{"info":{"_postman_id":"d5fb8837-e3f6-4146-9067-a8e358b16fc1","name":"CovidCountyData","description":"

Rest API

\n

The REST API does not require any software to be installed on your computer, it allows you to\ninteract with our data through standard web protocols.

\n

Our API is build using PostgREST. For more information on the\ndifferent features of this API, please see their documentation.

\n

API Key

\n

Our data is free and open for anyone to use (and always will be). Our team agreed that this was central to our mission when we agreed to begin this project. However, we do find it useful to have information about our users and to see how they use the data for two reasons:

\n
    \n
  1. It helps us focus and improve the datasets that are seeing the most use.
    2. \n
  2. The number of users, as measured by active API keys, is one metric that we use to show that the\nproject is useful when we are discussing additional grant funding.
    3. \n
\n

We are grateful to everyone who is willing to register for and use their API key when interacting\nwith our data.

\n

To register for an API key, see the registration form on our home page.

\n

After obtaining an API key, please attach it as either the apikey header or query parameter in future requests

\n

For example, if my API key were abc123 and I was getting data from https://api.covidcountydata.org/covid_us?fips=eq.6, I\nwould adjust the url to be https://api.covidcountydata.org/covid_us?fips=eq.6&apikey=abc123

\n

Request structure

\n

In order to be able to request data, you will need to know which endpoint the data comes from and,\noptionally, which filters you would like to apply to the data before it's delivered:

\n

API Endpoints

\n

The data in our database is broken into tables of related information with a separate endpoint for\neach table. For example, all of the U.S. COVID-19 related data is stored in the covid_us table\nand it has a corresponding endpoint of https://api.covid.valorum.ai/covid_us. For a complete\nlist of the available endpoints, see the interactive playground near the bottom of the page.

\n

Filters

\n

There are a two types of parameters that can be included as filters:

\n\n

The data parameters that you are able to apply will depend on what columns are available in a\nparticular dataset. Many of the tables will have the columns dt (date of the obervation),\nlocation (a geographical identifier, for the U.S. this is often the fips code), variable (name\nof the variable being observed), and value (the value of the variable in that location at that\ntime).

\n

For example, if you wanted to request 5 observations of the tests_total variable from after\nAugust 1, 2020 then you would use the following query:

\n

https://api.covid.valorum.ai/covid_us?dt=gt.2020-08-01&variable=eq.tests_total&limit=5

\n

Of course, rather than input this address into your browser, you could query the API for this\ninformation using a more generic tool such as curl or javascript.

\n

We make two additional observations:

\n
    \n
  1. Rather than use >, <, =, etc..., the REST API expects you to use gt., lt., eq.,\netc... For a complete list of comparisons, see PostgREST documentation
    2. \n
  2. Much of the data is stored in long form rather than wide form. In long form each data\n observation, or value, is associated with its unique identifiers. For example, in many of our\n datasets the identifiers are dt, location, and variable, and the value of the observation\n is stored in value. This can be seen in the example section below.
    3. \n
\n

Examples

\n

We will do some examples to illustrate these points using the example table below. We will demonstrate\nthe example api requests using the covid_us endpoint (at https://api.covidcountydata.org/covid_us),\nbut the same concepts apply to all endpoints. Note that we will add limit=20 to most of the requests\nbelow to prevent unnecessary data transfer, but removing this query parameter will allow you to fetch the\nwhole dataset. Finally, note also that we'll use the same apikey=abc123 argument as shown in the\nexample above, but the abc123 should be replaced by your API key.

