31 datasets found
  1. Provisional Death Counts for Influenza, Pneumonia, and COVID-19

    • catalog.data.gov
    • odgavaprod.ogopendata.com
    • +6more
    Updated Apr 23, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). Provisional Death Counts for Influenza, Pneumonia, and COVID-19 [Dataset]. https://catalog.data.gov/dataset/provisional-death-counts-for-influenza-pneumonia-and-covid-19
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    Dataset updated
    Apr 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

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

  2. Monthly Cumulative Number and Percent of Persons Who Received ≥1 Influenza...

    • data.cdc.gov
    • healthdata.gov
    • +1more
    csv, xlsx, xml
    Updated Sep 3, 2024
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    National Center for Immunization and Respiratory Diseases (NCIRD) (2024). Monthly Cumulative Number and Percent of Persons Who Received ≥1 Influenza Vaccination Doses, by Flu Season, Age Group, and Jurisdiction [Dataset]. https://data.cdc.gov/Flu-Vaccinations/Monthly-Cumulative-Number-and-Percent-of-Persons-W/udwr-3en6
    Explore at:
    xml, csv, xlsxAvailable download formats
    Dataset updated
    Sep 3, 2024
    Dataset provided by
    National Center for Immunization and Respiratory Diseases
    Authors
    National Center for Immunization and Respiratory Diseases (NCIRD)
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    Monthly Cumulative Number and Percent of Persons Who Received ≥1 Influenza Vaccination Doses, by Flu Season, Age Group, and Jurisdiction

    • Influenza vaccination coverage for children and adults is assessed through U.S. jurisdictions’ Immunization Information Systems (IIS) data, submitted from jurisdictions to CDC monthly in aggregate by age group. More information about the IIS can be found at https://www.cdc.gov/vaccines/programs/iis/about.html.

    • Influenza vaccination coverage estimate numerators include the number of people receiving at least one dose of influenza vaccine in a given flu season, based on information that state, territorial, and local public health agencies report to CDC. Some jurisdictions’ data may include data submitted by tribes. Estimates include persons who are deceased but received a vaccination during the current season. People receiving doses are attributed to the jurisdiction in which the person resides unless noted otherwise. Quality and completeness of data may vary across jurisdictions. Influenza vaccination coverage denominators are obtained from 2020 U.S. Census Bureau population estimates.

    • Monthly estimates shown are cumulative, reflecting all persons vaccinated from July through a given month of that flu season. Cumulative estimates include any historical data reported since the previous submission. National estimates are not presented since not all U.S. jurisdictions are currently reporting their IIS data to CDC. Jurisdictions reporting data to CDC include U.S. states, some localities, and territories.

    • Because IIS data contain all vaccinations administered within a jurisdiction rather than a sample, standard errors were not calculated and statistical testing for differences in estimates across years were not performed.

    • Laws and policies regarding the submission of vaccination data to an IIS vary by state, which may impact the completeness of vaccination coverage reflected for a jurisdiction. More information on laws and policies are found at https://www.cdc.gov/vaccines/programs/iis/policy-legislation.html.

    • Coverage estimates based on IIS data are expected to differ from National Immunization Survey (NIS) estimates for children (https://www.cdc.gov/flu/fluvaxview/dashboard/vaccination-coverage-race.html) and adults (https://www.cdc.gov/flu/fluvaxview/dashboard/vaccination-adult-coverage.html) because NIS estimates are based on a sample that may not be representative after survey weighting and vaccination status is determined by survey respondent rather than vaccine records or administrations, and quality and completeness of IIS data may vary across jurisdictions. In general, NIS estimates tend to overestimate coverage due to overreporting and IIS estimates may underestimate coverage due to incompleteness of data in certain jurisdictions.

  3. A

    ‘COVID-19 State Data’ analyzed by Analyst-2

    • analyst-2.ai
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com), ‘COVID-19 State Data’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-covid-19-state-data-287b/0959fdcb/?iid=017-872&v=presentation
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    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘COVID-19 State Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/nightranger77/covid19-state-data on 30 September 2021.

    --- Dataset description provided by original source is as follows ---

    This dataset is a per-state amalgamation of demographic, public health and other relevant predictors for COVID-19.

    Deaths, Infections and Tests by State

    The COVID Tracking Project: https://covidtracking.com/data/api

    Used positive, death and totalTestResults from the API for, respectively, Infected, Deaths and Tested in this dataset. Please read the documentation of the API for more context on those columns

    Predictor Data and Sources

    Population (2020)

    Density is people per meter squared https://worldpopulationreview.com/states/

    ICU Beds and Age 60+

    https://khn.org/news/as-coronavirus-spreads-widely-millions-of-older-americans-live-in-counties-with-no-icu-beds/

    GDP

    https://worldpopulationreview.com/states/gdp-by-state/

    Income per capita (2018)

    https://worldpopulationreview.com/states/per-capita-income-by-state/

    Gini

    https://en.wikipedia.org/wiki/List_of_U.S._states_by_Gini_coefficient

    Unemployment (2020)

    Rates from Feb 2020 and are percentage of labor force
    https://www.bls.gov/web/laus/laumstrk.htm

    Sex (2017)

    Ratio is Male / Female
    https://www.kff.org/other/state-indicator/distribution-by-gender/

    Smoking Percentage (2020)

    https://worldpopulationreview.com/states/smoking-rates-by-state/

    Influenza and Pneumonia Death Rate (2018)

