100+ datasets found
  1. d

    MD COVID-19 - Testing Volume

    • catalog.data.gov
    • opendata.maryland.gov
    • +1more
    Updated Jun 29, 2025
    + more versions
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    opendata.maryland.gov (2025). MD COVID-19 - Testing Volume [Dataset]. https://catalog.data.gov/dataset/md-covid-19-testing-volume
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    Dataset updated
    Jun 29, 2025
    Dataset provided by
    opendata.maryland.gov
    Area covered
    Maryland
    Description

    NOTE: This dataset is no longer being updated as of 4/27/2023. It is retired and no longer included in public COVID-19 data dissemination. See this link for more information https://imap.maryland.gov/pages/covid-data Summary The daily cumulative total of COVID-19 tests administered in Maryland and the average percent daily positive rate. Description Testing volume data represent the static daily total of PCR COVID-19 tests electronically reported for Maryland residents; this count does not include test results submitted by labs and other clinical facilities through non-electronic means. The percent positive rate is a seven-day rolling average of positive results as a percentage of all tests. Data are lectronic lab reports from NEDDSS. Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

  2. d

    COVID-19 case rate per 100,000 population and percent test positivity in the...

    • datasets.ai
    • data.ct.gov
    • +1more
    23, 40, 55, 8
    Updated Sep 8, 2024
    + more versions
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    State of Connecticut (2024). COVID-19 case rate per 100,000 population and percent test positivity in the last 7 days by town - ARCHIVE [Dataset]. https://datasets.ai/datasets/covid-19-case-rate-per-100000-population-and-percent-test-positivity-in-the-last-7-days-by
    Explore at:
    23, 55, 40, 8Available download formats
    Dataset updated
    Sep 8, 2024
    Dataset authored and provided by
    State of Connecticut
    Description

    DPH note about change from 7-day to 14-day metrics: As of 10/15/2020, this dataset is no longer being updated. Starting on 10/15/2020, these metrics will be calculated using a 14-day average rather than a 7-day average. The new dataset using 14-day averages can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/hree-nys2

    As you know, we are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH has decided to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well.

    With respect to geography, we also have learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as there has been variation within counties in COVID-19 activity (for example, rates that are higher in one town than in most other towns in the county).

    This dataset includes a weekly count and weekly rate per 100,000 population for COVID-19 cases, a weekly count of COVID-19 PCR diagnostic tests, and a weekly percent positivity rate for tests among people living in community settings. Dates are based on date of specimen collection (cases and positivity).

    A person is considered a new case only upon their first COVID-19 testing result because a case is defined as an instance or bout of illness. If they are tested again subsequently and are still positive, it still counts toward the test positivity metric but they are not considered another case.

    These case and test counts do not include cases or tests among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities.

    These data are updated weekly; the previous week period for each dataset is the previous Sunday-Saturday, known as an MMWR week (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf). The date listed is the date the dataset was last updated and corresponds to a reporting period of the previous MMWR week. For instance, the data for 8/20/2020 corresponds to a reporting period of 8/9/2020-8/15/2020.

    Notes: 9/25/2020: Data for Mansfield and Middletown for the week of Sept 13-19 were unavailable at the time of reporting due to delays in lab reporting.

  3. n

    Coronavirus (Covid-19) Data in the United States

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

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

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

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

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

  4. d

    COVID-19 Daily Counts of Cases, Hospitalizations, and Deaths

    • catalog.data.gov
    • data.cityofnewyork.us
    • +1more
    Updated Sep 27, 2025
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    data.cityofnewyork.us (2025). COVID-19 Daily Counts of Cases, Hospitalizations, and Deaths [Dataset]. https://catalog.data.gov/dataset/covid-19-daily-counts-of-cases-hospitalizations-and-deaths
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    Dataset updated
    Sep 27, 2025
    Dataset provided by
    data.cityofnewyork.us
    Description

    Daily count of NYC residents who tested positive for SARS-CoV-2, who were hospitalized with COVID-19, and deaths among COVID-19 patients. Note that this dataset currently pulls from https://raw.githubusercontent.com/nychealth/coronavirus-data/master/trends/data-by-day.csv on a daily basis.

