66 datasets found
  1. d

    Compendium – Mortality from respiratory disease

    • digital.nhs.uk
    csv, xls
    Updated Jul 21, 2022
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    (2022). Compendium – Mortality from respiratory disease [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/compendium-mortality/current/mortality-from-respiratory-diseases
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    xls(54.8 kB), csv(14.8 kB)Available download formats
    Dataset updated
    Jul 21, 2022
    License

    https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

    Time period covered
    Jan 1, 2018 - Dec 31, 2020
    Area covered
    Wales, England
    Description

    Mortality from pneumonia (ICD-10 J12-J18 equivalent to ICD-9 480-486). To reduce deaths from pneumonia. Legacy unique identifier: P00597

  2. Deaths by influenza and pneumonia in the U.S. 1950-2023

    • statista.com
    • abripper.com
    Updated Nov 29, 2025
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    Statista (2025). Deaths by influenza and pneumonia in the U.S. 1950-2023 [Dataset]. https://www.statista.com/statistics/184574/deaths-by-influenza-and-pneumonia-in-the-us-since-1950/
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    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Influenza and pneumonia caused around 10.9 deaths in the U.S. per 100,000 population in 2023. Influenza, or the flu, is a viral infection that is highly contagious and especially common in the winter season. Influenza is a common cause of pneumonia, although most cases of the flu do not develop into pneumonia. Pneumonia is an infection or inflammation of the lungs and is particularly deadly among young children and the elderly. Influenza cases Influenza is very common in the United States, with an estimated 40 million cases reported in 2023-2024. Common symptoms of the flu include cough, fever, runny or stuffy nose, sore throat and headache. Symptoms can be mild but can also be severe enough to require medical attention. In 2023-2024, there were around 18 million influenza-related medical visits in the United States. Prevention To prevent contracting the flu, people can take everyday precautions such as regularly washing their hands and avoiding those who are sick, but the best way to prevent the flu is by receiving the flu vaccination every year. Receiving a flu vaccination is especially important for young children and the elderly, as they are most susceptible to flu complications and associated death. In 2024, around 70 percent of those aged 65 years and older received a flu vaccine, while only 33 percent of those aged 18 to 49 years had done so.

  3. u

    Pneumonia death rates by county, 2019-2023 - Dataset - Healthy Communities...

    • midb.uspatial.umn.edu
    Updated Oct 24, 2025
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    (2025). Pneumonia death rates by county, 2019-2023 - Dataset - Healthy Communities Data Portal [Dataset]. https://midb.uspatial.umn.edu/hcdp/dataset/pneumonia-death-rates-by-county-2019-2023
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    Dataset updated
    Oct 24, 2025
    Description

    Pneumonia death rates by county, all races (includes Hispanic/Latino), all sexes, all ages, 2019-2023. Death data were provided by the National Vital Statistics System. Death rates (deaths per 100,000 population per year) are age-adjusted to the 2000 US standard population (20 age groups: <1, 1-4, 5-9, ... , 80-84, 85-89, 90+). Rates calculated using SEER*Stat. Population counts for denominators are based on Census populations as modified by the National Cancer Institute. The US Population Data File is used for mortality data. The Average Annual Percent Change is based onthe APCs calculated by the Joinpoint Regression Program (Version 4.9.0.0). Due to data availability issues, the time period used in the calculation of the joinpoint regression model may differ for selected counties. Counties with a (3) after their name may have their joinpoint regresssion model calculated using a different time period due to data availability issues.

  4. d

    Compendium – Years of life lost

    • digital.nhs.uk
    csv, xls
    Updated Jul 21, 2022
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    (2022). Compendium – Years of life lost [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/compendium-mortality/current/years-of-life-lost
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    csv(127.9 kB), xls(180.2 kB)Available download formats
    Dataset updated
    Jul 21, 2022
    License

    https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

    Time period covered
    Jan 1, 2018 - Dec 31, 2020
    Area covered
    Wales, England
    Description

    Years of life lost due to mortality from pneumonia (ICD-10 J12-J18). Years of life lost (YLL) is a measure of premature mortality. Its primary purpose is to compare the relative importance of different causes of premature death within a particular population and it can therefore be used by health planners to define priorities for the prevention of such deaths. It can also be used to compare the premature mortality experience of different populations for a particular cause of death. The concept of years of life lost is to estimate the length of time a person would have lived had they not died prematurely. By inherently including the age at which the death occurs, rather than just the fact of its occurrence, the calculation is an attempt to better quantify the burden, or impact, on society from the specified cause of mortality. Legacy unique identifier: P00519

