The HCUP Visualization of Inpatient Trends in COVID-19 and Other Conditions displays State-specific monthly trends in inpatient stays related to COVID-19 and other conditions, and facilitates comparisons of the number of hospital discharges, the average length of stays, and in-hospital mortality rates across patient/stay characteristics and States. This information is based on the HCUP State Inpatient Databases (SID), starting with 2018 data, plus newer annual and quarterly inpatient data, if and when available.
Includes a staic and dynamic visualization of sample data of Covid Infections in London. Open: - static visualization of covid infections - dynamicCovidVisualization
The purpose of this code is to produce a line graph visualization of COVID-19 data. This Jupyter notebook was built and run on Google Colab. This code will serve mostly as a guide and will need to be adapted where necessary to be run locally. The separate COVID-19 datasets uploaded to this Dataverse can be used with this code. This upload is made up of the IPYNB and PDF files of the code.
This dataset tracks the updates made on the dataset "HCUP Visualization of Inpatient Trends in COVID-19 and Other Conditions" as a repository for previous versions of the data and metadata.
Analytics and Data Visualization for COVID-19 Intelligence.An ArcGIS Blog arcticle that explains how to leverage ready-to-use reports and tutorials to gauge COVID-19 pandemic's impact worldwide._Communities around the world are taking strides in mitigating the threat that COVID-19 (coronavirus) poses. Geography and location analysis have a crucial role in better understanding this evolving pandemic.When you need help quickly, Esri can provide data, software, configurable applications, and technical support for your emergency GIS operations. Use GIS to rapidly access and visualize mission-critical information. Get the information you need quickly, in a way that’s easy to understand, to make better decisions during a crisis.Esri’s Disaster Response Program (DRP) assists with disasters worldwide as part of our corporate citizenship. We support response and relief efforts with GIS technology and expertise.More information...
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Interactive data map of COVID-19 cases around the world. Shows number of total cases and deaths by country over time, starting from December 31, 2019 to present time.
Data visualizations of the COVID-19 pandemic in the United States often have presented case and death rates by state in separate visualizations making it difficult to discern the temporal relationship between these two epidemiological metrics. By combining the COVID-19 case and death rates into a single visualization we have provided an intuitive format for depicting the relationship between cases and deaths. Moreover, by using animation we have made the temporal lag between cases and subsequent deaths more obvious and apparent. This work helps to inform expectations for the trajectory of death rates in the United States given the recent surge in case rates.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
USA covid 19 dataset describes the situation of the country from early covid till early march of 2021.
the dataset comprises 17 columns and a huge number of rows.
check out the whole dataset and do whatever you want to.
https://www.usa.gov/government-workshttps://www.usa.gov/government-works
Note: Reporting of new COVID-19 Case Surveillance data will be discontinued July 1, 2024, to align with the process of removing SARS-CoV-2 infections (COVID-19 cases) from the list of nationally notifiable diseases. Although these data will continue to be publicly available, the dataset will no longer be updated.
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 12 elements for all COVID-19 cases shared with CDC and includes demographics, any exposure history, disease severity indicators and outcomes, presence of any underlying medical conditions and risk behaviors, and no geographic data.
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.
The deidentified data in the “COVID-19 Case Surveillance Public Use Data” include demographic characteristics, any exposure history, disease severity indicators and outcomes, clinical data, laboratory diagnostic test results, and presence of any underlying medical conditions and risk behaviors. All data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf.
COVID-19 case reports have been routinely submitted using nationally standardized case reporting forms. On April 5, 2020, CSTE released an Interim Position Statement with national surveillance case definitions for COVID-19 included. Current versions of these case definitions are available here: 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 laboratory-confirmed or probable cases. On May 5, 2020, the standardized case reporting form was revised. Case reporting using this new form is ongoing among U.S. states and territories.
To learn more about the limitations in using case surveillance data, visit FAQ: COVID-19 Data and Surveillance.
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:
To prevent release of data that could be used to identify people, data cells are suppressed for low frequency (<5) records and indirect identifiers (e.g., date of first positive specimen). Suppression includes rare combinations of demographic characteristics (sex, age group, race/ethnicity). Suppressed values are re-coded to the NA answer option; records with data suppression are never removed.
For questions, please contact Ask SRRG (eocevent394@cdc.gov).
