87 datasets found
  1. COVID-19 infection and death rates per 100,000 population in Italy as of...

    • statista.com
    Updated Jul 8, 2020
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    Statista (2020). COVID-19 infection and death rates per 100,000 population in Italy as of June 2020 [Dataset]. https://www.statista.com/statistics/1119146/covid-19-infection-and-death-rates-per-100-000-inhabitants-italy/
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    Dataset updated
    Jul 8, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    Italy
    Description

    As of July 8, 2020, the total number of coronavirus (COVID-19) cases reached nearly 242 thousand, while the number of deaths stood at approximately 35 thousand. This means that the infection rate per 100 thousand population was 400.4, while the death rate per 100 thousand population was 57.7. Both figures were among the highest recorded worldwide. In fact, Italy was one of the worst hit countries by the pandemic.

  2. d

    COVID-19 Cases and Deaths by Age Group - ARCHIVE

    • catalog.data.gov
    • data.ct.gov
    • +1more
    Updated Aug 12, 2023
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    data.ct.gov (2023). COVID-19 Cases and Deaths by Age Group - ARCHIVE [Dataset]. https://catalog.data.gov/dataset/covid-19-cases-and-deaths-by-age-group
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    Dataset updated
    Aug 12, 2023
    Dataset provided by
    data.ct.gov
    Description

    Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken out by age group. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the daily COVID-19 update. Data are reported daily, with timestamps indicated in the daily briefings posted at: portal.ct.gov/coronavirus. Data are subject to future revision as reporting changes. Starting in July 2020, this dataset will be updated every weekday. Additional notes: A delay in the data pull schedule occurred on 06/23/2020. Data from 06/22/2020 was processed on 06/23/2020 at 3:30 PM. The normal data cycle resumed with the data for 06/23/2020. A network outage on 05/19/2020 resulted in a change in the data pull schedule. Data from 5/19/2020 was processed on 05/20/2020 at 12:00 PM. Data from 5/20/2020 was processed on 5/20/2020 8:30 PM. The normal data cycle resumed on 05/20/2020 with the 8:30 PM data pull. As a result of the network outage, the timestamp on the datasets on the Open Data Portal differ from the timestamp in DPH's daily PDF reports. Starting 5/10/2021, the date field will represent the date this data was updated on data.ct.gov. Previously the date the data was pulled by DPH was listed, which typically coincided with the date before the data was published on data.ct.gov. This change was made to standardize the COVID-19 data sets on data.ct.gov.

  3. COVID-19 cases and deaths per million in 210 countries as of July 13, 2022

    • statista.com
    Updated Jul 13, 2022
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    Statista (2022). COVID-19 cases and deaths per million in 210 countries as of July 13, 2022 [Dataset]. https://www.statista.com/statistics/1104709/coronavirus-deaths-worldwide-per-million-inhabitants/
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    Dataset updated
    Jul 13, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

    The difficulties of death figures

    This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

    Where are these numbers coming from?

    The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

  4. d

    Nursing Homes with Residents Positive for COVID-19, April - June 2020 -...

    • catalog.data.gov
    • data.ct.gov
    • +1more
    Updated Jun 28, 2025
    + more versions
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    data.ct.gov (2025). Nursing Homes with Residents Positive for COVID-19, April - June 2020 - Archive [Dataset]. https://catalog.data.gov/dataset/nursing-homes-with-residents-positive-for-covid-19-april-june-2020
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    Dataset updated
    Jun 28, 2025
    Dataset provided by
    data.ct.gov
    Description

