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.

In an effort to help combat COVID-19, we created a COVID-19 Public Datasets program to make data more accessible to researchers, data scientists and analysts. The program will host a repository of public datasets that relate to the COVID-19 crisis and make them free to access and analyze. These include datasets from the New York Times, European Centre for Disease Prevention and Control, Google, Global Health Data from the World Bank, and OpenStreetMap. Free hosting and queries of COVID datasets As with all data in the Google Cloud Public Datasets Program , Google pays for storage of datasets in the program. BigQuery also provides free queries over certain COVID-related datasets to support the response to COVID-19. Queries on COVID datasets will not count against the BigQuery sandbox free tier , where you can query up to 1TB free each month. Limitations and duration Queries of COVID data are free. If, during your analysis, you join COVID datasets with non-COVID datasets, the bytes processed in the non-COVID datasets will be counted against the free tier, then charged accordingly, to prevent abuse. Queries of COVID datasets will remain free until Sept 15, 2021. The contents of these datasets are provided to the public strictly for educational and research purposes only. We are not onboarding or managing PHI or PII data as part of the COVID-19 Public Dataset Program. Google has practices & policies in place to ensure that data is handled in accordance with widely recognized patient privacy and data security policies. See the list of all datasets included in the program

This Master COVID-19 Dataset contains a combination of primary datasets (originally identified by the COVID-19 Task Force Strategic Analysis team and currently maintained by the PPL Metrics Team) grouped by factors, cleaned, and ready for on-demand analytics products. This list is organized into seven Factors, covering the range of first-order and second-order impacts, host country and donor responses, underlying vulnerabilities, and broader country contextual factors that are influencing and influenced by the COVID-19 crisis. The Factors are delineated by those pertaining to first-order impacts and second-order impacts, even though the two issue sets are highly interrelated. Note that this resource is internal to USAID.

Note: Authorizations to collect certain public health data expired at the end of the U.S. public health emergency declaration on May 11, 2023. The following jurisdictions discontinued COVID-19 case notifications to CDC: Iowa (11/8/21), Kansas (5/12/23), Kentucky (1/1/24), Louisiana (10/31/23), New Hampshire (5/23/23), and Oklahoma (5/2/23). Please note that these jurisdictions will not routinely send new case data after the dates indicated. As of 7/13/23, case notifications from Oregon will only include pediatric cases resulting in death.

This case surveillance public use dataset has 19 elements for all COVID-19 cases shared with CDC and includes demographics, geography (county and state of residence), any exposure history, disease severity indicators and outcomes, and presence of any underlying medical conditions and risk behaviors.

Currently, CDC provides the public with three versions of COVID-19 case surveillance line-listed data: this 19 data element dataset with geography, a 12 data element public use dataset, and a 33 data element restricted access dataset.

The following apply to the public use datasets and the restricted access dataset:

• Data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf.
• Data are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers.
• Some data are suppressed to protect individual privacy.
• Datasets will include all cases with the earliest date available in each record (date received by CDC or date related to illness/specimen collection) at least 14 days prior to the creation of the current datasets. This 14-day lag allows case reporting to be stabilized and ensure that time-dependent outcome data are accurately captured.
• Datasets are updated monthly.
• Datasets are created using CDC’s Policy on Public Health Research and Nonresearch Data Management and Access and include protections designed to protect individual privacy.
• For more information about data collection and reporting, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/about-us-cases-deaths.html.
• For more information about the COVID-19 case surveillance data, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html
  

Overview

The COVID-19 case surveillance database includes individual-level data reported to U.S. states and autonomous reporting entities, including New York City and the District of Columbia (D.C.), as well as U.S. territories and affiliates. On April 5, 2020, COVID-19 was added to the Nationally Notifiable Condition List and classified as “immediately notifiable, urgent (within 24 hours)” by a Council of State and Territorial Epidemiologists (CSTE) Interim Position Statement (Interim-20-ID-01). CSTE updated the position statement on August 5, 2020, to clarify the interpretation of antigen detection tests and serologic test results within the case classification (Interim-20-ID-02). The statement also recommended that all states and territories enact laws to make COVID-19 reportable in their jurisdiction, and that jurisdictions conducting surveillance should submit case notifications to CDC. COVID-19 case surveillance data are collected by jurisdictions and reported voluntarily to CDC.

For more information: NNDSS Supports the COVID-19 Response | CDC.

