19 datasets found
  1. t

    NC COVID-19 Cases & Deaths

    • data.townofcary.org
    • s.cnmilf.com
    • +1more
    csv, excel, json
    Updated Sep 14, 2021
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    (2021). NC COVID-19 Cases & Deaths [Dataset]. https://data.townofcary.org/explore/dataset/nc-covid-19-cases-deaths/
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    excel, csv, jsonAvailable download formats
    Dataset updated
    Sep 14, 2021
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    North Carolina
    Description

    This dataset contains counts of COVID-19 cases and deaths in North Carolina from March 2, 2020 to May 31, 2021. The data was extracted from NC Department of Health and Human Services' NC COVID-19 dashboard: Daily Cases and Deaths Metrics. This dataset is an archive - it is not being updated.

    Data Source: NCDHHS (2021). Daily Cases and Deaths Metrics (Version 1.3) [Data set]. https://covid19.ncdhhs.gov/dashboard/data-behind-dashboards

  2. a

    NC COVID-19 Cases by County

    • coronavirus-onslow.hub.arcgis.com
    Updated Feb 22, 2021
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    Onslow County GIS (2021). NC COVID-19 Cases by County [Dataset]. https://coronavirus-onslow.hub.arcgis.com/maps/nc-covid-19-cases-by-county
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    Dataset updated
    Feb 22, 2021
    Dataset authored and provided by
    Onslow County GIS
    Area covered
    Description

    Data from the state on statistics & counts of COVID-19 data by zipcode. This data is updated and maintained by the North Carolina GIS Department. It is typically updated manually once a day. Any questions please call the Onslow County GIS Department at 1-910-937-1190, Monday - Friday 8am - 5pm.

  3. Weekly United States COVID-19 Cases and Deaths by State - ARCHIVED

    • data.cdc.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Jun 1, 2023
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    CDC COVID-19 Response (2023). Weekly United States COVID-19 Cases and Deaths by State - ARCHIVED [Dataset]. https://data.cdc.gov/Case-Surveillance/Weekly-United-States-COVID-19-Cases-and-Deaths-by-/pwn4-m3yp
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    csv, application/rdfxml, xml, tsv, json, application/rssxmlAvailable download formats
    Dataset updated
    Jun 1, 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 new Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. This dataset will receive a final update on June 1, 2023, to reconcile historical data through May 10, 2023, and will remain publicly available.

    Aggregate Data Collection Process Since the start of the COVID-19 pandemic, data have been gathered through a robust process with the following steps:

    • A CDC data team reviews and validates the information obtained from jurisdictions’ state and local websites via an overnight data review process.
    • If more than one official county data source exists, CDC uses a comprehensive data selection process comparing each official county data source, and takes the highest case and death counts respectively, unless otherwise specified by the state.
    • CDC compiles these data and posts the finalized information on COVID Data Tracker.
    • County level data is aggregated to obtain state and territory specific totals.
    This process is collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provide the most up-to-date numbers on cases and deaths by report date. CDC may retrospectively update counts to correct data quality issues.

    Methodology Changes Several differences exist between the current, weekly-updated dataset and the archived version:

    • Source: The current Weekly-Updated Version is based on county-level aggregate count data, while the Archived Version is based on State-level aggregate count data.
    • Confirmed/Probable Cases/Death breakdown:  While the probable cases and deaths are included in the total case and total death counts in both versions (if applicable), they were reported separately from the confirmed cases and deaths by jurisdiction in the Archived Version.  In the current Weekly-Updated Version, the counts by jurisdiction are not reported by confirmed or probable status (See Confirmed and Probable Counts section for more detail).
    • Time Series Frequency: The current Weekly-Updated Version contains weekly time series data (i.e., one record per week per jurisdiction), while the Archived Version contains daily time series data (i.e., one record per day per jurisdiction).
    • Update Frequency: The current Weekly-Updated Version is updated weekly, while the Archived Version was updated twice daily up to October 20, 2022.
    Important note: The counts reflected during a given time period in this dataset may not match the counts reflected for the same time period in the archived dataset noted above. Discrepancies may exist due to differences between county and state COVID-19 case surveillance and reconciliation efforts.

    Confirmed and Probable Counts In this dataset, counts by jurisdiction are not displayed by confirmed or probable status. Instead, confirmed and probable cases and deaths are included in the Total Cases and Total Deaths columns, when available. Not all jurisdictions report probable cases and deaths to CDC.* Confirmed and probable case definition criteria are described here:

    Council of State and Territorial Epidemiologists (ymaws.com).

    Deaths CDC reports death data on other sections of the website: CDC COVID Data Tracker: Home, CDC COVID Data Tracker: Cases, Deaths, and Testing, and NCHS Provisional Death Counts. Information presented on the COVID Data Tracker pages is based on the same source (total case counts) as the present dataset; however, NCHS Death Counts are based on death certificates that use information reported by physicians, medical examiners, or coroners in the cause-of-death section of each certificate. Data from each of these pages are considered provisional (not complete and pending verification) and are therefore subject to change. Counts from previous weeks are continually revised as more records are received and processed.

    Number of Jurisdictions Reporting There are currently 60 public health jurisdictions reporting cases of COVID-19. This includes the 50 states, the District of Columbia, New York City, the U.S. territories of American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, Puerto Rico, and the U.S Virgin Islands as well as three independent countries in compacts of free association with the United States, Federated States of Micronesia, Republic of the Marshall Islands, and Republic of Palau. New York State’s reported case and death counts do not include New York City’s counts as they separately report nationally notifiable conditions to CDC.

    CDC COVID-19 data are available to the public as summary or aggregate count files, including total counts of cases and deaths, available by state and by county. These and other data on COVID-19 are available from multiple public locations, such as:

    https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html

    https://www.cdc.gov/covid-data-tracker/index.html

    https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html

    https://www.cdc.gov/coronavirus/2019-ncov/php/open-america/surveillance-data-analytics.html

    Additional COVID-19 public use datasets, include line-level (patient-level) data, are available at: https://data.cdc.gov/browse?tags=covid-19.

    Archived Data Notes:

    November 3, 2022: Due to a reporting cadence issue, case rates for Missouri counties are calculated based on 11 days’ worth of case count data in the Weekly United States COVID-19 Cases and Deaths by State data released on November 3, 2022, instead of the customary 7 days’ worth of data.

    November 10, 2022: Due to a reporting cadence change, case rates for Alabama counties are calculated based on 13 days’ worth of case count data in the Weekly United States COVID-19 Cases and Deaths by State data released on November 10, 2022, instead of the customary 7 days’ worth of data.

    November 10, 2022: Per the request of the jurisdiction, cases and deaths among non-residents have been removed from all Hawaii county totals throughout the entire time series. Cumulative case and death counts reported by CDC will no longer match Hawaii’s COVID-19 Dashboard, which still includes non-resident cases and deaths. 

