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 the first reported coronavirus case in Washington State on Jan. 21, 2020, 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.

NOTE: This dataset is no longer updated as of 1/31/2024. Please use COVID-19 Treatments. Locations of publicly available COVID-19 Therapeutics. Dataset only includes locations for Paxlovid (oral antiviral), Lagevrio (oral antiviral), and outpatient Veklury (intravenous antiviral infusion). COVID-19 therapeutics require a prescription to obtain. Limitations: public contact information. To filter, click 'View Data' below, then 'Filter.' To save your view, click 'Save as,' and this configuration will be saved in your profile under 'My Assets.' Please try not to publish dataset publicly, unless necessary. On 1/3/2022 - The following changes were made to this dataset. - Dropped the Expected Deliver Date column - This was a derived field set to 3 days after the Last Order Date field. - Added the following fields Last Date Delivered Total Courses Courses Available Courses Available Date On 1/4/2022 - Added Geocoded Address On 1/11/2022 - Added NPI - National Provider Identifier On 2/18/2022 - Added new therapeutics, Bebtelovimab & Sotrovimab. On 3/16/2022 - Dropped the following columns - last_order_date - last_date_delivered - total_courses - courses_available_date Added the following columns - facility_id - last_report_date - grantee_code - provider_pin - state_provider_pin On 3/31/2022 - Dropped the following columns - facility_id - grantee_code - provider_pin - state_provider_pin Added the following columns - provider_status - provider_note

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.

  • CDC Weekly case and death counts (national and state level)
  • CDC County level cases and deaths
  • HHS New hospital admissions
  • CDC NowCast COVID variant proportions (national and regional level)

• 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

• Filter cases by state here

• Rank states by their status as current hotspots. Calculates the 7-day rolling average of new cases per capita in each state: https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker/workspace/query?queryid=481e82a4-1b2f-41c2-9ea1-d91aa4b3b1ac

• Find recent hotspots within your state by running a query to calculate the 7-day rolling average of new cases by capita in each county: https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker/workspace/query?queryid=b566f1db-3231-40fe-8099-311909b7b687&showTemplatePreview=true

• Join county-level case data to an earlier dataset released by AP on local hospital capacity here. To find out more about the hospital capacity dataset, see the full details.

• Pull the 100 counties with the highest per-capita confirmed cases here

• Rank all the counties by the highest per-capita rate of new cases in the past 7 days here. Be aware that because this ranks per-capita caseloads, very small counties may rise to the very top, so take into account raw caseload figures as well.

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

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.

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.

With the federal COVID-19 Public Health Emergency ending on May 11th, the Montana Department of Health & Human Services will discontinue weekly updates to the COVID-19 case tracking and vaccine map dashboards and feature services. The last weekly update to the dashboards will take place on May 5th, 2023. After this final data update, the dashboards will remain available to viewers until July 14th, 2023. However, it should be noted that data will not be current after May 5th, 2023.To access up-to-date COVID-19 data for Montana after 5/11/2023, visit the CDC’s COVID Data Tracker website: https://covid.cdc.gov/covid-data-trackerA story map depicting crucial global, national, and state information resources for the COVID 19 - Coronavirus outbreak. Listed below is a description for each tab included in the story map.

COVID-19 Community Levels and Cases - Dashboard featuring Montana CDC.gov Community Level data, cumulative & active COVID-19 cases in Montana and COVID-19 hospitalization / ICU data.COVID-19 Vaccine - Dashboard featuring total doses administered and total Montanans fully immunized against COVID-19 for the State of Montana and by Montana county. Local Vaccine Contacts - Tab directing users to CDC's Vaccines.gov - Find COVID‑19 vaccine locations near youCOVID-19 Demographics - Tab showing Montana Department of Health & Human Service's Coronavirus Disease 2019 (COVID-19) webpage. GIS Data Hub - Tab showing the Montana State Library COVID-19 GIS Data Hub. The ArcGIS Hub serves as an open data platform that allows users to view, query, and download Montana COVID-19 case and vaccination data.

