48 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
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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
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    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. COVID-19 deaths reported in the U.S. as of June 14, 2023, by age

    • statista.com
    Updated Jun 21, 2023
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    Statista (2023). COVID-19 deaths reported in the U.S. as of June 14, 2023, by age [Dataset]. https://www.statista.com/statistics/1191568/reported-deaths-from-covid-by-age-us/
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    Dataset updated
    Jun 21, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 1, 2020 - Jun 14, 2023
    Area covered
    United States
    Description

    Between the beginning of January 2020 and June 14, 2023, of the 1,134,641 deaths caused by COVID-19 in the United States, around 307,169 had occurred among those aged 85 years and older. This statistic shows the number of coronavirus disease 2019 (COVID-19) deaths in the U.S. from January 2020 to June 2023, by age.

  3. COVID-19 deaths in Latin America 2024, by country

    • statista.com
    Updated Aug 13, 2024
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    Statista (2024). COVID-19 deaths in Latin America 2024, by country [Dataset]. https://www.statista.com/statistics/1103965/latin-america-caribbean-coronavirus-deaths/
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    Dataset updated
    Aug 13, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Latin America, LAC
    Description

    As of July 28, 2024, nearly 1.8 million people have died due COVID-19 in Latin America and the Caribbean. The country with the highest number was Brazil, reporting around 700,000 deaths. As a result of the pandemic, Brazil's GDP was forecast to decline by approximately six percent in 2020. Meanwhile, Mexico ranked second in number of deaths, with approximately 335 thousand occurrences. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

  4. Provisional COVID-19 death counts, rates, and percent of total deaths, by...

    • catalog.data.gov
    • data.virginia.gov
    • +2more
    Updated Mar 22, 2025
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    Centers for Disease Control and Prevention (2025). Provisional COVID-19 death counts, rates, and percent of total deaths, by jurisdiction of residence [Dataset]. https://catalog.data.gov/dataset/provisional-covid-19-death-counts-rates-and-percent-of-total-deaths-by-jurisdiction-of-res
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    Dataset updated
    Mar 22, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This file contains COVID-19 death counts, death rates, and percent of total deaths by jurisdiction of residence. The data is grouped by different time periods including 3-month period, weekly, and total (cumulative since January 1, 2020). United States death counts and rates include the 50 states, plus the District of Columbia and New York City. New York state estimates exclude New York City. Puerto Rico is included in HHS Region 2 estimates. Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file. Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death. Death counts should not be compared across states. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly. The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York, New York City, Puerto Rico; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington. Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf). Rates are based on deaths occurring in the specified week/month and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly/monthly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly/monthly) rate prevailed for a full year. Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

  5. d

    Johns Hopkins COVID-19 Case Tracker

    • data.world
    csv, zip
    Updated Mar 25, 2025
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    The Associated Press (2025). Johns Hopkins COVID-19 Case Tracker [Dataset]. https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker
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    zip, csvAvailable download formats
    Dataset updated
    Mar 25, 2025
    Authors
    The Associated Press
    Time period covered
    Jan 22, 2020 - Mar 9, 2023
    Area covered
    Description

    Updates

    • Notice of data discontinuation: Since the start of the pandemic, AP has reported case and death counts from data provided by Johns Hopkins University. Johns Hopkins University has announced that they will stop their daily data collection efforts after March 10. As Johns Hopkins stops providing data, the AP will also stop collecting daily numbers for COVID cases and deaths. The HHS and CDC now collect and visualize key metrics for the pandemic. AP advises using those resources when reporting on the pandemic going forward.

    • April 9, 2020

      • The population estimate data for New York County, NY has been updated to include all five New York City counties (Kings County, Queens County, Bronx County, Richmond County and New York County). This has been done to match the Johns Hopkins COVID-19 data, which aggregates counts for the five New York City counties to New York County.
    • April 20, 2020

      • Johns Hopkins death totals in the US now include confirmed and probable deaths in accordance with CDC guidelines as of April 14. One significant result of this change was an increase of more than 3,700 deaths in the New York City count. This change will likely result in increases for death counts elsewhere as well. The AP does not alter the Johns Hopkins source data, so probable deaths are included in this dataset as well.
    • April 29, 2020

      • The AP is now providing timeseries data for counts of COVID-19 cases and deaths. The raw counts are provided here unaltered, along with a population column with Census ACS-5 estimates and calculated daily case and death rates per 100,000 people. Please read the updated caveats section for more information.
    • September 1st, 2020

