16 datasets found
  1. O

    CDC COVID-19 Community Levels by County

    • opendata.ramseycountymn.gov
    csv, xlsx, xml
    Updated Dec 2, 2025
    + more versions
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    Center for Disease Control and Prevention (2025). CDC COVID-19 Community Levels by County [Dataset]. https://opendata.ramseycountymn.gov/Public-Health/CDC-COVID-19-Community-Levels-by-County/uazb-iwdp
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    csv, xlsx, xmlAvailable download formats
    Dataset updated
    Dec 2, 2025
    Dataset authored and provided by
    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.

  2. y

    Minnesota Coronavirus Cases Per Day (DISCONTINUED)

    • ycharts.com
    html
    Updated Jun 8, 2023
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    Center for Disease Control and Prevention (2023). Minnesota Coronavirus Cases Per Day (DISCONTINUED) [Dataset]. https://ycharts.com/indicators/minnesota_coronavirus_cases_per_day
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    htmlAvailable download formats
    Dataset updated
    Jun 8, 2023
    Dataset provided by
    YCharts
    Authors
    Center for Disease Control and Prevention
    License

    https://www.ycharts.com/termshttps://www.ycharts.com/terms

    Time period covered
    Jan 23, 2020 - Oct 18, 2022
    Area covered
    Minnesota
    Variables measured
    Minnesota Coronavirus Cases Per Day (DISCONTINUED)
    Description

    View daily updates and historical trends for Minnesota Coronavirus Cases Per Day (DISCONTINUED). Source: Center for Disease Control and Prevention. Track …

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

    • statista.com
    Updated May 15, 2024
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    Statista (2024). COVID-19 death rates in the United States as of March 10, 2023, by state [Dataset]. https://www.statista.com/statistics/1109011/coronavirus-covid19-death-rates-us-by-state/
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    Dataset updated
    May 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

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

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

    • statista.com
    Updated Jun 15, 2020
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    Statista (2020). 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
    Jun 15, 2020
    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

  5. M

    Project Tycho Dataset; Counts of COVID-19 Reported In UNITED STATES OF...

    • catalog.midasnetwork.us
    • tycho.pitt.edu
    • +1more
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    MIDAS Coordination Center, Project Tycho Dataset; Counts of COVID-19 Reported In UNITED STATES OF AMERICA: 2019-2021 [Dataset]. http://doi.org/10.25337/T7/ptycho.v2.0/US.840539006
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    Dataset provided by
    MIDAS COORDINATION CENTER
    Authors
    MIDAS Coordination Center
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

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

    Time period covered
    Dec 30, 2019 - Jul 31, 2021
    Area covered
    Region, City, Country, Second-order administrative division, First-order administrative division, Health region, United States
    Variables measured
    Viruses, disease, COVID-19, pathogen, mortality data, Population count, infectious disease, hospital stay dataset, viral Infectious disease, vaccine-preventable Disease, and 3 more
    Dataset funded by
    National Institute of General Medical Sciences
    Description

    This Project Tycho dataset includes a CSV file with COVID-19 data reported in UNITED STATES OF AMERICA: 2019-12-30 - 2021-07-31. It contains counts of cases, deaths, hospitalizations, and demographics. Data for this Project Tycho dataset comes from: "Alabama Department of Public Health Website Dashboard", "Arkansas Department of Health COVID-19 Website Dashboard", "California Health and Human Services Open Data Portal, California Department of Public Health COVID-19 Data", "Colorado Department of Public Health and Environment Open Data Website", "Connecticut Open Data Website, Department of Public Health COVID-19 Data", "Delaware Environmental Public Health Tracking Network, Delaware Health and Social Services Website", "Georgia Department of Public Health Website", "Illinois Department of Public Health Website", "Indiana Data Hub Website, Indiana State Department of Health COVID-19 Data", "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University", "Kentucky Department of Public Health COVID-19 Website Dashboard", "Maine Center for Disease Control & Prevention; Division of the Maine Department of Health and Human Services Website", "Maryland Department of Health COVID-19 Website Dashboard", "Minnesota Department of Health COVID-19 Website Dashboard", "Montana Department of Health & Human Services COVID-19 Website Dashboard", "New York State Department of Health Data Website", "COVID-19 Data Repository by The New York Times", "Ohio Department of Health COVID-19 website", "Pennsylvania Department of Health Data Website", "Tennessee Department of Health Website", "Texas Department of Health Services Website", "United States Centers for Disease Control and Prevention, COVID-19 Response", "Vermont Department of Health, Vermont Center for Geographic Information Open Geodata Portal", "Virginia Department of Health Website", "European Centre for Disease Prevention and Control Website", "World Health Organization COVID-19 Dashboard". The data have been pre-processed into the standard Project Tycho data format v1.1.