    Nursing homes with residents positive for COVID-19 from 4/22/2020 to 6/19/2020. Starting in July 2020, this dataset will no longer be updated and will be replaced by the CMS COVID-19 Nursing Home Dataset, available at the following link: https://data.ct.gov/Health-and-Human-Services/CMS-COVID-19-Nursing-Home-Dataset/w8wc-65i5. Methods: 1) Laboratory-confirmed case counts are based upon data reported via the FLIS web portal. Nursing homes were asked to provide cumulative totals of residents with laboratory confirmed covid. This includes residents currently in-house, in the hospital, or who are deceased. Residents were excluded if they tested positive prior to initial admission to the nursing home. 2) The cumulative number of deaths among nursing home residents is based upon data reported by the Office of the Chief Medical Examiner. For public health surveillance, COVID-19-associated deaths include persons who tested positive for COVID-19 around the time of death (laboratory-confirmed) and persons whose death certificate lists COVID-19 disease as a cause of death or a significant condition contributing to death (probable). Limitations: 1) As of the week of 5/10/20, Point Prevalence Survey testing is being offered to all asymptomatic nursing home residents to inform infection prevention efforts. Point prevalence surveys will be conducted over a period of several weeks. Some nursing homes had adequate testing resources available to conduct surveys prior to this date. Differences in survey timing will impact the number of positive results that a nursing home reports. 2) Cumulative totals of residents testing positive are being collected rather than individual resident data. Thus we cannot verify the counts, de-duplicate, and/or verify whether there is a record of a positive lab test. This may result in either under- or over-counting. 3) The number of COVID-19 positive residents and the number of confirmed deaths among residents are tabulated from different data sources. Due to the timing of availability of test results for deceased residents, it is not appropriate to calculate the percent of cases who died due to COVID-19 at any particular facility based upon this data. 4) The count of deaths reported for 4/14 are not included in this dataset, as they were not broken out by laboratory-confirmed or probable. They can be viewed in the DPH Report here: https://portal.ct.gov/-/media/Coronavirus/CTDPHCOVID19summary4162020.pdf?la=en

  5. O

    COVID-19 Cases and Deaths by Race/Ethnicity - ARCHIVE

    • data.ct.gov
    • s.cnmilf.com
    • +2more
    csv, xlsx, xml
    Updated Jun 24, 2022
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    Department of Public Health (2022). COVID-19 Cases and Deaths by Race/Ethnicity - ARCHIVE [Dataset]. https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-and-Deaths-by-Race-Ethnicity-ARCHIV/7rne-efic
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    xlsx, csv, xmlAvailable download formats
    Dataset updated
    Jun 24, 2022
    Dataset authored and provided by
    Department of Public Health
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve.

    The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj.

    The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 .

    The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 .

    The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed.

    COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update.

    The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates.

    The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used.

    Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf

    Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic.

    Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics

    Data are subject to future revision as reporting changes.

    Starting in July 2020, this dataset will be updated every weekday.

    Additional notes: A delay in the data pull schedule occurred on 06/23/2020. Data from 06/22/2020 was processed on 06/23/2020 at 3:30 PM. The normal data cycle resumed with the data for 06/23/2020.

    A network outage on 05/19/2020 resulted in a change in the data pull schedule. Data from 5/19/2020 was processed on 05/20/2020 at 12:00 PM. Data from 5/20/2020 was processed on 5/20/2020 8:30 PM. The normal data cycle resumed on 05/20/2020 with the 8:30 PM data pull. As a result of the network outage, the timestamp on the datasets on the Open Data Portal differ from the timestamp in DPH's daily PDF reports.

    Starting 5/10/2021, the date field will represent the date this data was updated on data.ct.gov. Previously the date the data was pulled by DPH was listed, which typically coincided with the date before the data was published on data.ct.gov. This change was made to standardize the COVID-19 data sets on data.ct.gov.

  6. d

    COVID-19 Tests, Cases, and Deaths (By Town) - ARCHIVE

    • catalog.data.gov
    • data.ct.gov
    Updated Aug 12, 2023
    + more versions
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    data.ct.gov (2023). COVID-19 Tests, Cases, and Deaths (By Town) - ARCHIVE [Dataset]. https://catalog.data.gov/dataset/covid-19-tests-cases-and-deaths-by-town
    Explore at:
    Dataset updated
    Aug 12, 2023
    Dataset provided by
    data.ct.gov
    Description

    DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases, tests, and associated deaths from COVID-19 that have been reported among Connecticut residents. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the daily COVID-19 update. The case rate per 100,000 includes probable and confirmed cases. Probable and confirmed are defined using the CSTE case definition, which is available online: https://cdn.ymaws.com/www.cste.org/resource/resmgr/2020ps/Interim-20-ID-01_COVID-19.pdf The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 CO

  7. Share of U.S. COVID-19 cases resulting in death from Feb. 12 to Mar. 16, by...

    • statista.com
    Updated Aug 28, 2020
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    Statista (2020). Share of U.S. COVID-19 cases resulting in death from Feb. 12 to Mar. 16, by age [Dataset]. https://www.statista.com/statistics/1105431/covid-case-fatality-rates-us-by-age-group/
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    Dataset updated
    Aug 28, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 12, 2020 - Mar 16, 2020
    Area covered
    United States
    Description

    Among COVID-19 patients in the United States from February 12 to March 16, 2020, estimated case-fatality rates were highest for adults aged 85 years and older. Younger people appeared to have milder symptoms, and there were no deaths reported among persons aged 19 years and under.