COVID-19 Case Reports COVID-19 case reports are routinely submitted to CDC by public health jurisdictions using nationally standardized case reporting forms. On April 5, 2020, CSTE released an Interim Position Statement with national surveillance case definitions for COVID-19. Current versions of these case definitions are available at: https://ndc.services.cdc.gov/case-definitions/coronavirus-disease-2019-2021/. All cases reported on or after were requested to be shared by public health departments to CDC using the standardized case definitions for lab-confirmed or probable cases. On May 5, 2020, the standardized case reporting form was revised. States and territories continue to use this form.

Data are Considered Provisional

• The COVID-19 case surveillance data are dynamic; case reports can be modified at any time by the jurisdictions sharing COVID-19 data with CDC. CDC may update prior cases shared with CDC based on any updated information from jurisdictions. For instance, as new information is gathered about previously reported cases, health departments provide updated data to CDC. As more information and data become available, analyses might find changes in surveillance data and trends during a previously reported time window. Data may also be shared late with CDC due to the volume of COVID-19 cases.
• Annual finalized data: To create the final NNDSS data used in the annual tables, CDC works carefully with the reporting jurisdictions to reconcile the data received during the year until each state or territorial epidemiologist confirms that the data from their area are correct.

Access Addressing Gaps in Public Health Reporting of Race and Ethnicity for COVID-19, a report from the Council of State and Territorial Epidemiologists, to better understand the challenges in completing race and ethnicity data for COVID-19 and recommendations for improvement.

Data Limitations

To learn more about the limitations in using case surveillance data, visit FAQ: COVID-19 Data and Surveillance.

Data Quality Assurance Procedures

CDC’s Case Surveillance Section routinely performs data quality assurance procedures (i.e., ongoing corrections and logic checks to address data errors). To date, the following data cleaning steps have been implemented:

• Questions that have been left unanswered (blank) on the case report form are reclassified to a Missing value, if applicable to the question. For example, in the question "Was the individual hospitalized?" where the possible answer choices include "Yes," "No," or "Unknown," the blank value is recoded to "Missing" because the case report form did not include a response to the question.
• Logic checks are performed for date data. If an illogical date has been provided, CDC reviews the data with the reporting jurisdiction. For example, if a symptom onset date in the future is reported to CDC, this value is set to null until the reporting jurisdiction updates the date appropriately.
• Additional data quality processing to recode free text data is ongoing. Data on symptoms, race, ethnicity, and healthcare worker status have been prioritized.

Data Suppression

To prevent release of data that could be used to identify people, data cells are suppressed for low frequency (<11 COVID-19 case records with a given values). Suppression includes low frequency combinations of case month, geographic characteristics (county and state of residence), and demographic characteristics (sex, age group, race, and ethnicity). Suppressed values are re-coded to the NA answer option; records with data suppression are never removed.

Additional COVID-19 Data

COVID-19 data are available to the public as summary or aggregate count files, including total counts of cases and deaths by state and by county. These and other COVID-19 data are available from multiple public locations: COVID Data Tracker; United States COVID-19 Cases and Deaths by State; COVID-19 Vaccination Reporting Data Systems; and COVID-19 Death Data and Resources.

Notes:

March 1, 2022: The "COVID-19 Case Surveillance Public Use Data with Geography" will be updated on a monthly basis.

April 7, 2022: An adjustment was made to CDC’s cleaning algorithm for COVID-19 line level case notification data. An assumption in CDC's algorithm led to misclassifying deaths that were not COVID-19 related. The algorithm has since been revised, and this dataset update reflects corrected individual level information about death status for all cases collected to date.

This repository attempts to assemble the largest Covid-19 epidemiological database in addition to a powerful set of expansive covariates. It includes open, publicly sourced, licensed data relating to demographics, economy, epidemiology, geography, health, hospitalizations, mobility, government response, weather, and more.

This particular dataset corresponds to a join of all the different tables that are part of the repository. Therefore, expect the resulting samples to be highly sparse.

To use this dataset:

import tensorflow_datasets as tfds

ds = tfds.load('covid19', split='train')
for ex in ds.take(4):
 print(ex)

See the guide for more informations on tensorflow_datasets.

This is the place to look for important information about how to use this dataset, so please expand this box and read on!

This is the source data for some of the metrics available at https://www.chicago.gov/city/en/sites/covid-19/home/latest-data.html.