\n

Below is an example table showing the structure of the data returned by the covid_us endpoint:

\n
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
dtfipsvariablevalue
2020-06-016deaths_total4251
2020-06-0112deaths_total2543
2020-06-0148deaths_total1678
2020-06-026deaths_total4286
2020-06-0212deaths_total2613
2020-06-0248deaths_total1698
2020-06-016positive_tests_total113006
2020-06-0112positive_tests_total56830
2020-06-0148positive_tests_total64880
2020-06-026positive_tests_total115310
2020-06-0212positive_tests_total57447
2020-06-0248positive_tests_total66568
\n

Only data from CA

\n

In order to select data from only California (fips code 06) we filter the parameter location to\nonly be 6

\n

https://api.covid.valorum.ai/covid_us?fips=eq.06&limit=20&apikey=abc123

\n

Only observations with more than 100,000 tests

\n

In order to only select observations with more than 100,000 tests, we would want to use the following parameters

\n

https://api.covid.valorum.ai/covid_us?variable=eq.positive_tests_total&value=gt.100000&limit=20&apikey=abc123

\n

Only observations after June 1, 2020

\n

In order to only select the data from after June 1, 2020, we would use the following parameter

\n

https://api.covid.valorum.ai/covid_us?dt=gt.2020-06-01&limit=20&apikey=abc123

\n

Select total deaths for Texas ordered by date

\n

In order to select only the total deaths variable for Texas and have the results be ordered by date, we would use the following parameters

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https://api.covid.valorum.ai/covid_us?location=eq.48&variable=eq.positive_tests_total&order=dt&limit=20&apikey=abc123

\n

Software

\n

We use the following open source technologies to build this API.

\n\n

We are grateful to all of these projects for simplifying the task of building, deploying, and\ndocumenting our API. We are also grateful to Google Cloud for helping us host and distribute our\ndata.

\n

API Endpoints

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Limiting and Pagination

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Limiting and Pagination

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Preference

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This table contains the complete Our World in Data's COVID-19 dataset. Please see the original source for more information.

\n

All of Our World in Data is completely open access and all work is licensed under the Creative Commons BY license. You have the permission to use, distribute, and reproduce in any medium, provided the source and authors are credited.

\n

This data has been collected, aggregated, and documented by Diana Beltekian, Daniel Gavrilov, Charlie Giattino, Joe Hasell, Bobbie Macdonald, Edouard Mathieu, Esteban Ortiz-Ospina, Hannah Ritchie, Max Roser.

\n

The mission of Our World in Data is to make data and research on the world’s largest problems understandable and accessible. Read more about our mission.

\n

The following documentation is taken from the Our World in Data COVID-19 page and the corresponding GitHub repository:

\n

The 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, and testing, as well as other variables of potential interest.

\n\n","urlObject":{"path":["covid_global"],"host":["https://api.covidcountydata.org"],"query":[{"description":{"content":"

ISO 3166-1 alpha-3 – three-letter country codes|International Organization for Standardization

\n","type":"text/plain"},"key":"iso_code","value":"eq.GBR"},{"disabled":true,"description":{"content":"

Continent of the geographical location|Our World in Data

\n","type":"text/plain"},"key":"continent","value":""},{"disabled":true,"description":{"content":"

Geographical location|Our World in Data

\n","type":"text/plain"},"key":"location","value":""},{"description":{"content":"

Date of observation|Our World in Data

\n","type":"text/plain"},"key":"dt","value":"gt.2020-07-20"},{"disabled":true,"description":{"content":"

Total confirmed cases of COVID-19|European Centre for Disease Prevention and Control

\n","type":"text/plain"},"key":"total_cases","value":""},{"disabled":true,"description":{"content":"

New confirmed cases of COVID-19|European Centre for Disease Prevention and Control

\n","type":"text/plain"},"key":"new_cases","value":""},{"disabled":true,"description":{"content":"

Total deaths attributed to COVID-19|European Centre for Disease Prevention and Control

\n","type":"text/plain"},"key":"total_deaths","value":""},{"disabled":true,"description":{"content":"

New deaths attributed to COVID-19|European Centre for Disease Prevention and Control

\n","type":"text/plain"},"key":"new_deaths","value":""},{"disabled":true,"description":{"content":"

Total confirmed cases of COVID-19 per 1,000,000 people|European Centre for Disease Prevention and Control

\n","type":"text/plain"},"key":"total_cases_per_million","value":""},{"disabled":true,"description":{"content":"