    Death rate per 100,000 people
    https://www.cdc.gov/nchs/pressroom/sosmap/flu_pneumonia_mortality/flu_pneumonia.htm

    Chronic Lower Respiratory Disease Death Rate (2018)

    Death rate per 100,000 people
    https://www.cdc.gov/nchs/pressroom/sosmap/lung_disease_mortality/lung_disease.htm

    Active Physicians (2019)

    https://www.kff.org/other/state-indicator/total-active-physicians/

    Hospitals (2018)

    https://www.kff.org/other/state-indicator/total-hospitals

    Health spending per capita

    Includes spending for all health care services and products by state of residence. Hospital spending is included and reflects the total net revenue. Costs such as insurance, administration, research, and construction expenses are not included.
    https://www.kff.org/other/state-indicator/avg-annual-growth-per-capita/

    Pollution (2019)

    Pollution: Average exposure of the general public to particulate matter of 2.5 microns or less (PM2.5) measured in micrograms per cubic meter (3-year estimate)
    https://www.americashealthrankings.org/explore/annual/measure/air/state/ALL

    Medium and Large Airports

    For each state, number of medium and large airports https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_the_United_States

    Temperature (2019)

    Note that FL was incorrect in the table, but is corrected in the Hottest States paragraph
    https://worldpopulationreview.com/states/average-temperatures-by-state/
    District of Columbia temperature computed as the average of Maryland and Virginia

    Urbanization (2010)

    Urbanization as a percentage of the population https://www.icip.iastate.edu/tables/population/urban-pct-states

    Age Groups (2018)

    https://www.kff.org/other/state-indicator/distribution-by-age/

    School Closure Dates

    Schools that haven't closed are marked NaN https://www.edweek.org/ew/section/multimedia/map-coronavirus-and-school-closures.html

    Note that some datasets above did not contain data for District of Columbia, this missing data was found via Google searches manually entered.

    --- Original source retains full ownership of the source dataset ---

  4. f

    The Annual Burden of Seasonal Influenza in the US Veterans Affairs...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    tiff
    Updated May 31, 2023
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    Yinong Young-Xu; Robertus van Aalst; Ellyn Russo; Jason K. H. Lee; Ayman Chit (2023). The Annual Burden of Seasonal Influenza in the US Veterans Affairs Population [Dataset]. http://doi.org/10.1371/journal.pone.0169344
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    tiffAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Yinong Young-Xu; Robertus van Aalst; Ellyn Russo; Jason K. H. Lee; Ayman Chit
    License

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

    Description

    Seasonal influenza epidemics have a substantial public health and economic burden in the United States (US). On average, over 200,000 people are hospitalized and an estimated 23,000 people die from respiratory and circulatory complications associated with seasonal influenza virus infections each year. Annual direct medical costs and indirect productivity costs across the US have been found to average respectively at $10.4 billion and $16.3 billion. The objective of this study was to estimate the economic impact of severe influenza-induced illness on the US Veterans Affairs population. The five-year study period included 2010 through 2014. Influenza-attributed outcomes were estimated with a statistical regression model using observed emergency department (ED) visits, hospitalizations, and deaths from the Veterans Health Administration of the Department of Veterans Affairs (VA) electronic medical records and respiratory viral surveillance data from the Centers for Disease Control and Prevention (CDC). Data from VA’s Managerial Cost Accounting system were used to estimate the costs of the emergency department and hospital visits. Data from the Bureau of Labor Statistics were used to estimate the costs of lost productivity; data on age at death, life expectancy and economic valuations for a statistical life year were used to estimate the costs of a premature death. An estimated 10,674 (95% CI 8,661–12,687) VA ED visits, 2,538 (95% CI 2,112–2,964) VA hospitalizations, 5,522 (95% CI 4,834–6,210) all-cause deaths, and 3,793 (95% CI 3,375–4,211) underlying respiratory or circulatory deaths (inside and outside VA) among adult Veterans were attributable to influenza each year from 2010 through 2014. The annual value of lost productivity amounted to $27 (95% CI $24–31) million and the annual costs for ED visits were $6.2 (95% CI $5.1–7.4) million. Ninety-six percent of VA hospitalizations resulted in either death or a discharge to home, with annual costs totaling $36 (95% CI $30–43) million. The remaining 4% of hospitalizations were followed by extended care at rehabilitation and skilled nursing facilities with annual costs totaling $5.5 (95% CI $4.4–6.8) million. The annual monetary value of quality-adjusted life years (QALYs) lost amounted to $1.1 (95% CI $1.0–1.2) billion. In total, the estimated annual economic burden was $1.2 (95% CI $1.0–1.3) billion, indicating the substantial burden of seasonal influenza epidemics on the US Veterans Affairs population. Premature death was found to be the largest driver of these costs, followed by hospitalization.

  5. The FluPRINT

    • kaggle.com
    Updated Jan 25, 2021
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    LogIN (2021). The FluPRINT [Dataset]. https://www.kaggle.com/datasets/genular/fluprint
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 25, 2021
    Dataset provided by
    Kaggle
    Authors
    LogIN
    License

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

    Description

    https://fluprint.com/about/section_1.png" alt="Influenza vaccination responders">

    The problem

    Influenza virus has a devastating societal impact, causing up to 650,000 deaths every year worldwide. Specifically, vulnerable are children and elderly. It is estimated that 1 in 1000 children and elderly every year are hospitalized due to influenza infection. Vaccination can prevent influenza-like illnesses, and thus lower the risk of the virus outbreak. However, currently available vaccines do not always provide protection, even among otherwise-healthy people, leading to serious pandemics. Development of better vaccines depends on our understanding why current vaccines work in some individuals, while fail in others.