      • Johns Hopkins is now providing counts for the five New York City counties individually.
    • February 12, 2021

      • The Ohio Department of Health recently announced that as many as 4,000 COVID-19 deaths may have been underreported through the state’s reporting system, and that the "daily reported death counts will be high for a two to three-day period."
      • Because deaths data will be anomalous for consecutive days, we have chosen to freeze Ohio's rolling average for daily deaths at the last valid measure until Johns Hopkins is able to back-distribute the data. The raw daily death counts, as reported by Johns Hopkins and including the backlogged death data, will still be present in the new_deaths column.
    • February 16, 2021

      - Johns Hopkins has reconciled Ohio's historical deaths data with the state.

      Overview

    The AP is using data collected by the Johns Hopkins University Center for Systems Science and Engineering as our source for outbreak caseloads and death counts for the United States and globally.

    The Hopkins data is available at the county level in the United States. The AP has paired this data with population figures and county rural/urban designations, and has calculated caseload and death rates per 100,000 people. Be aware that caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.

    This data is from the Hopkins dashboard that is updated regularly throughout the day. Like all organizations dealing with data, Hopkins is constantly refining and cleaning up their feed, so there may be brief moments where data does not appear correctly. At this link, you’ll find the Hopkins daily data reports, and a clean version of their feed.

    The AP is updating this dataset hourly at 45 minutes past the hour.

    To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

    Queries

    Use AP's queries to filter the data or to join to other datasets we've made available to help cover the coronavirus pandemic

    Interactive

    The AP has designed an interactive map to track COVID-19 cases reported by Johns Hopkins.

    @(https://datawrapper.dwcdn.net/nRyaf/15/)

    Interactive Embed Code

    <iframe title="USA counties (2018) choropleth map Mapping COVID-19 cases by county" aria-describedby="" id="datawrapper-chart-nRyaf" src="https://datawrapper.dwcdn.net/nRyaf/10/" scrolling="no" frameborder="0" style="width: 0; min-width: 100% !important;" height="400"></iframe><script type="text/javascript">(function() {'use strict';window.addEventListener('message', function(event) {if (typeof event.data['datawrapper-height'] !== 'undefined') {for (var chartId in event.data['datawrapper-height']) {var iframe = document.getElementById('datawrapper-chart-' + chartId) || document.querySelector("iframe[src*='" + chartId + "']");if (!iframe) {continue;}iframe.style.height = event.data['datawrapper-height'][chartId] + 'px';}}});})();</script>
    

    Caveats

    • This data represents the number of cases and deaths reported by each state and has been collected by Johns Hopkins from a number of sources cited on their website.
    • In some cases, deaths or cases of people who've crossed state lines -- either to receive treatment or because they became sick and couldn't return home while traveling -- are reported in a state they aren't currently in, because of state reporting rules.
    • In some states, there are a number of cases not assigned to a specific county -- for those cases, the county name is "unassigned to a single county"
    • This data should be credited to Johns Hopkins University's COVID-19 tracking project. The AP is simply making it available here for ease of use for reporters and members.
    • Caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.
    • Population estimates at the county level are drawn from 2014-18 5-year estimates from the American Community Survey.
    • The Urban/Rural classification scheme is from the Center for Disease Control and Preventions's National Center for Health Statistics. It puts each county into one of six categories -- from Large Central Metro to Non-Core -- according to population and other characteristics. More details about the classifications can be found here.

    Johns Hopkins timeseries data - Johns Hopkins pulls data regularly to update their dashboard. Once a day, around 8pm EDT, Johns Hopkins adds the counts for all areas they cover to the timeseries file. These counts are snapshots of the latest cumulative counts provided by the source on that day. This can lead to inconsistencies if a source updates their historical data for accuracy, either increasing or decreasing the latest cumulative count. - Johns Hopkins periodically edits their historical timeseries data for accuracy. They provide a file documenting all errors in their timeseries files that they have identified and fixed here

    Attribution

    This data should be credited to Johns Hopkins University COVID-19 tracking project

  6. Total number of COVID-19 deaths APAC April 2024, by country or territory

    • statista.com
    Updated Sep 18, 2024
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    Statista (2024). Total number of COVID-19 deaths APAC April 2024, by country or territory [Dataset]. https://www.statista.com/statistics/1104268/apac-covid-19-deaths-by-country/
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    Dataset updated
    Sep 18, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Asia–Pacific
    Description

    As of April 13, 2024, India had the highest number of confirmed deaths due to the outbreak of the novel coronavirus in the Asia-Pacific region, with over 533 thousand deaths. Comparatively, Indonesia, which had the second highest number of coronavirus deaths in the Asia-Pacific region, recorded approximately 162 thousand COVID-19 related deaths as of April 13, 2024. Contrastingly, Bhutan had reported 21 deaths due to COVID-19 as of April 13, 2024.