    November 17, 2022: Two new columns, weekly historic cases and weekly historic deaths, were added to this dataset on November 17, 2022. These columns reflect case and death counts that were reported that week but were historical in nature and not reflective of the current burden within the jurisdiction. These historical cases and deaths are not included in the new weekly case and new weekly death columns; however, they are reflected in the cumulative totals provided for each jurisdiction. These data are used to account for artificial increases in case and death totals due to batched reporting of historical data.

    December 1, 2022: Due to cadence changes over the Thanksgiving holiday, case rates for all Ohio counties are reported as 0 in the data released on December 1, 2022.

    January 5, 2023: Due to North Carolina’s holiday reporting cadence, aggregate case and death data will contain 14 days’ worth of data instead of the customary 7 days. As a result, case and death metrics will appear higher than expected in the January 5, 2023, weekly release.

    January 12, 2023: Due to data processing delays, Mississippi’s aggregate case and death data will be reported as 0. As a result, case and death metrics will appear lower than expected in the January 12, 2023, weekly release.

    January 19, 2023: Due to a reporting cadence issue, Mississippi’s aggregate case and death data will be calculated based on 14 days’ worth of data instead of the customary 7 days in the January 19, 2023, weekly release.

    January 26, 2023: Due to a reporting backlog of historic COVID-19 cases, case rates for two Michigan counties (Livingston and Washtenaw) were higher than expected in the January 19, 2023 weekly release.

    January 26, 2023: Due to a backlog of historic COVID-19 cases being reported this week, aggregate case and death counts in Charlotte County and Sarasota County, Florida, will appear higher than expected in the January 26, 2023 weekly release.

    January 26, 2023: Due to data processing delays, Mississippi’s aggregate case and death data will be reported as 0 in the weekly release posted on January 26, 2023.

    February 2, 2023: As of the data collection deadline, CDC observed an abnormally large increase in aggregate COVID-19 cases and deaths reported for Washington State. In response, totals for new cases and new deaths released on February 2, 2023, have been displayed as zero at the state level until the issue is addressed with state officials. CDC is working with state officials to address the issue.

    February 2, 2023: Due to a decrease reported in cumulative case counts by Wyoming, case rates will be reported as 0 in the February 2, 2023, weekly release. CDC is working with state officials to verify the data submitted.

    February 16, 2023: Due to data processing delays, Utah’s aggregate case and death data will be reported as 0 in the weekly release posted on February 16, 2023. As a result, case and death metrics will appear lower than expected and should be interpreted with caution.

    February 16, 2023: Due to a reporting cadence change, Maine’s

  4. f

    COVID-19 testing and cases in North Carolina June 1, 2020—August 31, 2020.

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Katherine LeMasters; Shabbar Ranapurwala; Morgan Maner; Kathryn M. Nowotny; Meghan Peterson; Lauren Brinkley-Rubinstein (2023). COVID-19 testing and cases in North Carolina June 1, 2020—August 31, 2020. [Dataset]. http://doi.org/10.1371/journal.pone.0266772.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Katherine LeMasters; Shabbar Ranapurwala; Morgan Maner; Kathryn M. Nowotny; Meghan Peterson; Lauren Brinkley-Rubinstein
    License

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

    Area covered
    North Carolina
    Description

    COVID-19 testing and cases in North Carolina June 1, 2020—August 31, 2020.

  5. United States COVID-19 Community Levels by County

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

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

    Area covered
    United States
    Description

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

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

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

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

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

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

    Archived Data Notes:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

  6. U

    United States COVID-19: No. of Deaths: To Date: North Carolina

    • ceicdata.com
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    CEICdata.com, United States COVID-19: No. of Deaths: To Date: North Carolina [Dataset]. https://www.ceicdata.com/en/united-states/center-for-disease-control-and-prevention-coronavirus-disease-2019-covid2019
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    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Apr 29, 2023 - May 10, 2023
    Area covered
    United States
    Description

    COVID-19: No. of Deaths: To Date: North Carolina data was reported at 29,059.000 Person in 10 May 2023. This records an increase from the previous number of 28,986.000 Person for 09 May 2023. COVID-19: No. of Deaths: To Date: North Carolina data is updated daily, averaging 16,191.000 Person from Jan 2020 (Median) to 10 May 2023, with 1205 observations. The data reached an all-time high of 29,059.000 Person in 10 May 2023 and a record low of 0.000 Person in 12 Mar 2020. COVID-19: No. of Deaths: To Date: North Carolina data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under High Frequency Database’s Disease Outbreaks – Table US.D001: Center for Disease Control and Prevention: Coronavirus Disease 2019 (COVID-2019). Data beginning Oct 19 is published weekly instead of daily. Data prior Oct 19 is based on state-level aggregate count data, while data starting Oct 19 is based on county-level aggregate count data. Discrepancies may exist due to differences between country and state COVID-19 case surveillance and reconcilaition efforts, which is why there is a decline in the data for some states.

  7. Weekly COVID-19 County Level of Community Transmission Historical Changes -...

    • data.cdc.gov
    • healthdata.gov
    • +1more
    application/rdfxml +5
    Updated May 8, 2024
    + more versions
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    CDC COVID-19 Response (2024). Weekly COVID-19 County Level of Community Transmission Historical Changes - ARCHIVED [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/Weekly-COVID-19-County-Level-of-Community-Transmis/jgk8-6dpn
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    csv, tsv, json, application/rssxml, xml, application/rdfxmlAvailable download formats
    Dataset updated
    May 8, 2024
    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

    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. This dataset will receive a final update on June 1, 2023, to reconcile historical data through May 10, 2023, and will remain publicly available.

    This archived public use dataset contains historical case and percent positivity data updated weekly for all available counties and jurisdictions. Each week, the dataset was refreshed to capture any historical updates. Please note, percent positivity data may be incomplete for the most recent time period.

    Related data CDC provides the public with two active versions of COVID-19 county-level community transmission level data: this dataset with historical case and percent positivity data for each county from January 22, 2020 (Weekly Historical Changes dataset) and a dataset with the levels as originally posted (Weekly Originally Posted dataset) since October 20, 2022. Please navigate to the Weekly Originally Posted dataset for the Community Transmission Levels published weekly on Thursdays.

    Methods for calculating county level of community transmission indicator The County Level of Community Transmission indicator uses two metrics: (1) total new COVID-19 cases per 100,000 persons in the last 7 days and (2) percentage of positive SARS-CoV-2 diagnostic nucleic acid amplification tests (NAAT) in the last 7 days. For each of these metrics, CDC classifies transmission values as low, moderate, substantial, or high (below and here). If the values for each of these two metrics differ (e.g., one indicates moderate and the other low), then the higher of the two should be used for decision-making.

    CDC core metrics of and thresholds for community transmission levels of SARS-CoV-2 Total New Case Rate Metric: "New cases per 100,000 persons in the past 7 days" is calculated by adding the number of new cases in the county (or other administrative level) in the last 7 days divided by the population in the county (or other administrative level) and multiplying by 100,000. "New cases per 100,000 persons in the past 7 days" is considered to have transmission level of Low (0-9.99); Moderate (10.00-49.99); Substantial (50.00-99.99); and High (greater than or equal to 100.00).