New confirmed cases of COVID-19 per 1,000,000 people|European Centre for Disease Prevention and Control

\n","type":"text/plain"},"key":"new_cases_per_million","value":""},{"disabled":true,"description":{"content":"

Total deaths attributed to COVID-19 per 1,000,000 people|European Centre for Disease Prevention and Control

\n","type":"text/plain"},"key":"total_deaths_per_million","value":""},{"disabled":true,"description":{"content":"

New deaths attributed to COVID-19 per 1,000,000 people|European Centre for Disease Prevention and Control

\n","type":"text/plain"},"key":"new_deaths_per_million","value":""},{"disabled":true,"description":{"content":"

Total tests for COVID-19|National government reports

\n","type":"text/plain"},"key":"total_tests","value":""},{"disabled":true,"description":{"content":"

New tests for COVID-19|National government reports

\n","type":"text/plain"},"key":"new_tests","value":""},{"disabled":true,"description":{"content":"

ew tests for COVID-19 (7-day smoothed). For countries that do not report testing data on a daily basis, we assume that testing changed equally on a daily basis over any periods in which no data was reported. This produces a complete series of daily figures, which is then averaged over a rolling 7-day window|National government reports

\n","type":"text/plain"},"key":"new_tests_smoothed","value":""},{"disabled":true,"description":{"content":"

Total tests for COVID-19 per 1,000 people|National government reports

\n","type":"text/plain"},"key":"total_tests_per_thousand","value":""},{"disabled":true,"description":{"content":"

New tests for COVID-19 per 1,000 people|National government reports

\n","type":"text/plain"},"key":"new_tests_per_thousand","value":""},{"disabled":true,"description":{"content":"

New tests for COVID-19 (7-day smoothed) per 1,000 people|National government reports

\n","type":"text/plain"},"key":"new_tests_smoothed_per_thousand","value":""},{"disabled":true,"description":{"content":"

Units used by the location to report its testing data|National government reports

\n","type":"text/plain"},"key":"tests_units","value":""},{"disabled":true,"description":{"content":"

Government Response Stringency Index: composite measure based on 9 response indicators including school closures, workplace closures, and travel bans, rescaled to a value from 0 to 100 (100 = strictest response)|Oxford COVID-19 Government Response Tracker, Blavatnik School of Government

\n","type":"text/plain"},"key":"stringency_index","value":""},{"disabled":true,"description":{"content":"

Population in 2020|United Nations, Department of Economic and Social Affairs, Population Division, World Population Prospects: The 2019 Revision

\n","type":"text/plain"},"key":"population","value":""},{"disabled":true,"description":{"content":"

Number of people divided by land area, measured in square kilometers, most recent year available|World Bank – World Development Indicators, sourced from Food and Agriculture Organization and World Bank estimates

\n","type":"text/plain"},"key":"population_density","value":""},{"disabled":true,"description":{"content":"

Median age of the population, UN projection for 2020|UN Population Division, World Population Prospects, 2017 Revision

\n","type":"text/plain"},"key":"median_age","value":""},{"disabled":true,"description":{"content":"

hare of the population that is 65 years and older, most recent year available|World Bank – World Development Indicators, based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision

\n","type":"text/plain"},"key":"aged_65_older","value":""},{"disabled":true,"description":{"content":"

Share of the population that is 70 years and older in 2015|United Nations, Department of Economic and Social Affairs, Population Division (2017), World Population Prospects: The 2017 Revision

\n","type":"text/plain"},"key":"aged_70_older","value":""},{"disabled":true,"description":{"content":"

Gross domestic product at purchasing power parity (constant 2011 international dollars), most recent year available|World Bank – World Development Indicators, source from World Bank, International Comparison Program database

\n","type":"text/plain"},"key":"gdp_per_capita","value":""},{"disabled":true,"description":{"content":"

Share of the population living in extreme poverty, most recent year available since 2010|World Bank – World Development Indicators, sourced from World Bank Development Research Group

\n","type":"text/plain"},"key":"extreme_poverty","value":""},{"disabled":true,"description":{"content":"

