100+ datasets found
  1. COVID-19 surge testing outcomes reports: management information

    • gov.uk
    • s3.amazonaws.com
    Updated Jul 1, 2021
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    Public Health England (2021). COVID-19 surge testing outcomes reports: management information [Dataset]. https://www.gov.uk/government/statistical-data-sets/covid-19-surge-testing-outcomes-reports-management-information
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    Dataset updated
    Jul 1, 2021
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Public Health England
    Description

    https://assets.publishing.service.gov.uk/media/60dc5850e90e077173ce61c3/Surge_testing_summary_2021-06-29.ods">Surge testing summary 1 July 2021

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  2. d

    Connecticut COVID-19 Community Levels by County as Originally Posted -...

    • catalog.data.gov
    • data.ct.gov
    Updated Jun 21, 2025
    + more versions
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    data.ct.gov (2025). Connecticut COVID-19 Community Levels by County as Originally Posted - Archive [Dataset]. https://catalog.data.gov/dataset/connecticut-covid-19-community-levels-by-county-as-originally-posted
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    Dataset updated
    Jun 21, 2025
    Dataset provided by
    data.ct.gov
    Area covered
    Connecticut
    Description

    This public use dataset has 11 data elements reflecting COVID-19 community levels for all available counties. This dataset contains the same values used to display information available at https://www.cdc.gov/coronavirus/2019-ncov/science/community-levels-county-map.html. CDC looks at the 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 — to determine the COVID-19 community level. The COVID-19 community level is 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 is classified as low, medium , or high. COVID-19 Community Levels can 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. See https://www.cdc.gov/coronavirus/2019-ncov/science/community-levels.html for more information. Visit CDC’s COVID Data Tracker County View* to learn more about the individual metrics used for CDC’s COVID-19 community level in your county. Please note that county-level data are not available for territories. Go to https://covid.cdc.gov/covid-data-tracker/#county-view.

  3. United States COVID-19 Community Levels by County

    • data.cdc.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Nov 2, 2023
    + more versions
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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
    Explore at:
    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,

  4. d

    COVID-19 Medical Surge Facilities

    • catalog.data.gov
    • data.ca.gov
    • +1more
    Updated Nov 27, 2024
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    California Office of Emergency Services (2024). COVID-19 Medical Surge Facilities [Dataset]. https://catalog.data.gov/dataset/covid-19-medical-surge-facilities
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    Dataset updated
    Nov 27, 2024
    Dataset provided by
    California Office of Emergency Services
    Description

    COVID-19 Medical Surge Facilities *THIS DATASET IS NO LONGER BEING UPDATED - The last update to the data occurred on August 5th, 2021.

  5. M

    Data from: COVID-19 Surge

    • catalog.midasnetwork.us
    xls
    Updated Jul 1, 2024
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    MIDAS Coordination Center (2024). COVID-19 Surge [Dataset]. https://catalog.midasnetwork.us/collection/293
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    xlsAvailable download formats
    Dataset updated
    Jul 1, 2024
    Dataset authored and provided by
    MIDAS Coordination Center
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Variables measured
    disease, COVID-19, modeling, pathogen, forecasting, Homo sapiens, host organism, modeling method, modeling purpose, infectious disease, and 3 more
    Dataset funded by
    National Institute of General Medical Sciences
    Description

    COVID-19Surge is a spreadsheet-based tool that hospital administrators and public health officials can use to estimate the surge in demand for hospital-based services during the COVID-19 pandemic. One can produce estimates of the number of COVID-19 patients that need to be hospitalized, the number requiring ICU care, and the number requiring ventilator support and then compare those estimates with hospital capacity, using either existing capacity or estimates of expanded capacity. COVID-19Surge uses the Windows* operating system (Microsoft Windows 2010 or higher) and Excel (Microsoft Office 2013 or higher).

  6. m

    COVID-19 reporting

    • mass.gov
    Updated Dec 4, 2023
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    Executive Office of Health and Human Services (2023). COVID-19 reporting [Dataset]. https://www.mass.gov/info-details/covid-19-reporting
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    Dataset updated
    Dec 4, 2023
    Dataset provided by
    Department of Public Health
    Executive Office of Health and Human Services
    Area covered
    Massachusetts
    Description

    The COVID-19 dashboard includes data on city/town COVID-19 activity, confirmed and probable cases of COVID-19, confirmed and probable deaths related to COVID-19, and the demographic characteristics of cases and deaths.