NOTE: As of 12/17/2024, this dataset is no longer updated. Please use ASPR Treatments Locator. This dataset displays pharmacies, clinics, and other locations with safe and effective COVID-19 medications. These medications require a prescription from a healthcare provider. Some locations, known as Test to Treat sites, give you the option to get tested, get assessed by a healthcare provider, and receive treatment – all in one visit. COVID-19 medications may be available at additional locations that are not shown in this dataset. The locations displayed have either self-attested they have inventory of Paxlovid (nirmatrelvir packaged with ritonavir), Lagevrio (molnupiravir), or Veklury (Remdesivir) within at least the last two months and/or reported participation in the Paxlovid Patient Assistance Program. Sites that have not reported in the last two weeks display a notification, "Inventory has not been reported in the last 2 weeks. Please contact the provider to make sure the product is available." Outpatient COVID-19 medications may be available at additional locations not listed on this website. All therapeutics identified in the locator not approved by the FDA must be used in alignment with the terms of the respective product’s Emergency Use Authorization. Visit COVID-19 Treatments and Therapeutics for more information on all treatment options. This website identifies sites that have commercially purchased inventory of COVID-19 treatments and, in some cases, may identify sites that have remaining, no-cost U.S. government distributed supply. Some sites may charge for services not covered by insurance. Some sites may offer telehealth services. This website is intended for informational purposes only and does not serve as an endorsement or recommendation for use of any of the locations listed on the sites. Clarification for DoD Facilities: Those individuals eligible for care in an MTF include Active Duty Service Members (ADSMs), covered beneficiaries enrolled in TRICARE Prime or Select, including TRICARE Reserve Select (TRS), TRICARE Retired Reserve (TRR) and TRICARE Young Adult (TYA) participants, TRICARE for Life beneficiaries, and individuals otherwise entitled by law to MTF care (e.g., regular retired members and their dependents who are not enrolled in TRICARE but who are otherwise eligible for MTF space-available care, certain foreign military members and their families registered in DEERS, and others).

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

This dataset represents preliminary estimates of cumulative U.S. COVID-19 disease burden for the 2024-2025 period, including illnesses, outpatient visits, hospitalizations, and deaths. The weekly COVID-19-associated burden estimates are preliminary and based on continuously collected surveillance data from patients hospitalized with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. The data come from the Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET), a surveillance platform that captures data from hospitals that serve about 10% of the U.S. population. Each week CDC estimates a range (i.e., lower estimate and an upper estimate) of COVID-19 -associated burden that have occurred since October 1, 2024.

Note: Data are preliminary and subject to change as more data become available. Rates for recent COVID-19-associated hospital admissions are subject to reporting delays; as new data are received each week, previous rates are updated accordingly.

References

1. Reed C, Chaves SS, Daily Kirley P, et al. Estimating influenza disease burden from population-based surveillance data in the United States. PLoS One. 2015;10(3):e0118369. https://doi.org/10.1371/journal.pone.0118369 
2. Rolfes, MA, Foppa, IM, Garg, S, et al. Annual estimates of the burden of seasonal influenza in the United States: A tool for strengthening influenza surveillance and preparedness. Influenza Other Respi Viruses. 2018; 12: 132– 137. https://doi.org/10.1111/irv.12486
3. Tokars JI, Rolfes MA, Foppa IM, Reed C. An evaluation and update of methods for estimating the number of influenza cases averted by vaccination in the United States. Vaccine. 2018;36(48):7331-7337. doi:10.1016/j.vaccine.2018.10.026 
4. Collier SA, Deng L, Adam EA, Benedict KM, Beshearse EM, Blackstock AJ, Bruce BB, Derado G, Edens C, Fullerton KE, Gargano JW, Geissler AL, Hall AJ, Havelaar AH, Hill VR, Hoekstra RM, Reddy SC, Scallan E, Stokes EK, Yoder JS, Beach MJ. Estimate of Burden and Direct Healthcare Cost of Infectious Waterborne Disease in the United States. Emerg Infect Dis. 2021 Jan;27(1):140-149. doi: 10.3201/eid2701.190676. PMID: 33350905; PMCID: PMC7774540.
5. Reed C, Kim IK, Singleton JA,  et al. Estimated influenza illnesses and hospitalizations averted by vaccination–United States, 2013-14 influenza season. MMWR Morb Mortal Wkly Rep. 2014 Dec 12;63(49):1151-4. https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6349a2.htm 
6. Reed C, Angulo FJ, Swerdlow DL, et al. Estimates of the Prevalence of Pandemic (H1N1) 2009, United States, April–July 2009. Emerg Infect Dis. 2009;15(12):2004-2007. https://dx.doi.org/10.3201/eid1512.091413  
7. Devine O, Pham H, Gunnels B, et al. Extrapolating Sentinel Surveillance Information to Estimate National COVID-19 Hospital Admission Rates: A Bayesian Modeling Approach. Influenza and Other Respiratory Viruses. https://onlinelibrary.wiley.com/doi/10.1111/irv.70026. Volume18, Issue10. October 2024.
8. https://www.cdc.gov/covid/php/covid-net/index.html">COVID-NET | COVID-19 | CDC 
9. https://www.cdc.gov/covid/hcp/clinical-care/systematic-review-process.html 
10. https://academic.oup.com/pnasnexus/article/1/3/pgac079/6604394?login=false">Excess natural-cause deaths in California by cause and setting: March 2020 through February 2021 | PNAS Nexus | Oxford Academic (oup.com)
11. Kruschke, J. K. 2011. Doing Bayesian data analysis: a tutorial with R and BUGS. Elsevier, Amsterdam, Section 3.3.5.