    About dataset

    The FluPRINT is the name of a unified database for a large-scale study exploring novel cellular and molecular underpinnings of successful immunity to influenza vaccines. It contains information on more than 3,000 parameters measured using mass cytometry, flow cytometry, phosphorylation-specific cytometry (phospho-flow), multiplex ELISA, clinical lab tests (hormones and complete blood count), serological profiling with hemagglutination inhibition assay, and virological tests. The dataset represents fully integrated and normalized immunology measurements from 747 individuals from eight clinical studies conducted between 2007 to 2015 at the Human Immune Monitoring Center of Stanford University. The dataset represents a unique source in terms of value and scale, which will broaden our understanding of influenza immunity.

    Additional info: https://zenodo.org/record/3222451#.XOb7MaR7lPY

    Citation

    Tomic A, Tomic I, Dekker CL, Maecker HT and Davis MM. The FluPRINT dataset, a multidimensional analysis of the influenza vaccine imprint on the immune system. Sci Data, doi: 10.1038/s41597-019-0213-4, 2019. 
    
  6. C

    Influenza Vaccination Coverage, ZIP Code

    • data.cityofchicago.org
    • catalog.data.gov
    Updated Jun 4, 2025
    + more versions
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    City of Chicago (2025). Influenza Vaccination Coverage, ZIP Code [Dataset]. https://data.cityofchicago.org/Health-Human-Services/Influenza-Vaccination-Coverage-ZIP-Code/nxdn-bvae
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    xlsx, application/geo+json, kml, csv, kmz, xmlAvailable download formats
    Dataset updated
    Jun 4, 2025
    Dataset authored and provided by
    City of Chicago
    Description

    Chicago residents who are up to date with influenza vaccines by ZIP Code, based on the reported home address and age group of the person vaccinated, as provided by the medical provider in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE).

    “Up to date” refers to individuals aged 6 months and older who have received 1+ doses of influenza vaccine during the current season, defined as the beginning of July (MMWR week 27) through the end of the following June (MMWR week 26).

    Data Notes:

    Weekly cumulative totals of people up to date are shown for each combination ZIP Code and age group. Note there are rows where age group is "All ages" so care should be taken when summing rows. Weeks begin on a Sunday and end on a Saturday.

    Coverage percentages are calculated based on the cumulative number of people in each ZIP Code and age group who are considered up to date as of the week ending date divided by the estimated number of people in that subgroup. Population counts are obtained from the 2020 U.S. Decennial Census. For ZIP Codes mostly outside Chicago, coverage percentages are not calculated because reliable Chicago-only population counts are not available. Actual counts may exceed population estimates and lead to coverage estimates that are greater than 100%, especially in smaller ZIP Codes with smaller populations. Additionally, the medical provider may report a work address or incorrect home address for the person receiving the vaccination, which may lead to over- or underestimation of vaccination coverage by geography. All coverage percentages are capped at 99%.

    The Chicago Department of Public Health (CDPH) uses the most complete data available to estimate influenza vaccination coverage among Chicagoans, but there are several limitations that impact our estimates. Influenza vaccine administration is not required to be reported in Illinois, except for publicly funded vaccine (e.g., Vaccines for Children, Section 317). Individuals may receive vaccinations that are not recorded in I-CARE, such as those administered in another state, or those administered by a provider that does not submit data to I-CARE, causing underestimation of the number individuals who received an influenza vaccine for the current season.

    All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects data currently known to CDPH.

    Numbers in this dataset may differ from other public sources due to when data are reported and how City of Chicago boundaries are defined.

    For all datasets related to influenza, see https://data.cityofchicago.org/browse?limitTo=datasets&sortBy=alpha&tags=flu .

    Data Source: Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE), U.S. Census Bureau 2020 Decennial Census

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

    • www150.statcan.gc.ca
    • open.canada.ca
    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
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    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.

  8. COVID-19 State Data

    • kaggle.com
    zip
    Updated Apr 5, 2020
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    Night Ranger (2020). COVID-19 State Data [Dataset]. https://www.kaggle.com/nightranger77/covid19-state-data
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    zip(4385 bytes)Available download formats
    Dataset updated
    Apr 5, 2020
    Authors
    Night Ranger
    Description

    This dataset is a per-state amalgamation of demographic, public health and other relevant predictors for COVID-19.

    Deaths, Infections and Tests by State

    Coronavirus API http://coronavirusapi.com/states.csv

    Predictor Data and Sources

    Testing data per state

    http://coronavirusapi.com/states.csv

    Population (2020)

    Density is people per meter squared https://worldpopulationreview.com/states/

    ICU Beds and Age 60+

    https://khn.org/news/as-coronavirus-spreads-widely-millions-of-older-americans-live-in-counties-with-no-icu-beds/

    GDP

    https://worldpopulationreview.com/states/gdp-by-state/

    Income per capita (2018)

    https://worldpopulationreview.com/states/per-capita-income-by-state/

    Gini

    https://en.wikipedia.org/wiki/List_of_U.S._states_by_Gini_coefficient

    Unemployment (2020)

    Rates from Feb 2020 and are percentage of labor force
    https://www.bls.gov/web/laus/laumstrk.htm

    Sex (2017)

    Ratio is Male / Female
    https://www.kff.org/other/state-indicator/distribution-by-gender/