For all datasets related to COVID-19, see https://data.cityofchicago.org/browse?limitTo=datasets&sortBy=alpha&tags=covid-19.

Only Chicago residents are included based on the home ZIP Code, as provided by the medical provider, or the address, as provided by the Cook County Medical Examiner.

Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted on the date the test specimen was collected. Deaths are those occurring among cases based on the day of death. Hospitalizations are based on the date of first hospitalization. Only one hospitalization is counted for each case. Demographic data are based on what is reported by medical providers or collected by CDPH during follow-up investigation.

Because of the nature of data reporting to CDPH, hospitalizations will be blank for recent dates They will fill in on later updates when the data are received, although, as for cases and deaths, may continue to be updated as further data are received.

All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects data currently known to CDPH.

Numbers in this dataset may differ from other public sources due to definitions of COVID-19-related cases, deaths, and hospitalizations, sources used, how cases, deaths and hospitalizations are associated to a specific date, and similar factors.

Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office

COVID-19 Projections

• Government-mandated social distancing
• Hospital resource use
• All beds
• ICU beds
• Invasive ventilators
• Deaths per day
• Total deaths

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.

Relation to Archived Dataset Prior to October 20, 2022, CDC collected aggregate case and death data at the state level. This data was compiled and published daily on data.cdc.gov in a dataset called United States COVID-19 Cases and Deaths by State over Time. As of 10/20/2022, this dataset has been archived and will no longer update.

Methodology Changes Several differences exist between the current, weekly-updated dataset and the archived version of the United States COVID-19 Cases and Deaths by State over Time dataset:

• 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

This data is synced hourly from https://github.com/CSSEGISandData/COVID-19. All credit is to them.

Latest Confirmed Cases

@(https://data.world/shad/covid-analysis/workspace/query?datasetid=covid-19-time-series-data&queryid=e066701e-fa8d-4c9f-97f8-aab3a6f219a8)

​

I have also added confirmed_pivot.csv which gives a slightly more workable view of the data. Extra columns/day makes things difficult.

@(https://data.world/shad/covid-analysis/workspace/file?datasetid=covid-19-time-series-data&filename=confirmed_pivot)

​

#

After Friday September 29th, 2023, as a result of changes in reporting cadence, this dataset will be updated twice a week on Wednesdays and Fridays. The following dataset provides state-aggregated data for hospital utilization in a timeseries format dating back to January 1, 2020. These are derived from reports with facility-level granularity across three main sources: (1) HHS TeleTracking, (2) reporting provided directly to HHS Protect by state/territorial health departments on behalf of their healthcare facilities and (3) National Healthcare Safety Network (before July 15). The file will be updated regularly and provides the latest values reported by each facility within the last four days for all time. This allows for a more comprehensive picture of the hospital utilization within a state by ensuring a hospital is represented, even if they miss a single day of reporting. No statistical analysis is applied to account for non-response and/or to account for missing data. The below table displays one value for each field (i.e., column). Sometimes, reports for a given facility will be provided to more than one reporting source: HHS TeleTracking, NHSN, and HHS Protect. When this occurs, to ensure that there are not duplicate reports, prioritization is applied to the numbers for each facility. On April 27, 2022 the following pediatric fields were added: all_pediatric_inpatient_bed_occupied all_pediatric_inpatient_bed_occupied_coverage all_pediatric_inpatient_beds all_pediatric_inpatient_beds_coverage previous_day_admission_pediatric_covid_confirmed_0_4 previous_day_admission_pediatric_covid_confirmed_0_4_coverage previous_day_admission_pediatric_covid_confirmed_12_17 previous_day_admission_pediatric_covid_confirmed_12_17_coverage previous_day_admission_pediatric_covid_confirmed_5_11 previous_day_admission_pediatric_covid_confirmed_5_11_coverage previous_day_admission_pediatric_covid_confirmed_unknown previous_day_admission_pediatric_covid_confirmed_unknown_coverage staffed_icu_pediatric_patients_confirmed_covid staffed_icu_pediatric_patients_confirmed_covid_coverage staffed_pediatric_icu_bed_occupancy staffed_pediatric_icu_bed_occupancy_coverage total_staffed_pediatric_icu_beds total_staffed_pediatric_icu_beds_coverage On January 19, 2022, the following fields have been added to this dataset: inpatient_beds_used_covid inpatient_beds_used_covid_coverage On September 17, 2021, this data set has had the following fields added: icu_patients_confirmed_influenza, icu_patients_confirmed_influenza_coverage, previous_day_admission_influenza_confirmed, previous_day_admission_influenza_confirmed_coverage, previous_day_deaths_covid_and_influenza, previous_day_deaths_covid_and_influenza_coverage, previous_day_deaths_influenza, previous_day_deaths_influenza_coverage, total_patients_hospitalized_confirmed_influenza, total_patients_hospitalized_confirmed_influenza_and_covid, total_patients_hospitalized_confirmed_influenza_and_covid_coverage, total_patients_hospitalized_confirmed_influenza_coverage On September 13, 2021, this data set has had the following fields added: on_hand_supply_therapeutic_a_casirivimab_imdevimab_courses, on_hand_supply_therapeutic_b_bamlanivimab_courses, on_hand_supply_therapeutic_c_bamlanivimab_etesevimab_courses, previous_week_therapeutic_a_casirivimab_imdevimab_courses_used, previous_week_therapeutic_b_bamlanivimab_courses_used, previous_week_therapeutic_c_bamlanivimab_etesevimab_courses_used On June 30, 2021, this data set has had the following fields added: deaths_covid deaths_covid_coverage On April 30, 2021, this data set has had the following fields added: previous_day_admission_adult_covid_confirmed_18-19 previous_day_admission_adult_covid_confirmed_18-19_coverage previous_day_admission_adult_covid_confirmed_20-2