This view is a copy of the original COVID-19 Testing Locations in the United States - public dataset (https://giscorps.maps.arcgis.com/home/item.html?id=d7d10caf1cec43e0985cc90fbbcf91cb). The parent hosted feature service is the same. This version is symbolized by site status.This feature layer view contains information about COVID-19 screening and testing locations. It is made available to the public using the GISCorps COVID-19 Testing Site Locator app (https://giscorps.maps.arcgis.com/apps/webappviewer/index.html?id=2ec47819f57c40598a4eaf45bf9e0d16) and on findcovidtesting.com. States and counties are encouraged to include this feature service in their own testing site locator apps as well.Please submit new testing sites or updated testing site information via this form: https://arcg.is/10S1ib. Including this link on your organization's testing site finder web app will allow testing providers to add their own sites directly to the map, improving the accuracy and completeness of the dataset. GISCorps volunteers verify each submission prior to including it in this public view. You can also add your sites in bulk by completing a copy of this template and emailing it to admin@giscorps.org. This dataset is updated daily. All information is sourced from public information shared by health departments, local governments, and healthcare providers. The data are aggregated by GISCorps volunteers in collaboration with volunteers from Coders Against COVID and should not be considered complete or authoritative. Please contact testing sites or your local health department directly for official information and testing requirements.The objective of this application is to aggregate and facilitate the public communications of local governments, health departments, and healthcare providers with regard to testing site locations. GISCorps does not share any screening or testing site location information not previously made public or provided to us by one of those entities.Latest Arcade code for popups available here: https://docs.google.com/document/d/1PDOq-CxUX9fuC2v3N8muuuxN5mLMinWdf7fiwUt1lOM/edit?usp=sharing

Note: This dataset has been archived and is no longer being updated.

COVID Alert CT is Connecticut's voluntary, anonymous, exposure-notification smartphone app. If downloaded, the app will alert users if they have come into close contact with somebody who tests positive for COVID-19.

This dataset includes the cumulative and weekly activations for COVID Alert CT for iOS and Android smartphones.

The location of app users is not tracked--the app uses Bluetooth technology to detect when another person with the same app comes within 6 feet. The phones exchange a secure code with the each other to record that they were near. The number of codes issued and claimed is also included in this dataset.

Data presented are based on a weekly reporting period (Sunday - Saturday). All data are preliminary and are subject to change.

Additional information on COVID-19 Contact Tracing can be found here: https://portal.ct.gov/coronavirus/covidalertCT/homepage

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.