  7. I

    Data from: Seasonal COVID-19 surge related hospital volumes and case...

    • data.niaid.nih.gov
    url
    Updated Dec 15, 2023
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    Susan Cheng (2023). Seasonal COVID-19 surge related hospital volumes and case fatality rates [Dataset]. http://doi.org/10.21430/M3JSHP7C23
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    urlAvailable download formats
    Dataset updated
    Dec 15, 2023
    Dataset provided by
    Cedars-sinai Medical Center
    Authors
    Susan Cheng
    License

    https://www.immport.org/agreementhttps://www.immport.org/agreement

    Description

    Background: Seasonal and regional surges in COVID-19 have imposed substantial strain on healthcare systems. Whereas sharp inclines in hospital volume were accompanied by overt increases in case fatality rates during the very early phases of the pandemic, the relative impact during later phases of the pandemic are less clear. We sought to characterize how the 2020 winter surge in COVID-19 volumes impacted case fatality in an adequately-resourced health system. Methods: We performed a retrospective cohort study of all adult diagnosed with COVID-19 in a large academic healthcare system between August 25, 2020 to May 8, 2021, using multivariable logistic regression to examine case fatality rates across 3 sequential time periods around the 2020 winter surge: pre-surge, surge, and post-surge. Subgroup analyses of patients admitted to the hospital and those receiving ICU-level care were also performed. Additionally, we used multivariable logistic regression to examine risk factors for mortality during the surge period. Results: We studied 7388 patients (aged 52.8 ± 19.6 years, 48% male) who received outpatient or inpatient care for COVID-19 during the study period. Patients treated during surge (N = 6372) compared to the pre-surge (N = 536) period had 2.64 greater odds (95% CI 1.46-5.27) of mortality after adjusting for sociodemographic and clinical factors. Adjusted mortality risk returned to pre-surge levels during the post-surge period. Notably, first-encounter patient-level measures of illness severity appeared higher during surge compared to non-surge periods. Conclusions: We observed excess mortality risk during a recent winter COVID-19 surge that was not explained by conventional risk factors or easily measurable variables, although recovered rapidly in the setting of targeted facility resources. These findings point to how complex interrelations of population- and patient-level pandemic factors can profoundly augment health system strain and drive dynamic, if short-lived, changes in outcomes.

  8. CDC COVID-19 Community Levels by County

    • opendata.ramseycounty.us
    application/rdfxml +5
    Updated Jul 23, 2025
    + more versions
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    Center for Disease Control and Prevention (2025). CDC COVID-19 Community Levels by County [Dataset]. https://opendata.ramseycounty.us/Public-Health/CDC-COVID-19-Community-Levels-by-County/uazb-iwdp
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    application/rdfxml, json, xml, csv, tsv, application/rssxmlAvailable download formats
    Dataset updated
    Jul 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    Center for Disease Control and Prevention
    License

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

    Description

    This public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties. This dataset contains the same values used to display information available on the COVID Data Tracker at: https://covid.cdc.gov/covid-data-tracker/#county-view?list_select_state=all_states&list_select_county=all_counties&data-type=CommunityLevels The data are updated weekly.

    CDC looks at the 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 — to determine the COVID-19 community level. The COVID-19 community level is 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 is classified as low, medium, or high. COVID-19 Community Levels can 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.

    See https://www.cdc.gov/coronavirus/2019-ncov/science/community-levels.html for more information.

    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.

    For more details on the Minnesota Department of Health COVID-19 thresholds, see COVID-19 Public Health Risk Measures: Data Notes (Updated 4/13/22). https://mn.gov/covid19/assets/phri_tcm1148-434773.pdf

    Note: 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.