  5. England and Wales: deaths caused by pneumonia 2023, by age and gender

    • statista.com
    Updated Jul 11, 2025
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    Statista (2025). England and Wales: deaths caused by pneumonia 2023, by age and gender [Dataset]. https://www.statista.com/statistics/970854/pneumonia-deaths-by-age-and-gender-england-wales/
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    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    England, Wales
    Description

    This statistic shows the deaths with pneumonia as an underlying cause in England and Wales in 2023, by age and gender. In this year, pneumonia was the underlying cause of over *** thousand deaths for women aged 90 years and older.

  6. Death rate for influenza and pneumonia in Canada 2000-2023

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). Death rate for influenza and pneumonia in Canada 2000-2023 [Dataset]. https://www.statista.com/statistics/434445/death-rate-for-influenza-and-pneumonia-in-canada/
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    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Canada
    Description

    In 2023, there were **** deaths from influenza and pneumonia in Canada per 100,000 population. Influenza, more commonly known as the flu, is a highly contagious viral infection and frequent cause of pneumonia. Pneumonia is a more serious infection of the lungs and is particularly deadly among young children, the elderly, and those with certain chronic conditions. Vaccination There exist vaccines for both influenza and pneumonia, and although effectiveness varies, vaccination remains one of the best ways to prevent these illnesses. Nevertheless, only around ** percent of Canadians received an influenza vaccination in the past year in 2022. The most common reason why Canadian adults received the influenza vaccination was to prevent infection or because they did not want to get sick. Pneumonia hospitalization Every year tens of thousand of people in Canada are hospitalized for pneumonia. In *********, there were over ****** emergency room visits for pneumonia in Canada, a substantial decrease from the numbers recorded from 2010 to 2020. Perhaps unsurprisingly, those aged 65 years and older account for the highest number of emergency room visits for pneumonia. The median length of stay for emergency department visits for pneumonia in Canada has increased in recent years, with the median length of stay around *** minutes in *********.

  7. d

    Mortality from pneumonia: crude death rate, by age group, 3-year average,...

    • digital.nhs.uk
    Updated Jul 21, 2022
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    (2022). Mortality from pneumonia: crude death rate, by age group, 3-year average, MFP [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/compendium-mortality/current/mortality-from-respiratory-diseases
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    Dataset updated
    Jul 21, 2022
    License

    https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

    Description

    Legacy unique identifier: P00597

  8. COVID-19 State Data

    • kaggle.com
    zip
    Updated Nov 3, 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(4501 bytes)Available download formats
    Dataset updated
    Nov 3, 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

    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.

  9. Number of influenza deaths in the United States from 2011-2024

    • statista.com
    Updated Nov 15, 2024
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    Statista (2024). Number of influenza deaths in the United States from 2011-2024 [Dataset]. https://www.statista.com/statistics/1124915/flu-deaths-number-us/
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    Dataset updated
    Nov 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The burden of influenza in the United States can vary from year to year depending on which viruses are circulating, how many people receive an influenza vaccination, and how effective the vaccination is in that particular year. During the 2023-2024 flu season, around 28,000 people lost their lives to the disease. Although most people recover from influenza without needing medical care, the disease can be deadly among young children, the elderly, and those with weakened immune systems or chronic illnesses. Deaths due to influenza Even though most people recover from influenza without medical care, influenza and pneumonia can be deadly, especially for older people and those with certain preexisting conditions. Influenza is a common cause of pneumonia and although most cases of influenza do not develop into pneumonia, those that do are often more severe and more deadly. Deaths due to influenza are most common among the elderly, with a mortality rate of around 32 per 100,000 population during the 2023-2024 flu season. In comparison, the mortality rate for those aged 50 to 64 years was 9.1 per 100,000 population. Flu vaccinations The most effective way to prevent influenza is to receive an annual influenza vaccination. These vaccines have proven to be safe and are usually cheap and easily accessible. Nevertheless, every year a large share of the population in the United States still fails to get vaccinated against influenza. For example, in the 2022-2023 flu season, only 35 percent of those aged 18 to 49 years received a flu vaccination. Unsurprisingly, children and the elderly are the most likely to get vaccinated. It is estimated that during the 2022-2023 flu season, vaccinations prevented over 929 thousand influenza cases among children aged 6 months to 4 years.