    Tracking the virus in the United States The outbreak of a previously unknown viral pneumonia was first reported in China toward the end of December 2019. The first U.S. case of COVID-19 was recorded in mid-January 2020, confirmed in a patient who had returned to the United States from China. The virus quickly started to spread, and the first community-acquired case was confirmed one month later in California. Overall, there had been approximately 4.5 million coronavirus cases in the country by the start of August 2020.

    U.S. health care system stretched California, Florida, and Texas are among the states with the most coronavirus cases. Even the best-resourced hospitals in the United States have struggled to cope with the crisis, and certain areas of the country were dealt further blows by new waves of infections in July 2020. Attention is rightly focused on fighting the pandemic, but as health workers are redirected to care for COVID-19 patients, the United States must not lose sight of other important health care issues.

  8. Examples of the different approaches to mitigate transmission of COVID-19...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 1, 2023
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    Lucy Bray; Bernie Carter; Lucy Blake; Holly Saron; Jennifer A. Kirton; Fanny Robichaud; Marla Avila; Karen Ford; Begonya Nafria; Maria Forsner; Stefan Nilsson; Andrea Chelkowski; Andrea Middleton; Anna-Clara Rullander; Janet Mattsson; Joanne Protheroe (2023). Examples of the different approaches to mitigate transmission of COVID-19 and provide information to children about COVID-19 (coronavirus) within the participating countries during the time of the study. [Dataset]. http://doi.org/10.1371/journal.pone.0246405.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Lucy Bray; Bernie Carter; Lucy Blake; Holly Saron; Jennifer A. Kirton; Fanny Robichaud; Marla Avila; Karen Ford; Begonya Nafria; Maria Forsner; Stefan Nilsson; Andrea Chelkowski; Andrea Middleton; Anna-Clara Rullander; Janet Mattsson; Joanne Protheroe
    License

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

    Description

    Examples of the different approaches to mitigate transmission of COVID-19 and provide information to children about COVID-19 (coronavirus) within the participating countries during the time of the study.

  9. O

    COVID-19 Death Counts by Demographic 5/11/2023

    • data.cambridgema.gov
    csv, xlsx, xml
    Updated May 11, 2023
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    Cambridge Department of Public Health (2023). COVID-19 Death Counts by Demographic 5/11/2023 [Dataset]. https://data.cambridgema.gov/Public-Health/COVID-19-Death-Counts-by-Demographic-5-11-2023/5rax-scyt
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    xlsx, csv, xmlAvailable download formats
    Dataset updated
    May 11, 2023
    Dataset authored and provided by
    Cambridge Department of Public Health
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    This dataset is no longer being updated as of 5/11/2023. It is being retained on the Open Data Portal for its potential historical interest.

    This table displays the number of COVID-19 deaths among Cambridge residents by race and ethnicity. The count reflects total deaths among Cambridge COVID-19 cases.

    The rate column shows the rate of COVID-19 deaths among Cambridge residents by race and ethnicity. The rates in this chart were calculated by dividing the total number of deaths among Cambridge COVID-19 cases for each racial or ethnic category by the total number of Cambridge residents in that racial or ethnic category, and multiplying by 10,000. The rates are considered “crude rates” because they are not age-adjusted. Population data are from the U.S. Census Bureau’s 2014–2018 American Community Survey estimates and may differ from actual population counts.

    Of note:

    This chart reflects the time period of March 25 (first known Cambridge death) through present.

    It is important to note that race and ethnicity data are collected and reported by multiple entities and may or may not reflect self-reporting by the individual case. The Cambridge Public Health Department (CPHD) is actively reaching out to cases to collect this information. Due to these efforts, race and ethnicity information have been confirmed for over 80% of Cambridge cases, as of June 2020.

    Race/Ethnicity Category Definitions: “White” indicates “White, not of Hispanic origin.” “Black” indicates “Black, not of Hispanic origin.” “Hispanic” refers to a person having Hispanic origin. A person having Hispanic origin may be of any race. “Asian” indicates “Asian, not of Hispanic origin.” To protect individual privacy, a category is suppressed when it has one to four people. Categories with zero cases are reported as zero. "Other" indicates multiple races, another race that is not listed above, and cases who have reported nationality in lieu of a race category recognized by the US Census. Population data are from the U.S. Census Bureau’s 2014–2018 American Community Survey estimates and may differ from actual population counts. "Other" also includes a small number of people who identify as Native American or Native Hawaiian/Pacific islander. Because the count for Native Americans or Native Hawaiian/Pacific Islanders is currently < 5 people, these categories have been combined with “Other” to protect individual privacy.