Death rate from cardiovascular disease in 2017|Global Burden of Disease Collaborative Network, Global Burden of Disease Study 2017 Results

\n","type":"text/plain"},"key":"cvd_death_rate","value":""},{"disabled":true,"description":{"content":"

Diabetes prevalence (% of population aged 20 to 79) in 2017|World Bank – World Development Indicators, sourced from International Diabetes Federation, Diabetes Atlas

\n","type":"text/plain"},"key":"diabetes_prevalence","value":""},{"disabled":true,"description":{"content":"

Share of women who smoke, most recent year available|World Bank – World Development Indicators, sourced from World Health Organization, Global Health Observatory Data Repository

\n","type":"text/plain"},"key":"female_smokers","value":""},{"disabled":true,"description":{"content":"

Share of men who smoke, most recent year available|World Bank – World Development Indicators, sourced from World Health Organization, Global Health Observatory Data Repository

\n","type":"text/plain"},"key":"male_smokers","value":""},{"disabled":true,"description":{"content":"

Share of the population with basic handwashing facilities on premises, most recent year available|United Nations Statistics Division

\n","type":"text/plain"},"key":"handwashing_facilities","value":""},{"disabled":true,"description":{"content":"

Hospital beds per 1,000 people, most recent year available since 2010|OECD, Eurostat, World Bank, national government records and other sources

\n","type":"text/plain"},"key":"hospital_beds_per_thousand","value":""},{"disabled":true,"description":{"content":"

Life expectancy at birth in 2019|James C. Riley, Clio Infra, United Nations Population Division

\n","type":"text/plain"},"key":"life_expectancy","value":""},{"disabled":true,"description":{"content":"

Filtering Columns

\n","type":"text/plain"},"key":"select","value":""},{"disabled":true,"description":{"content":"

Ordering

\n","type":"text/plain"},"key":"order","value":""},{"disabled":true,"description":{"content":"

Limiting and Pagination

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Limiting and Pagination

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\n","key":"Prefer","value":""}],"url":"https://api.covidcountydata.org/covid_historical?vintage=eq.2020-08-25&limit=12","description":"

This table contains relevant information on COVID-19

\n

This table returns all vintages (data from different collection dates) of data in our system.

\n

For only the most recent data, please use the covid endpoint.

\n

Currently, the following variables are collected in the database

\n
    \n
  • cases_suspected: Total number of suspected cases
    • \n
  • cases_confirmed: Total number of confirmed cases
    • \n
  • cases_total: The number of suspected or confirmed cases
    • \n
  • deaths_suspected: The number of deaths that are suspected to have been caused by COVID-19
    • \n
  • deaths_confirmed: The number of deaths that are confirmed to have been caused by COVID-19
    • \n
  • deaths_total: The number of deaths that are either suspected or confirmed to have been caused by COVID-19
    • \n
  • positive_tests_total: The total number of tests that have been positive
    • \n
  • negative_tests_total: The total number of tests that have been negative
    • \n
  • icu_beds_capacity_count: The number of ICU beds available in the geography
    • \n
  • icu_beds_in_use_any: The number of ICU beds currently in use
    • \n
  • icu_beds_in_use_covid_suspected: The number of ICU beds currently in use by a patient suspected of COVID-19
    • \n
  • icu_beds_in_use_covid_confirmed: The number of ICU beds currently in use by a patient confirmed to have COVID-19
    • \n
  • icu_beds_in_use_covid_total: The number of ICU beds currently in use by a patient who is suspected of having or confirmed to have COVID-19
    • \n
  • icu_beds_in_use_covid_new: The number of ICU beds occupied by an individual suspected or confirmed of having COVID-19 that have been admitted today
    • \n
  • hospital_beds_capacity_count: The number of hospital beds available in the geography
    • \n
  • hospital_beds_in_use_any: The number of hospital beds currently in use
    • \n
  • hospital_beds_in_use_covid_suspected: The number of hospital beds currently in use by a patient suspected of COVID-19
    • \n
  • hospital_beds_in_use_covid_confirmed: The number of hospital beds currently in use by a patient confirmed to have COVID-19
    • \n
  • hospital_beds_in_use_covid_total: The number of hospital beds currently in use by a patient who is suspected of having or confirmed to have COVID-19
    • \n
  • hospital_beds_in_use_covid_new: The number of hospital beds occupied by an individual suspected or confirmed of having COVID-19 that have been admitted today
    • \n
  • ventilators_capacity_count: The number of individuals who can be supported by a ventilator
    • \n
  • ventilators_in_use_any: The number of individuals who are currently on a ventilator
    • \n
  • ventilators_in_use_covid_suspected: The number of individuals who are suspected of having COVID-19 that are currently on a ventilator
    • \n
  • ventilators_in_use_covid_confirmed: The number of individuals who are confirmed to have COVID-19 that are currently on a ventilator
    • \n
  • ventilators_in_use_covid_total: The number of individuals who are either suspected of having or confirmed to have COVID-19 that are on a ventilator
    • \n
  • ventilators_in_use_covid_new: The number of ventilators that are currently on a ventilator that are suspected of having or confirmed to have COVID-19 that started the ventilator today
    • \n
  • recovered_total: The number of individuals who tested positive for COVID-19 and no longer test positive
    • \n
  • active_total: The number of currently active COVID-19 cases
    • \n
\n