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
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
AbstractThe dataset provided here contains the efforts of independent data aggregation, quality control, and visualization of the University of Arizona (UofA) COVID-19 testing programs for the 2019 novel Coronavirus pandemic. The dataset is provided in the form of machine-readable tables in comma-separated value (.csv) and Microsoft Excel (.xlsx) formats.Additional InformationAs part of the UofA response to the 2019-20 Coronavirus pandemic, testing was conducted on students, staff, and faculty prior to start of the academic year and throughout the school year. These testings were done at the UofA Campus Health Center and through their instance program called "Test All Test Smart" (TATS). These tests identify active cases of SARS-nCoV-2 infections using the reverse transcription polymerase chain reaction (RT-PCR) test and the Antigen test. Because the Antigen test provided more rapid diagnosis, it was greatly used three weeks prior to the start of the Fall semester and throughout the academic year.As these tests were occurring, results were provided on the COVID-19 websites. First, beginning in early March, the Campus Health Alerts website reported the total number of positive cases. Later, numbers were provided for the total number of tests (March 12 and thereafter). According to the website, these numbers were updated daily for positive cases and weekly for total tests. These numbers were reported until early September where they were then included in the reporting for the TATS program.For the TATS program, numbers were provided through the UofA COVID-19 Update website. Initially on August 21, the numbers provided were the total number (July 31 and thereafter) of tests and positive cases. Later (August 25), additional information was provided where both PCR and Antigen testings were available. Here, the daily numbers were also included. On September 3, this website then provided both the Campus Health and TATS data. Here, PCR and Antigen were combined and referred to as "Total", and daily and cumulative numbers were provided.At this time, no official data dashboard was available until September 16, and aside from the information provided on these websites, the full dataset was not made publicly available. As such, the authors of this dataset independently aggregated data from multiple sources. These data were made publicly available through a Google Sheet with graphical illustration provided through the spreadsheet and on social media. The goal of providing the data and illustrations publicly was to provide factual information and to understand the infection rate of SARS-nCoV-2 in the UofA community.Because of differences in reported data between Campus Health and the TATS program, the dataset provides Campus Health numbers on September 3 and thereafter. TATS numbers are provided beginning on August 14, 2020.Description of Dataset ContentThe following terms are used in describing the dataset.1. "Report Date" is the date and time in which the website was updated to reflect the new numbers2. "Test Date" is to the date of testing/sample collection3. "Total" is the combination of Campus Health and TATS numbers4. "Daily" is to the new data associated with the Test Date5. "To Date (07/31--)" provides the cumulative numbers from 07/31 and thereafter6. "Sources" provides the source of information. The number prior to the colon refers to the number of sources. Here, "UACU" refers to the UA COVID-19 Update page, and "UARB" refers to the UA Weekly Re-Entry Briefing. "SS" and "WBM" refers to screenshot (manually acquired) and "Wayback Machine" (see Reference section for links) with initials provided to indicate which author recorded the values. These screenshots are available in the records.zip file.The dataset is distinguished where available by the testing program and the methods of testing. Where data are not available, calculations are made to fill in missing data (e.g., extrapolating backwards on the total number of tests based on daily numbers that are deemed reliable). Where errors are found (by comparing to previous numbers), those are reported on the above Google Sheet with specifics noted.For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu
This dataset was created by Dhrumil Gohel
https://www.usa.gov/government-workshttps://www.usa.gov/government-works
Note: Reporting of new COVID-19 Case Surveillance data will be discontinued July 1, 2024, to align with the process of removing SARS-CoV-2 infections (COVID-19 cases) from the list of nationally notifiable diseases. Although these data will continue to be publicly available, the dataset will no longer be updated.
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 publicly available dataset has 33 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. This dataset requires a registration process and a data use agreement.
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.
COVID-19 case surveillance data are collected by jurisdictions and are shared voluntarily with CDC. For more information, visit: https://www.cdc.gov/coronavirus/2019-ncov/covid-data/about-us-cases-deaths.html.
The deidentified data in the restricted access dataset include demographic characteristics, state and county of residence, any exposure history, disease severity indicators and outcomes, clinical data, laboratory diagnostic test results, and comorbidities.
All data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf.
COVID-19 case reports have been routinely submitted using standardized case reporting forms.