    Test Percent Positivity Metric: "Percentage of positive NAAT in the past 7 days" is calculated by dividing the number of positive tests in the county (or other administrative level) during the last 7 days by the total number of tests resulted over the last 7 days. "Percentage of positive NAAT in the past 7 days" is considered to have transmission level of Low (less than 5.00); Moderate (5.00-7.99); Substantial (8.00-9.99); and High (greater than or equal to 10.00).

    The data in this dataset are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers.

    This dataset is created using CDC’s Policy on Public Health Research and Nonresearch Data Management and Access.

    Archived data CDC has archived two prior versions of these datasets. Both versions contain the same 7 data elements reflecting community transmission levels for all available counties and jurisdictions; however, the datasets updated daily. The archived datasets can be found here:

    Archived Originally Posted dataset

    Archived Historical Changes dataset

    Archived Data Notes:

    October 27, 2022: Due to a processing issue this dataset will not be posted this week. CDC is currently working to address the issue and will publish the data when able.

    November 10, 2022: As of 11/10/2022, this dataset will continue to incorporate historical updates made to case and percent positivity data; however, community transmission level will only be published in the corresponding Weekly COVID-19 County Level of Community Transmission as Originally Posted dataset (Weekly Originally Posted dataset).

    Note:

    October 20, 2022: Due to a data reporting error, the case rate for Philadelphia County, Pennsylvania is lower than expected in the COVID-19 Community Transmission Level data released on October 20, 2022. This could lead to the COVID-19 Community Transmission Level for Philadelphia County being underestimated; therefore, it should be interpreted with caution.

    November 3, 2022: Due to a reporting cadence issue, case rates for Missouri counties are calculated based on 11 days’ worth of case count data in the COVID-19 Community Transmission Level data released on November 3, 2022, instead of the customary 7 days’ worth of data. This could lead to the COVID-19 Community Transmission Levels metrics for Missouri counties being overestimated; therefore, they should be interpreted with caution.

    November 10, 2022: Due to a reporting cadence change, case rates for Alabama counties are calculated based on 13 days’ worth of case count data in the COVID-19 Community Transmission Level data released on November 10, 2022, instead of the customary 7 days’ worth of data. This could lead to the COVID-19 Community Transmission Levels metrics for Alabama counties being overestimated; therefore, they should be interpreted with caution.

    November 10, 2022: Per the request of the jurisdiction, cases among non-residents have been removed from all Hawaii county totals throughout the entire time series. Cumulative case counts reported by CDC will no longer match Hawaii’s COVID-19 Dashboard, which still includes non-resident cases. 

    November 10, 2022: In the COVID-19 Community Transmission Level data released on November 10, 2022, multiple municipalities in Puerto Rico are reporting higher than expected increases in case counts. CDC is working with territory officials to verify the data submitted. 

    December 1, 2022: Due to cadence changes over the Thanksgiving holiday, case rates for all Ohio counties are reported as 0 in the COVID-19 Community Transmission Level data released on December 1, 2022. Therefore, the COVID-19 Community Transmission Levels may be underestimated and should be interpreted with caution. 

    December 22, 2022: Due to an internal revision process, case rates for some Tennessee counties may appear higher than expected in the December 22, 2022, weekly release. Therefore, the COVID-19 Community Transmission Levels metrics for some Tennessee counties may be overestimated and should be interpreted with caution.

    December 22, 2022: Due to reporting of a backlog of historic COVID-19 cases, case rates for some Louisiana counties will appear higher than expected in the December 22, 2022, weekly release. Therefore, the COVID-19 Community Transmission Levels metrics for some Louisiana counties may be overestimated and should be interpreted with caution.

    December 29, 2022: Due to technical difficulties, county data from Alabama could not be incorporated via standard practices. As a result, case and death metrics will be reported as 0 in the December 29, 2022, weekly release. Therefore, the COVID-19 Community Transmission Levels metrics for Alabama counties will be underestimated and should be interpreted with caution.

    January 5, 2023: Due to a reporting cadence issue, case rates for all Alabama counties will be calculated based on 14 days’ worth of case count data in the COVID-19 Community Transmission Level information released on January 5, 2023, instead of the customary 7 days’ worth of case count data. Therefore, the weekly case rates will be overestimated, which could affect counties’ COVID-19 Community Transmission Level classification and should be interpreted with caution.

    January 5, 2023: Due to North Carolina’s holiday reporting cadence, aggregate case data will contain 14 days’ worth of data instead of the customary 7 days. As a result, case metrics will appear higher than expected in the January 5, 2023, weekly release. COVID-19 Community Transmission metrics may be overestimated and should be interpreted with caution.

    January 12, 2023: Due to data processing delays, Mississippi’s aggregate case data will be reported as 0. As a result, case metrics will appear lower than expected in the January 12, 2023, weekly release. COVID-19 Community Transmission metrics may be underestimated and should be interpreted with caution. 

    January 13, 2023: Aggregate case data released for Los Angeles County, California for the week of December 22nd, 2022, and December 29th, 2022, have been corrected for a data processing error.

    January 19, 2023: Due to a reporting cadence issue, Mississippi’s aggregate case data will be calculated based on 14 days’ worth of data instead of the customary 7 days in the January 19, 2023, weekly release. Therefore, COVID-19 Community Transmission metrics may be overestimated and should be interpreted with caution.

    January 26, 2023: Due to a reporting backlog of historic COVID-19 cases, case rates for two Michigan counties

  8. I

    Data from: Household Transmission of Severe Acute Respiratory Syndrome...

    • data.niaid.nih.gov
    url
    Updated Jan 30, 2025
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    (2025). Household Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 in the United States: Living Density, Viral Load, and Disproportionate Impact on Communities of Color [Dataset]. http://doi.org/10.21430/M31ZDULPAH
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    urlAvailable download formats
    Dataset updated
    Jan 30, 2025
    License

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

    Area covered
    United States
    Description

    Background: Households are hot spots for severe acute respiratory syndrome coronavirus 2 transmission. Methods: This prospective study enrolled 100 coronavirus disease 2019 (COVID-19) cases and 208 of their household members in North Carolina though October 2020, including 44% who identified as Hispanic or non-White. Households were enrolled a median of 6 days from symptom onset in the index case. Incident secondary cases within the household were detected using quantitative polymerase chain reaction of weekly nasal swabs (days 7, 14, 21) or by seroconversion at day 28. Results: Excluding 73 household contacts who were PCR-positive at baseline, the secondary attack rate (SAR) among household contacts was 32% (33 of 103; 95% confidence interval [CI], 22%-44%). The majority of cases occurred by day 7, with later cases confirmed as household-acquired by viral sequencing. Infected persons in the same household had similar nasopharyngeal viral loads (intraclass correlation coefficient = 0.45; 95% CI, .23-.62). Households with secondary transmission had index cases with a median viral load that was 1.4 log10 higher than those without transmission (P = .03), as well as higher living density (more than 3 persons occupying fewer than 6 rooms; odds ratio, 3.3; 95% CI, 1.02-10.9). Minority households were more likely to experience high living density and had a higher risk of incident infection than did White households (SAR, 51% vs 19%; P = .01). Conclusions: Household crowding in the context of high-inoculum infections may amplify the spread of COVID-19, potentially contributing to disproportionate impact on communities of color.