  7. N

    Confirmed COVID-19 Case and Hospitalization Counts

    • data.cityofnewyork.us
    application/rdfxml +5
    Updated Mar 26, 2025
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    Department of Health and Mental Hygiene (DOHMH) (2025). Confirmed COVID-19 Case and Hospitalization Counts [Dataset]. https://data.cityofnewyork.us/Health/Confirmed-COVID-19-Case-and-Hospitalization-Counts/3w37-3kr9
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    csv, application/rssxml, json, xml, application/rdfxml, tsvAvailable download formats
    Dataset updated
    Mar 26, 2025
    Authors
    Department of Health and Mental Hygiene (DOHMH)
    Description

    Daily count of NYC residents who tested positive for SARS-CoV-2, who were hospitalized with COVID-19, and deaths among COVID-19 patients.

    Note that this dataset currently pulls from https://raw.githubusercontent.com/nychealth/coronavirus-data/master/case-hosp-death.csv on a daily basis.

  8. COVID-19 death rates in the United States as of March 10, 2023, by state

    • statista.com
    Updated Mar 28, 2023
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    Statista (2023). COVID-19 death rates in the United States as of March 10, 2023, by state [Dataset]. https://www.statista.com/statistics/1109011/coronavirus-covid19-death-rates-us-by-state/
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    Dataset updated
    Mar 28, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of March 10, 2023, the death rate from COVID-19 in the state of New York was 397 per 100,000 people. New York is one of the states with the highest number of COVID-19 cases.

  9. United States COVID-19 Community Levels by County

    • data.cdc.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Nov 2, 2023
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    CDC COVID-19 Response (2023). United States COVID-19 Community Levels by County [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/United-States-COVID-19-Community-Levels-by-County/3nnm-4jni
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    application/rdfxml, application/rssxml, csv, tsv, xml, jsonAvailable download formats
    Dataset updated
    Nov 2, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    CDC COVID-19 Response
    License

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

    Area covered
    United States
    Description

    Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

    This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.

    The COVID-19 community levels were developed using a combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days. The COVID-19 community level was determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.

    Using these data, the COVID-19 community level was classified as low, medium, or high.

    COVID-19 Community Levels were used to help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals.

    For the most accurate and up-to-date data for any county or state, visit the relevant health department website. COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.

    Archived Data Notes:

    This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.

    March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.

    March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.

    March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.

    March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.

    March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).

    March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.

    April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.

    April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials to verify the data submitted, as other data systems are not providing alerts for substantial increases in disease transmission or severity in the state.

    May 26, 2022: COVID-19 Community Level (CCL) data released for McCracken County, KY for the week of May 5, 2022 have been updated to correct a data processing error. McCracken County, KY should have appeared in the low community level category during the week of May 5, 2022. This correction is reflected in this update.

    May 26, 2022: COVID-19 Community Level (CCL) data released for several Florida counties for the week of May 19th, 2022, have been corrected for a data processing error. Of note, Broward, Miami-Dade, Palm Beach Counties should have appeared in the high CCL category, and Osceola County should have appeared in the medium CCL category. These corrections are reflected in this update.

    May 26, 2022: COVID-19 Community Level (CCL) data released for Orange County, New York for the week of May 26, 2022 displayed an erroneous case rate of zero and a CCL category of low due to a data source error. This county should have appeared in the medium CCL category.

    June 2, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a data processing error. Tolland County, CT should have appeared in the medium community level category during the week of May 26, 2022. This correction is reflected in this update.

    June 9, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a misspelling. The medium community level category for Tolland County, CT on the week of May 26, 2022 was misspelled as “meduim” in the data set. This correction is reflected in this update.

    June 9, 2022: COVID-19 Community Level (CCL) data released for Mississippi counties for the week of June 9, 2022 should be interpreted with caution due to a reporting cadence change over the Memorial Day holiday that resulted in artificially inflated case rates in the state.

    July 7, 2022: COVID-19 Community Level (CCL) data released for Rock County, Minnesota for the week of July 7, 2022 displayed an artificially low case rate and CCL category due to a data source error. This county should have appeared in the high CCL category.