On April 5, 2020, CSTE released an Interim Position Statement with national surveillance case definitions for COVID-19 included. Current versions of these case definitions are available here: https://ndc.services.cdc.gov/case-definitions/coronavirus-disease-2019-2021/.
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. 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. Case reporting using this new form is ongoing among U.S. states and territories.
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.
To learn more about the limitations in using case surveillance data, visit FAQ: COVID-19 Data and Surveillance.
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:
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.
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:
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This dataset focuses on Twitter engagement metrics related to the Coronavirus disease (COVID-19), an infectious disease caused by the SARS-CoV-2 virus [1]. It provides a detailed collection of tweets, including their text content, the accounts that posted them, any hashtags used, and the geographical locations associated with the accounts [1]. The dataset is valuable for understanding public discourse, information dissemination, and engagement patterns on Twitter concerning COVID-19, particularly for analysing how people experience mild to moderate symptoms and recover, or require medical attention [1].
The dataset is structured with daily tweet counts and covers a period from 10 January 2020 to 28 February 2020 [2, 6, 7]. It includes approximately 179,040 daily tweet entries during this timeframe, derived from the sum of daily counts and tweet ID counts [2, 3, 6-11]. Tweet activity shows distinct peaks, with notable increases in late January (e.g., 6,091 tweets between 23-24 January 2020) [2] and a significant surge in late February, reaching 47,643 tweets between 26-27 February 2020, followed by 42,289 and 44,824 in subsequent days [7, 10, 11]. The distribution of certain tweet engagement metrics, such as replies or retweets, indicates that a substantial majority of tweets (over 152,500 records) fall within lower engagement ranges (e.g., 0-43 or 0-1628.96), with fewer tweets showing very high engagement (e.g., only 1 record between 79819.04-81448.00) [4, 5]. The data file would typically be in CSV format [12].
This dataset is ideal for: * Data Science and Analytics projects focused on social media [1]. * Visualization of tweet trends and engagement over time. * Exploratory data analysis to uncover patterns in COVID-19 related discussions [1]. * Natural Language Processing (NLP) tasks, such as sentiment analysis or topic modelling on tweet content [1]. * Data cleaning and preparation exercises for social media data [1].
The dataset has a global geographic scope [13]. It covers tweet data from 10 January 2020 to 28 February 2020 [2, 6, 7]. The content is specific to the Coronavirus disease (COVID-19) [1].
CC0
This dataset is particularly useful for: * Data scientists and analysts interested in social media trends and public health discourse [1]. * Researchers studying information spread and public sentiment during health crises. * Developers building AI and LLM data solutions [13]. * Individuals interested in exploratory analysis and data visualization of real-world social media data [1].
Original Data Source: Covid_19 Tweets Dataset
Visual map at kumu.io/access2perspectives/covid19-resources
Data set doi: 10.5281/zenodo.3732377 // available in different formats (pdf, xls, ods, csv,)
Correspondence: (JH) info@access2perspectives.com
Objectives
Provide citizens with crucial and reliable information
Encourage and facilitate South South collaboration
Bridging language barriers
Provide local governments and cities with lessons learned about COVID-19 crisis response
Facilitate global cooperation and immediate response on all societal levels
Enable LMICs to collaborate and innovate across distances and leverage locally available and context-relevant resources
Methodology
The data feeding the map at kumu.io was compiled from online resources and information shared in various community communication channels.
Kumu.io is a visualization platform for mapping complex systems and to provide a deeper understanding of their intrinsic relationships. It provides blended systems thinking, stakeholder mapping, and social network analysis.
Explore the map // https://kumu.io/access2perspectives/covid19-resources#global
Click on individual nodes and view the information by country
info hotlines
governmental informational websites, Twitter feeds & Facebook pages
fact checking online resources
language indicator
DIY resources
clinical staff capacity building
etc.
With the navigation buttons to the right, you can zoom in and out, select and focus on specific elements.