Read about this volunteer-driven effort, access data and apps, and contribute your own testing site data:https://covid-19-giscorps.hub.arcgis.com/pages/contribute-covid-19-testing-sites-dataItem details page:https://giscorps.maps.arcgis.com/home/item.html?id=d7d10caf1cec43e0985cc90fbbcf91cbThis view is the originalCOVID-19 Testing Locations in the United States - public dataset. A backup copy also exists:https://giscorps.maps.arcgis.com/home/item.html?id=11fe8f374c344549815a716c8472832f. The parent hosted feature service is the same.This version is symbolized by type of test (molecular, antibody, antigen, or combinations thereof).This feature layer view contains information about COVID-19 screening and testing locations. It is made available to the public using the GISCorps COVID-19 Testing Site Locator app (https://giscorps.maps.arcgis.com/apps/webappviewer/index.html?id=2ec47819f57c40598a4eaf45bf9e0d16) and onfindcovidtesting.com. States and counties are encouraged to include this feature service in their own testing site locator apps as well.Please submit new testing sites or updated testing site information via this form:https://arcg.is/10S1ib. Including this link on your organization's testing site finder web app will allow testing providers to add their own sites directly to the map, improving the accuracy and completeness of the dataset.GISCorps volunteers verify each submission prior to including it in this public view. You can also add your sites in bulk by completing a copy ofthis templateand emailing it to admin@giscorps.org.This dataset is updated daily. All information is sourced from public information shared by health departments, local governments, and healthcare providers. The data are aggregated byGISCorps volunteers in collaboration with volunteers from Coders Against COVID and should not be considered complete or authoritative. Please contact testing sites or your local health department directly for official information and testing requirements.The objective of this application is to aggregate and facilitate the public communications of local governments, health departments, and healthcare providers with regard to testing site locations. GISCorps does not share any screening or testing site location information not previously made public or provided to us by one of those entities.Data dictionary document:https://docs.google.com/document/d/1HlFmtsT3GzibixPR_QJiGqGOuia9r-exN3i5UK8c6h4/edit?usp=sharingArcade code for popups:https://docs.google.com/document/d/1PDOq-CxUX9fuC2v3N8muuuxN5mLMinWdf7fiwUt1lOM/edit?usp=sharing

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.

Count of COVID-19-associated deaths by date of death. Deaths reported to either the OCME or DPH are included in the COVID-19 data. COVID-19-associated deaths include persons who tested positive for COVID-19 around the time of death and persons who were not tested for COVID-19 whose death certificate lists COVID-19 disease as a cause of death or a significant condition contributing to death.

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

Note the counts in this dataset may vary from the death counts in the other COVID-19-related datasets published on data.ct.gov, where deaths are counted on the date reported rather than the date of death.

Starting in July 2020, this dataset will be updated every weekday. Data are subject to future revision as reporting changes.

Context

These datasets are from Our World in Data. Their complete COVID-19 dataset is a collection of the COVID-19 data maintained by Our World in Data. It is updated daily and includes data on confirmed cases, deaths, hospitalizations, testing, and vaccinations as well as other variables of potential interest.

Content

Confirmed cases and deaths:

our data comes from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). We discuss how and when JHU collects and publishes this data. The cases & deaths dataset is updated daily. Note: the number of cases or deaths reported by any institution—including JHU, the WHO, the ECDC, and others—on a given day does not necessarily represent the actual number on that date. This is because of the long reporting chain that exists between a new case/death and its inclusion in statistics. This also means that negative values in cases and deaths can sometimes appear when a country corrects historical data because it had previously overestimated the number of cases/deaths. Alternatively, large changes can sometimes (although rarely) be made to a country's entire time series if JHU decides (and has access to the necessary data) to correct values retrospectively.

Hospitalizations and intensive care unit (ICU) admissions:

our data comes from the European Centre for Disease Prevention and Control (ECDC) for a select number of European countries; the government of the United Kingdom; the Department of Health & Human Services for the United States; the COVID-19 Tracker for Canada. Unfortunately, we are unable to provide data on hospitalizations for other countries: there is currently no global, aggregated database on COVID-19 hospitalization, and our team at Our World in Data does not have the capacity to build such a dataset.

Testing for COVID-19:

this data is collected by the Our World in Data team from official reports; you can find further details in our post on COVID-19 testing, including our checklist of questions to understand testing data, information on geographical and temporal coverage, and detailed country-by-country source information. The testing dataset is updated around twice a week.

Acknowledgements

Our World in Data GitHub repository for covid-19.

