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

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.

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

The surveillance case definition for COVID-19, a nationally notifiable disease, was first described in a position statement from the Council for State and Territorial Epidemiologists, which was later revised. However, there is some variation in how jurisdictions implemented these case definitions. More information on how CDC collects COVID-19 case surveillance data can be found at FAQ: COVID-19 Data and Surveillance.

Aggregate Data Collection Process Since the beginning of the COVID-19 pandemic, data were reported from state and local health departments through a robust process with the following steps:

• Aggregate county-level counts were obtained indirectly, via automated overnight web collection, or directly, via a data submission process.
• If more than one official county data source existed, CDC used a comprehensive data selection process comparing each official county data source to retrieve the highest case and death counts, unless otherwise specified by the state.
• A CDC data team reviewed counts for congruency prior to integration and set up alerts to monitor for discrepancies in the data.
• CDC routinely compiled these data and post the finalized information on COVID Data Tracker.
• County level data were aggregated to obtain state- and territory- specific totals.
• Counting of cases and deaths is based on date of report and not on the date of symptom onset. CDC calculates rates in these data by using population estimates provided by the US Census Bureau Population Estimates Program (2019 Vintage).
• COVID-19 aggregate case and death data are organized in a time series that includes cumulative number of cases and deaths as reported by a jurisdiction on a given date. New case and death counts are calculated as the week-to-week change in cumulative counts of cases and deaths reported (i.e., newly reported cases and deaths = cumulative number of cases/deaths reported this week minus the cumulative total reported the prior week.

This process was collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provided the most up-to-date numbers on cases and deaths by report date. Throughout data collection, CDC retrospectively updated counts to correct known data quality issues.

Description This archived public use dataset focuses on the cumulative and weekly case and death rates per 100,000 persons within various sociodemographic factors across all states and their counties. All resulting data are expressed as rates calculated as the number of cases or deaths per 100,000 persons in counties meeting various classification criteria using the US Census Bureau Population Estimates Program (2019 Vintage).

Each county within jurisdictions is classified into multiple categories for each factor. All rates in this dataset are based on classification of counties by the characteristics of their population, not individual-level factors. This applies to each of the available factors observed in this dataset. Specific factors and their corresponding categories are detailed below.

Population-level factors Each unique population factor is detailed below. Please note that the “Classification” column describes each of the 12 factors in the dataset, including a data dict

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

On October 20, 2022, CDC began retrieving aggregate case and death data from jurisdictional and state partners weekly instead of daily. This dataset contains archived community transmission and related data elements by county as originally displayed on the COVID Data Tracker. Although these data will continue to be publicly available, this dataset has not been updated since October 20, 2022. An archived dataset containing weekly community transmission data by county as originally posted can also be found here: Weekly COVID-19 County Level of Community Transmission as Originally Posted | Data | Centers for Disease Control and Prevention (cdc.gov).

Related data CDC has been providing the public with two versions of COVID-19 county-level community transmission level data: this dataset with the daily values as originally posted on the COVID Data Tracker, and an historical dataset with daily data as well as the updates and corrections from state and local health departments. Similar to this dataset, the original historical dataset is archived on 10/20/2022. It will continue to be publicly available but will no longer be updated. A new dataset containing historical community transmission data by county is now published weekly and can be found at: Weekly COVID-19 County Level of Community Transmission Historical Changes | Data | Centers for Disease Control and Prevention (cdc.gov).

This public use dataset has 7 data elements reflecting community transmission levels for all available counties and jurisdictions. It contains reported daily transmission levels at the county level with the same values used to display transmission maps on the COVID Data Tracker. Each day, the dataset is appended to contain the most recent day's data. Transmission level is set to low, moderate, substantial, or high using the calculation rules below.

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

CDC core metrics of and thresholds for community transmission levels of SARS-CoV-2

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

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

If

Note: The cumulative case count for some counties (with small population) is higher than expected due to the inclusion of non-permanent residents in COVID-19 case counts.