If you have comments, questions or suggestions for improvements on this map email us at info@access2perspectives.com
Contribute
Please add data to the spreadsheet at https://tinyurl.com/COVID19-global-response
you can add additional information on country, city or neighbourhood level (see e.g. the Cape Town entry)
Related documents
Google Doc: tinyurl.com/COVID19-Africa-Response
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
The dataset data visualization contains information on where COVID-19 is spreading by tracking new cases found each day and the total number of cases and deaths in the US on the county-level. The data can be dowloaded and visualized on the website.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The datasets used for this manuscript were derived from multiple sources: Denver Public Health, Esri, Google, and SafeGraph. Any reuse or redistribution of the datasets are subjected to the restrictions of the data providers: Denver Public Health, Esri, Google, and SafeGraph and should consult relevant parties for permissions.1. COVID-19 case dataset were retrieved from Denver Public Health (Link: https://storymaps.arcgis.com/stories/50dbb5e7dfb6495292b71b7d8df56d0a )2. Point of Interests (POIs) data were retrieved from Esri and SafeGraph (Link: https://coronavirus-disasterresponse.hub.arcgis.com/datasets/6c8c635b1ea94001a52bf28179d1e32b/data?selectedAttribute=naics_code) and verified with Google Places Service (Link: https://developers.google.com/maps/documentation/javascript/reference/places-service)3. The activity risk information is accessible from Texas Medical Association (TMA) (Link: https://www.texmed.org/TexasMedicineDetail.aspx?id=54216 )The datasets for risk assessment and mapping are included in a geodatabase. Per SafeGraph data sharing guidelines, raw data cannot be shared publicly. To view the content of the geodatabase, users should have installed ArcGIS Pro 2.7. The geodatabase includes the following:1. POI. Major attributes are locations, name, and daily popularity.2. Denver neighborhood with weekly COVID-19 cases and computed regional risk levels.3. Simulated four travel logs with anchor points provided. Each is a separate point layer.
COVID-19 Time-Series Metrics by County and State Data is from the California COVID-19 State Dashboard at https://covid19.ca.gov/state-dashboard/
https://i0.wp.com/post.healthline.com/wp-content/uploads/2021/08/doctor-patient-covid-hospital-1296x728-header.jpg?w=1155&h=1528">
Statewide COVID-19 Cases Deaths TestsCSV Popular Statewide COVID-19 Cases Deaths Tests
Statewide COVID-19 Cases Deaths DemographicsCSV Popular State COVID-19 Cases Deaths Demographics
All resource dataZIP
COVID-19 Cases Deaths Tests Data DictionaryXLSX Popular
COVID-19 Cases Deaths Demographics Data DictionaryXLSX Popular
COVID-19 Response Data, Informatics, Surveillance, Clinical and Outbreaks (DISCO) Team
Last Updated : September 27, 2021, 1:00 AM (UTC+08:00)
More Source : https://data.ca.gov/dataset/covid-19-time-series-metrics-by-county-and-state1
The DATESET is of US-COUNTRIES for COVID19.
Prediction can be done for column CovidImpacted by choosing Deaths,confirmed cases by some algo and show the accuracy,performance etc
As because we are in COVID19 hope this DATA can be used for beginners,intermediate to work in it Hope it Helps!
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.
April 9, 2020
April 20, 2020
April 29, 2020
September 1st, 2020
February 12, 2021
new_deaths
column.February 16, 2021
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.
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.
The AP has designed an interactive map to track COVID-19 cases reported by Johns Hopkins.
@(https://datawrapper.dwcdn.net/nRyaf/15/)
<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>
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
This data should be credited to Johns Hopkins University COVID-19 tracking project
https://www.usa.gov/government-workshttps://www.usa.gov/government-works
Note: Reporting of new COVID-19 Case Surveillance data will be discontinued July 1, 2024, to align with the process of removing SARS-CoV-2 infections (COVID-19 cases) from the list of nationally notifiable diseases. Although these data will continue to be publicly available, the dataset will no longer be updated.
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:
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.
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.
To learn more about the limitations in using case surveillance data, visit FAQ: COVID-19 Data and Surveillance.
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:
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.
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.
June 25, 2024: An adjustment
The HCUP Visualization of Inpatient Trends in COVID-19 and Other Conditions displays State-specific monthly trends in inpatient stays related to COVID-19 and other conditions, and facilitates comparisons of the number of hospital discharges, the average length of stays, and in-hospital mortality rates across patient/stay characteristics and States. This information is based on the HCUP State Inpatient Databases (SID), starting with 2018 data, plus newer annual and quarterly inpatient data, if and when available.