These variables are only collected from official US federal/state/county government sources or redistributed from reputable sources like CovidTracking Project, USAFacts, and the New York Times.

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This table contains relevant information on COVID-19

\n

This table only includes the most recent observation for each date, location, and variable.

\n

For a full history of all data we have collected see covid_historical

\n

Currently, the following variables are collected in the database

\n
    \n
  • cases_suspected: Total number of suspected cases
    • \n
  • cases_confirmed: Total number of confirmed cases
    • \n
  • cases_total: The number of suspected or confirmed cases
    • \n
  • deaths_suspected: The number of deaths that are suspected to have been caused by COVID-19
    • \n
  • deaths_confirmed: The number of deaths that are confirmed to have been caused by COVID-19
    • \n
  • deaths_total: The number of deaths that are either suspected or confirmed to have been caused by COVID-19
    • \n
  • positive_tests_total: The total number of tests that have been positive
    • \n
  • negative_tests_total: The total number of tests that have been negative
    • \n
  • icu_beds_capacity_count: The number of ICU beds available in the geography
    • \n
  • icu_beds_in_use_any: The number of ICU beds currently in use
    • \n
  • icu_beds_in_use_covid_suspected: The number of ICU beds currently in use by a patient suspected of COVID-19
    • \n
  • icu_beds_in_use_covid_confirmed: The number of ICU beds currently in use by a patient confirmed to have COVID-19
    • \n
  • icu_beds_in_use_covid_total: The number of ICU beds currently in use by a patient who is suspected of having or confirmed to have COVID-19
    • \n
  • icu_beds_in_use_covid_new: The number of ICU beds occupied by an individual suspected or confirmed of having COVID-19 that have been admitted today
    • \n
  • hospital_beds_capacity_count: The number of hospital beds available in the geography
    • \n
  • hospital_beds_in_use_any: The number of hospital beds currently in use
    • \n
  • hospital_beds_in_use_covid_suspected: The number of hospital beds currently in use by a patient suspected of COVID-19
    • \n
  • hospital_beds_in_use_covid_confirmed: The number of hospital beds currently in use by a patient confirmed to have COVID-19
    • \n
  • hospital_beds_in_use_covid_total: The number of hospital beds currently in use by a patient who is suspected of having or confirmed to have COVID-19
    • \n
  • hospital_beds_in_use_covid_new: The number of hospital beds occupied by an individual suspected or confirmed of having COVID-19 that have been admitted today
    • \n
  • ventilators_capacity_count: The number of individuals who can be supported by a ventilator
    • \n
  • ventilators_in_use_any: The number of individuals who are currently on a ventilator
    • \n
  • ventilators_in_use_covid_suspected: The number of individuals who are suspected of having COVID-19 that are currently on a ventilator
    • \n
  • ventilators_in_use_covid_confirmed: The number of individuals who are confirmed to have COVID-19 that are currently on a ventilator
    • \n
  • ventilators_in_use_covid_total: The number of individuals who are either suspected of having or confirmed to have COVID-19 that are on a ventilator
    • \n
  • ventilators_in_use_covid_new: The number of ventilators that are currently on a ventilator that are suspected of having or confirmed to have COVID-19 that started the ventilator today
    • \n
  • recovered_total: The number of individuals who tested positive for COVID-19 and no longer test positive
    • \n
  • active_total: The number of currently active COVID-19 cases
    • \n
\n