    Smoking Percentage (2020)

    https://worldpopulationreview.com/states/smoking-rates-by-state/

    Influenza and Pneumonia Death Rate (2018)

    Death rate per 100,000 people
    https://www.cdc.gov/nchs/pressroom/sosmap/flu_pneumonia_mortality/flu_pneumonia.htm

    Chronic Lower Respiratory Disease Death Rate (2018)

    Death rate per 100,000 people
    https://www.cdc.gov/nchs/pressroom/sosmap/lung_disease_mortality/lung_disease.htm

    Active Physicians (2019)

    https://www.kff.org/other/state-indicator/total-active-physicians/

    Hospitals (2018)

    https://www.kff.org/other/state-indicator/total-hospitals

    Health spending per capita

    Includes spending for all health care services and products by state of residence. Hospital spending is included and reflects the total net revenue. Costs such as insurance, administration, research, and construction expenses are not included.
    https://www.kff.org/other/state-indicator/avg-annual-growth-per-capita/

    Pollution (2019)

    Pollution: Average exposure of the general public to particulate matter of 2.5 microns or less (PM2.5) measured in micrograms per cubic meter (3-year estimate)
    https://www.americashealthrankings.org/explore/annual/measure/air/state/ALL

    Medium and Large Airports

    For each state, number of medium and large airports https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_the_United_States

    Temperature (2019)

    Note that FL was incorrect in the table, but is corrected in the Hottest States paragraph
    https://worldpopulationreview.com/states/average-temperatures-by-state/
    District of Columbia temperature computed as the average of Maryland and Virginia

    Urbanization (2010)

    Urbanization as a percentage of the population https://www.icip.iastate.edu/tables/population/urban-pct-states

    Age Groups (2018)

    https://www.kff.org/other/state-indicator/distribution-by-age/

    School Closure Dates

    Schools that haven't closed are marked NaN https://www.edweek.org/ew/section/multimedia/map-coronavirus-and-school-closures.html

    Note that some datasets above did not contain data for District of Columbia, this missing data was found via Google searches manually entered.

  9. Deaths by vaccination status, England

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Aug 25, 2023
    + more versions
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    Office for National Statistics (2023). Deaths by vaccination status, England [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/deathsbyvaccinationstatusengland
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    xlsxAvailable download formats
    Dataset updated
    Aug 25, 2023
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Age-standardised mortality rates for deaths involving coronavirus (COVID-19), non-COVID-19 deaths and all deaths by vaccination status, broken down by age group.

  10. Provisional COVID-19 Deaths by Sex and Age

    • catalog.data.gov
    • healthdata.gov
    • +5more
    Updated Apr 23, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). Provisional COVID-19 Deaths by Sex and Age [Dataset]. https://catalog.data.gov/dataset/provisional-covid-19-death-counts-by-sex-age-and-state
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    Dataset updated
    Apr 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    Effective September 27, 2023, this dataset will no longer be updated. Similar data are accessible from wonder.cdc.gov. Deaths involving COVID-19, pneumonia, and influenza reported to NCHS by sex, age group, and jurisdiction of occurrence.

  11. v

    Influenza Vaccination Coverage, Region (HCEZ)

    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    Updated Jul 12, 2025
    + more versions
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    data.cityofchicago.org (2025). Influenza Vaccination Coverage, Region (HCEZ) [Dataset]. https://res1catalogd-o-tdatad-o-tgov.vcapture.xyz/dataset/influenza-vaccination-coverage-region-hcez
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    Dataset updated
    Jul 12, 2025
    Dataset provided by
    data.cityofchicago.org
    Description

    Chicago residents who are up to date with influenza vaccines by Healthy Chicago Equity Zone (HCEZ), based on the reported address, race-ethnicity, and age group of the person vaccinated, as provided by the medical provider in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE). Healthy Chicago Equity Zones is an initiative of the Chicago Department of Public Health to organize and support hyperlocal, community-led efforts that promote health and racial equity. Chicago is divided into six HCEZs. Combinations of Chicago’s 77 community areas make up each HCEZ, based on geography. For more information about HCEZs including which community areas are in each zone see: https://res1datad-o-tcityofchicagod-o-torg.vcapture.xyz/Health-Human-Services/Healthy-Chicago-Equity-Zones/nk2j-663f “Up to date” refers to individuals aged 6 months and older who have received 1+ doses of influenza vaccine during the current season, defined as the beginning of July (MMWR week 27) through the end of the following June (MMWR week 26). Data notes: Weekly cumulative totals of people up to date are shown for each combination of race-ethnicity and age group within an HCEZ. Note that each HCEZ has a row where HCEZ is “Citywide” and each HCEZ has a row where age is "All" and race-ethnicity is “All Race/Ethnicity Groups” so care should be taken when summing rows. Weeks begin on a Sunday and end on a Saturday. Coverage percentages are calculated based on the cumulative number of people in each population subgroup (age group by race-ethnicity within an HCEZ) who are up to date, divided by the estimated number of people in that subgroup. Population counts are from the 2020 U.S. Decennial Census. Actual counts may exceed population estimates and lead to >100% coverage, especially in small race-ethnicity subgroups of each age group within an HCEZ. All coverage percentages are capped at 99%. Summing all race/ethnicity group populations to obtain citywide populations may provide a population count that differs slightly from the citywide population count listed in the dataset. Differences in these estimates are due to how community area populations are calculated. The Chicago Department of Public Health (CDPH) uses the most complete data available to estimate influenza vaccination coverage among Chicagoans, but there are several limitations that impact our estimates. Influenza vaccine administration is not required to be reported in Illinois, except for publicly funded vaccine (e.g., Vaccines for Children, Section 317). Individuals may receive vaccinations that are not recorded in I-CARE, such as those administered in another state, or those administered by a provider that does not submit data to I-CARE, causing underestimation of the number individuals who received an influenza vaccine for the current season. All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources due to when data are reported and how City of Chicago boundaries are defined. For all datasets related to influenza, see https://res1datad-o-tcityofchicagod-o-torg.vcapture.xyz/browse?limitTo=datasets&sortBy=alpha&tags=flu . Data Source: Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE), U.S. Census Bureau 2020 Decennial Census

