths: The total number of deaths reported in the respective year. Causes of Death: Categorized causes of death (e.g., natural causes, accidents, diseases, etc.) Age Groups: Death count categorized by different age groups. Gender: Gender-wise death distribution (Male, Female, Others). Urban/Rural: Distinction between deaths in urban and rural areas. Additional Notes: Any additional notes or anomalies for specific years or states. Potential Applications Trend Analysis: Identify trends in mortality rates over the years and analyze the possible reasons for any significant changes. Predictive Modeling: Develop predictive models to forecast future death rates and potential public health crises. Health Policy Development: Assist policymakers in formulating effective health policies and intervention strategies. Technology Development: Inspire technological innovations geared towards health monitoring, early warning systems, and improving healthcare services. Sociodemographic Research: Study the impact of sociodemographic factors on mortality rates, including effects of urbanization, economic status, and healthcare access. Mystery Behind the Deaths The dataset can also be a valuable resource in uncovering the mysteries behind deaths in India, enabling researchers to:

    Investigate the causes behind unusually high death rates in certain states or periods. Study the impact of natural disasters, pandemics, and other calamities on mortality. Analyze the correlation between healthcare infrastructure and death rates. Examine gender disparities and their causes. Understand the impact of public health initiatives and their effectiveness. Data Collection and Accuracy The data has been meticulously collected from various reliable sources, ensuring high accuracy and consistency. Any discrepancies or missing data have been noted in the 'Additional Notes' column to maintain transparency.

    How to Use This Dataset Exploration: Initial exploration and summarization of the data using statistical tools and visualizations. Cleaning: Undertake any necessary data cleaning to handle missing or anomalous values. Analysis: Conduct detailed analysis using statistical methods or machine learning models. Reporting: Generate reports and visualizations to convey findings effectively. Sharing: Share insights and findings with other researchers, policymakers, or the public to drive informed decision-making.

  20. d

    Year, State and Gender-wise Cases and Deaths due to Acute Diarrheal Disease...

    • dataful.in
    Updated Nov 13, 2025
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    Dataful (Factly) (2025). Year, State and Gender-wise Cases and Deaths due to Acute Diarrheal Disease in India [Dataset]. https://dataful.in/datasets/18574
    Explore at:
    csv, xlsx, application/x-parquetAvailable download formats
    Dataset updated
    Nov 13, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    India
    Variables measured
    Cases and deaths due to Acute diarrheal disease
    Description

    This dataset contains the total state-wise cases and deaths due to Acute Diarrheal disease in India

    Note: 1. Gender-wise data for 2011 is not available 2. Data for 2022 is Provisional

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CEICdata.com (2018). India IN: Probability of Dying at Age 20-24 Years: per 1000 [Dataset]. https://www.ceicdata.com/en/india/health-statistics/in-probability-of-dying-at-age-2024-years-per-1000

India IN: Probability of Dying at Age 20-24 Years: per 1000

Explore at:
Dataset updated
Feb 3, 2018
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, 2008 - Dec 1, 2019
Area covered
India
Description

India IN: Probability of Dying at Age 20-24 Years: per 1000 data was reported at 6.000 Ratio in 2019. This records a decrease from the previous number of 6.100 Ratio for 2018. India IN: Probability of Dying at Age 20-24 Years: per 1000 data is updated yearly, averaging 10.350 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 14.000 Ratio in 1990 and a record low of 6.000 Ratio in 2019. India IN: Probability of Dying at Age 20-24 Years: per 1000 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Health Statistics. Probability of dying between age 20-24 years of age expressed per 1,000 youths age 20, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

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