    July 14, 2022: COVID-19 Community Level (CCL) data released for Massachusetts counties for the week of July 14, 2022 should be interpreted with caution due to a reporting cadence change that resulted in lower than expected case rates and CCL categories in the state.

    July 28, 2022: COVID-19 Community Level (CCL) data released for all Montana counties for the week of July 21, 2022 had case rates of 0 due to a reporting issue. The case rates have been corrected in this update.

    July 28, 2022: COVID-19 Community Level (CCL) data released for Alaska for all weeks prior to July 21, 2022 included non-resident cases. The case rates for the time series have been corrected in this update.

    July 28, 2022: A laboratory in Nevada reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate will be inflated in Clark County, NV for the week of July 28, 2022.

    August 4, 2022: COVID-19 Community Level (CCL) data was updated on August 2, 2022 in error during performance testing. Data for the week of July 28, 2022 was changed during this update due to additional case and hospital data as a result of late reporting between July 28, 2022 and August 2, 2022. Since the purpose of this data set is to provide point-in-time views of COVID-19 Community Levels on Thursdays, any changes made to the data set during the August 2, 2022 update have been reverted in this update.

    August 4, 2022: COVID-19 Community Level (CCL) data for the week of July 28, 2022 for 8 counties in Utah (Beaver County, Daggett County, Duchesne County, Garfield County, Iron County, Kane County, Uintah County, and Washington County) case data was missing due to data collection issues. CDC and its partners have resolved the issue and the correction is reflected in this update.

    August 4, 2022: Due to a reporting cadence change, case rates for all Alabama counties will be lower than expected. As a result, the CCL levels published on August 4, 2022 should be interpreted with caution.

    August 11, 2022: COVID-19 Community Level (CCL) data for the week of August 4, 2022 for South Carolina have been updated to correct a data collection error that resulted in incorrect case data. CDC and its partners have resolved the issue and the correction is reflected in this update.

    August 18, 2022: COVID-19 Community Level (CCL) data for the week of August 11, 2022 for Connecticut have been updated to correct a data ingestion error that inflated the CT case rates. CDC, in collaboration with CT, has resolved the issue and the correction is reflected in this update.

    August 25, 2022: A laboratory in Tennessee reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate may be inflated in many counties and the CCLs published on August 25, 2022 should be interpreted with caution.

    August 25, 2022: Due to a data source error, the 7-day case rate for St. Louis County, Missouri, is reported as zero in the COVID-19 Community Level data released on August 25, 2022. Therefore, the COVID-19 Community Level for this county should be interpreted with caution.

    September 1, 2022: Due to a reporting issue, case rates for all Nebraska counties will include 6 days of data instead of 7 days in the COVID-19 Community Level (CCL) data released on September 1, 2022. Therefore, the CCLs for all Nebraska counties should be interpreted with caution.

    September 8, 2022: Due to a data processing error, the case rate for Philadelphia County, Pennsylvania,

  10. COVID-19 Case Surveillance Public Use Data

    • data.virginia.gov
    • paperswithcode.com
    • +6more
    csv, json, rdf, xsl
    Updated Feb 23, 2025
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    Centers for Disease Control and Prevention (2025). COVID-19 Case Surveillance Public Use Data [Dataset]. https://data.virginia.gov/dataset/covid-19-case-surveillance-public-use-data
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    rdf, csv, json, xslAvailable download formats
    Dataset updated
    Feb 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    Note: Reporting of new COVID-19 Case Surveillance data will be discontinued July 1, 2024, to align with the process of removing SARS-CoV-2 infections (COVID-19 cases) from the list of nationally notifiable diseases. Although these data will continue to be publicly available, the dataset will no longer be updated.

    Authorizations to collect certain public health data expired at the end of the U.S. public health emergency declaration on May 11, 2023. The following jurisdictions discontinued COVID-19 case notifications to CDC: Iowa (11/8/21), Kansas (5/12/23), Kentucky (1/1/24), Louisiana (10/31/23), New Hampshire (5/23/23), and Oklahoma (5/2/23). Please note that these jurisdictions will not routinely send new case data after the dates indicated. As of 7/13/23, case notifications from Oregon will only include pediatric cases resulting in death.

    This case surveillance public use dataset has 12 elements for all COVID-19 cases shared with CDC and includes demographics, any exposure history, disease severity indicators and outcomes, presence of any underlying medical conditions and risk behaviors, and no geographic data.