  5. m

    COVID-19 reporting

    • mass.gov
    Updated Oct 21, 2022
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    Executive Office of Health and Human Services (2022). COVID-19 reporting [Dataset]. https://www.mass.gov/info-details/covid-19-reporting
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    Dataset updated
    Oct 21, 2022
    Dataset provided by
    Executive Office of Health and Human Services
    Department of Public Health
    Area covered
    Massachusetts
    Description

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

  6. c

    The COVID Tracking Project

    • covidtracking.com
    google sheets
    + more versions
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    The COVID Tracking Project [Dataset]. https://covidtracking.com/
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    google sheetsAvailable download formats
    Description

    The COVID Tracking Project collects information from 50 US states, the District of Columbia, and 5 other US territories to provide the most comprehensive testing data we can collect for the novel coronavirus, SARS-CoV-2. We attempt to include positive and negative results, pending tests, and total people tested for each state or district currently reporting that data.

    Testing is a crucial part of any public health response, and sharing test data is essential to understanding this outbreak. The CDC is currently not publishing complete testing data, so we’re doing our best to collect it from each state and provide it to the public. The information is patchy and inconsistent, so we’re being transparent about what we find and how we handle it—the spreadsheet includes our live comments about changing data and how we’re working with incomplete information.

    From here, you can also learn about our methodology, see who makes this, and find out what information states provide and how we handle it.

  7. O

    COVID-19 case rate per 100,000 population and percent test positivity in the...

    • data.ct.gov
    • catalog.data.gov
    application/rdfxml +5
    Updated Jun 23, 2022
    + more versions
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    Department of Public Health (2022). COVID-19 case rate per 100,000 population and percent test positivity in the last 14 days by town - ARCHIVE [Dataset]. https://data.ct.gov/widgets/hree-nys2
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    application/rdfxml, csv, application/rssxml, json, xml, tsvAvailable download formats
    Dataset updated
    Jun 23, 2022
    Dataset authored and provided by
    Department of Public Health
    License

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

    Description

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

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

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

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

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

    This dataset includes a count and rate per 100,000 population for COVID-19 cases, a count of COVID-19 molecular diagnostic tests, and a percent positivity rate for tests among people living in community settings for the previous two-week period. Dates are based on date of specimen collection (cases and positivity).

    A person is considered a new case only upon their first COVID-19 testing result because a case is defined as an instance or bout of illness. If they are tested again subsequently and are still positive, it still counts toward the test positivity metric but they are not considered another case.

    Percent positivity is calculated as the number of positive tests among community residents conducted during the 14 days divided by the total number of positive and negative tests among community residents during the same period. If someone was tested more than once during that 14 day period, then those multiple test results (regardless of whether they were positive or negative) are included in the calculation.

    These case and test counts do not include cases or tests among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities.

    These data are updated weekly and reflect the previous two full Sunday-Saturday (MMWR) weeks (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf).

    DPH note about change from 7-day to 14-day metrics: Prior to 10/15/2020, these metrics were calculated using a 7-day average rather than a 14-day average. The 7-day metrics are no longer being updated as of 10/15/2020 but the archived dataset can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/s22x-83rd

    As you know, we are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH has decided to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well.

    With respect to geography, we also have learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as there has been variation within counties in COVID-19 activity (for example, rates that are higher in one town than in most other towns in the county).

    Additional notes: As of 11/5/2020, CT DPH has added antigen testing for SARS-CoV-2 to reported test counts in this dataset. The tests included in this dataset include both molecular and antigen datasets. Molecular tests reported include polymerase chain reaction (PCR) and nucleic acid amplicfication (NAAT) tests.