  10. f

    Data from: Risk Factors for Long-Term Mortality after Hospitalization for...

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Feb 22, 2016
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    Aukrust, Pål; Frøland, Stig S.; Brunborg, Cathrine; Ueland, Thor; Müller, Fredrik; Husebye, Einar; Jenum, Pål A.; Heggelund, Lars; Holter, Jan C. (2016). Risk Factors for Long-Term Mortality after Hospitalization for Community-Acquired Pneumonia: A 5-Year Prospective Follow-Up Study [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001505748
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    Dataset updated
    Feb 22, 2016
    Authors
    Aukrust, Pål; Frøland, Stig S.; Brunborg, Cathrine; Ueland, Thor; Müller, Fredrik; Husebye, Einar; Jenum, Pål A.; Heggelund, Lars; Holter, Jan C.
    Description

    BackgroundContributors to long-term mortality in patients with community-acquired pneumonia (CAP) remain unclear, with little attention paid to pneumonia etiology. We examined long-term survival, causes of death, and risk factors for long-term mortality in adult patients who had been hospitalized for CAP, with emphasis on demographic, clinical, laboratory, and microbiological characteristics.MethodsTwo hundred and sixty-seven consecutive patients admitted in 2008–2011 to a general hospital with CAP were prospectively recruited and followed up. Patients who died during hospital stay were excluded. Demographic, clinical, and laboratory data were collected within 48 hours of admission. Extensive microbiological work-up was performed to establish the etiology of CAP in 63% of patients. Mortality data were obtained from the Norwegian Cause of Death Registry. Cox regression models were used to identify independent risk factors for all-cause mortality.ResultsOf 259 hospital survivors of CAP (median age 66 years), 79 (30.5%) died over a median of 1,804 days (range 1–2,520 days). Cumulative 5-year survival rate was 72.9% (95% CI 67.4–78.4%). Standardized mortality ratio was 2.90 for men and 2.05 for women. The main causes of death were chronic obstructive pulmonary disease (COPD), vascular diseases, and malignancy. Independent risk factors for death were the following (hazard ratio, 95% CI): age (1.83 per decade, 1.47–2.28), cardiovascular disease (2.63, 1.61–4.32), COPD (2.09, 1.27–3.45), immunocompromization (1.98, 1.17–3.37), and low serum albumin level at admission (0.75 per 5g/L higher, 0.58–0.96), whereas active smoking was protective (0.32, 0.14–0.74); active smokers were younger than non-smokers (P < 0.001). Microbial etiology did not predict mortality.ConclusionsResults largely confirm substantial comorbidity-related 5-year mortality after hospitalization for CAP and the impact of several well-known risk factors for death, and extend previous findings on the prognostic value of serum albumin level at hospital admission. Pneumonia etiology had no prognostic value, but this remains to be substantiated by further studies using extensive diagnostic microbiological methods in the identification of causative agents of CAP.

  11. 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
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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.

  12. Dataset related to article "High mortality in COVID-19 patients with mild...

    • zenodo.org
    • data.niaid.nih.gov
    Updated May 20, 2021
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    Chiara Masetti; Elena Generali; Francesca Colapietro; Antonio Voza; Maurizio Cecconi; Antonio Messina; Paolo Omodei; Claudio Angelini; Michele Ciccarelli; Salvatore Badalamenti; Giorgio Walter Canonica; Giorgio Walter Canonica; Ana Lleo; Ana Lleo; Alessio Aghemo; Alessio Aghemo; the Humanitas Covid-19 Task Force; Chiara Masetti; Elena Generali; Francesca Colapietro; Antonio Voza; Maurizio Cecconi; Antonio Messina; Paolo Omodei; Claudio Angelini; Michele Ciccarelli; Salvatore Badalamenti; the Humanitas Covid-19 Task Force (2021). Dataset related to article "High mortality in COVID-19 patients with mild respiratory disease " [Dataset]. http://doi.org/10.5281/zenodo.4774885
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    Dataset updated
    May 20, 2021
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Chiara Masetti; Elena Generali; Francesca Colapietro; Antonio Voza; Maurizio Cecconi; Antonio Messina; Paolo Omodei; Claudio Angelini; Michele Ciccarelli; Salvatore Badalamenti; Giorgio Walter Canonica; Giorgio Walter Canonica; Ana Lleo; Ana Lleo; Alessio Aghemo; Alessio Aghemo; the Humanitas Covid-19 Task Force; Chiara Masetti; Elena Generali; Francesca Colapietro; Antonio Voza; Maurizio Cecconi; Antonio Messina; Paolo Omodei; Claudio Angelini; Michele Ciccarelli; Salvatore Badalamenti; the Humanitas Covid-19 Task Force
    Description