  9. e

    COVID-19: Army Corps Uses Maps and Models to Create Surge Hospital Capacity

    • coronavirus-resources.esri.com
    • coronavirus-disasterresponse.hub.arcgis.com
    Updated Dec 22, 2020
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    Esri’s Disaster Response Program (2020). COVID-19: Army Corps Uses Maps and Models to Create Surge Hospital Capacity [Dataset]. https://coronavirus-resources.esri.com/documents/8703e0d2dd354491ae891f328027f14e
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    Dataset updated
    Dec 22, 2020
    Dataset authored and provided by
    Esri’s Disaster Response Program
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    COVID-19: Army Corps Uses Maps and Models to Create Surge Hospital CapacityAfter recognizing the possibility that the COVID-19 pandemic could cause hospital bed capacity to be exceeded, the US Army Corps of Engineers (USACE) was tasked with working with the states to build and inspect alternate care facilities.A team from USACE developed engineering plans for converting existing facilities with rooms (such as hotels or college dormitories) and those with large open areas (like field houses or convention centers). From there, the team developed standardized designs, then used mobile applications to quickly assess candidate sites and inspect the retrofitted facilities for readiness._Communities around the world are taking strides in mitigating the threat that COVID-19 (coronavirus) poses. Geography and location analysis have a crucial role in better understanding this evolving pandemic.When you need help quickly, Esri can provide data, software, configurable applications, and technical support for your emergency GIS operations. Use GIS to rapidly access and visualize mission-critical information. Get the information you need quickly, in a way that’s easy to understand, to make better decisions during a crisis.Esri’s Disaster Response Program (DRP) assists with disasters worldwide as part of our corporate citizenship. We support response and relief efforts with GIS technology and expertise.More information...

  10. d

    ARCHIVED: COVID-19 Hospital Capacity

    • catalog.data.gov
    • data.sfgov.org
    • +1more
    Updated Mar 29, 2025
    + more versions
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    data.sfgov.org (2025). ARCHIVED: COVID-19 Hospital Capacity [Dataset]. https://catalog.data.gov/dataset/covid-19-hospital-capacity
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    Dataset updated
    Mar 29, 2025
    Dataset provided by
    data.sfgov.org
    Description

    Note: As of July 21, 2021, this dataset no longer updates. A. SUMMARY Data on daily hospital bed use and available capacity at San Francisco acute care hospitals from April 2020 onward. Long Term Care facilities (like Laguna Honda and Kentfield) are not included in this data as acute care patients cannot be admitted to these facilities. B. HOW THE DATASET IS CREATED This hospital capacity information is based on data that all SF acute care hospitals report to the San Francisco Department of Public Health. C. UPDATE PROCESS Updates automatically at 05:00 Pacific Time each day. Redundant runs are scheduled at 07:00 and 09:00 in case of pipeline failure. This data is on a 4-day lag to account for the time needed to complete and validate data from all SF acute care hospitals. D. HOW TO USE THIS DATASET This data provides visibility into current occupancy levels and use of San Francisco acute care hospitals and potential ability to accommodate anticipated surges of COVID patients. Data includes current census of COVID-19 patients (including both confirmed cases and suspected COVID patients) and other patients in acute care hospitals, shown in the “Status” column. The “Status” column also includes all available beds. This daily census information is stratified by type of bed (acute care, intensive care, and surge) in the “Bed Type” column. Acute care beds treat patients with illnesses and injuries including recovery from surgeries. Intensive care (ICU) beds are for sicker patients in need of critical and life support services that can include the use of a ventilator. Surge beds are the additional beds that can be made available to handle an influx of COVID-19 patients; surge beds are differentiated between acute care surge beds and ICU surge beds. Note: The current census of COVID patients shown here may not always match the hospitalizations data (https://data.sfgov.org/COVID-19/COVID-19-Hospitalizations/nxjg-bhem), as that data includes all hospitals and long term care facilities. As described above, those long term care facilities are not included here as they don’t have the capacity to take in additional acute care patients and therefore aren’t included in capacity measures.

  11. COVID-19 Patient Data

    • s.cnmilf.com
    • catalog.data.gov
    Updated Nov 27, 2024
    + more versions
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    California Department of State Hospitals (2024). COVID-19 Patient Data [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/covid-19-patient-data-9604c
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    Dataset updated
    Nov 27, 2024
    Dataset provided by
    California Department of State Hospitals
    Description

    DSH COVID-19 Patient Testing: Last updated -11/07/2024 DSH COVID-19 Patient Data reports on patient positives and testing counts at the facility level for DSH. The table reports on the following data fields: Total patients that tested positive for COVID-19 since 5/16/2020 Patients newly positive for COVID-19 in the last 14 days Patient deaths while patient was positive for COVID-19 since 5/30/2020 Total number of tests administered since 3/23/2020 Table Notes: COVID-19 test results for patients include DSH patients who are tested while receiving treatment at an outside medical facility. Data has been de-identified in accordance with CalHHS Data De-identification Guidelines. Counts between 1-10 are masked with "<11". Includes Patients Under Investigation (PUIs) testing and proactive testing of asymptomatic patients for surveillance of geriatric, medically fragile, and skilled nursing facility units and for patients upon admission, re-admission, or discharge. Includes all individuals who were positive for COVID-19 at time of death, regardless of underlying health conditions or whether the cause of death has been confirmed to be COVID-19 related illness. Metro-Norwalk is additional COVID-19 surge space and technically a branch _location that is part of DSH Metropolitan Hospital.