Inspiration

All we love data, cause we love to go inside it and discover the truth that's the main inspiration I have.

Note: Starting October 10th, 2025 this dataset is deprecated and is no longer being updated. As of April 27, 2023 updates changed 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.

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)

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

Context

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most people infected with COVID-19 virus will experience mild to moderate respiratory illness and recover without requiring special treatment. Older people, and those with underlying medical problems like cardiovascular disease, diabetes, chronic respiratory disease, and cancer are more likely to develop serious illness. During the entire course of the pandemic, one of the main problems that healthcare providers have faced is the shortage of medical resources and a proper plan to efficiently distribute them. In these tough times, being able to predict what kind of resource an individual might require at the time of being tested positive or even before that will be of immense help to the authorities as they would be able to procure and arrange for the resources necessary to save the life of that patient.

The main goal of this project is to build a machine learning model that, given a Covid-19 patient's current symptom, status, and medical history, will predict whether the patient is in high risk or not.

content

The dataset was provided by the Mexican government (link). This dataset contains an enormous number of anonymized patient-related information including pre-conditions. The raw dataset consists of 21 unique features and 1,048,576 unique patients. In the Boolean features, 1 means "yes" and 2 means "no". values as 97 and 99 are missing data.

• sex: 1 for female and 2 for male.
• age: of the patient.
• classification: covid test findings. Values 1-3 mean that the patient was diagnosed with covid in different degrees. 4 or higher means that the patient is not a carrier of covid or that the test is inconclusive.
• patient type: type of care the patient received in the unit. 1 for returned home and 2 for hospitalization.
• pneumonia: whether the patient already have air sacs inflammation or not.
• pregnancy: whether the patient is pregnant or not.
• diabetes: whether the patient has diabetes or not.
• copd: Indicates whether the patient has Chronic obstructive pulmonary disease or not.
• asthma: whether the patient has asthma or not.
• inmsupr: whether the patient is immunosuppressed or not.
• hypertension: whether the patient has hypertension or not.
• cardiovascular: whether the patient has heart or blood vessels related disease.
• renal chronic: whether the patient has chronic renal disease or not.
• other disease: whether the patient has other disease or not.
• obesity: whether the patient is obese or not.
• tobacco: whether the patient is a tobacco user.
• usmr: Indicates whether the patient treated medical units of the first, second or third level.
• medical unit: type of institution of the National Health System that provided the care.
• intubed: whether the patient was connected to the ventilator.
• icu: Indicates whether the patient had been admitted to an Intensive Care Unit.
• date died: If the patient died indicate the date of death, and 9999-99-99 otherwise.

This dashboard displays reported Maine COVID-19 confirmed positive cases, recovered cases, and deaths throughout the state at the county level. The dashboard is updated daily with data compiled from the Maine CDC Novel Coronavirus 2019 (COVID-19) status web page: https://www.maine.gov/dhhs/mecdc/infectious-disease/epi/airborne/coronavirus.shtml.

Summary This layer has been DEPRECATED. (last updated 12/1/2021). Was formerly a weekly update.

The Outbreak-Associated Cases in Congregate Living data dashboard on coronavirus.maryland.gov was redesigned on 11/17/21 to align with other outbreak reporting. Visit https://opendata.maryland.gov/dataset/MD-COVID-19-Congregate-Outbreak/ey5n-qn5s to view Outbreak-Associated Cases in Congregate Living data as reported after 11/17/21.

Confirmed COVID-19 cases among Maryland residents who live and work in congregate living facilities in Maryland for the reporting period.

Description The MD COVID-19 - Total Cases in Congregate Facility Settings data layer is a total of positive COVID-19 test results have been reported to MDH in nursing homes, assisted living facilities, group homes of 10 or more and state and local facilities for the reporting period. Data are reported to MDH by local health departments, the Department of Public Safety and Correctional Services and the Department of Juvenile Services. To appear on the list, facilities report at least one confirmed case of COVID-19 over the prior 14 days. Facilities are removed from the list when health officials determine 14 days have passed with no new cases and no tests pending. The list provides a point-in-time picture of COVID-19 case activity among these facilities. Numbers reported for each facility listed reflect totals ever reported for cases. Data are updated once weekly.

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.