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

Aggregate Data Collection Process Since the beginning of the COVID-19 pandemic, data were reported through a robust process with the following steps:

• Aggregate county-level counts were obtained indirectly, via automated overnight web collection, or directly, via a data submission process.
• If more than one official county data source existed, CDC used a comprehensive data selection process comparing each official county data source to retrieve the highest case and death counts, unless otherwise specified by the state.
• A CDC data team reviewed counts for congruency prior to integration. CDC routinely compiled these data and post the finalized information on COVID Data Tracker.
• Cases and deaths are based on date of report and not on the date of symptom onset. CDC calculates rates in this data by using population estimates provided by the US Census Bureau Population Estimates Program (2019 Vintage).
• COVID-19 aggregate case and death data were organized in a time series that includes cumulative number of cases and deaths as reported by a jurisdiction on a given date. New case and death counts were calculated as the week-to-week change in reported cumulative cases and deaths (i.e., newly reported cases and deaths = cumulative number of cases/deaths reported this week minus the cumulative total reported the week before.

This process was collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provided the most up-to-date numbers on cases and deaths by report date. Throughout data collection, CDC retrospectively updated counts to correct known data quality issues. CDC also worked with jurisdictions after the end of the public health emergency declaration to finalize county data.

• Source: The weekly archived dataset is based on county-level aggregate count data
• Confirmed/Probable Cases/Death breakdown: Cumulative cases and deaths for each county are included. Total reported cases include probable and confirmed cases.
• Time Series Frequency: The weekly archived dataset contains weekly time series data (i.e., one record per week per county)

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 daily archived dataset noted above. Discrepancies may exist due to differences between county and state COVID-19 case surveillance and reconciliation efforts.

The surveillance case definition for COVID-19, a nationally notifiable disease, was first described in a position statement from the Council for State and Territorial Epidemiologists, which was later revised. However, there is some variation in how jurisdictions implement these case classifications. More information on how CDC collects COVID-19 case surveillance data can be found at FAQ: COVID-19 Data and Surveillance.

Confirmed and Probable Counts In this dataset, counts by jurisdiction are not displayed by confirmed or probable status. Instead, counts of confirmed and probable cases and deaths are included in the Total Cases and Total Deaths columns, when available. Not all jurisdictions report

Note: This COVID-19 data set is no longer being updated as of December 1, 2023. Access current COVID-19 data on the CDPH respiratory virus dashboard (https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Respiratory-Viruses/RespiratoryDashboard.aspx) or in open data format (https://data.chhs.ca.gov/dataset/respiratory-virus-dashboard-metrics).

As of August 17, 2023, data is being updated each Friday.

For death data after December 31, 2022, California uses Provisional Deaths from the Center for Disease Control and Prevention’s National Center for Health Statistics (NCHS) National Vital Statistics System (NVSS). Prior to January 1, 2023, death data was sourced from the COVID-19 registry. The change in data source occurred in July 2023 and was applied retroactively to all 2023 data to provide a consistent source of death data for the year of 2023.

As of May 11, 2023, data on cases, deaths, and testing is being updated each Thursday. Metrics by report date have been removed, but previous versions of files with report date metrics are archived below.

All metrics include people in state and federal prisons, US Immigration and Customs Enforcement facilities, US Marshal detention facilities, and Department of State Hospitals facilities. Members of California's tribal communities are also included.

The "Total Tests" and "Positive Tests" columns show totals based on the collection date. There is a lag between when a specimen is collected and when it is reported in this dataset. As a result, the most recent dates on the table will temporarily show NONE in the "Total Tests" and "Positive Tests" columns. This should not be interpreted as no tests being conducted on these dates. Instead, these values will be updated with the number of tests conducted as data is received.

Copyright 2020 by The New York Times Company

Coronavirus (Covid-19) Data in the United States

[ U.S. Data (Raw CSV) | U.S. State-Level Data (Raw CSV) | U.S. County-Level Data (Raw CSV) ]

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.

United States Data Data on cumulative coronavirus cases and deaths can be found in three files, one for each of these geographic levels: U.S., states and counties.

Each row of data reports cumulative counts based on our best reporting up to the moment we publish an update. We do our best to revise earlier entries in the data when we receive new information. If a county is not listed for a date, then there were zero reported confirmed cases and deaths.

State and county files contain FIPS codes, a standard geographic identifier, to make it easier for an analyst to combine this data with other data sets like a map file or population data.

Download all the data or clone this repository by clicking the green "Clone or download" button above.

U.S. National-Level Data The daily number of cases and deaths nationwide, including states, U.S. territories and the District of Columbia, can be found in the us.csv file. (Raw CSV file here.)

date,cases,deaths 2020-01-21,1,0 ... State-Level Data State-level data can be found in the states.csv file. (Raw CSV file here.)

date,state,fips,cases,deaths 2020-01-21,Washington,53,1,0 ... County-Level Data County-level data can be found in the counties.csv file. (Raw CSV file here.)

date,county,state,fips,cases,deaths 2020-01-21,Snohomish,Washington,53061,1,0 ... In some cases, the geographies where cases are reported do not map to standard county boundaries. See the list of geographic exceptions for more detail on these.

