NEW: The data in the counties.csv, states.csv and us.csv now include both confirmed and probable Covid-19 cases and deaths. Because of changes in how states and local health departments are reporting their data, it is no longer possible to report a comprehensive “confirmed-only” dataset. Please see our note for a full explanation of the differences and how probable cases are defined.
[ 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.
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 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.
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 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 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.
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 information about their locations later, once it became available.
- Confirmed Cases
Confirmed cases and deaths are counts of individuals whose coronavirus infections were confirmed by a laboratory test and reported by a federal, state, territorial or local government agency.
The number of cases includes all cases, including those who have since recovered or died.
- "Probable" Cases and Deaths
Probable cases and deaths count individuals who did not have a confirmed test but were evaluated using criteria developed by states and the federal government.
On April 5, the Council of State and Territorial Epidemiologists Centers advised states to include both confirmed cases, based on laboratory testing, and probable cases, based on specific criteria for symptoms and exposure. The Centers for Disease Control adopted these definitions and national CDC data began including confirmed and probable cases on April 14.
Some governments continue to report only confirmed cases, while others are reporting both confirmed and probable numbers. And there is also another set of governments that are reporting the two types of numbers combined without providing a way to separate the confirmed from the probable.
Please see the Geographic Exceptions section below for more details on specific areas, with the understanding that this changes frequently.
- 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.
Each date includes all cases and deaths announced that day through midnight Eastern Time. As the West Coast and Hawaii tend to release all of their new data early enough in the day.
- Declining Counts
In some cases, the number of cases or deaths for a state or county will decline. This can occur when a state or county corrects an error in the number of cases or deaths they've reported in the past, or when a state moves cases from one county to another. When we are able, we will historically revise counts for all impacted dates. In other cases, this will be reflected in a single-day drop in the number of cases or deaths.
- 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.
- New York
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. There is a large jump in the number of deaths on April 6th due to switching from data from New York City to data from New York state for deaths. We are not currently including the probable deaths reported by New York City.
For all New York state counties, starting on April 8th we are reporting deaths by place of fatality instead of residence of individual. There were no new deaths reported by the state on April 17th or April 18th.
- Georgia
Starting April 12th, our case count excludes cases labeled by the state as "Non-Georgia Resident" leading to a one day drop in cases. These cases were previously included as cases with "Unknown" county.
- Alabama
Alabama's numbers for April 17th contained an error in reporting of lab test results that the state is working to correct. The number of deaths drops on April 23rd for an unknown reason.
- 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 own line.
- Alameda County, Calif.
Counts for Alameda County include cases and deaths from Berkeley and the Grand Princess cruise ship.
- Douglas County, Neb.
Counts for Douglas County include cases brought to the state from the Diamond Princess cruise ship.
- Chicago
All cases and deaths for Chicago are reported as part of Cook County.
- Guam
Counts for Guam include cases reported from the USS Theodore Roosevelt.
- Puerto Rico
On April 21st, the territory's health department revised their number of cases downward, saying they had been double counting some coronavirus patients in official reports, leading to a higher number of cases reported than actually confirmed.
Additionally, from approximately April 12th through April 18th, the count of deaths for Puerto Rico include some probable Covid-19 related deaths that were not lab-confirmed. Starting April 19th these have been removed. We will revise the numbers for the 12th to 18th as possible.
- Colorado
Numbers reflect the combined number of lab-confirmed and probable cases and deaths as reported by the state. On April 25th, the state revised downward the number of deaths after removing "about 29 duplicates" from the number of "probable deaths" included in the total.
- Idaho
The total cases number includes only lab-confirmed cases, but the deaths number does include the deaths of probable Covid-19 cases.
- Louisiana
The total cases number and total deaths number include only lab-confirmed cases and deaths. The state appears to be reporting the deaths of probable Covid-19 cases separately from the total number of deaths statewide and in each parish but we are not yet including those cases in our numbers.
- Ohio
The state reports lab-confirmed and probable cases and deaths separately at the state level but combine lab-confirmed and probable cases and deaths at the county level. Our statewide and county numbers combine both case types.
- Pennsylvania
The total cases number includes lab-confirmed and probable cases starting around April 16th, but the deaths number does not include probable deaths, except for on April 21st and April 22nd when it does.
- Virginia
The state reports lab-confirmed and probable cases and deaths separately at the state level but combine lab-confirmed and probable cases and deaths at the county level. Our statewide and county numbers combine both case types.
- Puerto Rico
Our number of cases for Puerto Rico includes the results of serological cases in their total number of cases, we believe this more closely matches the definition of probable cases than confirmed cases as reported elsewhere. Our number of deaths is only deaths with a confirmed test.
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 [email protected].
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.
If you have questions about the data or licensing conditions, please contact us at:
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.