5 datasets found
  1. Preliminary 2024-2025 U.S. COVID-19 Burden Estimates

    • data.cdc.gov
    • data.virginia.gov
    application/rdfxml +5
    Updated Mar 21, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    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.

  2. Provisional COVID-19 Deaths by County, and Race and Hispanic Origin

    • datasets.ai
    • data.virginia.gov
    • +3more
    23, 40, 55, 8
    Updated Sep 27, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    U.S. Department of Health & Human Services (2023). Provisional COVID-19 Deaths by County, and Race and Hispanic Origin [Dataset]. https://datasets.ai/datasets/provisional-covid-19-death-counts-by-county-and-race
    Explore at:
    23, 40, 55, 8Available download formats
    Dataset updated
    Sep 27, 2023
    Dataset provided by
    United States Department of Health and Human Serviceshttp://www.hhs.gov/
    Authors
    U.S. Department of Health & Human Services
    Description

    Effective September 27, 2023, this dataset will no longer be updated. Similar data are accessible from wonder.cdc.gov.

    County data on race and Hispanic origin is available for counties with more than 100 COVID-19 deaths. Deaths are cumulative from the week ending January 4, 2020 to the most recent reporting week, and based on county of occurrence. Data is provisional.

    Urban-rural classification is based on the 2013 National Center for Health Statistics Urban-Rural Classification Scheme for Counties (https://www.cdc.gov/nchs/data_access/urban_rural.htm).

  3. Weekly Summary of U.S. COVID-19 Trends

    • beta-search-prod-pre-a-hub.hub.arcgis.com
    Updated Jul 3, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Urban Observatory by Esri (2020). Weekly Summary of U.S. COVID-19 Trends [Dataset]. https://beta-search-prod-pre-a-hub.hub.arcgis.com/datasets/UrbanObservatory::weekly-summary-of-u-s-covid-19-trends-1
    Explore at:
    Dataset updated
    Jul 3, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    United States
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This map is updated weekly and currently shows data through Mar 5, 2023. Notes: as of 5/25/2021, Nebraska stopped sharing COVID-19 testing and on 9/26/21 began, but with a lump sum for the previous four months. Nebraska's reporting became unconsumable by JHU on July 1, 2022. Maryland stopped reporting results for several weeks on 12/4/2021 due to a website hack.It shows COVID-19 Trend for the most recent Monday with a colored dot for each county. The larger the dot, the longer the county has had this trend.Includes Puerto Rico, Guam, Northern Marianas, U.S. Virgin Islands.The intent of this map is to give more context than just the current day of new data because daily data for COVID-19 cases is volatile and can be unreliable on the day it is first reported. Weekly summaries in the counts of new cases smooth out this volatility.Click or tap on a county to see a history of trend changes and a weekly graph of new cases going back to February 1, 2020.For more information about COVID-19 trends, see the full methodology.Data Source: Johns Hopkins University CSSE US Cases by County dashboard and USAFacts for Utah County level Data.

  4. Coronavirus (COVID-19) cases, recoveries, and deaths worldwide as of May 2,...

    • statista.com
    Updated Dec 15, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Coronavirus (COVID-19) cases, recoveries, and deaths worldwide as of May 2, 2023 [Dataset]. https://www.statista.com/statistics/1087466/covid19-cases-recoveries-deaths-worldwide/
    Explore at:
    Dataset updated
    Dec 15, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 2, 2023
    Area covered
    Worldwide
    Description

    As of May 2, 2023, there were roughly 687 million global cases of COVID-19. Around 660 million people had recovered from the disease, while there had been almost 6.87 million deaths. The United States, India, and Brazil have been among the countries hardest hit by the pandemic.

    The various types of human coronavirus The SARS-CoV-2 virus is the seventh known coronavirus to infect humans. Its emergence makes it the third in recent years to cause widespread infectious disease following the viruses responsible for SARS and MERS. A continual problem is that viruses naturally mutate as they attempt to survive. Notable new variants of SARS-CoV-2 were first identified in the UK, South Africa, and Brazil. Variants are of particular interest because they are associated with increased transmission.

    Vaccination campaigns Common human coronaviruses typically cause mild symptoms such as a cough or a cold, but the novel coronavirus SARS-CoV-2 has led to more severe respiratory illnesses and deaths worldwide. Several COVID-19 vaccines have now been approved and are being used around the world.

  5. a

    Coronavirus COVID-19 (2019-nCoV)

    • hub.arcgis.com
    • covid-hub.gio.georgia.gov
    • +6more
    Updated Jan 22, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CSSE_covid19 (2020). Coronavirus COVID-19 (2019-nCoV) [Dataset]. https://hub.arcgis.com/datasets/bda7594740fd40299423467b48e9ecf6
    Explore at:
    Dataset updated
    Jan 22, 2020
    Dataset authored and provided by
    CSSE_covid19
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources:Global: World Health Organization (WHO)U.S.: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This dashboard created by Operations Dashboard contains the most up-to-date coronavirus COVID-19 cases and latest trend plot. It covers China, the US, Canada, Australia (at province/state level), and the rest of the world (at country level, represented by either the country centroids or their capitals). Data sources are WHO, US CDC, China NHC, ECDC, and DXY. The China data is automatically updating at least once per hour, and non China data is updating manually. This layer is created and maintained by the Center for Systems Science and Engineering (CSSE) at the Johns Hopkins University. This service is supported by Esri Living Atlas team and JHU Data Services.

  6. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
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
Organization logo

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

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.

Search
Clear search
Close search
Google apps
Main menu