  9. Total number of U.S. COVID-19 cases as of March 10, 2023, by state

    • statista.com
    Updated May 15, 2024
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    Statista (2024). Total number of U.S. COVID-19 cases as of March 10, 2023, by state [Dataset]. https://www.statista.com/statistics/1102807/coronavirus-covid19-cases-number-us-americans-by-state/
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    Dataset updated
    May 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of March 10, 2023, the state with the highest number of COVID-19 cases was California. Almost 104 million cases have been reported across the United States, with the states of California, Texas, and Florida reporting the highest numbers.

    From an epidemic to a pandemic The World Health Organization declared the COVID-19 outbreak a pandemic on March 11, 2020. The term pandemic refers to multiple outbreaks of an infectious illness threatening multiple parts of the world at the same time. When the transmission is this widespread, it can no longer be traced back to the country where it originated. The number of COVID-19 cases worldwide has now reached over 669 million.

    The symptoms and those who are most at risk Most people who contract the virus will suffer only mild symptoms, such as a cough, a cold, or a high temperature. However, in more severe cases, the infection can cause breathing difficulties and even pneumonia. Those at higher risk include older persons and people with pre-existing medical conditions, including diabetes, heart disease, and lung disease. People aged 85 years and older have accounted for around 27 percent of all COVID-19 deaths in the United States, although this age group makes up just two percent of the U.S. population

  10. Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status

    • healthdata.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Jun 16, 2023
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    data.cdc.gov (2023). Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status [Dataset]. https://healthdata.gov/CDC/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/894y-jyp5
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    csv, xml, application/rssxml, application/rdfxml, json, tsvAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset provided by
    data.cdc.gov
    Description

    Data for CDC’s COVID Data Tracker site on Rates of COVID-19 Cases and Deaths by Vaccination Status. Click 'More' for important dataset description and footnotes

    Dataset and data visualization details: These data were posted on October 21, 2022, archived on November 18, 2022, and revised on February 22, 2023. These data reflect cases among persons with a positive specimen collection date through September 24, 2022, and deaths among persons with a positive specimen collection date through September 3, 2022.

    Vaccination status: A person vaccinated with a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. Additional or booster dose: A person vaccinated with a primary series and an additional or booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after receipt of an additional or booster dose of any COVID-19 vaccine on or after August 13, 2021. For people ages 18 years and older, data are graphed starting the week including September 24, 2021, when a COVID-19 booster dose was first recommended by CDC for adults 65+ years old and people in certain populations and high risk occupational and institutional settings. For people ages 12-17 years, data are graphed starting the week of December 26, 2021, 2 weeks after the first recommendation for a booster dose for adolescents ages 16-17 years. For people ages 5-11 years, data are included starting the week of June 5, 2022, 2 weeks after the first recommendation for a booster dose for children aged 5-11 years. For people ages 50 years and older, data on second booster doses are graphed starting the week including March 29, 2022, when the recommendation was made for second boosters. Vertical lines represent dates when changes occurred in U.S. policy for COVID-19 vaccination (details provided above). Reporting is by primary series vaccine type rather than additional or booster dose vaccine type. The booster dose vaccine type may be different than the primary series vaccine type. ** Because data on the immune status of cases and associated deaths are unavailable, an additional dose in an immunocompromised person cannot be distinguished from a booster dose. This is a relevant consideration because vaccines can be less effective in this group. Deaths: A COVID-19–associated death occurred in a person with a documented COVID-19 diagnosis who died; health department staff reviewed to make a determination using vital records, public health investigation, or other data sources. Rates of COVID-19 deaths by vaccination status are reported based on when the patient was tested for COVID-19, not the date they died. Deaths usually occur up to 30 days after COVID-19 diagnosis. Participating jurisdictions: Currently, these 31 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Arkansas, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (New York), North Carolina, Philadelphia (Pennsylvania), Rhode Island, South Dakota, Tennessee, Texas, Utah, Washington, and West Virginia; 30 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 72% of the total U.S. population and all ten of the Health and Human Services Regions. Data on cases

  11. Provisional COVID-19 death counts and rates by month, jurisdiction of...

    • catalog.data.gov
    • data.virginia.gov
    • +3more
    Updated Aug 1, 2025
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    Centers for Disease Control and Prevention (2025). Provisional COVID-19 death counts and rates by month, jurisdiction of residence, and demographic characteristics [Dataset]. https://catalog.data.gov/dataset/provisional-covid-19-death-counts-and-rates-by-month-jurisdiction-of-residence-and-demogra
    Explore at:
    Dataset updated
    Aug 1, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This file contains COVID-19 death counts and rates by month and year of death, jurisdiction of residence (U.S., HHS Region) and demographic characteristics (sex, age, race and Hispanic origin, and age/race and Hispanic origin). United States death counts and rates include the 50 states, plus the District of Columbia. 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 jurisdictions. 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; 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). Rate are based on deaths occurring in the specified week 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 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) 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.).

  12. Rate of U.S. COVID-19 cases as of March 10, 2023, by state

    • statista.com
    Updated May 15, 2024
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    Statista (2024). Rate of U.S. COVID-19 cases as of March 10, 2023, by state [Dataset]. https://www.statista.com/statistics/1109004/coronavirus-covid19-cases-rate-us-americans-by-state/
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    Dataset updated
    May 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of March 10, 2023, the state with the highest rate of COVID-19 cases was Rhode Island followed by Alaska. Around 103.9 million cases have been reported across the United States, with the states of California, Texas, and Florida reporting the highest numbers of infections.

    From an epidemic to a pandemic The World Health Organization declared the COVID-19 outbreak as a pandemic on March 11, 2020. The term pandemic refers to multiple outbreaks of an infectious illness threatening multiple parts of the world at the same time; when the transmission is this widespread, it can no longer be traced back to the country where it originated. The number of COVID-19 cases worldwide is roughly 683 million, and it has affected almost every country in the world.

    The symptoms and those who are most at risk Most people who contract the virus will suffer only mild symptoms, such as a cough, a cold, or a high temperature. However, in more severe cases, the infection can cause breathing difficulties and even pneumonia. Those at higher risk include older persons and people with pre-existing medical conditions, including diabetes, heart disease, and lung disease. Those aged 85 years and older have accounted for around 27 percent of all COVID deaths in the United States, although this age group makes up just two percent of the total population

  13. f

    Table_1_Assessing the Impact of Neighborhood Socioeconomic Characteristics...