Methodology and Definitions The data is the product of dozens of journalists working across several time zones to monitor news conferences, analyze data releases and seek clarification from public officials on how they categorize cases.

It is also a response to a fragmented American public health system in which overwhelmed public servants at the state, county and territorial level have sometimes struggled to report information accurately, consistently and speedily. On several occasions, officials have corrected information hours or days after first reporting it. At times, cases have disappeared from a local government database, or officials have moved a patient first identified in one state or county to another, often with no explanation. In those instances, which have become more common as the number of cases has grown, our team has made every effort to update the data to reflect the most current, accurate information while ensuring that every known case is counted.

When the information is available, we count patients where they are being treated, not necessarily where they live.

In most instances, the process of recording cases has been straightforward. But because of the patchwork of reporting methods for this data across more than 50 state and territorial governments and hundreds of local health departments, our journalists sometimes had to make difficult interpretations about how to count and record cases.

For those reasons, our data will in some cases not exactly match with the information reported by states and counties. Those differences include these cases: When the federal government arranged flights to the United States for Americans exposed to the coronavirus in China and Japan, our team recorded those cases in the states where the patients subsequently were treated, even though local health departments generally did not. When a resident of Florida died in Los Angeles, we recorded her death as having occurred in California rather than Florida, though officials in Florida counted her case in their own records. And when officials in some states reported new cases without immediately identifying where the patients were being treated, we attempted to add informati...

Note: This dataset is no longer being updated as of June 2, 2025.

This dataset contains numbers of COVID-19 outbreaks and associated cases, categorized by setting, reported to CDPH since January 1, 2021.

AB 685 (Chapter 84, Statutes of 2020) and the Cal/OSHA COVID-19 Emergency Temporary Standards (Title 8, Subchapter 7, Sections 3205-3205.4) required non-healthcare employers in California to report workplace COVID-19 outbreaks to their local health department (LHD) between January 1, 2021 – December 31, 2022. Beginning January 1, 2023, non-healthcare employer reporting of COVID-19 outbreaks to local health departments is voluntary, unless a local order is in place. More recent data collected without mandated reporting may therefore be less representative of all outbreaks that have occurred, compared to earlier data collected during mandated reporting. Licensed health facilities continue to be mandated to report outbreaks to LHDs.

LHDs report confirmed outbreaks to the California Department of Public Health (CDPH) via the California Reportable Disease Information Exchange (CalREDIE), the California Connected (CalCONNECT) system, or other established processes. Data are compiled and categorized by setting by CDPH. Settings are categorized by U.S. Census industry codes. Total outbreaks and cases are included for individual industries as well as for broader industrial sectors.

The first dataset includes numbers of outbreaks in each setting by month of onset, for outbreaks reported to CDPH since January 1, 2021. This dataset includes some outbreaks with onset prior to January 1 that were reported to CDPH after January 1; these outbreaks are denoted with month of onset “Before Jan 2021.” The second dataset includes cumulative numbers of COVID-19 outbreaks with onset after January 1, 2021, categorized by setting. Due to reporting delays, the reported numbers may not reflect all outbreaks that have occurred as of the reporting date; additional outbreaks may have occurred that have not yet been reported to CDPH.

While many of these settings are workplaces, cases may have occurred among workers, other community members who visited the setting, or both. Accordingly, these data do not distinguish between outbreaks involving only workers, outbreaks involving only residents or patrons, or outbreaks involving both.

Several additional data limitations should be kept in mind:

• Outbreaks are classified as “Insufficient information” for outbreaks where not enough information was available for CDPH to assign an industry code.

• Some sectors, particularly congregate residential settings, may have increased testing and therefore increased likelihood of outbreak recognition and reporting. As a result, in congregate residential settings, the number of outbreak-associated cases may be more accurate.

• However, in most settings, outbreak and case counts are likely underestimates. For most cases, it is not possible to identify the source of exposure, as many cases have multiple possible exposures.

• Because some settings have been at times been closed or open with capacity restrictions, numbers of outbreak reports in those settings do not reflect COVID-19 transmission risk.

• The number of outbreaks in different settings will depend on the number of different workplaces in each setting. More outbreaks would be expected in settings with many workplaces compared to settings with few workplaces.