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

    Data suppression is applied when the rate is <5 cases per 100,000 or if there are <5 cases within the town. Information on why data suppression rules are applied can be found online here: https://www.cdc.gov/cancer/uscs/technical_notes/stat_methods/suppression.htm

  8. 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/
    Explore at:
    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

  9. COVID-19 Community Profile Report

    • healthdata.gov
    • datahub.hhs.gov
    • +3more
    application/rdfxml +5
    Updated Dec 16, 2020
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    White House COVID-19 Team, Joint Coordination Cell, Data Strategy and Execution Workgroup (2020). COVID-19 Community Profile Report [Dataset]. https://healthdata.gov/Health/COVID-19-Community-Profile-Report/gqxm-d9w9
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    tsv, xml, application/rdfxml, csv, json, application/rssxmlAvailable download formats
    Dataset updated
    Dec 16, 2020
    Dataset authored and provided by
    White House COVID-19 Team, Joint Coordination Cell, Data Strategy and Execution Workgroup
    License

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

    Description

    After over two years of public reporting, the Community Profile Report will no longer be produced and distributed after February 2023. The final release will be on February 23, 2023. We want to thank everyone who contributed to the design, production, and review of this report and we hope that it provided insight into the data trends throughout the COVID-19 pandemic. Data about COVID-19 will continue to be updated at CDC’s COVID Data Tracker.

    The Community Profile Report (CPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, under the White House COVID-19 Team. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services, the Centers for Disease Control and Prevention, the Assistant Secretary for Preparedness and Response, and the Indian Health Service). The CPR provides easily interpretable information on key indicators for all regions, states, core-based statistical areas (CBSAs), and counties across the United States. It is a snapshot in time that:

  10. Focuses on recent COVID-19 outcomes in the last seven days and changes relative to the week prior
  11. Provides additional contextual information at the county, CBSA, state and regional levels
  12. Supports rapid visual interpretation of results with color thresholds*

    Data in this report may differ from data on state and local websites. This may be due to differences in how data were reported (e.g., date specimen obtained, or date reported for cases) or how the metrics are calculated. Historical data may be updated over time due to delayed reporting. Data presented here use standard metrics across all geographic levels in the United States. It facilitates the understanding of COVID-19 pandemic trends across the United States by using standardized data. The footnotes describe each data source and the methods used for calculating the metrics. For additional data for any particular locality, visit the relevant health department website. Additional data and features are forthcoming.

    *Color thresholds for each category are defined on the color thresholds tab

    Effective April 30, 2021, the Community Profile Report will be distributed on Monday through Friday. There will be no impact to the data represented in these reports due to this change.

    Effective June 22, 2021, the Community Profile Report will only be updated twice a week, on Tuesdays and Fridays.

    Effective August 2, 2021, the Community Profile Report will return to being updated Monday through Friday.

    Effective June 22, 2022, the Community Profile Report will only be updated twice a week, on Wednesdays and Fridays.

  • Rate of coronavirus (COVID-19) cases in New York as of April 19, 2021, by...

    • statista.com
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    Statista, Rate of coronavirus (COVID-19) cases in New York as of April 19, 2021, by county [Dataset]. https://www.statista.com/statistics/1109409/coronavirus-covid19-cases-rate-new-york-by-county/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    New York
    Description

    In the state of New York, Richmond and Rockland have the highest coronavirus case rates when adjusted for the population of a county. Rockland County had around 1,404 positive cases per 10,000 people as of April 19, 2021.

    The five boroughs of NYC With around 894,400 positive infections as of mid-April 2021, New York City has the highest number of coronavirus cases in New York State – this means that there were approximately 1,065 cases per 10,000 people. New York City is composed of five boroughs; each borough is coextensive with a county of New York State. Staten Island is the smallest in terms of population, but it is the borough with the highest rate of COVID-19 cases.

    Public warned against complacency The number of new COVID-19 cases in New York City spiked for the second time as the winter holiday season led to an increase in social gatherings. New York State is slowly recovering – indoor dining reopened in February 2021 – but now is not the time for people to become complacent. Despite the positive rollout of vaccines, experts have urged citizens to adhere to guidelines and warned that face masks might have to be worn for at least another year.

  • COVID-19 Dashboard

    • data.chhs.ca.gov
    • data.ca.gov
    • +2more
    csv, zip
    Updated Sep 19, 2025
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    California Department of Public Health (2025). COVID-19 Dashboard [Dataset]. https://data.chhs.ca.gov/dataset/covid-19-dashboard
    Explore at:
    zip, csv(349074)Available download formats
    Dataset updated
    Sep 19, 2025
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    Description

    The dashboard is updated each Friday.