  6. COVID-19 vaccination status of campers and staff at the residential summer...

    • plos.figshare.com
    xls
    Updated Nov 27, 2023
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    Tirzah Weiss; Tate Reuter; Evan Dowell; Mitchell Singstock; Katherine Smith; Jeffrey Schlaudecker (2023). COVID-19 vaccination status of campers and staff at the residential summer camps. [Dataset]. http://doi.org/10.1371/journal.pone.0282560.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Nov 27, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Tirzah Weiss; Tate Reuter; Evan Dowell; Mitchell Singstock; Katherine Smith; Jeffrey Schlaudecker
    License

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

    Description

    COVID-19 vaccination status of campers and staff at the residential summer camps.

  7. Rt of COVID-19 in the U.S. as of January 23, 2021, by state

    • statista.com
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    Statista, Rt of COVID-19 in the U.S. as of January 23, 2021, by state [Dataset]. https://www.statista.com/statistics/1119412/covid-19-transmission-rate-us-by-state/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of January 23, 2021, Vermont had the highest Rt value of any U.S. state. The Rt value indicates the average number of people that one person with COVID-19 is expected to infect. A number higher than one means each infected person is passing the virus to more than one other person.

    Which are the hardest-hit states? The U.S. reported its first confirmed coronavirus case toward the end of January 2020. More than 28 million positive cases have since been recorded as of February 24, 2021 – California and Texas are the states with the highest number of coronavirus cases in the United States. When figures are adjusted to reflect each state’s population, North Dakota has the highest rate of coronavirus cases. The vaccine rollout has provided Americans with a significant morale boost, and California is the state with the highest number of COVID-19 vaccine doses administered.

    How have other nations responded? Countries around the world have responded to the pandemic in varied ways. The United Kingdom has approved three vaccines for emergency use and ranks among the countries with the highest number of COVID-19 vaccine doses administered worldwide. In the Asia-Pacific region, the outbreak has been brought under control in New Zealand, and the country’s response to the pandemic has been widely praised.

  8. S1 File -

    • plos.figshare.com
    xls
    Updated Jan 19, 2024
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    Genjie Lu; Wei Chen; Yangfang Lu; Qilin Yu; Li Gao; Shijun Xin; Guanbao Zhou (2024). S1 File - [Dataset]. http://doi.org/10.1371/journal.pone.0296917.s001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jan 19, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Genjie Lu; Wei Chen; Yangfang Lu; Qilin Yu; Li Gao; Shijun Xin; Guanbao Zhou
    License