  10. Total death by COVID-19 in different regions

    • kaggle.com
    zip
    Updated Jul 11, 2020
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    Salman Ibne Eunus (2020). Total death by COVID-19 in different regions [Dataset]. https://www.kaggle.com/salmaneunus/total-death-by-covid19-in-different-regions
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    zip(101276 bytes)Available download formats
    Dataset updated
    Jul 11, 2020
    Authors
    Salman Ibne Eunus
    Description

    Context

    Death in COVID-19 from March to June 2020

    Content

    Number of Deaths in different countries

    Acknowledgements

    We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.

    Inspiration

    Your data will be in front of the world's largest data science community. What questions do you want to see answered?

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

    • statista.com
    Updated Jun 15, 2023
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    Statista (2023). 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
    Jun 15, 2023
    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.

  12. d

    Percentage of provider spells with COVID-19 coding

    • digital.nhs.uk
    csv, pdf, xls, xlsx
    Updated May 13, 2021
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    (2021). Percentage of provider spells with COVID-19 coding [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/shmi/2021-05
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    csv(9.7 kB), xlsx(31.8 kB), xls(76.8 kB), pdf(205.0 kB)Available download formats
    Dataset updated
    May 13, 2021
    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, 2020 - Dec 31, 2020
    Area covered
    England
    Description

    This is an indicator designed to accompany the Summary Hospital-level Mortality Indicator (SHMI). As of the July 2020 publication, COVID-19 activity has been excluded from the SHMI. The SHMI is not designed for this type of pandemic activity and the statistical modelling used to calculate the SHMI may not be as robust if such activity were included. This indicator shows the number of provider spells which are coded as COVID-19, and therefore excluded from the SHMI, as a percentage of all provider spells in the SHMI (prior to the exclusion). This indicator is being published as an experimental statistic. Experimental statistics are official statistics which are published in order to involve users and stakeholders in their development and as a means to build in quality at an early stage. Notes: 1. Please note that there has been a fall in the number of spells for most trusts between this publication and the previous SHMI publication, ranging from 0 per cent to 5 per cent. This is due to COVID-19 impacting on activity from March 2020 onwards and appears to be an accurate reflection of hospital activity rather than a case of missing data. 2. The data for St Helens and Knowsley Teaching Hospitals NHS Trust (trust code RBN) has incomplete information on secondary conditions that the patients suffers from, and this will have affected the calculation of this indicator. Values for this trust should therefore be interpreted with caution. Please note, this issue was not identified until after this publication was initially released on 13th May 2021. Data quality notices were later added to this publication in July 2021. 3. Day cases and regular day attenders are excluded from the SHMI. However, some day cases for University College London Hospitals NHS Foundation Trust (trust code RRV) have been incorrectly classified as ordinary admissions meaning that they have been included in the SHMI. Maidstone and Tunbridge Wells NHS Trust (trust code RWF) has submitted a number of records with a patient classification of ‘day case’ or ‘regular day attender’ and an intended management value of ‘patient to stay in hospital for at least one night’. This mismatch has resulted in the patient classification being updated to ‘ordinary admission’ by the HES data cleaning rules. This may have resulted in the number of ordinary admissions being overstated. The trust has been contacted to clarify what the correct patient classification is for these records. Values for these trusts should therefore be interpreted with caution. 4. There is a shortfall in the number of records for Mid Cheshire Hospitals NHS Foundation Trust (trust code RBT), meaning that values for this trust are based on incomplete data and should therefore be interpreted with caution. 5. We recommend that values for Guy’s and St Thomas’ NHS Foundation Trust (trust code RJ1) are interpreted with caution as there is a possible shortfall in the number of records which is currently under investigation. 6. On 1 April 2021 Western Sussex Hospitals NHS Foundation Trust (trust code RYR) merged with Brighton and Sussex University Hospitals NHS Trust (trust code RXH). The new trust is called University Hospitals Sussex NHS Foundation Trust (trust code RYR). However, as we received notification of this change after data processing for this publication began, separate indicator values have been produced for this publication. The next publication in this series will reflect the updated organisation structure. 7. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of the publication page.