    CDC has three COVID-19 case surveillance datasets:

    The following apply to all three datasets:

    Overview

    The COVID-19 case surveillance database includes individual-level data reported to U.S. states and aut

  11. T

    CORONAVIRUS DEATHS by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 4, 2020
    + more versions
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    CORONAVIRUS DEATHS by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/coronavirus-deaths
    Explore at:
    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Mar 4, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    2025
    Area covered
    World
    Description

    This dataset provides values for CORONAVIRUS DEATHS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  12. Total number of U.S. COVID-19 cases and deaths April 26, 2023

    • statista.com
    Updated May 15, 2024
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    Statista (2024). Total number of U.S. COVID-19 cases and deaths April 26, 2023 [Dataset]. https://www.statista.com/statistics/1101932/coronavirus-covid19-cases-and-deaths-number-us-americans/
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    Dataset updated
    May 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of April 26, 2023, the number of both confirmed and presumptive positive cases of the COVID-19 disease reported in the United States had reached over 104 million with over 1.1 million deaths reported among these cases.

    Coronavirus deaths by age in the U.S. Daily new cases of COVID-19 hit record highs in the United States at the beginning of 2022. Underlying health conditions can worsen cases of coronavirus, and case fatality rates among confirmed COVID-19 patients increase with age. The highest number of deaths from COVID-19 have been among those aged 85 years and older, with this age group accounting for over 300 thousand deaths.

    Where has this coronavirus come from? Coronaviruses are a large group of viruses transmitted between animals and people that cause illnesses ranging from the common cold to more severe diseases. The novel coronavirus that is currently infecting humans was already circulating among certain animal species. The first human case of this new coronavirus strain was reported in China at the end of December 2019. The coronavirus was named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and its associated disease is known as COVID-19.

  13. Share of U.S. adults who had COVID-19 and experienced Long COVID, 2024, by...

    • statista.com
    Updated Oct 29, 2024
    + more versions
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    Statista (2024). Share of U.S. adults who had COVID-19 and experienced Long COVID, 2024, by age group [Dataset]. https://www.statista.com/statistics/1401587/percentage-of-adults-who-ever-experienced-long-covid-in-the-us-by-age-group/
    Explore at:
    Dataset updated
    Oct 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 20, 2024 - Sep 16, 2024
    Area covered
    United States
    Description

    According to a survey conducted from August 20 to September 16, 2024, approximately 35 percent of U.S. adults aged between 50 and 59 years who had COVID-19 experienced Long COVID, the highest share compared to other age groups. Individuals aged 40 to 49 followed, with 34 percent experiencing Long COVID symptoms. This statistic shows the percentage of adults who had COVID-19 and ever experienced Long COVID in the United States from August 20 to September 16, 2024, by age group.

  14. Number of COVID-19 deaths in the United States from 2020 to 2022, by year

    • statista.com
    Updated May 8, 2023
    + more versions
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    Statista (2023). Number of COVID-19 deaths in the United States from 2020 to 2022, by year [Dataset]. https://www.statista.com/statistics/1382334/number-covid-deaths-us-by-year/
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    Dataset updated
    May 8, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2020, there were around 384,536 deaths in the United States caused by COVID-19, compared to 462,193 COVID-19 deaths in 2021. This statistic shows the total number of deaths due to COVID-19 in the United States in 2020, 2021, and 2022.

  15. COVID-19 deaths reported in the U.S. as of June 14, 2023, by place of death

    • statista.com
    Updated May 15, 2024
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    COVID-19 deaths reported in the U.S. as of June 14, 2023, by place of death [Dataset]. https://www.statista.com/statistics/1113068/reported-deaths-from-covid-by-place-of-death-us/
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    Dataset updated
    May 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Between the beginning of January 2020 and June 14, 2023, of 1,134,660 deaths caused by COVID-19 in the United States, around 742,587 occurred in an inpatient healthcare setting. This statistic shows the number of coronavirus disease 2019 (COVID-19) deaths in the U.S. from January 2020 to June 2023, by place of death.

  16. Death Care market will grow at a CAGR of 4.50% from 2024 to 2031.

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
    Updated Jan 15, 2025
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    Cognitive Market Research (2025). Death Care market will grow at a CAGR of 4.50% from 2024 to 2031. [Dataset]. https://www.cognitivemarketresearch.com/death-care-market-report
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jan 15, 2025
    Dataset authored and provided by
    Cognitive Market Research
    License

    https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy

    Time period covered
    2021 - 2033
    Area covered
    Global
    Description

    According to Cognitive Market Research, the global Death Care market size is USD 122584.2 million in 2024 and will expand at a compound annual growth rate (CAGR) of 4.50% from 2024 to 2031.