These variables are only collected from official US federal/state/county government sources or redistributed from reputable sources like CovidTracking Project, USAFacts, and the New York Times

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\n

This table only includes the most recent observation for each date, location, and variable. If you are interested in historical revisions of this data, please reach out -- We have previous \"vintages\" of the CTP data but, in order to simplify our list of tables, we have chosen not to expose (but are happy to if it would be useful).

\n

The COVID Tracking Project collects data on the number of cases, test results, and hospitaliztions at the state level. As always, if you intend to use this data, we recommend that you read the corresponding documentation on their data page as it provides insights into how data collection changed at various points in time and highlights other data caveats.

\n

The data can also be found at on the COVID Tracking Project page.

\n

The COVID Tracking Project data is released under the following license:

\n

You are welcome to copy, distribute, and develop data and website content from The COVID Tracking Project at The Atlantic for all healthcare, medical, journalistic and non-commercial uses, including any personal, editorial, academic, or research purposes.

\n

The COVID Tracking Project at The Atlantic data and website content is published under a Creative Commons CC BY-NC-4.0 license, which requires users to attribute the source and license type (CC BY-NC-4.0) when sharing our data or website content. The COVID Tracking Project at The Atlantic also grants permission for any derivative use of this data and website content that supports healthcare or medical research (including institutional use by public health and for-profit organizations), or journalistic usage (by nonprofit or for-profit organizations). All other commercial uses are not permitted under the Creative Commons license, and will require permission from The COVID Tracking Project at The Atlantic.

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\n

For the United States, this data comes from the American Community Survey that is administered by the US Census. Currently, the following variables are collected in the database

\n
    \n
  • Total population
    • \n
  • Median age
    • \n
  • Fraction of the population over 65
    • \n
  • Fraction of the population who identify as various races or as Hispanic/Latino
    • \n
  • Fraction of the population with various degrees of education
    • \n
  • Fraction of the population that commutes in various ways
    • \n
  • Mean travel time to work (minutes)
    • \n
  • Median household income
    • \n
  • Mean household income
    • \n
  • Fraction of the (civilian) population with/without health insurance
    • \n
  • Fraction of families who had an income less than poverty level in the last year
    • \n
\n

Please note that we are willing (and easily able!) to add other years or variables if there is interest --- The variables that we do include are because people have asked about them.

\n

Source(s):

\n

US Census American Community Survey (https://www.census.gov/programs-surveys/acs)

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\n

These variables are not typically collected at a sufficiently high frequency to use them as time-series data but rather we use\nthem to characterize the economic features of different locations. For example, while unemployment claims is observed on a\nweekly basis, data on the industry make-up of a geographic region is only available at a yearly frequency.

\n

The variables currently included here are:

\n
    \n
  • Industry specific GDP at the county/state level
    • \n
\n

These variables are collected from a variety of sources.

\n

Source(s):

\n
    \n
  • Bureau of Economic Analysis
    • \n
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\n

These variables tend to be observed at a daily/weekly/monthly/quarterly frequency and we can use them to think\nabout changes in the economy as opposed to the slow moving variables included in the economic_snapshots table

\n

These economic variables currently include:

\n
    \n
  • Weekly Economic Index produced by Jim Stock
    • \n
  • State unemployment claims (county forthcoming)
    • \n
\n

These variables are collected from a variety of sources.