The Public Health Emergency (PHE) declaration for COVID-19 expired on May 11, 2023. As a result, the Aggregate Case and Death Surveillance System will be discontinued. Although these data will continue to be publicly available, this dataset will no longer be updated.

On October 20, 2022, CDC began retrieving aggregate case and death data from jurisdictional and state partners weekly instead of daily.

This dataset includes the URLs that were used by the aggregate county data collection process that compiled aggregate case and death counts by county. Within this file, each of the states (plus select jurisdictions and territories) are listed along with the county web sources which were used for pulling these numbers. Some states had a single statewide source for collecting the county data, while other states and local health jurisdictions may have had standalone sources for individual counties. In the cases where both local and state web sources were listed, a composite approach was taken so that the maximum value reported for a location from either source was used. The initial raw data were sourced from these links and ingested into the CDC aggregate county dataset before being published on the COVID Data Tracker.

Coronavirus (COVID-19) Data in the United States

[ U.S. State-Level Data (Raw CSV) | U.S. County-Level Data (Raw CSV) ]

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.

United States Data

Data on cumulative coronavirus cases and deaths can be found in two files for states and counties.

Each row of data reports cumulative counts based on our best reporting up to the moment we publish an update. We do our best to revise earlier entries in the data when we receive new information.

Both files contain FIPS codes, a standard geographic identifier, to make it easier for an analyst to combine this data with other data sets like a map file or population data.

Download all the data or clone this repository by clicking the green "Clone or download" button above.

State-Level Data

State-level data can be found in the states.csv file. (Raw CSV file here.)

date,state,fips,cases,deaths
2020-01-21,Washington,53,1,0
...

County-Level Data

County-level data can be found in the counties.csv file. (Raw CSV file here.)

date,county,state,fips,cases,deaths
2020-01-21,Snohomish,Washington,53061,1,0
...

In some cases, the geographies where cases are reported do not map to standard county boundaries. See the list of geographic exceptions for more detail on these.

Methodology and Definitions

The data is the product of dozens of journalists working across several time zones to monitor news conferences, analyze data releases and seek clarification from public officials on how they categorize cases.

It is also a response to a fragmented American public health system in which overwhelmed public servants at the state, county and territorial levels have sometimes struggled to report information accurately, consistently and speedily. On several occasions, officials have corrected information hours or days after first reporting it. At times, cases have disappeared from a local government database, or officials have moved a patient first identified in one state or county to another, often with no explanation. In those instances, which have become more common as the number of cases has grown, our team has made every effort to update the data to reflect the most current, accurate information while ensuring that every known case is counted.

When the information is available, we count patients where they are being treated, not necessarily where they live.

In most instances, the process of recording cases has been straightforward. But because of the patchwork of reporting methods for this data across more than 50 state and territorial governments and hundreds of local health departments, our journalists sometimes had to make difficult interpretations about how to count and record cases.

For those reasons, our data will in some cases not exactly match the information reported by states and counties. Those differences include these cases: When the federal government arranged flights to the United States for Americans exposed to the coronavirus in China and Japan, our team recorded those cases in the states where the patients subsequently were treated, even though local health departments generally did not. When a resident of Florida died in Los Angeles, we recorded her death as having occurred in California rather than Florida, though officials in Florida counted her case in their records. And when officials in some states reported new cases without immediately identifying where the patients were being treated, we attempted to add information about their locations later, once it became available.

• Confirmed Cases

Confirmed cases are patients who test positive for the coronavirus. We consider a case confirmed when it is reported by a federal, state, territorial or local government agency.

• Dates

For each date, we show the cumulative number of confirmed cases and deaths as reported that day in that county or state. All cases and deaths are counted on the date they are first announced.

• Counties

In some instances, we report data from multiple counties or other non-county geographies as a single county. For instance, we report a single value for New York City, comprising the cases for New York, Kings, Queens, Bronx and Richmond Counties. In these instances, the FIPS code field will be empty. (We may assign FIPS codes to these geographies in the future.) See the list of geographic exceptions.

Cities like St. Louis and Baltimore that are administered separately from an adjacent county of the same name are counted separately.

• “Unknown” Counties

Many state health departments choose to report cases separately when the patient’s county of residence is unknown or pending determination. In these instances, we record the county name as “Unknown.” As more information about these cases becomes available, the cumulative number of cases in “Unknown” counties may fluctuate.

Sometimes, cases are first reported in one county and then moved to another county. As a result, the cumulative number of cases may change for a given county.