    Laboratory surveillance data: California laboratories report SARS-CoV-2 test results to CDPH through electronic laboratory reporting. Los Angeles County SARS-CoV-2 lab data has a 7-day reporting lag. Test positivity is calculated using SARS-CoV-2 lab tests that has a specimen collection date reported during a given week. Specimens for testing are collected from patients in healthcare settings and do not reflect all testing for COVID-19 in California. Test positivity for a given week is calculated by dividing the number of positive COVID-19 results by the total number of specimens tested for that virus. Weekly laboratory surveillance data are defined as Sunday through Saturday.

    Hospitalization data: Data on COVID-19 and influenza hospital admissions are from Centers for Disease Control and Prevention’s (CDC) National Healthcare Safety Network (NHSN) Hospitalization dataset. The requirement to report COVID-19-associated hospitalizations was effective November 1, 2024. CDPH pulls NHSN data from the CDC on the Wednesday prior to the publication of the report. Results may differ depending on which day data are pulled. Admission rates are calculated using population estimates from the P-3: Complete State and County Projections Dataset (https://dof.ca.gov/forecasting/demographics/projections/) provided by the State of California Department of Finance. Reported weekly admission rates for the entire season use the population estimates for the year the season started. For more information on NHSN data including the protocol and data collection information, see the CDC NHSN webpage (https://www.cdc.gov/nhsn/index.html). Weekly hospitalization data are defined as Sunday through Saturday.

    Death certificate data: CDPH receives weekly year-to-date dynamic data on deaths occurring in California from the CDPH Center for Health Statistics and Informatics. These data are limited to deaths occurring among California residents and are analyzed to identify COVID-19-coded deaths. These deaths are not necessarily laboratory-confirmed and are an underestimate of all COVID-19-associated deaths in California. Weekly death data are defined as Sunday through Saturday.

  • D

    Percent Positivity of COVID-19 Nucleic Acid Amplification Tests by HHS...

    • data.cdc.gov
    • data.virginia.gov
    • +1more
    csv, xlsx, xml
    Updated Oct 2, 2025
    + more versions
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    CDC (2025). Percent Positivity of COVID-19 Nucleic Acid Amplification Tests by HHS Region, National Respiratory and Enteric Virus Surveillance System [Dataset]. https://data.cdc.gov/Laboratory-Surveillance/Percent-Positivity-of-COVID-19-Nucleic-Acid-Amplif/gvsb-yw6g
    Explore at:
    xml, csv, xlsxAvailable download formats
    Dataset updated
    Oct 2, 2025
    Dataset authored and provided by
    CDC
    Description

    More than 450 public health and clinical laboratories located throughout the United States participate in surveillance for severe acute respiratory virus coronavirus type 2 (SARS-CoV-2), the virus that causes COVID-19, through CDC's National Respiratory and Enteric Virus Surveillance System (NREVSS). The dataset contains a weekly summary of aggregate counts of the total SARS-CoV-2 tests and SARS-CoV-2 detections reported to NREVSS since March 14, 2020. These data are reported weekly on a voluntary basis. Clinical laboratories do not report demographic data through NREVSS. Testing practices may vary regionally, and the number of participating laboratories may change from year to year. Results can be changed for up to 2 years after the initial reporting week. However, discrepancies may be noted and updated at the discretion of the data stewards and key stakeholders.

    While NREVSS strives to present the most precise estimates of respiratory viral trends with reporting burden minimized for participating laboratories, there are several inherent limitations to this surveillance system.

    NREVSS does not collect patient-specific data or demographic information. Multiple samples may be collected from a single patient, so NREVSS results do not necessarily reflect the number of patients tested, nor do they directly reflect hospitalizations or deaths related to COVID-19.

    Participating laboratories vary in size, testing capabilities, and areas served. Some institutions may receive and test samples from sites across a given state or even from multiple states. Without direct knowledge of the population base, NREVSS cannot be used to determine the prevalence or incidence of infection.