    • frontiersin.figshare.com
    docx
    Updated Jun 1, 2023
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    Elham Hatef; Hsien-Yen Chang; Christopher Kitchen; Jonathan P. Weiner; Hadi Kharrazi (2023). Table_1_Assessing the Impact of Neighborhood Socioeconomic Characteristics on COVID-19 Prevalence Across Seven States in the United States.DOCX [Dataset]. http://doi.org/10.3389/fpubh.2020.571808.s001
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Frontiers
    Authors
    Elham Hatef; Hsien-Yen Chang; Christopher Kitchen; Jonathan P. Weiner; Hadi Kharrazi
    License

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

    Area covered
    United States
    Description

    Introduction: The spread of Coronavirus Disease 2019 (COVID-19) across the United States has highlighted the long-standing nationwide health inequalities with socioeconomically challenged communities experiencing a higher burden of the disease. We assessed the impact of neighborhood socioeconomic characteristics on the COVID-19 prevalence across seven selected states (i.e., Arizona, Florida, Illinois, Maryland, North Carolina, South Carolina, and Virginia).Methods: We obtained cumulative COVID-19 cases reported at the neighborhood aggregation level by Departments of Health in selected states on two dates (May 3rd, 2020, and May 30th, 2020) and assessed the correlation between the COVID-19 prevalence and neighborhood characteristics. We developed Area Deprivation Index (ADI), a composite measure to rank neighborhoods by their socioeconomic characteristics, using the 2018 US Census American Community Survey. The higher ADI rank represented more disadvantaged neighborhoods.Results: After controlling for age, gender, and the square mileage of each community we identified Zip-codes with higher ADI (more disadvantaged neighborhoods) in Illinois and Maryland had higher COVID-19 prevalence comparing to zip-codes across the country and in the same state with lower ADI (less disadvantaged neighborhoods) using data on May 3rd. We detected the same pattern across all states except for Florida and Virginia using data on May 30th, 2020.Conclusion: Our study provides evidence that not all Americans are at equal risk for COVID-19. Socioeconomic characteristics of communities appear to be associated with their COVID-19 susceptibility, at least among those study states with high rates of disease.

  14. f

    Weekly deliverables for key stakeholders.

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 8, 2023
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    Stacy Endres-Dighe; Kasey Jones; Emily Hadley; Alexander Preiss; Caroline Kery; Marie Stoner; Susan Eversole; Sarah Rhea (2023). Weekly deliverables for key stakeholders. [Dataset]. http://doi.org/10.1371/journal.pone.0260310.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 8, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Stacy Endres-Dighe; Kasey Jones; Emily Hadley; Alexander Preiss; Caroline Kery; Marie Stoner; Susan Eversole; Sarah Rhea
    License

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

    Description

    Weekly deliverables for key stakeholders.

  15. Rates of COVID-19 Cases or Deaths by Age Group and Updated (Bivalent)...

    • data.virginia.gov
    • healthdata.gov
    • +1more
    csv, json, rdf, xsl
    Updated Jun 1, 2023
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    Centers for Disease Control and Prevention (2023). Rates of COVID-19 Cases or Deaths by Age Group and Updated (Bivalent) Booster Status [Dataset]. https://data.virginia.gov/dataset/rates-of-covid-19-cases-or-deaths-by-age-group-and-updated-bivalent-booster-status
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    xsl, csv, json, rdfAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    Data for CDC’s COVID Data Tracker site on Rates of COVID-19 Cases and Deaths by Updated (Bivalent) Booster Status. Click 'More' for important dataset description and footnotes

    Webpage: https://covid.cdc.gov/covid-data-tracker/#rates-by-vaccine-status

    Dataset and data visualization details:

    These data were posted and archived on May 30, 2023 and reflect cases among persons with a positive specimen collection date through April 22, 2023, and deaths among persons with a positive specimen collection date through April 1, 2023. These data will no longer be updated after May 2023.

    Vaccination status: A person vaccinated with at least a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. A person vaccinated with a primary series and a monovalent booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably receiving a primary series of an FDA-authorized or approved vaccine and at least one additional dose of any monovalent FDA-authorized or approved COVID-19 vaccine on or after August 13, 2021. (Note: this definition does not distinguish between vaccine recipients who are immunocompromised and are receiving an additional dose versus those who are not immunocompromised and receiving a booster dose.) A person vaccinated with a primary series and an updated (bivalent) booster dose had SARS-CoV-2 RNA or antigen detected in a respiratory specimen collected ≥14 days after verifiably receiving a primary series of an FDA-authorized or approved vaccine and an additional dose of any bivalent FDA-authorized or approved vaccine COVID-19 vaccine on or after September 1, 2022. (Note: Doses with bivalent doses reported as first or second doses are classified as vaccinated with a bivalent booster dose.) People with primary series or a monovalent booster dose were combined in the “vaccinated without an updated booster” category.

    Deaths: A COVID-19–associated death occurred in a person with a documented COVID-19 diagnosis who died; health department staff reviewed to make a determination using vital records, public health investigation, or other data sources. Per the interim guidance of the Council of State and Territorial Epidemiologists (CSTE), this should include persons whose death certificate lists COVID-19 disease or SARS-CoV-2 as the underlying cause of death or as a significant condition contributing to death. Rates of COVID-19 deaths by vaccination status are primarily reported based on when the patient was tested for COVID-19. In select jurisdictions, deaths are included that are not laboratory confirmed and are reported based on alternative dates (i.e., onset date for most; or date of death or report date, where onset date is unavailable). Deaths usually occur up to 30 days after COVID-19 diagnosis.

    Participating jurisdictions: Currently, these 24 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Colorado, District of Columbia, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (NY), North Carolina, Rhode Island, Tennessee, Texas, Utah, and West Virginia; 23 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 48% of the total U.S. population and all ten of the Health and Human Services Regions. This list will be

  16. f

    Datasheet1_Transmission prevention behaviors in US households with...