Geographic Exceptions

• New York City

All cases for the five boroughs of New York City (New York, Kings, Queens, Bronx and Richmond counties) are assigned to a single area called New York City.

• Kansas City, Mo.

Four counties (Cass, Clay, Jackson, and Platte) overlap the municipality of Kansas City, Mo. The cases and deaths that we show for these four counties are only for the portions exclusive of Kansas City. Cases and deaths for Kansas City are reported as their line.

• Alameda, Calif.

Counts for Alameda County include cases and deaths from Berkeley and the Grand Princess cruise ship.

• Chicago

All cases and deaths for Chicago are reported as part of Cook County.

License and Attribution

In general, we are making this data publicly available for broad, noncommercial public use including by medical and public health researchers, policymakers, analysts and local news media.

If you use this data, you must attribute it to “The New York Times” in any publication. If you would like a more expanded description of the data, you could say “Data from The New York Times, based on reports from state and local health agencies.”

If you use it in an online presentation, we would appreciate it if you would link to our U.S. tracking page at https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html.

If you use this data, please let us know at covid-data@nytimes.com and indicate if you would be willing to talk to a reporter about your research.

See our LICENSE for the full terms of use for this data.

This license is co-extensive with the Creative Commons Attribution-NonCommercial 4.0 International license, and licensees should refer to that license (CC BY-NC) if they have questions about the scope of the license.

Contact Us

If you have questions about the data or licensing conditions, please contact us at:

covid-data@nytimes.com

Contributors

Mitch Smith, Karen Yourish, Sarah Almukhtar, Keith Collins, Danielle Ivory, and Amy Harmon have been leading our U.S. data collection efforts.

Data has also been compiled by Jordan Allen, Jeff Arnold, Aliza Aufrichtig, Mike Baker, Robin Berjon, Matthew Bloch, Nicholas Bogel-Burroughs, Maddie Burakoff, Christopher Calabrese, Andrew Chavez, Robert Chiarito, Carmen Cincotti, Alastair Coote, Matt Craig, John Eligon, Tiff Fehr, Andrew Fischer, Matt Furber, Rich Harris, Lauryn Higgins, Jake Holland, Will Houp, Jon Huang, Danya Issawi, Jacob LaGesse, Hugh Mandeville, Patricia Mazzei, Allison McCann, Jesse McKinley, Miles McKinley, Sarah Mervosh, Andrea Michelson, Blacki Migliozzi, Steven Moity, Richard A. Oppel Jr., Jugal K. Patel, Nina Pavlich, Azi Paybarah, Sean Plambeck, Carrie Price, Scott Reinhard, Thomas Rivas, Michael Robles, Alison Saldanha, Alex Schwartz, Libby Seline, Shelly Seroussi, Rachel Shorey, Anjali Singhvi, Charlie Smart, Ben Smithgall, Steven Speicher, Michael Strickland, Albert Sun, Thu Trinh, Tracey Tully, Maura Turcotte, Miles Watkins, Jeremy White, Josh Williams, and Jin Wu.

Context

There's a story behind every dataset and here's your opportunity to share yours.# Coronavirus (Covid-19) Data in the United States

[ U.S. State-Level Data ([Raw

State level COVID-19 metrics. As of 6/1/2023 this data set is no longer being updated. The COVID-19 Data Report is posted on the Open Data Portal every day at 3pm. The report uses data from multiple sources, including external partners; if data from external partners are not received by 3pm, they are not available for inclusion in the report and will not be displayed. Data that are received after 3pm will still be incorporated and published in the next report update. The cumulative number of COVID-19 cases (cumulative_cases) includes all cases of COVID-19 that have ever been reported to DPH. The cumulative number of COVID_19 cases in the last 7 days (cases_7days) only includes cases where the specimen collection date is within the past 7 days. While most cases are reported to DPH within 48 hours of specimen collection, there are a small number of cases that routinely are delayed, and will have specimen collection dates that fall outside of the rolling 7 day reporting window. Additionally, reporting entities may submit correction files to contribute historic data during initial onboarding or to address data quality issues; while this is rare, these correction files may cause a large amount of data from outside of the current reporting window to be uploaded in a single day; this would result in the change in cumulative_cases being much larger than the value of cases_7days. On June 4, 2020, the US Department of Health and Human Services issued guidance requiring the reporting of positive and negative test results for SARS-CoV-2; this guidance expired with the end of the federal PHE on 5/11/2023, and negative SARS-CoV-2 results were removed from the List of Reportable Laboratory Findings. DPH will no longer be reporting metrics that were dependent on the collection of negative test results, specifically total tests performed or percent positivity. Positive antigen and PCR/NAAT results will continue to be reportable.

Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. This dataset will receive a final update on June 1, 2023, to reconcile historical data through May 10, 2023, and will remain publicly available.

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

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

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

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

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

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

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

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

<a href="https://data.cdc.gov/Public-Health-Surveillance/United-States-COVID-19-County-Level-of-Community-T

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. COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update. The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates. 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. Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic. 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

Context

The United States have recently become the country with the most reported cases of 2019 Novel Coronavirus (COVID-19). This dataset contains daily updated number of reported cases & deaths in the US on the state and county level, as provided by the Johns Hopkins University. In addition, I provide matching demographic information for US counties.

Content

The dataset consists of two main csv files: covid_us_county.csv and us_county.csv. See the column descriptions below for more detailed information. In addition, I've added US county shape files for geospatial plots: us_county.shp/dbf/prj/shx.

• covid_us_county.csv: COVID-19 cases and deaths which will be updated daily. The data is provided by the Johns Hopkins University through their excellent github repo. I combined the separate "confirmed cases" and "deaths" files into a single table, removed a few (I think to be) redundant geo identifier columns, and reshaped the data into long format with a single date column. The earliest recorded cases are from 2020-01-22.

• us_counties.csv: Demographic information on the US county level based on the (most recent) 2014-18 release of the Amercian Community Survey. Derived via the great tidycensus package.

Column Description

COVID-19 dataset covid_us_county.csv:

• fips: County code in numeric format (i.e. no leading zeros). A small number of cases have NA values here, but can still be used for state-wise aggregation. Currently, this only affect the states of Massachusetts and Missouri.

• county: Name of the US county. This is NA for the (aggregated counts of the) territories of American Samoa, Guam, Northern Mariana Islands, Puerto Rico, and Virgin Islands.

• state: Name of US state or territory.

• state_code: Two letter abbreviation of US state (e.g. "CA" for "California"). This feature has NA values for the territories listed above.

• lat and long: coordinates of the county or territory.

• date: Reporting date.

• cases & deaths: Cumulative numbers for cases & deaths.

Demographic dataset us_counties.csv:

• fips, county, state, state_code: same as above. The county names are slightly different, but mostly the difference is that this dataset has the word "County" added. I recommend to join on fips.

• male & female: Population numbers for male and female.

• population: Total population for the county. Provided as convenience feature; is always the sum of male + female.

• female_percentage: Another convenience feature: female / population in percent.

• median_age: Overall median age for the county.

Acknowledgements

Data provided for educational and academic research purposes by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE).

Licence

The github repo states that:

This GitHub repo and its contents herein, including all data, mapping, and analysis, copyright 2020 Johns Hopkins University, all rights reserved, is provided to the public strictly for educational and academic research purposes. The Website relies upon publicly available data from multiple sources, that do not always agree. The Johns Hopkins University hereby disclaims any and all representations and warranties with respect to the Website, including accuracy, fitness for use, and merchantability. Reliance on the Website for medical guidance or use of the Website in commerce is strictly prohibited.

Version history

• In version 1, a small number of cases had values of `county == "Unassigned". Those have been superseded.
• Version 5: added US county shape files

Overview

The Marshall Project, the nonprofit investigative newsroom dedicated to the U.S. criminal justice system, has partnered with The Associated Press to compile data on the prevalence of COVID-19 infection in prisons across the country. The Associated Press is sharing this data as the most comprehensive current national source of COVID-19 outbreaks in state and federal prisons.

Lawyers, criminal justice reform advocates and families of the incarcerated have worried about what was happening in prisons across the nation as coronavirus began to take hold in the communities outside. Data collected by The Marshall Project and AP shows that hundreds of thousands of prisoners, workers, correctional officers and staff have caught the illness as prisons became the center of some of the country’s largest outbreaks. And thousands of people — most of them incarcerated — have died.

In December, as COVID-19 cases spiked across the U.S., the news organizations also shared cumulative rates of infection among prison populations, to better gauge the total effects of the pandemic on prison populations. The analysis found that by mid-December, one in five state and federal prisoners in the United States had tested positive for the coronavirus -- a rate more than four times higher than the general population.

This data, which is updated weekly, is an effort to track how those people have been affected and where the crisis has hit the hardest.