  12. SHIP Annual Season Influenza Vaccinations 2011-2021

    • healthdata.gov
    • opendata.maryland.gov
    • +1more
    application/rdfxml +5
    Updated Apr 8, 2025
    + more versions
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    opendata.maryland.gov (2025). SHIP Annual Season Influenza Vaccinations 2011-2021 [Dataset]. https://healthdata.gov/State/SHIP-Annual-Season-Influenza-Vaccinations-2011-202/yj7s-xrxn/data
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    xml, application/rdfxml, csv, json, application/rssxml, tsvAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    opendata.maryland.gov
    Description

    This is historical data. The update frequency has been set to "Static Data" and is here for historic value. Updated on 8/14/2024

    Annual Season Influenza Vaccinations - This indicator shows the percentage of adults who are vaccinated annually against seasonal influenza. For many people, the seasonal flu is a mild illness, but for some it can lead to pneumonia, hospitalization, or death. Vaccination of persons in high-risk populations is especially important to reduce their risk of severe illness or death. Link to Data Details

  13. Health Care Personnel Influenza Vaccination

    • data.chhs.ca.gov
    • data.ca.gov
    • +2more
    csv, xlsx, zip
    Updated Aug 6, 2025
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    California Department of Public Health (2025). Health Care Personnel Influenza Vaccination [Dataset]. https://data.chhs.ca.gov/dataset/cdph-health-care-personnel-influenza-vaccination
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    xlsx(51293), xlsx, xlsx(13377), xlsx(51573), xlsx(50725), csv(12941), xlsx(13339), xlsx(13542), csv(9253), csv(80314), xlsx(12105), csv(78652), xlsx(13453), xlsx(101592), xlsx(15900), xlsx(13022), xlsx(7337), csv(8825), xlsx(9860), zip, xlsx(13350), xlsx(13494), xlsx(13055), xlsx(61182), xlsx(13141), xlsx(13514), xlsx(15937), xlsx(15983), xlsx(15397), xlsx(62110), csv(111370), xlsx(13718)Available download formats
    Dataset updated
    Aug 6, 2025
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    Description

    Health and Safety Code section 1288.7(a) requires California acute care hospitals to offer influenza vaccine free of charge to all healthcare providers (HCP) or sign a declination form if a HCP chooses not to be vaccinated. Hospitals must report HCP influenza vaccination data to the California Department of Public Health (CDPH), including the percentage of HCP vaccinated. CDPH is required to make this information public on an annual basis [Health and Safety Code section 1288.8 (b)].

    California acute care hospitals are required to offer free influenza vaccine to HCP. Hospital HCP must receive an annual vaccine or sign a declination form. Hospitals collect vaccination data for all HCP physically working in the hospital for at least one day during influenza season, regardless of clinical responsibility or patient contact. Hospitals report HCP vaccination rates to the California Department of Public Health (CDPH) and CDPH publishes the hospital results annually. CDPH reports data separately for hospital employees, licensed independent practitioners such as physicians, other contract staff, and trainees and volunteers (Health and Safety Code section 1288.7-1288.8).

    Detailed information about the variables included in each dataset are described in the accompanying data dictionaries for the year of interest.

    For general information about NHSN, surveillance definitions, and reporting requirements for HCP influenza vaccination, please visit: https://www.cdc.gov/nhsn/hps/vaccination/index.html

    To link the CDPH facility IDs with those from other Departments, including OSHPD, please reference the "Licensed Facility Cross-Walk" Open Data table at: https://data.chhs.ca.gov/dataset/licensed-facility-crosswalk.

    For information about healthcare personnel influenza vaccinations in California hospitals, please visit: https://www.cdph.ca.gov/Programs/CHCQ/HAI/Pages/HealthcarePersonnelInfluenzaVaccinationReportingInCA_Hospitals.aspx

