4 datasets found
  1. COVID-19 and Influenza | New York Datasets

    • kaggle.com
    zip
    Updated May 9, 2020
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    Angel Henriquez (2020). COVID-19 and Influenza | New York Datasets [Dataset]. https://www.kaggle.com/datasets/angelhenriquez1/covid19-influenza-newyorkdatasets/discussion
    Explore at:
    zip(648794 bytes)Available download formats
    Dataset updated
    May 9, 2020
    Authors
    Angel Henriquez
    Description

    Context

    New York has presented the most cases compared to all states across the U.S..There have also been critiques regarding how much more unnoticed impact the flu has caused. My dataset allows us to compare whether or not this is true according to the most recent data.

    Content

    This COVID-19 data is from Kaggle whereas the New York influenza data comes from the U.S. government health data website. I merged the two datasets by county and FIPS code and listed the most recent reports of 2020 COVID-19 cases and deaths alongside the 2019 known influenza cases for comparison.

    Acknowledgements

    I am thankful to Kaggle and the U.S. government for making the data that made this possible openly available.

    Inspiration

    This data can be extended to answer the common misconceptions of the scale of the COVID-19 and common flu. My inspiration stems from supporting conclusions with data rather than simply intuition.

    I would like my data to help answer how we can make U.S. citizens realize what diseases are most impactful.

  2. Leading causes of death, total population, by age group

    • www150.statcan.gc.ca
    • ouvert.canada.ca
    • +1more
    Updated Feb 19, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Leading causes of death, total population, by age group [Dataset]. http://doi.org/10.25318/1310039401-eng
    Explore at:
    Dataset updated
    Feb 19, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

  3. NNDSS - TABLE 1R. Hepatitis C, perinatal infection to Influenza-associated...

    • catalog.data.gov
    • healthdata.gov
    • +4more
    Updated Jul 9, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). NNDSS - TABLE 1R. Hepatitis C, perinatal infection to Influenza-associated pediatric mortality [Dataset]. https://catalog.data.gov/dataset/nndss-table-1r-hepatitis-c-perinatal-infection-to-influenza-associated-pediatric-mortality
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    Dataset updated
    Jul 9, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    NNDSS - TABLE 1R. Hepatitis C, perinatal infection to Influenza-associated pediatric mortality - 2020. In this Table, provisional cases* of notifiable diseases are displayed for United States, U.S. territories, and Non-U.S. residents. Notice: Data from California published in week 29 for years 2019 and 2020 were incomplete when originally published on July 24, 2020. On August 4, 2020, incomplete case counts were replaced with a "U" indicating case counts are not available for specified time period. Note: This table contains provisional cases of national notifiable diseases from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data from the 50 states, New York City, the District of Columbia and the U.S. territories are collated and published weekly on the NNDSS Data and Statistics web page (https://wwwn.cdc.gov/nndss/data-and-statistics.html). Cases reported by state health departments to CDC for weekly publication are provisional because of the time needed to complete case follow-up. Therefore, numbers presented in later weeks may reflect changes made to these counts as additional information becomes available. The national surveillance case definitions used to define a case are available on the NNDSS web site at https://wwwn.cdc.gov/nndss/. Information about the weekly provisional data and guides to interpreting data are available at: https://wwwn.cdc.gov/nndss/infectious-tables.html. Footnotes: U: Unavailable — The reporting jurisdiction was unable to send the data to CDC or CDC was unable to process the data. -: No reported cases — The reporting jurisdiction did not submit any cases to CDC. N: Not reportable — The disease or condition was not reportable by law, statute, or regulation in the reporting jurisdiction. NN: Not nationally notifiable — This condition was not designated as being nationally notifiable. NP: Nationally notifiable but not published. NC: Not calculated — There is insufficient data available to support the calculation of this statistic. Cum: Cumulative year-to-date counts. Max: Maximum — Maximum case count during the previous 52 weeks. * Case counts for reporting years 2019 and 2020 are provisional and subject to change. Cases are assigned to the reporting jurisdiction submitting the case to NNDSS, if the case's country of usual residence is the U.S., a U.S. territory, unknown, or null (i.e. country not reported); otherwise, the case is assigned to the 'Non-U.S. Residents' category. Country of usual residence is currently not reported by all jurisdictions or for all conditions. For further information on interpretation of these data, see https://wwwn.cdc.gov/nndss/document/Users_guide_WONDER_tables_cleared_final.pdf. †Previous 52 week maximum and cumulative YTD are determined from periods of time when the condition was reportable in the jurisdiction (i.e., may be less than 52 weeks of data or incomplete YTD data). § Please refer to the CDC WONDER publication for weekly updates to the footnote for this condition.

  4. All-cause, COVID-19, and non-COVID-19 ASDR for ages 25+ by state and time...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 21, 2023
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    Anneliese N. Luck; Andrew C. Stokes; Katherine Hempstead; Eugenio Paglino; Samuel H. Preston (2023). All-cause, COVID-19, and non-COVID-19 ASDR for ages 25+ by state and time period. [Dataset]. http://doi.org/10.1371/journal.pone.0281683.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Anneliese N. Luck; Andrew C. Stokes; Katherine Hempstead; Eugenio Paglino; Samuel H. Preston
    License

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

    Description

    All-cause, COVID-19, and non-COVID-19 ASDR for ages 25+ by state and time period.

  5. Not seeing a result you expected?
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Click to copy link
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Angel Henriquez (2020). COVID-19 and Influenza | New York Datasets [Dataset]. https://www.kaggle.com/datasets/angelhenriquez1/covid19-influenza-newyorkdatasets/discussion
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COVID-19 and Influenza | New York Datasets

Useful Dataset to Compare COVID-19 and Influenza Death Tolls in New York

Explore at:
zip(648794 bytes)Available download formats
Dataset updated
May 9, 2020
Authors
Angel Henriquez
Description

Context

New York has presented the most cases compared to all states across the U.S..There have also been critiques regarding how much more unnoticed impact the flu has caused. My dataset allows us to compare whether or not this is true according to the most recent data.

Content

This COVID-19 data is from Kaggle whereas the New York influenza data comes from the U.S. government health data website. I merged the two datasets by county and FIPS code and listed the most recent reports of 2020 COVID-19 cases and deaths alongside the 2019 known influenza cases for comparison.

Acknowledgements

I am thankful to Kaggle and the U.S. government for making the data that made this possible openly available.

Inspiration

This data can be extended to answer the common misconceptions of the scale of the COVID-19 and common flu. My inspiration stems from supporting conclusions with data rather than simply intuition.

I would like my data to help answer how we can make U.S. citizens realize what diseases are most impactful.

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