    This record contains raw data related to article "High mortality in COVID-19 patients with mild respiratory disease"

    Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected 189 000 people in Italy, with more than 25 000 deaths. Several predictive factors of mortality have been identified; however, none has been validated in patients presenting with mild disease.

    Methods: Patients with a diagnosis of interstitial pneumonia caused by SARS-CoV-2, presenting with mild symptoms, and requiring hospitalization in a non-intensive care unit with known discharge status were prospectively collected and retrospectively analysed. Demographical, clinical and biochemical parameters were recorded, as need for non-invasive mechanical ventilation and admission in intensive care unit. Univariate and multivariate logistic regression analyses were used to identify independent predictors of death.

    Results: Between 28 February and 10 April 2020, 229 consecutive patients were included in the study cohort; the majority were males with a mean age of 60 years. 54% of patients had at least one comorbidity, with hypertension being the most commonly represented, followed by diabetes mellitus. 196 patients were discharged after a mean of 9 days, while 14.4% died during hospitalization because of respiratory failure. Age higher than 75 years, low platelet count (<150 × 103 /mm3 ) and higher ferritin levels (>750 ng/mL) were independent predictors of death. Comorbidities were not independently associated with in-hospital mortality.

    Conclusions: In-hospital mortality of patients with COVID-19 presenting with mild symptoms is high and is associated with older age, platelet count and ferritin levels. Identifying early predictors of outcome can be useful in the clinical practice to better stratify and manage patients with COVID-19.

  13. n

    Data from: Disparities in influenza mortality and transmission related to...

    • data.niaid.nih.gov
    • datadryad.org
    • +1more
    zip
    Updated Nov 1, 2017
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    Kyra H. Grantz; Madhura S. Rane; Henrik Salje; Gregory E. Glass; Stephen E. Schachterle; Derek A. T. Cummings (2017). Disparities in influenza mortality and transmission related to sociodemographic factors within Chicago in the pandemic of 1918 [Dataset]. http://doi.org/10.5061/dryad.48nv3
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    zipAvailable download formats
    Dataset updated
    Nov 1, 2017
    Dataset provided by
    University of Washington
    Johns Hopkins Bloomberg School of Public Health
    University of Florida
    Pfizer Inc.
    Authors
    Kyra H. Grantz; Madhura S. Rane; Henrik Salje; Gregory E. Glass; Stephen E. Schachterle; Derek A. T. Cummings
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Chicago, United States
    Description

    Social factors have been shown to create differential burden of influenza across different geographic areas. We explored the relationship between potential aggregate-level social determinants and mortality during the 1918 influenza pandemic in Chicago using a historical dataset of 7,971 influenza and pneumonia deaths. Census tract-level social factors, including rates of illiteracy, homeownership, population, and unemployment, were assessed as predictors of pandemic mortality in Chicago. Poisson models fit with generalized estimating equations (GEEs) were used to estimate the association between social factors and the risk of influenza and pneumonia mortality. The Poisson model showed that influenza and pneumonia mortality increased, on average, by 32.2% for every 10% increase in illiteracy rate adjusted for population density, homeownership, unemployment, and age. We also found a significant association between transmissibility and population density, illiteracy, and unemployment but not homeownership. Lastly, analysis of the point locations of reported influenza and pneumonia deaths revealed fine-scale spatiotemporal clustering. This study shows that living in census tracts with higher illiteracy rates increased the risk of influenza and pneumonia mortality during the 1918 influenza pandemic in Chicago. Our observation that disparities in structural determinants of neighborhood-level health lead to disparities in influenza incidence in this pandemic suggests that disparities and their determinants should remain targets of research and control in future pandemics.