    • frontiersin.figshare.com
    docx
    Updated Jun 2, 2023
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    Rebecca J. Rubinstein; Wenwen Mei; Caitlin A. Cassidy; Gabrielle Streeter; Christopher Basham; Carla Cerami; Feng-Chang Lin; Jessica T. Lin; Katie R. Mollan (2023). Datasheet1_Transmission prevention behaviors in US households with SARS-CoV-2 cases in 2020.docx [Dataset]. http://doi.org/10.3389/fepid.2023.1160214.s001
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    docxAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    Frontiers
    Authors
    Rebecca J. Rubinstein; Wenwen Mei; Caitlin A. Cassidy; Gabrielle Streeter; Christopher Basham; Carla Cerami; Feng-Chang Lin; Jessica T. Lin; Katie R. Mollan
    License

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

    Description

    IntroductionSevere acute respiratory syndrome coronavirus-2 (SARS-CoV-2) transmission frequently occurs within households, yet few studies describe which household contacts and household units are most likely to engage in transmission-interrupting behaviors.MethodsWe analyzed a COVID-19 prospective household transmission cohort in North Carolina (April to October 2020) to quantify changes in physical distancing behaviors among household contacts over 14 days. We evaluated which household contacts were most likely to ever mask at home and to ever share a bedroom with the index case between days 7–14.ResultsIn the presence of a household COVID-19 infection, 24% of household contacts reported ever masking at home during the week before study entry. Masking in the home between days 7–14 was reported by 26% of household contacts and was more likely for participants who observed their household index case wearing a mask. Participants of color and participants in high-density households were more likely to mask at home. After adjusting for race/ethnicity, living density was not as clearly associated with masking. Symptomatic household contacts were more likely to share a bedroom with the index case. Working individuals and those with comorbidities avoided sharing a bedroom with the index case.DiscussionIn-home masking during household exposure to COVID-19 was infrequent in 2020. In light of the ongoing transmission of SARS-CoV-2, these findings underscore a need for health campaigns to increase the feasibility and social desirability of in-home masking among exposed household members. Joint messaging on social responsibility and prevention of breakthrough infections, reinfections, and long COVID-19 may help motivate transmission-interruption behaviors.

  17. Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status and...

    • data.cdc.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Feb 22, 2023
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    CDC COVID-19 Response, Epidemiology Task Force (2023). Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status and Booster Dose [Dataset]. https://data.cdc.gov/w/d6p8-wqjm/tdwk-ruhb?cur=4YYJdVztK25&from=9zXKUZts2P5
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    json, tsv, csv, xml, application/rdfxml, application/rssxmlAvailable download formats
    Dataset updated
    Feb 22, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    CDC COVID-19 Response, Epidemiology Task Force
    Description

    Data for CDC’s COVID Data Tracker site on Rates of COVID-19 Cases and Deaths by Vaccination Status. Click 'More' for important dataset description and footnotes

    Dataset and data visualization details: These data were posted on October 21, 2022, archived on November 18, 2022, and revised on February 22, 2023. These data reflect cases among persons with a positive specimen collection date through September 24, 2022, and deaths among persons with a positive specimen collection date through September 3, 2022.

    Vaccination status: A person vaccinated with a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. Additional or booster dose: A person vaccinated with a primary series and an additional or booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after receipt of an additional or booster dose of any COVID-19 vaccine on or after August 13, 2021. For people ages 18 years and older, data are graphed starting the week including September 24, 2021, when a COVID-19 booster dose was first recommended by CDC for adults 65+ years old and people in certain populations and high risk occupational and institutional settings. For people ages 12-17 years, data are graphed starting the week of December 26, 2021, 2 weeks after the first recommendation for a booster dose for adolescents ages 16-17 years. For people ages 5-11 years, data are included starting the week of June 5, 2022, 2 weeks after the first recommendation for a booster dose for children aged 5-11 years. For people ages 50 years and older, data on second booster doses are graphed starting the week including March 29, 2022, when the recommendation was made for second boosters. Vertical lines represent dates when changes occurred in U.S. policy for COVID-19 vaccination (details provided above). Reporting is by primary series vaccine type rather than additional or booster dose vaccine type. The booster dose vaccine type may be different than the primary series vaccine type. ** Because data on the immune status of cases and associated deaths are unavailable, an additional dose in an immunocompromised person cannot be distinguished from a booster dose. This is a relevant consideration because vaccines can be less effective in this group. Deaths: A COVID-19–associated death occurred in a person with a documented COVID-19 diagnosis who died; health department staff reviewed to make a determination using vital records, public health investigation, or other data sources. Rates of COVID-19 deaths by vaccination status are reported based on when the patient was tested for COVID-19, not the date they died. Deaths usually occur up to 30 days after COVID-19 diagnosis. Participating jurisdictions: Currently, these 31 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Arkansas, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (New York), North Carolina, Philadelphia (Pennsylvania), Rhode Island, South Dakota, Tennessee, Texas, Utah, Washington, and West Virginia; 30 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 72% of the total U.S. population and all ten of the Health and Human Services Regions. Data on cases among people who received additional or booster doses were reported from 31 jurisdictions; 30 jurisdictions also reported data on deaths among people who received one or more additional or booster dose; 28 jurisdictions reported cases among people who received two or more additional or booster doses; and 26 jurisdictions reported deaths among people who received two or more additional or booster doses. This list will be updated as more jurisdictions participate. Incidence rate estimates: Weekly age-specific incidence rates by vaccination status were calculated as the number of cases or deaths divided by the number of people vaccinated with a primary series, overall or with/without a booster dose (cumulative) or unvaccinated (obtained by subtracting the cumulative number of people vaccinated with a primary series and partially vaccinated people from the 2019 U.S. intercensal population estimates) and multiplied by 100,000. Overall incidence rates were age-standardized using the 2000 U.S. Census standard population. To estimate population counts for ages 6 months through 1 year, half of the single-year population counts for ages 0 through 1 year were used. All rates are plotted by positive specimen collection date to reflect when incident infections occurred. For the primary series analysis, age-standardized rates include ages 12 years and older from April 4, 2021 through December 4, 2021, ages 5 years and older from December 5, 2021 through July 30, 2022 and ages 6 months and older from July 31, 2022 onwards. For the booster dose analysis, age-standardized rates include ages 18 years and older from September 19, 2021 through December 25, 2021, ages 12 years and older from December 26, 2021, and ages 5 years and older from June 5, 2022 onwards. Small numbers could contribute to less precision when calculating death rates among some groups. Continuity correction: A continuity correction has been applied to the denominators by capping the percent population coverage at 95%. To do this, we assumed that at least 5% of each age group would always be unvaccinated in each jurisdiction. Adding this correction ensures that there is always a reasonable denominator for the unvaccinated population that would prevent incidence and death rates from growing unrealistically large due to potential overestimates of vaccination coverage. Incidence rate ratios (IRRs): IRRs for the past one month were calculated by dividing the average weekly incidence rates among unvaccinated people by that among people vaccinated with a primary series either overall or with a booster dose. Publications: Scobie HM, Johnson AG, Suthar AB, et al. Monitoring Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Status — 13 U.S. Jurisdictions, April 4–July 17, 2021. MMWR Morb Mortal Wkly Rep 2021;70:1284–1290. Johnson AG, Amin AB, Ali AR, et al. COVID-19 Incidence and Death Rates Among Unvaccinated and Fully Vaccinated Adults with and Without Booster Doses During Periods of Delta and Omicron Variant Emergence — 25 U.S. Jurisdictions, April 4–December 25, 2021. MMWR Morb Mortal Wkly Rep 2022;71:132–138

  18. F

    Face Shield Market Report

    • promarketreports.com
    doc, pdf, ppt
    Updated Feb 5, 2025
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    Pro Market Reports (2025). Face Shield Market Report [Dataset]. https://www.promarketreports.com/reports/face-shield-market-3312
    Explore at:
    ppt, pdf, docAvailable download formats
    Dataset updated
    Feb 5, 2025
    Dataset authored and provided by
    Pro Market Reports
    License