  14. b

    Vaccination coverage: Flu (at risk individuals) - WMCA

    • cityobservatory.birmingham.gov.uk
    csv, excel, geojson +1
    Updated Sep 3, 2025
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    (2025). Vaccination coverage: Flu (at risk individuals) - WMCA [Dataset]. https://cityobservatory.birmingham.gov.uk/explore/dataset/vaccination-coverage-flu-at-risk-individuals-wmca/
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    json, excel, geojson, csvAvailable download formats
    Dataset updated
    Sep 3, 2025
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Flu vaccine uptake (percent) in at risk individuals aged 6 months to 65 years (excluding pregnant women), who received the flu vaccination between 1st September to the end of February as recorded in the GP record. The February collection has been adopted for our end of season figures from 2017 to 2018. All previous data is the same definitions but until the end of January rather than February to consider data returning from outside the practice and later in practice vaccinations.RationaleInfluenza (also known as Flu) is a highly infectious viral illness spread by droplet infection. The flu vaccination is offered to people who are at greater risk of developing serious complications if they catch the flu. The seasonal influenza programme for England is set out in the Annual Flu Letter. Both the flu letter and the flu plan have the support of the Chief Medical Officer (CMO), Chief Pharmaceutical Officer (CPhO), and Director of Nursing.Vaccination coverage is the best indicator of the level of protection a population will have against vaccine-preventable communicable diseases. Immunisation is one of the most effective healthcare interventions available, and flu vaccines can prevent illness and hospital admissions among these groups of people. Increasing the uptake of the flu vaccine among these high-risk groups should also contribute to easing winter pressure on primary care services and hospital admissions. Coverage is closely related to levels of disease. Monitoring coverage identifies possible drops in immunity before levels of disease rise.The UK Health Security Agency (UKHSA) will continue to provide expert advice and monitoring of public health, including immunisation. NHS England now has responsibility for commissioning the flu programme, and GPs continue to play a key role. NHS England teams will ensure that robust plans are in place locally and that high vaccination uptake levels are reached in the clinical risk groups. For more information, see the Green Book chapter 19 on Influenza.The Annual Flu Letter sets out the national vaccine uptake ambitions each year. In 2021 to 2022, the national ambition was to achieve at least 85 percent vaccine uptake in those aged 65 and over. Prior to this, the national vaccine uptake ambition was 75 percent, in line with WHO targets.Definition of numeratorNumerator is the number of vaccinations administered during the influenza season between 1st September and the end of February.Definition of denominatorDenominator is the GP registered population on the date of extraction including patients who have been offered the vaccine but refused it, as the uptake rate is measured against the overall eligible population. For more detailed information please see the user guide, available to view and download from https://www.gov.uk/government/collections/vaccine-uptake#seasonal-flu-vaccine-uptakeCaveatsRead codes are primarily used for data collection purposes to extract vaccine uptake data for patients who fall into one or more of the designated clinical risk groups. The codes identify individuals at risk, and therefore eligible for flu vaccination. However, it is important to note that there may be some individuals with conditions not specified in the recommended risk groups for vaccination, who may be offered influenza vaccine by their GP based on clinical judgement and according to advice contained in the flu letter and Green Book, and thus are likely to fall outside the listed Read codes. Therefore, this data should not be used for GP payment purposes.

  15. D

    Provisional COVID-19 Death Counts by Week Ending Date and State

    • data.cdc.gov
    • healthdata.gov
    • +7more
    csv, xlsx, xml
    Updated Aug 21, 2025
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    NCHS/DVS (2025). Provisional COVID-19 Death Counts by Week Ending Date and State [Dataset]. https://data.cdc.gov/National-Center-for-Health-Statistics/Provisional-COVID-19-Death-Counts-by-Week-Ending-D/r8kw-7aab
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    xml, csv, xlsxAvailable download formats
    Dataset updated
    Aug 21, 2025
    Dataset authored and provided by
    NCHS/DVS
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    Effective September 27, 2023, this dataset will be updated weekly on Thursdays.

    Deaths involving COVID-19, pneumonia, and influenza reported to NCHS by week ending date and by state

  16. A

    10to12 Iquery Flu Data

    • data.amerigeoss.org
    csv, json, rdf, xml
    Updated Jul 27, 2019
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    United States[old] (2019). 10to12 Iquery Flu Data [Dataset]. https://data.amerigeoss.org/ca/dataset/10to12-iquery-flu-data-0fc7d
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    json, csv, rdf, xmlAvailable download formats
    Dataset updated
    Jul 27, 2019
    Dataset provided by
    United States[old]
    Description

    The reported number of illnesses caused by strains of the Influenza virus that required the case to be in the Intensive Care Unit (ICU) during a hospital stay. Influenza, commonly called "the flu," is an infection of the respiratory tract caused by the influenza virus. Compared with most viral respiratory infections, such as the common cold, influenza infection often causes a more severe illness. Typical influenza illness includes fever (usually 100 degrees F to 103 degrees F in adults and often even higher in children) and respiratory symptoms, such as cough, sore throat, runny or stuffy nose, as well as headache, muscle aches and extreme fatigue. Although nausea, vomiting and diarrhea can sometimes accompany influenza infection, especially in children, these symptoms are rarely the primary symptoms. The term "stomach flu" is a misnomer that is sometimes used to describe gastrointestinal illnesses caused by organisms other than influenza viruses. During most flu seasons, which typically run from November to April, between 10 percent and 20 percent of the population is infected with influenza viruses. Most people who get the flu recover completely in 1 to 2 weeks, but some people develop serious and potentially life-threatening medical complications, such as pneumonia. Flu-related complications can occur at any age, but the elderly and people with chronic health problems are much more likely to develop serious complications after influenza infection than are young, healthier people. Since 2010, IDPH has collected information about influenza cases that required Intensive Care Unit (ICU) hospitalization as a way to measure the severity of disease.

  17. Dataset from A Phase III Study for Evaluation of Immunogenicity and...

    • data.niaid.nih.gov
    Updated Nov 27, 2024
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    GSK Clinical Trials (2024). Dataset from A Phase III Study for Evaluation of Immunogenicity and Reactogenicity of Fluarix™ (Influsplit SSW®) 2006/2007 in People Aged 18 Years or Above [Dataset]. http://doi.org/10.25934/00000357
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    Dataset updated
    Nov 27, 2024
    Dataset provided by
    GSK plchttp://gsk.com/
    Authors
    GSK Clinical Trials
    Area covered
    Germany
    Variables measured
    Adverse Event, Vaccine Response, Serious Adverse Event
    Description

    Vaccination is currently the most effective mean of controlling influenza and preventing its complications and mortality in persons at risk. Because of the variable nature of influenza viruses, the composition of influenza vaccines changes almost every year, to target the 3 main circulating strains. Each year the influenza vaccine formulation may thus be different and clinical studies are mandated to ensure that the immunogenicity and safety of the vaccine formulated from the three annual circulating strains are similar to what was observed during the previous years. This study is designed to test the immunogenicity and reactogenicity of the Fluarix™ vaccine containing the influenza strains recommended for the 2006-2007 season.