  13. d

    COVID-19 Cases and Deaths by Gender - ARCHIVE

    • catalog.data.gov
    • data.ct.gov
    Updated Aug 12, 2023
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    data.ct.gov (2023). COVID-19 Cases and Deaths by Gender - ARCHIVE [Dataset]. https://catalog.data.gov/dataset/covid-19-cases-and-deaths-by-gender
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    Dataset updated
    Aug 12, 2023
    Dataset provided by
    data.ct.gov
    Description

    Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by gender. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the daily COVID-19 update. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics Data are reported daily, with timestamps indicated in the daily briefings posted at: portal.ct.gov/coronavirus. Data are subject to future revision as reporting changes. Starting in Ju

  14. Excess Mortality and COVID-19 Related Deaths in Northern Ireland: March-June...

    • gov.uk
    Updated Jul 28, 2020
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    Northern Ireland Statistics and Research Agency (2020). Excess Mortality and COVID-19 Related Deaths in Northern Ireland: March-June 2020 [Dataset]. https://www.gov.uk/government/statistics/excess-mortality-and-covid-19-related-deaths-in-northern-ireland-march-june-2020
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    Dataset updated
    Jul 28, 2020
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Northern Ireland Statistics and Research Agency
    Area covered
    Ireland, Northern Ireland
    Description

    This bulletin reports on excess mortality based on deaths occurring during the first four months (March to June) of the pandemic in Northern Ireland. Excess mortality is the difference between actual deaths in a period minus the expected number of deaths, based on historic data (average of previous five years). Excess mortality is analysed by age, sex, place of death, Local Government District and deprivation.

  15. Descriptive statistics on nursing home to CBSA COVID-19 mortality rate...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 9, 2023
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    Debasree Das Gupta; Uma Kelekar; Sidney C. Turner; Anupam A. Sule; Taya G. Jerman (2023). Descriptive statistics on nursing home to CBSA COVID-19 mortality rate ratio, June 2020—January 2021. [Dataset]. http://doi.org/10.1371/journal.pone.0256767.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 9, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Debasree Das Gupta; Uma Kelekar; Sidney C. Turner; Anupam A. Sule; Taya G. Jerman
    License

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

    Description

    Descriptive statistics on nursing home to CBSA COVID-19 mortality rate ratio, June 2020—January 2021.

  16. Data_Sheet_1_A chronological review of COVID-19 case fatality rate and its...

    • frontiersin.figshare.com
    pdf
    Updated Sep 15, 2023
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    Jing-Xing Li; Pei-Lun Liao; James Cheng-Chung Wei; Shu-Bai Hsu; Chih-Jung Yeh (2023). Data_Sheet_1_A chronological review of COVID-19 case fatality rate and its secular trend and investigation of all-cause mortality and hospitalization during the Delta and Omicron waves in the United States: a retrospective cohort study.PDF [Dataset]. http://doi.org/10.3389/fpubh.2023.1143650.s001
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    pdfAvailable download formats
    Dataset updated
    Sep 15, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Jing-Xing Li; Pei-Lun Liao; James Cheng-Chung Wei; Shu-Bai Hsu; Chih-Jung Yeh
    License

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

    Description

    IntroductionCoronavirus disease 2019 (COVID-19) has caused more than 690 million deaths worldwide. Different results concerning the death rates of the Delta and Omicron variants have been recorded. We aimed to assess the secular trend of case fatality rate (CFR), identify risk factors associated with mortality following COVID-19 diagnosis, and investigate the risks of mortality and hospitalization during Delta and Omicron waves in the United States.MethodsThis study assessed 2,857,925 individuals diagnosed with COVID-19 in the United States from January 2020, to June 2022. The inclusion criterion was the presence of COVID-19 diagnostic codes in electronic medical record or a positive laboratory test of the SARS-CoV-2. Statistical analysis was bifurcated into two components, longitudinal analysis and comparative analysis. To assess the discrepancies in hospitalization and mortality rates for COVID-19, we identified the prevailing periods for the Delta and Omicron variants.ResultsLongitudinal analysis demonstrated four sharp surges in the number of deaths and CFR. The CFR was persistently higher in males and older age. The CFR of Black and White remained higher than Asians since January 2022. In comparative analysis, the adjusted hazard ratios for all-cause mortality and hospitalization were higher in Delta wave compared to the Omicron wave. Risk of all-cause mortality was found to be greater 14–30 days after a COVID-19 diagnosis, while the likelihood of hospitalization was higher in the first 14 days following a COVID-19 diagnosis in Delta wave compared with Omicron wave. Kaplan–Meier analysis revealed the cumulative probability of mortality was approximately 2-fold on day 30 in Delta than in Omicron cases (log-rank p 

  17. f

    Table_1_Addition of Tocilizumab to the Standard of Care Reduces Mortality in...