Methodology and Caveats

The data tracks the number of COVID-19 tests administered to people incarcerated in all state and federal prisons, as well as the staff in those facilities. It is collected on a weekly basis by Marshall Project and AP reporters who contact each prison agency directly and verify published figures with officials.

Each week, the reporters ask every prison agency for the total number of coronavirus tests administered to its staff members and prisoners, the cumulative number who tested positive among staff and prisoners, and the numbers of deaths for each group.

The time series data is aggregated to the system level; there is one record for each prison agency on each date of collection. Not all departments could provide data for the exact date requested, and the data indicates the date for the figures.

To estimate the rate of infection among prisoners, we collected population data for each prison system before the pandemic, roughly in mid-March, in April, June, July, August, September and October. Beginning the week of July 28, we updated all prisoner population numbers, reflecting the number of incarcerated adults in state or federal prisons. Prior to that, population figures may have included additional populations, such as prisoners housed in other facilities, which were not captured in our COVID-19 data. In states with unified prison and jail systems, we include both detainees awaiting trial and sentenced prisoners.

To estimate the rate of infection among prison employees, we collected staffing numbers for each system. Where current data was not publicly available, we acquired other numbers through our reporting, including calling agencies or from state budget documents. In six states, we were unable to find recent staffing figures: Alaska, Hawaii, Kentucky, Maryland, Montana, Utah.

To calculate the cumulative COVID-19 impact on prisoner and prison worker populations, we aggregated prisoner and staff COVID case and death data up through Dec. 15. Because population snapshots do not account for movement in and out of prisons since March, and because many systems have significantly slowed the number of new people being sent to prison, it’s difficult to estimate the total number of people who have been held in a state system since March. To be conservative, we calculated our rates of infection using the largest prisoner population snapshots we had during this time period.

As with all COVID-19 data, our understanding of the spread and impact of the virus is limited by the availability of testing. Epidemiology and public health experts say that aside from a few states that have recently begun aggressively testing in prisons, it is likely that there are more cases of COVID-19 circulating undetected in facilities. Sixteen prison systems, including the Federal Bureau of Prisons, would not release information about how many prisoners they are testing.

Corrections departments in Indiana, Kansas, Montana, North Dakota and Wisconsin report coronavirus testing and case data for juvenile facilities; West Virginia reports figures for juvenile facilities and jails. For consistency of comparison with other state prison systems, we removed those facilities from our data that had been included prior to July 28. For these states we have also removed staff data. Similarly, Pennsylvania’s coronavirus data includes testing and cases for those who have been released on parole. We removed these tests and cases for prisoners from the data prior to July 28. The staff cases remain.

About the Data

There are four tables in this data:

• covid_prison_cases.csv contains weekly time series data on tests, infections and deaths in prisons. The first dates in the table are on March 26. Any questions that a prison agency could not or would not answer are left blank.

• prison_populations.csv contains snapshots of the population of people incarcerated in each of these prison systems for whom data on COVID testing and cases are available. This varies by state and may not always be the entire number of people incarcerated in each system. In some states, it may include other populations, such as those on parole or held in state-run jails. This data is primarily for use in calculating rates of testing and infection, and we would not recommend using these numbers to compare the change in how many people are being held in each prison system.

• staff_populations.csv contains a one-time, recent snapshot of the headcount of workers for each prison agency, collected as close to April 15 as possible.

• covid_prison_rates.csv contains the rates of cases and deaths for prisoners. There is one row for every state and federal prison system and an additional row with the National totals.

Queries

The Associated Press and The Marshall Project have created several queries to help you use this data:

Get your state's prison COVID data: Provides each week's data from just your state and calculates a cases-per-100000-prisoners rate, a deaths-per-100000-prisoners rate, a cases-per-100000-workers rate and a deaths-per-100000-workers rate here

Rank all systems' most recent data by cases per 100,000 prisoners here

Find what percentage of your state's total cases and deaths -- as reported by Johns Hopkins University -- occurred within the prison system here

Attribution

In stories, attribute this data to: “According to an analysis of state prison cases by The Marshall Project, a nonprofit investigative newsroom dedicated to the U.S. criminal justice system, and The Associated Press.”