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

The complete COVID-19 dataset is a collection of the COVID-19 data maintained by Our World in Data that is updated throughout the duration of COVID-19. It includes information related to confirmed cases and deaths, hospitalization, intensive care unit admissions, testing for COVID-19, and vaccination for COVID-19.Confirmed cases and deaths: this data is collected from the World Health Organization Coronavirus Dashboard. The cases & deaths dataset is updated daily.Note 1: Time/date stamps reflect when the data was last updated by WHO. Due to the time required to process and validate the incoming data, there is a delay between reporting to WHO and the update of the dashboard.Note 2: Counts and corrections made after these times will be carried forward to the next reporting cycle for that specific region. Delayed reporting for any specific country, territory or area may result in pooled counts for multiple days being presented, with a retrospective update to counts on previous days to accurately reflect trends. Significant data errors detected or reported to WHO may be corrected at more frequent intervals.Hospitalizations and intensive care unit (ICU) admissions: our data is collected from official sources and collated by Our World in Data. The complete list of country-by-country sources is available here.Testing for COVID-19: this data is collected by the Our World in Data team from official reports; you can find further details in our post on COVID-19 testing, including our checklist of questions to understand testing data, information on geographical and temporal coverage, and detailed country-by-country source information. On 23 June 2022, we stopped adding new datapoints to our COVID-19 testing dataset. You can read more here.Vaccinations against COVID-19: this data is collected by the Our World in Data team from official reports.Other variables: this data is collected from a variety of sources (United Nations, World Bank, Global Burden of Disease, Blavatnik School of Government, etc.). More information is available in our codebook.

Abstract

JHU Coronavirus COVID-19 Global Cases, by country

Documentation

PHS is updating the Coronavirus Global Cases dataset weekly, Monday, Wednesday and Friday from Cloud Marketplace.

This data comes from the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). This database was created in response to the Coronavirus public health emergency to track reported cases in real-time. The data include the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries, aggregated at the appropriate province or state. It was developed to enable researchers, public health authorities and the general public to track the outbreak as it unfolds. Additional information is available in the blog post.

Visual Dashboard (desktop): https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

Section 2

Included Data Sources are:

• World Health Organization (WHO): https://www.who.int/
• DXY.cn. Pneumonia. 2020. http://3g.dxy.cn/newh5/view/pneumonia.
• BNO News: https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/
• National Health Commission of the People’s Republic of China (NHC): http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml
• China CDC (CCDC): http://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm
• Hong Kong Department of Health: https://www.chp.gov.hk/en/features/102465.html
• Macau Government: https://www.ssm.gov.mo/portal/
• Taiwan CDC: https://sites.google.com/cdc.gov.tw/2019ncov/taiwan?authuser=0
• US CDC: https://www.cdc.gov/coronavirus/2019-ncov/index.html
• Government of Canada: https://www.canada.ca/en/public-health/services/diseases/coronavirus.html
• Australia Government Department of Health: https://www.health.gov.au/news/coronavirus-update-at-a-glance
• European Centre for Disease Prevention and Control (ECDC): https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases
• Ministry of Health Singapore (MOH): https://www.moh.gov.sg/covid-19
• Italy Ministry of Health: http://www.salute.gov.it/nuovocoronavirus
• 1Point3Arces: https://coronavirus.1point3acres.com/en
• WorldoMeters: https://www.worldometers.info/coronavirus/

%3C!-- --%3E

Section 3

**Terms of Use: **

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.