\n

Source(s):

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This table contains the data from the HHS COVID data

\n

This table only includes the most recent observation for each date, location, and variable. If you are interested in historical revisions of this data, please reach out -- We have previous \"vintages\" of the HHS data but, in order to simplify our list of tables, we have chosen not to expose (but are happy to if it would be useful).

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\n","key":"Prefer","value":""}],"url":"https://api.covidcountydata.org/mobility_devices?location=eq.36061&limit=100","description":"

The DEX, or device exposure index, is an index that measures how much movement there is within a particular geography (state or county). This data is currently only available for the US.

\n

The DEX answers the question, for a smartphone residing in a given geography, how many distinct devices also visited any of the commercial venues that this device visited today?

\n

The state-level (county-level) DEX reports the state-level average of this number across all devices residing in the state (county) that day. The DEX values are necessarily only a fraction of the number of distinct individuals that also visited any of the commercial venues visited by a device, since only a fraction of individuals, venues, and visits are in the device sample.

\n

In the context of the ongoing pandemic, the DEX measure may be biased if devices sheltering-in-place are not in the sample due to lack of movement. We report adjusted DEX values to help address this selection bias. DEX-adjusted is computed assuming that the number of devices has not declined since the early-2020 peak and that unobserved devices did not visit any commercial venues.

\n

Both the county and state level DEX have information on the number of devices in the sample and the adjusted DEX values as described above. Additionally, the state DEX has information in which the data has been separated into geographic regions that share demographic characteristics...

\n

This data is produced by Victor Couture, Jonathan Dingel, Allison Green, Jessie Handbury, and Kevin Williams with assistance from Hayden Parsley and Serena Xu. They are derived from anonymized, aggregated smartphone movement data provided by PlaceIQ. We are grateful to the authors and to PlaceIQ for making this data available to us.

\n

If you use this dataset, we recommend seeing the notes for users of the DEX dataset and DEX documentation produced by the original authors.

\n

Source: https://github.com/COVIDExposureIndices/COVIDExposureIndices

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The variable associated with the DEX value --- This will either be a number of devices or a DEX value.

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The value of the variable on date dt in geography fips.

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The Location Exposure Index (LEX) is a measure of how much exposure there is across different geographies. This data is currently only available for the US.

\n

Among smartphones that pinged in a given state (county) today, what share of those devices pinged in each state (county) at least once during the previous 14 days? The daily state-level (county-level) LEX is a 51-by-51 (ncounties-by-ncounties) matrix in which each cell reports, among devices that pinged today in the column state (county), the share of devices that pinged in the row state (county) at least once during the previous 14 days. It is important to note that a cell phone can ping in more than a single state (county) which means that these shares will not necessarily sum to 1.

\n

This index is produced by Victor Couture, Jonathan Dingel, Allison Green, Jessie Handbury, and Kevin Williams with assistance from Hayden Parsley and Serena Xu. They are derived from anonymized, aggregated smartphone movement data provided by PlaceIQ. We are grateful to the authors and to PlaceIQ for making this data available to us.

\n

If you use this dataset, we recommend seeing the notes for users of the LEX dataset and LEX documentation produced by the original authors.

\n

Source: https://github.com/COVIDExposureIndices/COVIDExposureIndices

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The state (county) for which a device was found in the previous 14 days.

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\n","key":"Range-Unit","value":"items"},{"description":"

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\n","key":"Prefer","value":""}],"url":"https://api.covidcountydata.org/npi_us?location=eq.6095&limit=30","description":"

This table contains information on the nonpharmaceutical interventions (NPIs) that were taken in the United States in response to COVID

\n

The data begins on March 1, 2020 and covers approximately 650 different US geographies (states and counties). There are 10 different NPIs covered in this dataset which include:

