4 datasets found
  1. Leading causes of death, total population, by age group

    • www150.statcan.gc.ca
    • ouvert.canada.ca
    • +2more
    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.

  2. National flu and COVID-19 surveillance reports: 2024 to 2025 season

    • gov.uk
    Updated Mar 20, 2025
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    UK Health Security Agency (2025). National flu and COVID-19 surveillance reports: 2024 to 2025 season [Dataset]. https://www.gov.uk/government/statistics/national-flu-and-covid-19-surveillance-reports-2024-to-2025-season
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    Dataset updated
    Mar 20, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    UK Health Security Agency
    Description

    These reports summarise the surveillance of influenza, COVID-19 and other seasonal respiratory illnesses in England.

    Weekly findings from community, primary care, secondary care and mortality surveillance systems are included in the reports.

    This page includes reports published from 18 July 2024 to the present.

    Please note that after the week 21 report (covering data up to week 20), this surveillance report will move to a condensed summer report and will be released every 2 weeks.

    Previous reports on influenza surveillance are also available for:

    View the pre-release access list for these reports.

    Our statistical practice is regulated by the Office for Statistics Regulation (OSR). The OSR sets the standards of trustworthiness, quality and value in the https://code.statisticsauthority.gov.uk/" class="govuk-link">Code of Practice for Statistics that all producers of Official Statistics should adhere to.

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

    • data.cdc.gov
    • data.virginia.gov
    application/rdfxml +5
    Updated Mar 21, 2025
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    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
    Explore at:
    csv, application/rdfxml, json, application/rssxml, xml, tsvAvailable download formats
    Dataset updated
    Mar 21, 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.

  4. Preliminary 2024-2025 U.S. RSV Burden Estimates

    • data.cdc.gov
    • data.virginia.gov
    application/rdfxml +5
    Updated Mar 21, 2025
    Share
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    Preliminary 2024-2025 U.S. RSV Burden Estimates [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/Preliminary-2024-2025-U-S-RSV-Burden-Estimates/sumd-iwm8
    Explore at:
    csv, tsv, application/rdfxml, json, application/rssxml, xmlAvailable download formats
    Dataset updated
    Mar 21, 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

    Description

    This dataset represents preliminary estimates of cumulative U.S. RSV –associated disease burden estimates for the 2024-2025 season, including outpatient visits, hospitalizations, and deaths. Real-time estimates are preliminary and based on continuously collected surveillance data from patients hospitalized with laboratory-confirmed respiratory syncytial virus (RSV) infections. The data come from the Respiratory Syncytial Virus Hospitalization Surveillance Network (RSV-NET), a surveillance platform that captures data from hospitals that serve about 8% of the U.S. population. Each week CDC estimates a range (i.e., lower estimate and an upper estimate) of RSV-associated disease burden estimates that have occurred since October 1, 2024.

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

    Note: Preliminary burden estimates are not inclusive of data from all RSV-NET sites. Due to model limitations, sites with small sample sizes can impact estimates in unpredictable ways and are excluded for the benefit of model stability. CDC is working to address model limitations and include data from all sites in final burden estimates.

    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.

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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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Leading causes of death, total population, by age group

1310039401

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.

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