  12. C

    COVID-19 Patient Data

    • data.ca.gov
    • data.chhs.ca.gov
    csv, zip
    Updated Feb 10, 2025
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    California Department of State Hospitals (2025). COVID-19 Patient Data [Dataset]. https://data.ca.gov/dataset/covid-19-patient-data
    Explore at:
    zip, csvAvailable download formats
    Dataset updated
    Feb 10, 2025
    Dataset provided by
    Department of State Hospitals
    Authors
    California Department of State Hospitals
    License

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

    Description

    DSH COVID-19 Patient Testing: Last updated -02/10/2025

    DSH COVID-19 Patient Data reports on patient positives and testing counts at the facility level for DSH. The table reports on the following data fields:

    • Total patients that tested positive for COVID-19 since 5/16/2020

    • Patients newly positive for COVID-19 in the last 14 days

    • Patient deaths while patient was positive for COVID-19 since 5/30/2020

    • Total number of tests administered since 3/23/2020

    Table Notes:

    COVID-19 test results for patients include DSH patients who are tested while receiving treatment at an outside medical facility. Data has been de-identified in accordance with CalHHS Data De-identification Guidelines. Counts between 1-10 are masked with "<11". Includes Patients Under Investigation (PUIs) testing and proactive testing of asymptomatic patients for surveillance of geriatric, medically fragile, and skilled nursing facility units and for patients upon admission, re-admission, or discharge. Includes all individuals who were positive for COVID-19 at time of death, regardless of underlying health conditions or whether the cause of death has been confirmed to be COVID-19 related illness. Metro-Norwalk is additional COVID-19 surge space and technically a branch location that is part of DSH Metropolitan Hospital.

  13. A

    ‘COVID-19 Medical Surge Facilities’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jul 29, 2020
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘COVID-19 Medical Surge Facilities’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-covid-19-medical-surge-facilities-2b7f/e86ab7ef/?iid=004-252&v=presentation
    Explore at:
    Dataset updated
    Jul 29, 2020
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘COVID-19 Medical Surge Facilities’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/262b566f-6d82-447a-8ac0-294534de98a3 on 27 January 2022.

    --- Dataset description provided by original source is as follows ---

    COVID-19 Medical Surge Facilities

    *THIS DATASET IS NO LONGER BEING UPDATED - The last update to the data occurred on August 5th, 2021.

    --- Original source retains full ownership of the source dataset ---

  14. f

    Proportion of variance explained from PCA analysis.

    • figshare.com
    xls
    Updated Jun 10, 2023
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    Jane K. L. Teh; David A. Bradley; Jack Bee Chook; Kee Huong Lai; Woo Teck Ang; Kok Lay Teo; Suat-Cheng Peh (2023). Proportion of variance explained from PCA analysis. [Dataset]. http://doi.org/10.1371/journal.pone.0252273.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Jane K. L. Teh; David A. Bradley; Jack Bee Chook; Kee Huong Lai; Woo Teck Ang; Kok Lay Teo; Suat-Cheng Peh
    License

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

    Description

    Proportion of variance explained from PCA analysis.

  15. n

    Coronavirus (Covid-19) Data in the United States

    • nytimes.com
    • openicpsr.org
    • +2more
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    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html
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    Dataset provided by
    New York Times
    Description

    The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

    Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

    We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

    The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

  16. Coronavirus (COVID-19) new cases in Italy as of January 2025, by date of...

    • statista.com
    Updated Jan 30, 2025
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    Statista (2025). Coronavirus (COVID-19) new cases in Italy as of January 2025, by date of report [Dataset]. https://www.statista.com/statistics/1101690/coronavirus-new-cases-development-italy/
    Explore at:
    Dataset updated
    Jan 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 22, 2020 - Jan 8, 2025
    Area covered
    Italy
    Description

    The first two cases of the new coronavirus (COVID-19) in Italy were recorded between the end of January and the beginning of February 2020. Since then, the number of cases in Italy increased steadily, reaching over 26.9 million as of January 8, 2025. The region mostly hit by the virus in the country was Lombardy, counting almost 4.4 million cases. On January 11, 2022, 220,532 new cases were registered, which represented the biggest daily increase in cases in Italy since the start of the pandemic. The virus originated in Wuhan, a Chinese city populated by millions and located in the province of Hubei. More statistics and facts about the virus in Italy are available here.For a global overview, visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