  14. Mean annual age-adjusted community-setting pneumonia-associated...

    • plos.figshare.com
    xls
    Updated Jun 13, 2023
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    Melody Wu; Katherine Whittemore; Chaorui C. Huang; Rachel E. Corrado; Gretchen M. Culp; Sungwoo Lim; Neil W. Schluger; Demetre C. Daskalakis; David E. Lucero; Neil M. Vora (2023). Mean annual age-adjusted community-setting pneumonia-associated hospitalization rates in New York City, non-New York City urban areas, suburban areas, and rural areas—New York State, 2010–2014a. [Dataset]. http://doi.org/10.1371/journal.pone.0244367.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Melody Wu; Katherine Whittemore; Chaorui C. Huang; Rachel E. Corrado; Gretchen M. Culp; Sungwoo Lim; Neil W. Schluger; Demetre C. Daskalakis; David E. Lucero; Neil M. Vora
    License

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

    Area covered
    New York, New York
    Description

    Mean annual age-adjusted community-setting pneumonia-associated hospitalization rates in New York City, non-New York City urban areas, suburban areas, and rural areas—New York State, 2010–2014a.

  15. f

    Pneumonia-associated hospitalizations (PAH) and in-hospital death by patient...

    • figshare.com
    xls
    Updated Jun 9, 2023
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    Kate Whittemore; Kristian M. Garcia; Chaorui C. Huang; Sungwoo Lim; Demetre C. Daskalakis; Neil M. Vora; David E. Lucero (2023). Pneumonia-associated hospitalizations (PAH) and in-hospital death by patient characteristics among adults—New York City, 2010–2014b'*'. [Dataset]. http://doi.org/10.1371/journal.pone.0256678.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 9, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kate Whittemore; Kristian M. Garcia; Chaorui C. Huang; Sungwoo Lim; Demetre C. Daskalakis; Neil M. Vora; David E. Lucero
    License

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

    Area covered
    New York
    Description

    Pneumonia-associated hospitalizations (PAH) and in-hospital death by patient characteristics among adults—New York City, 2010–2014b'*'.

  16. e

    Mortality from acute respiratory infections, pneumonia and influenza in...

    • data.europa.eu
    unknown
    Updated Oct 7, 2025
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    Comunidad Autónoma del País Vasco (2025). Mortality from acute respiratory infections, pneumonia and influenza in women in the Basque Country (1996-2003) [Dataset]. https://data.europa.eu/data/datasets/https-opendata-euskadi-eus-catalogo-informes-estudios-mortalidad-por-infecciones-respiratorias-agudas-neumonia-y-gripe-en-mujeres-en-euskadi-1996-2003-?locale=en
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    unknown(1468006), unknown(23552)Available download formats
    Dataset updated
    Oct 7, 2025
    Dataset authored and provided by
    Comunidad Autónoma del País Vasco
    License

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

    Area covered
    Basque Country
    Description

    Acute respiratory infections, pneumonia and flu (SCI-9: 460-466,480-487; ICD-10: J00-J22)* ranked seventh in the mortality ranking, with 2 % of total deaths among women. Mortality from these causes has had a downward evolution in recent years, with an average annual decrease of 3.2 %. The distribution of mortality in the CAPV does not follow an obvious geographical pattern

  17. Flu vaccines availability data

    • kaggle.com
    zip
    Updated Nov 28, 2023
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    AmirHosein Mousavian (2023). Flu vaccines availability data [Dataset]. https://www.kaggle.com/datasets/amirhoseinmousavian/flu-vaccines-availability-data
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    zip(3668 bytes)Available download formats
    Dataset updated
    Nov 28, 2023
    Authors
    AmirHosein Mousavian
    License

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

    Description

    The flu is estimated to cause 400,000 respiratory deaths each year on average across the world. These deaths come from pneumonia and other respiratory symptoms caused by the flu. People also die from other complications of the flu – such as a stroke or heart attack – but global estimates have not been made of their death toll. The Spanish flu caused the largest influenza pandemic in history. Yet, data on the flu is limited. With better testing, countries could improve their response to flu epidemics. It could help to rapidly identify new strains, detect epidemics early, and design better-matched vaccines to target flu strains circulating in the population.

    this data set contains the vaccine coverage around the world from 2018 to 2022.