\n
    \n
  • closing_of_public_venues: Public venues closed. A government order closing gathering venues for in-person service, such as restaurants, bars, and theaters.
    • \n
  • lockdown: Lock down
    • \n
  • non-essential_services_closure: Non-essential services closure
    • \n
  • religious_gatherings_banned: Cancelling of religious gatherings, either explicitly or implicitly by applying gathering size/shelter-in-place limitations to religious gatherings as well
    • \n
  • shelter_in_place: An order indicating that people should shelter in their homes except for essential reasons
    • \n
  • social_distancing: Social distancing mandate of at least 6 ft between people
    • \n
  • gathering_size_10_0: Gatherings are limited to between 0 and 10 people
    • \n
  • gathering_size_25_11: Gatherings are limited to between 11 and 25 people
    • \n
  • gathering_size_100_26: Gatherings are limited to between 26 and 100 people
    • \n
  • gathering_size_500_101: Gatherings are limited to between 101 and 500 people
    • \n
\n

The original data was collected by Keystone Strategy and is distributed under the Creative Commons Attribution 4.0 International Public License.

\n

Keystone Strategy COVID page: https://www.keystonestrategy.com/coronavirus-covid19-intervention-dataset-model/\nSource: https://github.com/Keystone-Strategy/covid19-intervention-data

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The FIPS code for the geography

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The NPI being considered

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Whether the intervention from variable was active in geography location on date dt

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This table contains the data from the NY Times COVID data

\n

This table only includes the most recent observation for each date, location, and variable. If you are interested in historical revisions of this data, please reach out -- We have previous \"vintages\" of the NYT data but, in order to simplify our list of tables, we have chosen not to expose (but are happy to if it would be useful).

\n

The data only includes total number of cases and total number of COVID related deaths. If you use this data, we recommend that you read the corresponding documentation on their github site as it provides useful insights to when certain variables changed how they were collected etc...

\n

The NYTimes COVID data can be found online at https://github.com/nytimes/covid-19-data and is released under the following license:

\n

Copyright 2020 by The New York Times Company

\n

In light of the current public health emergency, The New York Times Company is\nproviding this database under the following free-of-cost, perpetual,\nnon-exclusive license. Anyone may copy, distribute, and display the database, or\nany part thereof, and make derivative works based on it, provided (a) any such\nuse is for non-commercial purposes only and (b) credit is given to The New York\nTimes in any public display of the database, in any publication derived in part\nor in full from the database, and in any other public use of the data contained\nin or derived from the database.

\n

By accessing or copying any part of the database, the user accepts the terms of\nthis license. Anyone seeking to use the database for other purposes is required\nto contact The New York Times Company at covid-data@nytimes.com to obtain\npermission.

\n

The New York Times has made every effort to ensure the accuracy of the\ninformation. However, the database may contain typographic errors or\ninaccuracies and may not be complete or current at any given time. Licensees\nfurther agree to assume all liability for any claims that may arise from or\nrelate in any way to their use of the database and to hold The New York Times\nCompany harmless from any such claims.

\n","urlObject":{"path":["nytimes_covid"],"host":["https://api.covidcountydata.org"],"query":[{"disabled":true,"description":{"content":"

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The fips code corresponding to the observation

\n","type":"text/plain"},"key":"fips","value":"eq.12095"},{"disabled":true,"description":{"content":"

Denotes whether observation is total cases or total deaths

\n","type":"text/plain"},"key":"variable","value":""},{"disabled":true,"description":{"content":"

The value of the observation

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This table only includes the most recent observation for each date, location, and variable. If you are interested in historical revisions of this data, please reach out -- We have previous \"vintages\" of the USAFacts data but, in order to simplify our list of tables, we have chosen not to expose (but are happy to if it would be useful).

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The data only includes total number of cases and total number of COVID related deaths. If you use this data, we recommend that you read the corresponding documentation on their webpage as it provides useful insights to how the data were collected and how they should be used etc...

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The USAFacts COVID data can be found online at https://usafacts.org/visualizations/coronavirus-covid-19-spread-map/ and is released under the Creative Commons Share Alike 4.0 license:

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To see the terms of this license refer to https://creativecommons.org/licenses/by-sa/4.0/

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