Section 4

**U.S. county-level characteristics relevant to COVID-19 **

Chin, Kahn, Krieger, Buckee, Balsari and Kiang (forthcoming) show that counties differ significantly in biological, demographic and socioeconomic factors that are associated with COVID-19 vulnerability. A range of publicly available county-specific data identifying these key factors, guided by international experiences and consideration of epidemiological parameters of importance, have been combined by the authors and are available for use:

https://github.com/mkiang/county_preparedness/

The COVID-19 Open Research Dataset is “a free resource of over 29,000 scholarly articles, including over 13,000 with full text, about COVID-19 and the coronavirus family of viruses for use by the global research community.”

in-the-news: On March 16, 2020, the White House issued a “call to action to the tech community” regarding the dataset, asking experts “to develop new text and data mining techniques that can help the science community answer high-priority scientific questions related to COVID-19.”

Included in this dataset: * Commercial use subset (includes PMC content) -- 9000 papers, 186Mb * Non-commercial use subset (includes PMC content) -- 1973 papers, 36Mb * PMC custom license subset -- 1426 papers, 19Mb * bioRxiv/medRxiv subset (pre-prints that are not peer reviewed) -- 803 papers, 13Mb

Each paper is represented as a single JSON object. The schema is available here.

We also provide a comprehensive metadata file of 29,000 coronavirus and COVID-19 research articles with links to PubMed, Microsoft Academic and the WHO COVID-19 database of publications (includes articles without open access full text): * Metadata file (readme) -- 47Mb

Source: https://pages.semanticscholar.org/coronavirus-research Updated: Weekly License: https://data.world/kgarrett/covid-19-open-research-dataset/workspace/file?filename=COVID.DATA.LIC.AGMT.pdf

See more COVID-19 data at data.world's Coronavirus (COVID-19) Data Resource Hub

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

CORD-19 is a free resource of tens of thousands of scholarly articles about COVID-19, SARS-CoV-2, and related coronaviruses for use by the global research community.

Note: This dataset is no longer being updated due to the end of the COVID-19 Public Health Emergency.

The California Department of Public Health (CDPH) is identifying ​the prevalence of circulating SARS-CoV-2 variants by analyzing ​CDPH Genomic Surveillance Data and ​CalREDIE, CDPH's communicable disease reporting and surveillance system. Viruses mutate into new strains or variants over time. Some variants emerge and then disappear. Other variants become common and circulate for a long time. Several specialized laboratories statewide sequence the genomes of a fraction of all positive COVID-19 tests to determine which variants are circulating. Sequencing and reporting of variant results takes several days after a test is identified as a positive for COVID-19. Not all ​viruses from positive COVID-19 tests are ​sequenced. Knowing what variants are circulating in California informs public health and clinical action.

Note: There is a natural reporting lag in these data due to the time commitment to complete whole genome sequencing; therefore, a 14 day lag is applied to these datasets to allow for data completeness. Please note that more recent data should be used with caution.

For more information, please see: https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/COVID-19/COVID-Variants.aspx

Full-text and metadata dataset of COVID-19 and coronavirus-related research articles optimized for machine readability.

This dataset is maintained by the European Centre for Disease Prevention and Control (ECDC) and reports on the geographic distribution of COVID-19 cases worldwide. This data includes COVID-19 reported cases and deaths broken out by country. This data can be visualized via ECDC’s Situation Dashboard . More information on ECDC’s response to COVID-19 is available here . This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery . This dataset is hosted in both the EU and US regions of BigQuery. See the links below for the appropriate dataset copy: US region EU region This dataset has significant public interest in light of the COVID-19 crisis. All bytes processed in queries against this dataset will be zeroed out, making this part of the query free. Data joined with the dataset will be billed at the normal rate to prevent abuse. After September 15, queries over these datasets will revert to the normal billing rate. Users of ECDC public-use data files must comply with data use restrictions to ensure that the information will be used solely for statistical analysis or reporting purposes.