    For more information on NREVSS and COVID-19 surveillance please visit: https://www.cdc.gov/surveillance/nrevss. These data appear starting May 25, 2023 on the CDC COVID Data Tracker at the following URLs: https://covid.cdc.gov/covid-data-tracker/#trends ; https://covid.cdc.gov/covid-data-tracker/#cases.

    NREVSS data are reported at the national and HHS regional levels. The ten (10) U.S. Department of HHS regions are defined here: https://www.hhs.gov/about/agencies/iea/regional-offices/index.html.

    The data represent SARS-CoV-2 Nucleic Acid Amplification Test (NAAT) results, which include reverse transcriptase-polymerase chain reaction (RT-PCR) tests from a voluntary, sentinel network of participating laboratories in the United States, including clinical, public health and commercial laboratories (https://www.cdc.gov/surveillance/nrevss/labs/index.html).

    These data exclude antigen, antibody, and at-home test results.

    All data are provisional and subject to change. Reporting is less complete for the past 1 week, and more complete (>90%) for the period 2 weeks earlier.

    There are data from all states across the 10 HHS regions. Because the data are from a sentinel network of laboratories, however, results may vary geographically. The data do not include all test results within a jurisdiction and therefore do not reflect all SARS-CoV-2 NAATs administered in the United States.

    Percent positivity is one of the surveillance metrics used to monitor COVID-19 transmission over time and by area. Percent positivity is calculated by dividing the number of positive NAATs by the total number of NAATs administered, then multiplying by 100 [(# of positive NAAT tests / total NAAT tests) x 100].

    The data represent laboratory tests performed, not individual (deduplicated) results in people. In the table and upon hovering on the map, the total test counts in the data reflect the latest data reported from NREVSS laboratories and may not match the data presented by various jurisdictions.

    On May 11, 2023, CDC discontinued utilizing the COVID electronic laboratory reporting (CELR) platform as the primary laboratory source of COVID-19 results. These data are archived at health.data.gov.

    For more information about NREVSS, please see: https://www.cdc.gov/surveillance/nrevss/index.html.

  • O

    COVID-19 cases, tests and positivity rate over time by zip code

    • data.sccgov.org
    • splitgraph.com
    csv, xlsx, xml
    Updated Jul 3, 2025
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    County of Santa Clara Public Health Department (2025). COVID-19 cases, tests and positivity rate over time by zip code [Dataset]. https://data.sccgov.org/widgets/hifm-rdvw
    Explore at:
    xml, xlsx, csvAvailable download formats
    Dataset updated
    Jul 3, 2025
    Dataset authored and provided by
    County of Santa Clara Public Health Department
    Description

    The dataset summarizes the number and rate of cases, tests and positivity at zip code level over time. Data are summarized as three-week time period.

    This dataset is updated every Thursday.

  • d

    COVID-19 Cases, Tests, and Deaths by ZIP Code - Historical

    • catalog.data.gov
    • data.cityofchicago.org
    • +3more
    Updated May 24, 2024
    + more versions
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    data.cityofchicago.org (2024). COVID-19 Cases, Tests, and Deaths by ZIP Code - Historical [Dataset]. https://catalog.data.gov/dataset/covid-19-cases-tests-and-deaths-by-zip-code
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    Dataset updated
    May 24, 2024
    Dataset provided by
    data.cityofchicago.org
    Description

    NOTE: This dataset has been retired and marked as historical-only. Only Chicago residents are included based on the home ZIP Code as provided by the medical provider. If a ZIP was missing or was not valid, it is displayed as "Unknown". Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted based on the week the test specimen was collected. For privacy reasons, until a ZIP Code reaches five cumulative cases, both the weekly and cumulative case counts will be blank. Therefore, summing the “Cases - Weekly” column is not a reliable way to determine case totals. Deaths are those that have occurred among cases based on the week of death. For tests, each test is counted once, based on the week the test specimen was collected. Tests performed prior to 3/1/2020 are not included. Test counts include multiple tests for the same person (a change made on 10/29/2020). PCR and antigen tests reported to Chicago Department of Public Health (CDPH) through electronic lab reporting are included. Electronic lab reporting has taken time to onboard and testing availability has shifted over time, so these counts are likely an underestimate of community infection. The “Percent Tested Positive” columns are calculated by dividing the number of positive tests by the number of total tests . Because of the data limitations for the Tests columns, such as persons being tested multiple times as a requirement for employment, these percentages may vary in either direction from the actual disease prevalence in the ZIP Code. All data are provisional and subject to change. Information is updated as additional details are received. To compare ZIP Codes to Chicago Community Areas, please see http://data.cmap.illinois.gov/opendata/uploads/CKAN/NONCENSUS/ADMINISTRATIVE_POLITICAL_BOUNDARIES/CCAzip.pdf. Both ZIP Codes and Community Areas are also geographic datasets on this data portal. Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, Illinois Vital Records, American Community Survey (2018)