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

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    Polycarbonate Face Shields: Polycarbonate shields offer high impact resistance and clarity, making them suitable for industrial and professional applications.Cellulose Acetate Face Shields: These shields are biodegradable and provide adequate protection for short-term use, such as in retail and hospitality settings. Recent developments include: September 2020: The Wisconsin Health Care Association and Wisconsin Centre for Assisted Living (WHCA/WiCAL) have established a relationship with one of North America's major industrial safety equipment suppliers, Magid Glove & Safety Manufacturing Company LLC., July 2022: BASF has joined forces with Vadodara-based membrane manufacturer Permionics Membranes to expand the use of its Ultrason E polyethersulphone PESU polymer into coated fabrics that serve as particulate and microbiological filters for face masks., May 2021: Aspen Surgical Products, Inc., a market leader in surgical disposables, has acquired North Carolina-based Precept Medical Products for an undisclosed sum. The acquisition will broaden Aspen's product offering by bringing in items essential for the well-being and safety of medical staff.. Notable trends are: Growing concern over cases of COVID-19 is driving the market growth.

  19. Data from: Evidence of molecular mimicry in multisystem inflammatory...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated May 9, 2024
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    Aaron Bodansky; Robert Mettelman; Joseph Sabatino; Sara Vazquez; Janet Chou; Tanya Novak; Kristin Moffitt; Haleigh Miller; Andrew Kung; Elze Rackaityte; Colin Zamecnik; Jayant Rajan; Hannah Kortbawi; Caleigh Mandel-Brehm; Anthea Mitchell; Chung-Yu Wang; Aditi Saxena; Kelsey Zorn; David Yu; Mikhail Pogorelyy; Walid Awad; Allison Kirk; John Pluvinage; Michael Wilson; Laura Loftis; Charlotte Hobbs; Keiko Tarquinio; Michelle Kong; Julie Fitzgerald; Paula Espinal; Tracie Walker; Stephanie Schwartz; Hillary Crandall; Katherine Irby; Mary Staat; Courtney Rowan; Jennifer Schuster; Natasha Halasa; Shira Gertz; Elizabeth Mack; Aline Maddux; Natalie Cvijanovich; Matt Zinter; Laura Zambrano; Angela Campbell; Paul Thomas; Adrienne Randolph; Mark Anderson; Joseph DeRisi (2024). Evidence of molecular mimicry in multisystem inflammatory syndrome in children (MIS-C) [Dataset]. http://doi.org/10.7272/Q6SJ1HVH
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    zipAvailable download formats
    Dataset updated
    May 9, 2024
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Harvard Medical School
    University of California San Francisco Medical Center
    Medical University of South Carolina
    Riley Hospital for Children
    Chan Zuckerberg Biohub San Francisco
    Saint Barnabas Medical Center
    Baylor College of Medicine
    Vanderbilt University Medical Center
    St. Jude Children's Research Hospital
    Arkansas Children's Hospital
    Children's Hospital of Philadelphia
    University of California, San Francisco
    University of Colorado Anschutz Medical Campus
    University of Alabama at Birmingham
    University of North Carolina at Chapel Hill
    University of Utah
    Children's Mercy Hospital
    Miami Children's Hospital
    Emory University
    Cincinnati Children's Hospital Medical Center
    University of Mississippi Medical Center
    UCSF Benioff Children's Hospital
    Authors
    Aaron Bodansky; Robert Mettelman; Joseph Sabatino; Sara Vazquez; Janet Chou; Tanya Novak; Kristin Moffitt; Haleigh Miller; Andrew Kung; Elze Rackaityte; Colin Zamecnik; Jayant Rajan; Hannah Kortbawi; Caleigh Mandel-Brehm; Anthea Mitchell; Chung-Yu Wang; Aditi Saxena; Kelsey Zorn; David Yu; Mikhail Pogorelyy; Walid Awad; Allison Kirk; John Pluvinage; Michael Wilson; Laura Loftis; Charlotte Hobbs; Keiko Tarquinio; Michelle Kong; Julie Fitzgerald; Paula Espinal; Tracie Walker; Stephanie Schwartz; Hillary Crandall; Katherine Irby; Mary Staat; Courtney Rowan; Jennifer Schuster; Natasha Halasa; Shira Gertz; Elizabeth Mack; Aline Maddux; Natalie Cvijanovich; Matt Zinter; Laura Zambrano; Angela Campbell; Paul Thomas; Adrienne Randolph; Mark Anderson; Joseph DeRisi
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Description