    North America holds the major market of more than 40% of the global revenue with a market size of USD 49033.68 million in 2024 and will grow at a compound annual growth rate (CAGR) of 2.7% from 2024 to 2031.
    Europe accounted for a share of over 30% of the global market size of USD 36775.26 million.
    Asia Pacific holds the market of around 23% of the global revenue with a market size of USD 28194.37 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.5% from 2024 to 2031.
    Latin America holds the market of more than 5% of the global revenue with a market size of USD 6129.21 million in 2024 and will grow at a compound annual growth rate (CAGR) of 3.9% from 2024 to 2031.
    Middle East and Africa holds the major market of around 2% of the global revenue with a market size of USD 2451.68 million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.2% from 2024 to 2031.
    Corporate holds the highest Death Care market revenue share in 2024.
    

    Market Dynamics of Death Care Market

    Key Drivers for Death Care Market

    Rising Geriatric Population to Increase the Demand Globally

    The growing number of senior persons worldwide is driving the geriatric population growth. Longer life expectancies increase mortality rates, which expands the need for death care services' customers. The need for all-inclusive end-of-life solutions, such as funeral planning, cremation services, and grief assistance, is highlighted by this shift in the population. The death care industry is seeing constant demand and innovation as societies struggle with the effects of an aging population. It is crucial for service providers to adjust to the changing needs of this particular demographic group in order to provide dignified and courteous end-of-life experiences.

    Increasing urbanization to Propel Market Growth

    The increasing trend of urbanization encourages a move toward smaller living areas, which reduces the number of house burials that are customary. In order to meet the demands of urban people, funeral houses, cemeteries, and cremation services are in high demand. The accessibility and availability of death care facilities become critical factors as cities grow and populations congregate. In metropolitan settings, funeral houses and crematoriums are essential for providing effective end-of-life care that are sensitive to cultural differences. This shift brought about by urbanization highlights the need for flexible death care methods so that people can pay their loved ones a proper tribute even in the face of physical limitations.

    Restraint Factor for the Death Care Market

    Lack of Awareness to Limit the Sales

    There's a widespread ignorance in many poor countries about the range of death care services available. This shortfall limits the market's ability to grow in terms of new and creative solutions. People who lack information are frequently forced to use traditional methods, which hinders the adoption of more modern, effective, and culturally sensitive death care options. In order to close this informational gap and enable communities to make knowledgeable decisions about end-of-life preparations, education and outreach programs become essential. A more dynamic and responsive death care sector that caters to the changing needs and preferences of varied people worldwide can be fostered by stakeholders by raising knowledge and understanding of the wide range of services that are offered.

    Impact of Covid-19 on the Death Care Market

    The COVID-19 pandemic has had a major effect on the death care industry, leading to changes in consumer behavior and disruptions. Health and safety concerns have prompted modifications in funeral customs, including gathering bans and social distancing measures that modify customary funeral settings. Due to the perception that cremations pose a reduced risk of transmission than traditional burials, demand for these services has surged. Furthermore, the state of the economy has affected how people spend their money, with some choosing more straightforward and affordable final arrangements. Funeral homes and death care providers have had to quickly adjust to accommodate the changing demands of bereaved families while adhering to health s...

  17. COVID-19 cases and deaths in Brazil 2020-2024

    • statista.com
    Updated Aug 13, 2024
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    Statista (2024). COVID-19 cases and deaths in Brazil 2020-2024 [Dataset]. https://www.statista.com/statistics/1107028/brazil-covid-19-cases-deaths/
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    Dataset updated
    Aug 13, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 27, 2020 - Jul 28, 2024
    Area covered
    Brazil
    Description