  18. Child and Infant Mortality

    • kaggle.com
    Updated Aug 21, 2022
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    hrterhrter (2022). Child and Infant Mortality [Dataset]. https://www.kaggle.com/datasets/programmerrdai/child-and-infant-mortality
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 21, 2022
    Dataset provided by
    Kaggle
    Authors
    hrterhrter
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    One in every 100 children dies before completing one year of life. Around 68 percent of infant mortality is attributed to deaths of children before completing 1 month. 15,000 children die every day – Child mortality is an everyday tragedy of enormous scale that rarely makes the headlines Child mortality rates have declined in all world regions, but the world is not on track to reach the Sustainable Development Goal for child mortality Before the Modern Revolution child mortality was very high in all societies that we have knowledge of – a quarter of all children died in the first year of life, almost half died before reaching the end of puberty Over the last two centuries all countries in the world have made very rapid progress against child mortality. From 1800 to 1950 global mortality has halved from around 43% to 22.5%. Since 1950 the mortality rate has declined five-fold to 4.5% in 2015. All countries in the world have benefitted from this progress In the past it was very common for parents to see children die, because both, child mortality rates and fertility rates were very high. In Europe in the mid 18th century parents lost on average between 3 and 4 of their children Based on this overview we are asking where the world is today – where are children dying and what are they dying from?

    5.4 million children died in 2017 – Where did these children die? Pneumonia is the most common cause of death, preterm births and neonatal disorders is second, and diarrheal diseases are third – What are children today dying from? This is the basis for answering the question what can we do to make further progress against child mortality? We will extend this entry over the course of 2020.

    @article{owidchildmortality, author = {Max Roser, Hannah Ritchie and Bernadeta Dadonaite}, title = {Child and Infant Mortality}, journal = {Our World in Data}, year = {2013}, note = {https://ourworldindata.org/child-mortality} }

  19. Latitude and longitude coordinates, population size, and mean baseline...

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Rodolfo Acuna-Soto; Cécile Viboud; Gerardo Chowell (2023). Latitude and longitude coordinates, population size, and mean baseline pneumonia and influenza death rates for 66 large US reporting cities (1910–1920) with 100, 000 or more inhabitants [10]. [Dataset]. http://doi.org/10.1371/journal.pone.0023467.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Rodolfo Acuna-Soto; Cécile Viboud; Gerardo Chowell
    License

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

    Description

    Latitude and longitude coordinates, population size, and mean baseline pneumonia and influenza death rates for 66 large US reporting cities (1910–1920) with 100, 000 or more inhabitants [10].

  20. Number of flu-related deaths in the U.S. in 2023-2024, by age group

    • statista.com
    Updated Nov 15, 2024
    + more versions
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    Statista (2024). Number of flu-related deaths in the U.S. in 2023-2024, by age group [Dataset]. https://www.statista.com/statistics/1127698/influenza-us-deaths-by-age-group/
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    Dataset updated
    Nov 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023 - 2024
    Area covered
    United States
    Description

    During the 2023-2024 flu season in the United States, an estimated 27,965 people died from influenza. The vast majority of deaths due to influenza occur among the elderly, with those aged 65 years and older accounting for 19,038 deaths during the 2023-2024 flu season. During this time, the mortality rate from influenza among those aged 65 years and older was around 32 per 100,000 population, compared to a mortality rate of two per 100,000 population among those aged 18 to 49 years. Influenza deaths Although most people recover from influenza without the need of medical care, influenza and pneumonia are still major causes of death in the United States. Influenza is a common cause of pneumonia and cases in which influenza develops into pneumonia tend to be more severe and more deadly. However, the impact of influenza varies from year to year depending on which viruses are circulating. For example, during the 2017-2018 flu season around 52,000 people died due to influenza, whereas in 2023-2024 total deaths amounted to 28,000. Preventing death The most effective way to prevent influenza is to receive an annual influenza vaccination. These vaccines have proven to be safe and are usually cheap and easily accessible. Each year, flu vaccinations prevent thousands of influenza cases, hospitalizations and deaths. It was estimated that during the 2022-2023 flu season, vaccinations prevented the deaths of around 2,479 people aged 65 years and older.

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(2022). Compendium – Mortality from respiratory disease [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/compendium-mortality/current/mortality-from-respiratory-diseases

Compendium – Mortality from respiratory disease

Mortality from pneumonia: crude death rate, by age group, 3-year average, MFP

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xls(54.8 kB), csv(14.8 kB)Available download formats
Dataset updated
Jul 21, 2022
License

https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

Time period covered
Jan 1, 2018 - Dec 31, 2020
Area covered
Wales, England
Description

Mortality from pneumonia (ICD-10 J12-J18 equivalent to ICD-9 480-486). To reduce deaths from pneumonia. Legacy unique identifier: P00597

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