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

    Description

    BackgroundPrevious studies have reported that the susceptibility to coronavirus disease 2019 (COVID-19) is related to ABO blood group, but the relationship with Rh phenotype and MN blood group is unknown. China had adopted a strict control policy on COVID-19 until December 5, 2022, when local communities were liberalized. Therefore, we aimed to explore the correlation between ABO blood group, Rh phenotype, MN blood group and susceptibility to COVID-19 based on the time sequence of infection during the pandemic.MethodsA total of 870 patients who were routinely hospitalized in Ningbo Medical Center Lihuili Hospital from March 1, 2023 to March 31, 2023 were randomly selected to enroll in this study. Patients were divided into susceptible group and non-susceptible group, according to the time of their previous infection. The demographics and clinical information of the enrolled participants were collected from electronic medical records. The association of ABO blood group, Rh phenotype and MN blood group with susceptibility to COVID-19 was analyzed.ResultsA total of 650 cases (74.7%) had been infected with COVID-19, with 157 cases (18.0%) in the second week and 252 cases (29.0%) in the third week, reaching the peak of infection. Compared with the non-susceptible group, the susceptible group had no statistically significant differences in ABO blood group and Rh phenotype, but the proportion of N+ was higher (75.6% vs 68.9%, P = 0.030) and the proportion of MM was lower (24.4% vs 31.1%, P = 0.030). Consistent with this, ABO blood group and Rh phenotype were not significantly associated with susceptibility to COVID-19 (P>0.05), while N+ and MM were associated with susceptibility to COVID-19 (OR: 1.432, 95% confidence interval [CI]: 1.049, 1.954, P = 0.024; OR: 0.698, 95% CI: 0.512, 0.953, P = 0.024, respectively), after adjusting for age, sex, BMI, basic disease, and vaccination status in multivariate logistic regression analysis.ConclusionOur study showed that ABO blood group and Rh phenotype may not be related to the susceptibility to COVID-19, but MN blood group may be associated with the susceptibility to COVID-19.

  9. Multivariate logistic regression analysis of ABO blood type, Rh phenotype,...

    • plos.figshare.com
    xls
    Updated Jan 19, 2024
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    Genjie Lu; Wei Chen; Yangfang Lu; Qilin Yu; Li Gao; Shijun Xin; Guanbao Zhou (2024). Multivariate logistic regression analysis of ABO blood type, Rh phenotype, and MN blood type associated with susceptibility to COVID-19b'*'. [Dataset]. http://doi.org/10.1371/journal.pone.0296917.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jan 19, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Genjie Lu; Wei Chen; Yangfang Lu; Qilin Yu; Li Gao; Shijun Xin; Guanbao Zhou
    License

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

    Description

    Multivariate logistic regression analysis of ABO blood type, Rh phenotype, and MN blood type associated with susceptibility to COVID-19b'*'.

  10. Results of symptomatic testing for COVID-19 during camp sessions.

    • plos.figshare.com
    xls
    Updated Nov 27, 2023
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    Tirzah Weiss; Tate Reuter; Evan Dowell; Mitchell Singstock; Katherine Smith; Jeffrey Schlaudecker (2023). Results of symptomatic testing for COVID-19 during camp sessions. [Dataset]. http://doi.org/10.1371/journal.pone.0282560.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Nov 27, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Tirzah Weiss; Tate Reuter; Evan Dowell; Mitchell Singstock; Katherine Smith; Jeffrey Schlaudecker
    License

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

    Description

    Results of symptomatic testing for COVID-19 during camp sessions.

  11. Table_1_Using a web platform for equitable distribution of COVID-19...

    • frontiersin.figshare.com
    docx
    Updated Nov 28, 2023
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    Jonathon P. Leider; Sarah Lim; Debra DeBruin; Alexandra T. Waterman; Barbara Smith; Umesh Ghimire; Haley Huhtala; Zachary Zirnhelt; Ruth Lynfield; John L. Hick (2023). Table_1_Using a web platform for equitable distribution of COVID-19 monoclonal antibodies: a case study in resource allocation.docx [Dataset]. http://doi.org/10.3389/fpubh.2023.1226935.s001
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    docxAvailable download formats
    Dataset updated
    Nov 28, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Jonathon P. Leider; Sarah Lim; Debra DeBruin; Alexandra T. Waterman; Barbara Smith; Umesh Ghimire; Haley Huhtala; Zachary Zirnhelt; Ruth Lynfield; John L. Hick
    License

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

    Description

    While medical countermeasures in COVID-19 have largely focused on vaccinations, monoclonal antibodies (mAbs) were early outpatient treatment options for COVID-positive patients. In Minnesota, a centralized access platform was developed to offer access to mAbs that linked over 31,000 patients to care during its operation. The website allowed patients, their representative, or providers to screen the patient for mAbs against Emergency Use Authorization (EUA) criteria and connect them with a treatment site if provisionally eligible. A validated clinical risk scoring system was used to prioritize patients during times of scarcity. Both an ethics and a clinical subject matter expert group advised the Minnesota Department of Health on equitable approaches to distribution across a range of situations as the pandemic evolved. This case study outlines the implementation of this online platform and clinical outcomes of its users. We assess the impact of referral for mAbs on hospitalizations and death during a period of scarcity, finding in particular that vaccination conferred a substantially larger protection against hospitalization than a referral for mAbs, but among unvaccinated users that did not get a referral, chances of hospitalization increased by 4.1 percentage points.