  • d

    MD COVID-19 - Cases by County

    • catalog.data.gov
    • opendata.maryland.gov
    • +2more
    Updated Sep 27, 2025
    + more versions
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    opendata.maryland.gov (2025). MD COVID-19 - Cases by County [Dataset]. https://catalog.data.gov/dataset/md-covid-19-cases-by-county
    Explore at:
    Dataset updated
    Sep 27, 2025
    Dataset provided by
    opendata.maryland.gov
    Area covered
    Maryland
    Description

    Note: Starting April 27, 2023 updates change from daily to weekly. Summary The cumulative number of positive COVID-19 cases among Maryland residents within a single Maryland jurisdiction. Description The MD COVID-19 - Cases by County data layer is a collection of positive COVID-19 test results that have been reported each day by the local health department via the ESSENCE system. Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

  • 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
    + more versions
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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
    Explore at:
    rdf, csv, xsl, jsonAvailable 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

  • S

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

    • splitgraph.com
    Updated Jul 20, 2023
    + more versions
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    cdc-gov (2023). Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status [Dataset]. https://www.splitgraph.com/cdc-gov/rates-of-covid19-cases-or-deaths-by-age-group-and-3rge-nu2a
    Explore at:
    application/vnd.splitgraph.image, application/openapi+json, jsonAvailable download formats
    Dataset updated
    Jul 20, 2023
    Authors
    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

    Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

    See the Splitgraph documentation for more information.

  • G

    Covid positive rate around the world | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated May 18, 2021
    + more versions
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    Globalen LLC (2021). Covid positive rate around the world | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/rankings/covid_positive_rate/
    Explore at:
    csv, xml, excelAvailable download formats
    Dataset updated
    May 18, 2021
    Dataset authored and provided by
    Globalen LLC
    License

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

    Time period covered
    2025
    Area covered
    World
    Description

    Trends in Covid positive rate. The latest data for over 100 countries around the world.

  • d

    Johns Hopkins COVID-19 Case Tracker

    • data.world
    csv, zip
    Updated Oct 3, 2025
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    The Associated Press (2025). Johns Hopkins COVID-19 Case Tracker [Dataset]. https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker
    Explore at:
    zip, csvAvailable download formats
    Dataset updated
    Oct 3, 2025
    Authors
    The Associated Press
    Time period covered
    Jan 22, 2020 - Mar 9, 2023
    Area covered
    Description

    Updates

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

    • April 9, 2020

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

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

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

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

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

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

      Overview

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

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

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

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

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

    Queries

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

    Interactive

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

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

    Interactive Embed Code

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

    Caveats

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

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

    Attribution

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

  • C

    Allegheny County COVID-19 Tests, Cases and Deaths (Archive)

    • data.wprdc.org
    csv, html
    Updated Jun 13, 2024
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    Allegheny County (2024). Allegheny County COVID-19 Tests, Cases and Deaths (Archive) [Dataset]. https://data.wprdc.org/dataset/allegheny-county-covid-19-tests-cases-and-deaths
    Explore at:
    html, csv, csv(339166949), csv(277234), csv(34046863), csv(14904), csv(16109), csv(840)Available download formats
    Dataset updated
    Jun 13, 2024
    Dataset authored and provided by
    Allegheny County
    License