    COVID-19 was first detected in Brazil on February 27, 2020, making it the first Latin American country to report a case of the novel coronavirus. Since then, the number of infections has risen drastically, reaching approximately 38 million cases by July 28, 2024. Meanwhile, the first local death due to the disease was reported in March 2020. Four years later, the number of fatal cases had surpassed 700,000. The highest COVID-19 death toll in Latin America With a population of more than 211 million inhabitants as of 2020, Brazil is the most populated country in Latin America. This nation is also among the most affected by COVID-19 in number of deaths, not only within the Latin American region, but also worldwide, just behind the United States. These figures have raised a debate on how the Brazilian government has dealt with the pandemic. In fact, according to a study carried out in May 2021, more than half of Brazilians surveyed disapproved of the way in which former president Jair Bolsonaro had been dealing with the health crisis. In comparison, a third of respondents had a similar opinion about the Ministry of Health. Brazil’s COVID-19 vaccination campaign rollout Brazil’s vaccination campaign started at the beginning of 2021, when a nurse from São Paulo became the first person in the country to get vaccinated against the disease. A few years later, roughly 88 percent of the Brazilian population had received at least one vaccine dose, while around 81 percent had already completed the basic immunization scheme. With more than 485.2 million vaccines administered as of March 2023, Brazil was the fourth country with the most administered doses of the COVID-19 vaccine globally, after China, India, and the United States.Find the most up-to-date information about the coronavirus pandemic in the world under Statista’s COVID-19 facts and figures site.

  18. Severe Acute Respiratory Syndrome Coronavirus Infection Market:...

    • imarcgroup.com
    pdf,excel,csv,ppt
    Updated Jul 18, 2023
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    IMARC Group (2023). Severe Acute Respiratory Syndrome Coronavirus Infection Market: Epidemiology, Industry Trends, Share, Size, Growth, Opportunity, and Forecast 2024-2034 [Dataset]. https://www.imarcgroup.com/severe-acute-respiratory-syndrome-coronavirus-infection-market
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jul 18, 2023
    Dataset provided by
    Imarc Group
    Authors
    IMARC Group
    License

    https://www.imarcgroup.com/privacy-policyhttps://www.imarcgroup.com/privacy-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Market Overview:

    The 7 major severe acute respiratory syndrome coronavirus infection markets reached a value of US$ 21.4 Billion in 2023. Looking forward, IMARC Group expects the 7MM to reach US$ 68.5 Billion by 2034, exhibiting a growth rate (CAGR) of 11.14% during 2024-2034.

    Report Attribute
    Key Statistics
    Base Year
    2023
    Forecast Years 2024-2034
    Historical Years
    2018-2023
    Market Size in 2023
    US$ 21.4 Billion
    Market Forecast in 2034
    US$ 68.5 Billion
    Market Growth Rate (2024-2034)
    11.14%


    The severe acute respiratory syndrome coronavirus infection market has been comprehensively analyzed in IMARC's new report titled "Severe Acute Respiratory Syndrome Coronavirus Infection Market: Epidemiology, Industry Trends, Share, Size, Growth, Opportunity, and Forecast 2024-2034". Severe acute respiratory syndrome coronavirus infection, commonly known as SARS-CoV, is a viral pulmonary illness caused by the SARS coronavirus. The primary transmission mode of this ailment is through respiratory droplets when an infected individual sneezes or coughs. It can also spread by contacting surfaces contaminated with the virus and then touching the face. The common symptoms of the disorder include high fever, cough, shortness of breath, difficulty breathing, chills, body aches, headaches, diarrhea, nausea, vomiting, etc. In severe cases, individuals suffering from this disease may also experience pneumonia, respiratory distress, hypoxemia, or multiple organ failure. The diagnosis of SARS-CoV infection typically requires a combination of clinical presentation, medical history review, and a physical examination. Polymerase chain reaction testing is also used to detect the genetic material (RNA) of the virus in respiratory samples, such as nasal swabs, throat swabs, or sputum. The healthcare provider may further conduct chest X-rays and computed tomography scans to assess lung involvement and identify any characteristic patterns associated with the disease, like ground-glass opacities or consolidation.

    Severe Acute Respiratory Syndrome Coronavirus Infection Markethttps://www.imarcgroup.com/CKEditor/a9888831-3dab-468f-bef9-f9e872ac7e88severe-acute-respiratory-syndrome-coronavirus-infection-market.webp" style="height:450px; width:800px" />

    The increasing prevalence of viral shedding through respiratory droplets when an infected individual sneezes, coughs, talks, or breathes heavily in close proximity to others is primarily driving the severe acute respiratory syndrome coronavirus infection market. In addition to this, the expanding geriatric population, who have weakened immunity, along with pre-existing health conditions like cardiovascular disease and diabetes, is also creating a positive outlook for the market. Moreover, the widespread adoption of immunomodulatory therapies, including intravenous immunoglobulin (IVIG) and monoclonal antibodies, to modulate the production and activity of pro-inflammatory cytokines is further bolstering the market growth. Apart from this, the inflating application of respiratory physiotherapy, since it involves techniques that help in clearing secretions from the lungs, improving pulmonary function, and promoting better breathing in patients is acting as another significant growth-inducing factor. Additionally, the emerging popularity of extracorporeal membrane oxygenation procedures, which provide circulatory support by ensuring adequate blood flow to vital organs, is expected to drive the severe acute respiratory syndrome coronavirus infection market during the forecast period.