  12. April 2021 CDC-recommended procedures for camps with incomplete camper...

    • plos.figshare.com
    xls
    Updated Nov 27, 2023
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    Tirzah Weiss; Tate Reuter; Evan Dowell; Mitchell Singstock; Katherine Smith; Jeffrey Schlaudecker (2023). April 2021 CDC-recommended procedures for camps with incomplete camper vaccination. [Dataset]. http://doi.org/10.1371/journal.pone.0282560.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Nov 27, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Tirzah Weiss; Tate Reuter; Evan Dowell; Mitchell Singstock; Katherine Smith; Jeffrey Schlaudecker
    License

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

    Description

    April 2021 CDC-recommended procedures for camps with incomplete camper vaccination.

  13. Characteristics of campers and staff at the residential summer camps.

    • plos.figshare.com
    xls
    Updated Nov 27, 2023
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    Tirzah Weiss; Tate Reuter; Evan Dowell; Mitchell Singstock; Katherine Smith; Jeffrey Schlaudecker (2023). Characteristics of campers and staff at the residential summer camps. [Dataset]. http://doi.org/10.1371/journal.pone.0282560.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Nov 27, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Tirzah Weiss; Tate Reuter; Evan Dowell; Mitchell Singstock; Katherine Smith; Jeffrey Schlaudecker
    License

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

    Description

    Characteristics of campers and staff at the residential summer camps.

  14. f

    Demographics and basic clinical characteristics in the study groupb'*'.

    • figshare.com
    • plos.figshare.com
    xls
    Updated Jan 19, 2024
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    Genjie Lu; Wei Chen; Yangfang Lu; Qilin Yu; Li Gao; Shijun Xin; Guanbao Zhou (2024). Demographics and basic clinical characteristics in the study groupb'*'. [Dataset]. http://doi.org/10.1371/journal.pone.0296917.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jan 19, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Genjie Lu; Wei Chen; Yangfang Lu; Qilin Yu; Li Gao; Shijun Xin; Guanbao Zhou
    License

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

    Description

    Demographics and basic clinical characteristics in the study groupb'*'.

  15. f

    Comparison of indexes between susceptible group and non-susceptible...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jan 19, 2024
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    Genjie Lu; Wei Chen; Yangfang Lu; Qilin Yu; Li Gao; Shijun Xin; Guanbao Zhou (2024). Comparison of indexes between susceptible group and non-susceptible groupb'*'. [Dataset]. http://doi.org/10.1371/journal.pone.0296917.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jan 19, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Genjie Lu; Wei Chen; Yangfang Lu; Qilin Yu; Li Gao; Shijun Xin; Guanbao Zhou
    License

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

    Description

    Comparison of indexes between susceptible group and non-susceptible groupb'*'.

  16. The difference in the distribution of ABO blood group between the study...

    • figshare.com
    xls
    Updated Jan 19, 2024
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    Genjie Lu; Wei Chen; Yangfang Lu; Qilin Yu; Li Gao; Shijun Xin; Guanbao Zhou (2024). The difference in the distribution of ABO blood group between the study group and the control group. [Dataset]. http://doi.org/10.1371/journal.pone.0296917.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jan 19, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Genjie Lu; Wei Chen; Yangfang Lu; Qilin Yu; Li Gao; Shijun Xin; Guanbao Zhou
    License

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

    Description

    The difference in the distribution of ABO blood group between the study group and the control group.

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

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Center for Disease Control and Prevention (2025). CDC COVID-19 Community Levels by County [Dataset]. https://opendata.ramseycountymn.gov/Public-Health/CDC-COVID-19-Community-Levels-by-County/uazb-iwdp

CDC COVID-19 Community Levels by County

Explore at:
csv, xlsx, xmlAvailable download formats
Dataset updated
Dec 2, 2025
Dataset authored and provided by
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.

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