    Multisystem inflammatory syndrome in children (MIS-C) is a severe, post-infectious sequela of SARS-CoV-2 infection, yet the pathophysiological mechanism connecting the infection to the broad inflammatory syndrome remains unknown. Here we leveraged a large set of MIS-C patient samples (n=199) to identify a distinct set of host proteins that are differentially targeted by patient autoantibodies relative to matched controls. We identified an autoreactive epitope within SNX8, a protein expressed primarily in immune cells that regulates an antiviral pathway associated with MIS-C pathogenesis. In parallel, we also probed the SARS-CoV-2 proteome-wide MIS-C patient antibody response and found it to be differentially reactive to a distinct domain of the SARS-CoV-2 nucleocapsid (N) protein relative to controls. This viral N region and the mapped SNX8 epitope bear remarkable biochemical similarity. Furthermore, we find that many children with anti-SNX8 autoantibodies also have T cells cross-reactive to both SNX8 and this distinct region of the SARS-CoV-2 N protein. Together, these findings suggest that MIS-C patients develop a characteristic immune response against the SARS-CoV-2 N protein that is associated with cross-reactivity to the self-protein SNX8, demonstrating a mechanistic link from the infection to the inflammatory syndrome with implications for better understanding a range of post-infectious autoinflammatory diseases. Methods Patients Patients were recruited through the prospectively enrolling multicenter Overcoming COVID-19 and Taking on COVID-19 Together study in the United States. The study was approved by the central Boston Children’s Hospital Institutional Review Board (IRB) and reviewed by IRBs of participating sites with CDC IRB reliance. A total of 292 patients were enrolled into 1 of the following independent cohorts between June 1, 2020 and September 9, 2021: 223 patients hospitalized with MIS-C (199 in the primary discovery cohort, 24 in a separate subsequent validation cohort), 29 patients hospitalized for COVID-19 in either an intensive care or step-down unit (referred to as severe acute COVID-19 in this study), and 45 outpatients (referred to as “at-risk controls” in this study) post-SARS-CoV-2 infections associated with mild or no symptoms. The demographic and clinical data are summarized in Table I, Extended Data Table 1, and Extended Data Table 2. The 2020 US Centers for Disease Control and Prevention case definition was used to define MIS-C(1). All patients with MIS-C had positive SARS-CoV-2 serology results and/or positive SARS-CoV-2 test results by reverse transcriptase quantitative PCR. All patients with severe COVID-19 or outpatient SARS-CoV-2 infections had a positive antigen test or nucleic acid amplification test for SARS-CoV-2. For outpatients, samples were collected from 36 to 190 days after the positive test (median, 70 days after the positive test; interquartile range, 56-81 days). For use as controls in the SARS-CoV-2 specific PhIP-Seq, plasma from 48 healthy, pre-COVID-19 controls was obtained as deidentified samples from the New York Blood Center. These samples were part of retention tubes collected at the time of blood donations from volunteer donors who provided informed consent for their samples to be used for research. Human proteome PhIP-Seq Human Proteome PhIP-Seq was performed following our previously published vacuum-based PhIP-Seq protocol (2) (https://www.protocols.io/view/scaled-high-throughput-vacuum-phip-protocol-ewov1459kvr2/v1). Our human peptidome library consists of a custom-designed phage library of 731,724 unique T7 bacteriophage each presenting a different 49 amino-acid peptide on its surface. Collectively these peptides tile the entire human proteome including all known isoforms (as of 2016) with 25 amino-acid overlaps. 1 milliliter of phage library was incubated with 1 microliter of human serum overnight at 4C and immunoprecipitated with 25 microliters of 1:1 mixed protein A and protein G magnetic beads (Thermo Fisher, Waltham, MA, #10008D and #10009D). These beads were then washed, and the remaining phage-antibody complexes were eluted in 1 milliliter of E.Coli (BLT5403, EMD Millipore, Burlington, MA) at 0.5-0.7 OD and amplified by growing in 37C incubator. This new phage library was then re-incubated with the same individual’s serum and the previously described protocol was repeated. DNA was then extracted from the final phage library, barcoded, and PCR-amplified, and Illumina adaptors were added. Next-generation sequencing was then performed using an Illumina sequencer (Illumina, San Diego, CA) to a read depth of approximately 1 million per sample. Human proteome PhIP-Seq analysis All human peptidome analysis (except when specifically stated otherwise) was performed at the gene level, in which all reads for all peptides mapping to the same gene were summed, and 0.5 reads were added to each gene to allow the inclusion of genes with zero reads in mathematical analyses. Within each individual sample, reads were normalized by converting to the percentage of total reads. To normalize each sample against background non-specific binding, a fold-change (FC) over mock-IP was calculated by dividing the sample read percentage for each gene by the mean read percentage of the same gene for the AG bead-only controls. This FC signal was then used for side-by-side comparison between samples and cohorts. FC values were also used to calculate z-scores for each MIS-C patient relative to controls and for each control sample by using all remaining controls. These z-scores were used for the logistic regression feature weighting. In instances of peptide-level analysis, raw reads were normalized by calculating the number of reads per 100,000 reads. SARS-CoV-2 proteome PhIP-Seq SARS-CoV-2 Proteome PhIP-Seq was performed as previously described(3). Briefly, 38 amino acid fragments tiling all open reading frames from SARS-CoV-2, SARS-CoV-1, and 7 other CoVs were expressed on T7 bacteriophage with 19 amino acid overlaps. 1 milliliter of phage library was incubated with 1 microliter of human serum overnight at 4C and immunoprecipitated with 25 microliters of 1:1 mixed protein A and protein G magnetic beads (Thermo Fisher, Waltham, MA, #10008D and #10009D). Beads were washed 5 times on a magnetic plate using a P1000 multichannel pipette. The remaining phage-antibody complexes were eluted in 1 milliliter of E.Coli (BLT5403, EMD Millipore, Burlington, MA) at 0.5-0.7 OD and amplified by growing in a 37°C incubator. This new phage library was then re-incubated with the same individual’s serum and the previously described protocol was repeated for a total of 3 rounds of immunoprecipitations. DNA was then extracted from the final phage library, barcoded, and PCR-amplified, and Illumina adaptors were added. Next-generation sequencing was then performed using an Illumina sequencer (Illumina, San Diego, CA) to a read depth of approximately 1 million per sample. Coronavirus proteome PhIP-Seq analysis To account for differing read depths between samples, the total number of reads for each peptide fragment was converted to the number of reads per 100k (RPK). To calculate normalized enrichment relative to pre-COVID controls (FC > Pre-COVID), the RPK for each peptide fragment within each sample was divided by the mean RPK of each peptide fragment among all pre-COVID controls. These FC > Pre-COVID values were used for all subsequent analyses as described in the text and figures.

    HAN Archive - 00432 (2021). https://emergency.cdc.gov/han/2020/han00432.asp. S. E. Vazquez, S. A. Mann, A. Bodansky, A. F. Kung, Z. Quandt, E. M. N. Ferré, N. Landegren, D. Eriksson, P. Bastard, S.-Y. Zhang, J. Liu, A. Mitchell, I. Proekt, D. Yu, C. Mandel-Brehm, C.-Y. Wang, B. Miao, G. Sowa, K. Zorn, A. Y. Chan, V. M. Tagi, C. Shimizu, A. Tremoulet, K. Lynch, M. R. Wilson, O. Kämpe, K. Dobbs, O. M. Delmonte, R. Bacchetta, L. D. Notarangelo, J. C. Burns, J.-L. Casanova, M. S. Lionakis, T. R. Torgerson, M. S. Anderson, J. L. DeRisi, Autoantibody discovery across monogenic, acquired, and COVID-19-associated autoimmunity with scalable PhIP-seq. Elife 11 (2022). C. R. Zamecnik, J. V. Rajan, K. A. Yamauchi, S. A. Mann, R. P. Loudermilk, G. M. Sowa, K. C. Zorn, B. D. Alvarenga, C. Gaebler, M. Caskey, M. Stone, P. J. Norris, W. Gu, C. Y. Chiu, D. Ng, J. R. Byrnes, X. X. Zhou, J. A. Wells, D. F. Robbiani, M. C. Nussenzweig, J. L. DeRisi, M. R. Wilson, ReScan, a Multiplex Diagnostic Pipeline, Pans Human Sera for SARS-CoV-2 Antigens. Cell Rep Med 1, 100123 (2020).

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

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(2021). NC COVID-19 Cases & Deaths [Dataset]. https://data.townofcary.org/explore/dataset/nc-covid-19-cases-deaths/

NC COVID-19 Cases & Deaths

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excel, csv, jsonAvailable download formats
Dataset updated
Sep 14, 2021
License

CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically

Area covered
North Carolina
Description

This dataset contains counts of COVID-19 cases and deaths in North Carolina from March 2, 2020 to May 31, 2021. The data was extracted from NC Department of Health and Human Services' NC COVID-19 dashboard: Daily Cases and Deaths Metrics. This dataset is an archive - it is not being updated.

Data Source: NCDHHS (2021). Daily Cases and Deaths Metrics (Version 1.3) [Data set]. https://covid19.ncdhhs.gov/dashboard/data-behind-dashboards

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