Contributors

Many reporters and editors at The Marshall Project and The Associated Press contributed to this data, including: Katie Park, Tom Meagher, Weihua Li, Gabe Isman, Cary Aspinwall, Keri Blakinger, Jake Bleiberg, Andrew R. Calderón, Maurice Chammah, Andrew DeMillo, Eli Hager, Jamiles Lartey, Claudia Lauer, Nicole Lewis, Humera Lodhi, Colleen Long, Joseph Neff, Michelle Pitcher, Alysia Santo, Beth Schwartzapfel, Damini Sharma, Colleen Slevin, Christie Thompson, Abbie VanSickle, Adria Watson, Andrew Welsh-Huggins.

Questions

If you have questions about the data, please email The Marshall Project at info+covidtracker@themarshallproject.org or file a Github issue.

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

COVID-19 case data by large age groups, sex, Hispanic ethnicity, date of specimen collection, zip code of residence, vital status, Feb-Dec 2020. Smaller analytic dataset of a door-to-door serologic survey carried out in December 2020.

Context

COVID-19 is on a rise worldwide. It was first identified in the city of Wuhan in China in 2019 and has now spread into a global pandemic. Michigan is currently the third largest affected state in USA. The state's confirmed cases have been on a rise since early March 2020. In this dire time, it is extremely important to understand the factors affecting the spread of the virus in Michigan, identify susceptible population and predict the trajectory of the infected and dead cases on a daily basis.

Content

Update: April 4, 2020 2:00 PM Eastern Standard Time (EST)

This data currently contains information about COVID-19 confirmed cases (14225) and deaths (540) in Michigan counties. The dataset also includes percentage of COVID-19 confirmed and dead cases by age, gender, race and ethnicity. The information is published by www.michigan.gov on a daily basis at 2:00 PM EST. The results are included as of 10:00 AM every day.

Acknowledgements

Michigan.gov - Coronavirus

Inspiration

1. This dataset will be useful in understanding and predicting the trajectory of the infected and dead cases in Michigan in the coming days.
2. The dataset can also give insight about the most vulnerable age groups in Michigan.

Please consider upvoting if the data is found useful in any way. If there are any improvement suggestions, do let me know.

Covid-19 Daily metrics at the county level

As of 6/1/2023, this data set is no longer being updated.

The COVID-19 Data Report is posted on the Open Data Portal every day at 3pm. The report uses data from multiple sources, including external partners; if data from external partners are not received by 3pm, they are not available for inclusion in the report and will not be displayed. Data that are received after 3pm will still be incorporated and published in the next report update.

The cumulative number of COVID-19 cases (cumulative_cases) includes all cases of COVID-19 that have ever been reported to DPH. The cumulative number of COVID_19 cases in the last 7 days (cases_7days) only includes cases where the specimen collection date is within the past 7 days. While most cases are reported to DPH within 48 hours of specimen collection, there are a small number of cases that routinely are delayed, and will have specimen collection dates that fall outside of the rolling 7 day reporting window. Additionally, reporting entities may submit correction files to contribute historic data during initial onboarding or to address data quality issues; while this is rare, these correction files may cause a large amount of data from outside of the current reporting window to be uploaded in a single day; this would result in the change in cumulative_cases being much larger than the value of cases_7days.

On June 4, 2020, the US Department of Health and Human Services issued guidance requiring the reporting of positive and negative test results for SARS-CoV-2; this guidance expired with the end of the federal PHE on 5/11/2023, and negative SARS-CoV-2 results were removed from the List of Reportable Laboratory Findings. DPH will no longer be reporting metrics that were dependent on the collection of negative test results, specifically total tests performed or percent positivity. Positive antigen and PCR/NAAT results will continue to be reportable.

Data is from the California COVID-19 State Dashboard at https://covid19.ca.gov/state-dashboard/

NOTE: Data is being updated on Tuesdays and Fridays.

Data on cases, deaths, and testing is not reported on weekends or state holidays. This data is reported on the first day following the weekend or holiday. All metrics include people in state and federal prisons, US Immigration and Customs Enforcement facilities, US Marshal detention facilities, and Department of State Hospitals facilities. Members of California's tribal communities are also included.

NOTE: The "Total Tests" and "Positive Tests" columns show totals based on the collection date. There is a lag between when a specimen is collected and when it is reported in this dataset. As a result, the most recent dates on the table will temporarily show NONE in the "Total Tests" and "Positive Tests" columns. This should not be interpreted as no tests being conducted on these dates. Instead, these values will be updated with the number of tests conducted as data is received.

When comparing to the state dashboard, the dashboard numbers will correspond to the "Reported" columns in this table. Also note that the dashboard displays data that is one day prior to today's date.