  17. COVID-19 mobile gaming surge predictions from U.S. and GB gamers 2021

    • statista.com
    Updated Jun 14, 2022
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    Statista (2022). COVID-19 mobile gaming surge predictions from U.S. and GB gamers 2021 [Dataset]. https://www.statista.com/statistics/1237584/mobile-gaming-predictions-us-gb-gamers/
    Explore at:
    Dataset updated
    Jun 14, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2021
    Area covered
    United Kingdom, United States
    Description

    As of April 2021, 77 percent of mobile gamers from the United States who spent more time on mobile games since the COVID-19 outbreak reported that they were very or somewhat likely going to continue playing mobile games at the same rate once the COVID-19 pandemic has ended. In comparison, 68 percent of mobile gamers from Great Britain reported the same thing.

  18. f

    Principal component loading vectors from PCA analysis.

    • plos.figshare.com
    xls
    Updated Jun 10, 2023
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    Jane K. L. Teh; David A. Bradley; Jack Bee Chook; Kee Huong Lai; Woo Teck Ang; Kok Lay Teo; Suat-Cheng Peh (2023). Principal component loading vectors from PCA analysis. [Dataset]. http://doi.org/10.1371/journal.pone.0252273.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Jane K. L. Teh; David A. Bradley; Jack Bee Chook; Kee Huong Lai; Woo Teck Ang; Kok Lay Teo; Suat-Cheng Peh
    License

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

    Description

    Principal component loading vectors from PCA analysis.

  19. r

    Montana COVID-19 Community Levels

    • opendata.rcmrd.org
    Updated May 13, 2022
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    Montana Geographic Information (2022). Montana COVID-19 Community Levels [Dataset]. https://opendata.rcmrd.org/maps/80005eedcc034f39a4ea59031e7e31b6_0/about
    Explore at:
    Dataset updated
    May 13, 2022
    Dataset authored and provided by
    Montana Geographic Information
    Area covered
    Description

    The Montana COVID-19 Community Levels Table web service hosts a data table showing Montana COVID-19 CDC Community Levels data. This public use dataset has 11 data elements reflecting Montana COVID-19 community levels for all available counties. CDC looks at the 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 — to determine the COVID-19 community level. The COVID-19 community level is 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. COVID-19 Community Levels can 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. This feature service is no longer maintained and the final update to this data was made on 05/05/2023.

  20. COVID-19 Staff Data

    • healthdata.gov
    • data.ca.gov
    • +2more
    application/rdfxml +5
    Updated Apr 8, 2025
    + more versions
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    chhs.data.ca.gov (2025). COVID-19 Staff Data [Dataset]. https://healthdata.gov/State/COVID-19-Staff-Data/rjih-wnzn
    Explore at:
    json, csv, application/rssxml, application/rdfxml, tsv, xmlAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    chhs.data.ca.gov
    Description

    DSH COVID-19 Staff Testing: Last updated - 02/10/2025

    DSH COVID-19 Staff Data reports on DSH staff and non-DSH personnel positives at the facility level for DSH. The table reports on the following data fields:

    • Total staff positive for COVID-19 confirmed by Public Health or medical facility since 3/20/2020

    • Staff newly positive for COVID-19 in the last 14 days

    • Non-DSH personnel positive for COVID-19 confirmed by Public Health or medical facility since 5/26/2020

    • Non-DSH personnel newly positive for COVID-19 in the last 14 days

    Table Notes:

    Data has been de-identified in accordance with CalHHS Data De-Identification Guidelines. Counts between 1-10 are masked with "<11". Other includes non-DSH personnel who perform work at DSH facilities and personnel working at sites located on DSH facilities that are operated by other organizations. Metro-Norwalk is additional COVID-19 surge space and technically a branch location that is part of DSH Metropolitan Hospital.

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Public Health England (2021). COVID-19 surge testing outcomes reports: management information [Dataset]. https://www.gov.uk/government/statistical-data-sets/covid-19-surge-testing-outcomes-reports-management-information
Organization logo

COVID-19 surge testing outcomes reports: management information

Explore at:
Dataset updated
Jul 1, 2021
Dataset provided by
GOV.UKhttp://gov.uk/
Authors
Public Health England
Description

https://assets.publishing.service.gov.uk/media/60dc5850e90e077173ce61c3/Surge_testing_summary_2021-06-29.ods">Surge testing summary 1 July 2021

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