    • datasetcatalog.nlm.nih.gov
    • frontiersin.figshare.com
    Updated Oct 2, 2020
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    Perisetti, Abhilash; Nanjappa, Arpitha; Goyal, Hemant; Boregowda, Umesha; Sridharan, Gurusaravanan Kutti; Gajendran, Mahesh (2020). Table_1_Addition of Tocilizumab to the Standard of Care Reduces Mortality in Severe COVID-19: A Systematic Review and Meta-Analysis.docx [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000559243
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    Dataset updated
    Oct 2, 2020
    Authors
    Perisetti, Abhilash; Nanjappa, Arpitha; Goyal, Hemant; Boregowda, Umesha; Sridharan, Gurusaravanan Kutti; Gajendran, Mahesh
    Description

    Introduction: Tocilizumab (TCZ) is an anti-interleukin-6 antibody that has been used for the treatment of severe coronavirus disease 2019 (COVID-19). However, concrete evidence of its benefit in reducing mortality in severe COVID-19 is lacking. Therefore, we performed a systematic review and meta-analysis of relevant studies that compared the efficacy of TCZ in severe COVID-19 vs. standard of care (SOC) alone.Methods: A literature search for studies that compared “tocilizumab” and “standard of care” in the treatment of COVID-19 was done using major online databases from December 2019 to June 14, 2020. Search words “Tocilizumab,” “anti-interleukin-6 antibody,” and “COVID-19” or “coronavirus 2019” in various combinations were used. Articles in the form of abstracts, letters without original data, case reports, and reviews were excluded. Data were gathered on an Excel sheet, and statistical analysis was performed using Review Manager 5.3.Results: Sixteen studies were eligible from 693 initial studies, including 3,641 patients (64% males). There were 13 retrospective studies and three prospective studies. There were 2,488 patients in the SOC group (61.7%) and 1,153 patients (68.7%) in the TCZ group. The death rate in the TCZ group, 22.4% (258/1,153), was lower than in the SOC group, 26.21% (652/2,488) [pooled odds ratio 0.57 (95% CI 0.36–0.92), p = 0.02]. There was a significant heterogeneity (inconsistency index = 80%) among the included studies.Conclusion: The addition of TCZ to the SOC might reduce mortality in severe COVID-19. More extensive randomized clinical trials are needed to validate these findings.

  18. Standardized mortality ratios for COVID-19 by age and male vs. female in São...

    • plos.figshare.com
    xls
    Updated Jun 3, 2023
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    Gisele Aparecida Fernandes; Antonio Paulo Nassar Junior; Gulnar Azevedo e Silva; Diego Feriani; Ivan Leonardo Avelino França e Silva; Pedro Caruso; Maria Paula Curado (2023). Standardized mortality ratios for COVID-19 by age and male vs. female in São Paulo, Brazil, from January to June 2020. [Dataset]. http://doi.org/10.1371/journal.pone.0252238.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Gisele Aparecida Fernandes; Antonio Paulo Nassar Junior; Gulnar Azevedo e Silva; Diego Feriani; Ivan Leonardo Avelino França e Silva; Pedro Caruso; Maria Paula Curado
    License

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

    Area covered
    Brazil, São Paulo
    Description

    Standardized mortality ratios for COVID-19 by age and male vs. female in São Paulo, Brazil, from January to June 2020.

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

    • catalog.data.gov
    • data.virginia.gov
    • +2more
    Updated Sep 26, 2025
    + more versions
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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
    Sep 26, 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.).

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

    • statista.com
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    Statista, 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 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.

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Statista (2020). COVID-19 infection and death rates per 100,000 population in Italy as of June 2020 [Dataset]. https://www.statista.com/statistics/1119146/covid-19-infection-and-death-rates-per-100-000-inhabitants-italy/
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COVID-19 infection and death rates per 100,000 population in Italy as of June 2020

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Dataset updated
Jul 8, 2020
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2020
Area covered
Italy
Description

As of July 8, 2020, the total number of coronavirus (COVID-19) cases reached nearly 242 thousand, while the number of deaths stood at approximately 35 thousand. This means that the infection rate per 100 thousand population was 400.4, while the death rate per 100 thousand population was 57.7. Both figures were among the highest recorded worldwide. In fact, Italy was one of the worst hit countries by the pandemic.

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