  18. V

    Dataset from VRC 304: A Phase I Study of the Safety and Immunogenicity of a...

    • data.niaid.nih.gov
    Updated Feb 6, 2025
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    ImmPort (a data-sharing platform funded by the National Institutes of Health) (2025). Dataset from VRC 304: A Phase I Study of the Safety and Immunogenicity of a Recombinant DNA Plasmid Vaccine (VRC-AVIDNA036-00-VP), Encoding for the Influenza Virus H5 Hemagglutinin Protein in Healthy Adults [Dataset]. http://doi.org/10.25934/00000445
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    Dataset updated
    Feb 6, 2025
    Dataset authored and provided by
    ImmPort (a data-sharing platform funded by the National Institutes of Health)
    Area covered
    United States
    Variables measured
    Response To Immunization
    Description

    This study will determine if an experimental avian flu (bird flu) vaccine is safe, whether it has side effects and if it can stimulate an immune response in people. The vaccine being tested in this study is made from DNA (genetic material) that codes for an influenza protein called hemagglutinin 5 (H5), which is based on the protein from the bird flu virus. The study will determine if the body creates resistance or immunity to the H5 protein. The hope is that an immune response to this protein may protect against bird flu virus infection. Healthy people between 18 and 60 years old who have been vaccinated with the current season's influenza vaccine may be eligible for this study. Participants are randomly assigned to receive injections of one of the following: 1) study vaccine at 1 mg dose, 2) study vaccine at 4 mg dose, or 3) placebo (salt-water solution). They receive three injections about 4 weeks apart in the upper arm muscle. Participants record their temperature and symptoms at home for 5 days after each injection, either on a diary card or electronically using the Internet, and report any side effects to a study physician or nurse as soon as possible. They return to NIH for clinic visits every 2 weeks for the first 12 weeks, then at week 26 and at week 42 to check for health changes or problems. Blood is drawn at all visits and urine samples are collected through week 10. If a participant develops serious side effects, the study physician may decide that he or she should not receive any further injections. However, all participants are asked to continue the follow-up visits even if they do not get the full set of three injections.

  19. Preliminary 2024-2025 U.S. COVID-19 Burden Estimates

    • data.cdc.gov
    • healthdata.gov
    • +1more
    csv, xlsx, xml
    Updated Sep 5, 2025
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    Coronavirus and Other Respiratory Viruses Division (CORVD), National Center for Immunization and Respiratory Diseases (NCIRD). (2025). Preliminary 2024-2025 U.S. COVID-19 Burden Estimates [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/Preliminary-2024-2025-U-S-COVID-19-Burden-Estimate/ahrf-yqdt
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    xlsx, csv, xmlAvailable download formats
    Dataset updated
    Sep 5, 2025
    Dataset provided by
    National Center for Immunization and Respiratory Diseases
    Authors
    Coronavirus and Other Respiratory Viruses Division (CORVD), National Center for Immunization and Respiratory Diseases (NCIRD).
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Area covered
    United States
    Description

    This dataset represents preliminary estimates of cumulative U.S. COVID-19 disease burden for the 2024-2025 period, including illnesses, outpatient visits, hospitalizations, and deaths. The weekly COVID-19-associated burden estimates are preliminary and based on continuously collected surveillance data from patients hospitalized with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. The data come from the Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET), a surveillance platform that captures data from hospitals that serve about 10% of the U.S. population. Each week CDC estimates a range (i.e., lower estimate and an upper estimate) of COVID-19 -associated burden that have occurred since October 1, 2024.

    Note: Data are preliminary and subject to change as more data become available. Rates for recent COVID-19-associated hospital admissions are subject to reporting delays; as new data are received each week, previous rates are updated accordingly.