    IMARC Group's new report provides an exhaustive analysis of the severe acute respiratory syndrome coronavirus infection market in the United States, EU4 (Germany, Spain, Italy, and France), United Kingdom, and Japan. This includes treatment practices, in-market, and pipeline drugs, share of individual therapies, market performance across the seven major markets, market performance of key companies and their drugs, etc. The report also provides the current and future patient pool across the seven major markets. According to the report, the United States has the largest patient pool for severe acute respiratory syndrome coronavirus infection and also represents the largest market for its treatment. Furthermore, the current treatment practice/algorithm, market drivers, challenges, opportunities, reimbursement scenario, unmet medical needs, etc., have also been provided in the report. This report is a must-read for manufacturers, investors, business strategists, researchers, consultants, and all those who have any kind of stake or are planning to foray into the severe acute respiratory syndrome coronavirus infection market in any manner.

    Key Highlights:

    • The majority of patients diagnosed with severe acute respiratory syndrome coronavirus infection were noted to be previously healthy individuals aged 25 to 70 years.
    • Several suspected cases of severe acute respiratory syndrome coronavirus infection have been recorded in children under the age of 15.
    • The case fatality rate among patients with sickness, fulfilling the new WHO case criteria for probable and suspected cases of severe acute respiratory syndrome coronavirus infection, is around 3%.
    • Approximately 75% of COVID-19 deaths in the United States were among people aged 65 and older.
    • The highest death rates were among non-Hispanic Black people and non-Hispanic American Indian or Alaska Native people.


    Drugs:

    Spikevax is a vaccination designed to prevent coronavirus disease 2019 (COVID-19) in people as young as six months old. The original Spikevax comprises elasomeran, a molecule known as messenger RNA (mRNA) containing instructions for creating a protein from the original strain of SARS-CoV-2, the virus that causes COVID-19.

    SNG001 is a recombinant interferon (IFN)-β1a formulation administered to the lungs by a nebulizer. IFN-β is a naturally occurring protein that stimulates host immune responses against most viruses, including severe acute respiratory syndrome coronavirus.

    NA-831 is a tiny pharmacological molecule with neuroprotective properties, which means it can prevent or reduce disease development by halting or decreasing neuronal death. The medication also has neurogenesis and cognitive protective characteristics across a variety of illness types. NA-831 is in Phase 2/3 clinical trials with FDA-approved antiviral medicines Atazanavir and Dexamethasone to treat Covid-19.


    Time Period of the Study

    • Base Year: 2023
    • Historical Period: 2018-2023
    • Market Forecast: 2024-2034

    Countries Covered

    • United States
    • Germany
    • France
    • United Kingdom
    • Italy
    • Spain
    • Japan

    Analysis Covered Across Each Country

    • Historical, current, and future epidemiology scenario
    • Historical, current, and future performance of the severe acute respiratory syndrome coronavirus infection market
    • Historical, current, and future performance of various therapeutic categories in the market
    • Sales of various drugs across the severe acute respiratory syndrome coronavirus infection market
    • Reimbursement scenario in the market
    • In-market and pipeline drugs


    Competitive Landscape:

    This report also provides a detailed analysis of the current severe acute respiratory syndrome coronavirus infection marketed drugs and late-stage pipeline drugs.

    In-Market Drugs

    • Drug Overview
    • <li

  19. 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
    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.

  20. h

    Country_Covid19_Daily_2021

    • huggingface.co
    Updated Apr 10, 2021
    + more versions
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    Work With Data (2021). Country_Covid19_Daily_2021 [Dataset]. https://huggingface.co/datasets/WorkWithData/Country_Covid19_Daily_2021
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 10, 2021
    Dataset authored and provided by
    Work With Data
    License

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

    Description

    This dataset shows daily cases and deaths from Covid-19 by country in 2020. The dataset can also be found on: https://www.workwithdata.com/datasets/covid-country-daily?f=2&fcol0=date&fcol1=date&fop0=%3C&fop1=%3E&fval0=2021-12-31&fval1=2021-01-01 Similar datasets can be found on: https://www.workwithdata.com

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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
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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.

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