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

    Area covered
    Allegheny County
    Description

    COVID-19 Cases information is reported through the Pennsylvania State Department’s National Electronic Disease Surveillance System (PA-NEDSS). As new cases are passed to the Allegheny County Health Department they are investigated by case investigators. During investigation some cases which are initially determined by the State to be in the Allegheny County jurisdiction may change, which can account for differences between publication of the files on the number of cases, deaths and tests. Additionally, information is not always reported to the State in a timely manner, delays can range from days to weeks, which can also account for discrepancies between previous and current files. Test and Case information will be updated daily. This resource contains individuals who received a COVID-19 test and individuals whom are probable cases. Every day, these records are overwritten with updates. Each row in the data reflects a person that is tested, not tests that are conducted. People that are tested more than once will have their testing and case data updated using the following rules:

    1. Positive tests overwrite negative tests.
    2. Polymerase chain reaction (PCR) tests overwrite antibody or antigen (AG) tests.
    3. The first positive PCR test is never overwritten. Data collected from additional tests do not replace the first positive PCR test.

    Note: On April 4th 2022 the Pennsylvania Department of Health no longer required labs to report negative AG tests. Therefore aggregated counts that included AG tests have been removed from the Municipality/Neighborhood files going forward. Versions of this data up to this cut-off have been retained as archived files.

    Individual Test information is also updated daily. This resource contains the details and results of individual tests along with demographic information of the individual tested. Only PCR and AG tests are included. Every day, these records are overwritten with updates. This resource should be used to determine positivity rates.

    The remaining datasets provide statistics on death demographics. Demographic, municipality and neighborhood information for deaths are reported on a weekly schedule and are not included with individual cases or tests. This has been done to protect the privacy and security of individuals and their families in accordance with the Health Insurance Portability and Accountability Act (HIPAA). Municipality or City of Pittsburgh Neighborhood is based off the geocoded home address of the individual tested.

    Individuals whose home address is incomplete may not be in Allegheny County but whose temporary residency, work or other mitigating circumstance are determined to be in Allegheny County by the Pennsylvania Department of Health are counted as "Undefined".

    Since the start of the pandemic, the ACHD has mapped every day’s COVID tests, cases, and deaths to their Allegheny County municipality and neighborhood. Tests were mapped to patient address, and if this was not available, to the provider location. This has recently resulted in apparent testing rates that exceeded the populations of various municipalities -- mostly those with healthcare providers. As this was brought to our attention, the health department and our data partners began researching and comparing methods to most accurately display the data. This has led us to leave those with missing home addresses off the map. Although these data will still appear in test, case and death counts, there will be over 20,000 fewer tests and almost 1000 fewer cases on the map. In addition to these map changes, we have identified specific health systems and laboratories that had data uploading errors that resulted in missing locations, and are working with them to correct these errors.

    Due to minor discrepancies in the Municipal boundary and the City of Pittsburgh Neighborhood files individuals whose City Neighborhood cannot be identified are be counted as “Undefined (Pittsburgh)”.

    On May 19, 2023, with the rescinding of the COVID-19 public health emergency, changes in data and reporting mechanisms prompted a change to an annual data sharing schedule for tests, cases, hospitalizations, and deaths. Dates for annual release are TBD. The weekly municipal counts and individual data produced before this changed are maintained as archive files.

    Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

  • Share
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    opendata.maryland.gov (2025). MD COVID-19 - Testing Volume [Dataset]. https://catalog.data.gov/dataset/md-covid-19-testing-volume

    MD COVID-19 - Testing Volume

    Explore at:
    Dataset updated
    Jun 29, 2025
    Dataset provided by
    opendata.maryland.gov
    Area covered
    Maryland
    Description

    NOTE: This dataset is no longer being updated as of 4/27/2023. It is retired and no longer included in public COVID-19 data dissemination. See this link for more information https://imap.maryland.gov/pages/covid-data Summary The daily cumulative total of COVID-19 tests administered in Maryland and the average percent daily positive rate. Description Testing volume data represent the static daily total of PCR COVID-19 tests electronically reported for Maryland residents; this count does not include test results submitted by labs and other clinical facilities through non-electronic means. The percent positive rate is a seven-day rolling average of positive results as a percentage of all tests. Data are lectronic lab reports from NEDDSS. Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

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