    References

    1. Reed C, Chaves SS, Daily Kirley P, et al. Estimating influenza disease burden from population-based surveillance data in the United States. PLoS One. 2015;10(3):e0118369. https://doi.org/10.1371/journal.pone.0118369 
    2. Rolfes, MA, Foppa, IM, Garg, S, et al. Annual estimates of the burden of seasonal influenza in the United States: A tool for strengthening influenza surveillance and preparedness. Influenza Other Respi Viruses. 2018; 12: 132– 137. https://doi.org/10.1111/irv.12486
    3. Tokars JI, Rolfes MA, Foppa IM, Reed C. An evaluation and update of methods for estimating the number of influenza cases averted by vaccination in the United States. Vaccine. 2018;36(48):7331-7337. doi:10.1016/j.vaccine.2018.10.026 
    4. Collier SA, Deng L, Adam EA, Benedict KM, Beshearse EM, Blackstock AJ, Bruce BB, Derado G, Edens C, Fullerton KE, Gargano JW, Geissler AL, Hall AJ, Havelaar AH, Hill VR, Hoekstra RM, Reddy SC, Scallan E, Stokes EK, Yoder JS, Beach MJ. Estimate of Burden and Direct Healthcare Cost of Infectious Waterborne Disease in the United States. Emerg Infect Dis. 2021 Jan;27(1):140-149. doi: 10.3201/eid2701.190676. PMID: 33350905; PMCID: PMC7774540.
    5. Reed C, Kim IK, Singleton JA,  et al. Estimated influenza illnesses and hospitalizations averted by vaccination–United States, 2013-14 influenza season. MMWR Morb Mortal Wkly Rep. 2014 Dec 12;63(49):1151-4. https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6349a2.htm 
    6. Reed C, Angulo FJ, Swerdlow DL, et al. Estimates of the Prevalence of Pandemic (H1N1) 2009, United States, April–July 2009. Emerg Infect Dis. 2009;15(12):2004-2007. https://dx.doi.org/10.3201/eid1512.091413
    7. Devine O, Pham H, Gunnels B, et al. Extrapolating Sentinel Surveillance Information to Estimate National COVID-19 Hospital Admission Rates: A Bayesian Modeling Approach. Influenza and Other Respiratory Viruses. https://onlinelibrary.wiley.com/doi/10.1111/irv.70026. Volume18, Issue10. October 2024.
    8. https://www.cdc.gov/covid/php/covid-net/index.html">COVID-NET | COVID-19 | CDC 
    9. https://www.cdc.gov/covid/hcp/clinical-care/systematic-review-process.html 
    10. https://academic.oup.com/pnasnexus/article/1/3/pgac079/6604394?login=false">Excess natural-cause deaths in California by cause and setting: March 2020 through February 2021 | PNAS Nexus | Oxford Academic (oup.com)
    11. Kruschke, J. K. 2011. Doing Bayesian data analysis: a tutorial with R and BUGS. Elsevier, Amsterdam, Section 3.3.5.

  20. f

    Table_3_VaximmutorDB: A Web-Based Vaccine Immune Factor Database and Its...

    • figshare.com
    xlsx
    Updated Jun 8, 2023
    + more versions
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    Kimberly Berke; Peter Sun; Edison Ong; Nasim Sanati; Anthony Huffman; Timothy Brunson; Fred Loney; Joseph Ostrow; Rebecca Racz; Bin Zhao; Zuoshuang Xiang; Anna Maria Masci; Jie Zheng; Guanming Wu; Yongqun He (2023). Table_3_VaximmutorDB: A Web-Based Vaccine Immune Factor Database and Its Application for Understanding Vaccine-Induced Immune Mechanisms.XLSX [Dataset]. http://doi.org/10.3389/fimmu.2021.639491.s007
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    xlsxAvailable download formats
    Dataset updated
    Jun 8, 2023
    Dataset provided by
    Frontiers
    Authors
    Kimberly Berke; Peter Sun; Edison Ong; Nasim Sanati; Anthony Huffman; Timothy Brunson; Fred Loney; Joseph Ostrow; Rebecca Racz; Bin Zhao; Zuoshuang Xiang; Anna Maria Masci; Jie Zheng; Guanming Wu; Yongqun He
    License

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

    Description

    Vaccines stimulate various immune factors critical to protective immune responses. However, a comprehensive picture of vaccine-induced immune factors and pathways have not been systematically collected and analyzed. To address this issue, we developed VaximmutorDB, a web-based database system of vaccine immune factors (abbreviated as “vaximmutors”) manually curated from peer-reviewed articles. VaximmutorDB currently stores 1,740 vaccine immune factors from 13 host species (e.g., human, mouse, and pig). These vaximmutors were induced by 154 vaccines for 46 pathogens. Top 10 vaximmutors include three antibodies (IgG, IgG2a and IgG1), Th1 immune factors (IFN-γ and IL-2), Th2 immune factors (IL-4 and IL-6), TNF-α, CASP-1, and TLR8. Many enriched host processes (e.g., stimulatory C-type lectin receptor signaling pathway, SRP-dependent cotranslational protein targeting to membrane) and cellular components (e.g., extracellular exosome, nucleoplasm) by all the vaximmutors were identified. Using influenza as a model, live attenuated and killed inactivated influenza vaccines stimulate many shared pathways such as signaling of many interleukins (including IL-1, IL-4, IL-6, IL-13, IL-20, and IL-27), interferon signaling, MARK1 activation, and neutrophil degranulation. However, they also present their unique response patterns. While live attenuated influenza vaccine FluMist induced significant signal transduction responses, killed inactivated influenza vaccine Fluarix induced significant metabolism of protein responses. Two different Yellow Fever vaccine (YF-Vax) studies resulted in overlapping gene lists; however, they shared more portions of pathways than gene lists. Interestingly, live attenuated YF-Vax simulates significant metabolism of protein responses, which was similar to the pattern induced by killed inactivated Fluarix. A user-friendly web interface was generated to access, browse and search the VaximmutorDB database information. As the first web-based database of vaccine immune factors, VaximmutorDB provides systematical collection, standardization, storage, and analysis of experimentally verified vaccine immune factors, supporting better understanding of protective vaccine immunity.

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Centers for Disease Control and Prevention (2025). Provisional Death Counts for Influenza, Pneumonia, and COVID-19 [Dataset]. https://catalog.data.gov/dataset/provisional-death-counts-for-influenza-pneumonia-and-covid-19
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Provisional Death Counts for Influenza, Pneumonia, and COVID-19

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Dataset updated
Apr 23, 2025
Dataset provided by
Centers for Disease Control and Preventionhttp://www.cdc.gov/
Description

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

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