After May 3, 2024, this dataset and webpage will no longer be updated because hospitals are no longer required to report data on COVID-19 hospital admissions, and hospital capacity and occupancy data, to HHS through CDC’s National Healthcare Safety Network. Data voluntarily reported to NHSN after May 1, 2024, will be available starting May 10, 2024, at COVID Data Tracker Hospitalizations. This report shows data completeness information on data submitted by hospitals for the previous week, from Friday to Thursday. The U.S. Department of Health and Human Services requires all hospitals licensed to provide 24-hour care to report certain data necessary to the all-of-America COVID-19 response. The report includes the following information for each hospital: The percentage of mandatory fields reported. The number of days in the preceding week where 100% of the fields were completed. Whether a hospital is required to report on Wednesdays only. A cell for each required field with the number of days that specific field was reported for the week. Hospitals are key partners in the Federal response to COVID-19, and this report is published to increase transparency into the type and amount of data being successfully reported to the U.S. Government. 9/12/2021 - Added a Summary page and broke out the attached Excel, tabbed spreadsheet into its own reports. You can access the Summary page with this link: https://healthdata.gov/stories/s/ws49-ddj5 6/17/2023 - With the new 28-day compliance reporting period, CoP reports will be posted every 4 weeks. Source: HHS Protect, U.S. Department of Health & Human Services

To create the dataset, the top 10 countries leading in the incidence of COVID-19 in the world were selected as of October 22, 2020 (on the eve of the second full of pandemics), which are presented in the Global 500 ranking for 2020: USA, India, Brazil, Russia, Spain, France and Mexico. For each of these countries, no more than 10 of the largest transnational corporations included in the Global 500 rating for 2020 and 2019 were selected separately. The arithmetic averages were calculated and the change (increase) in indicators such as profitability and profitability of enterprises, their ranking position (competitiveness), asset value and number of employees. The arithmetic mean values of these indicators for all countries of the sample were found, characterizing the situation in international entrepreneurship as a whole in the context of the COVID-19 crisis in 2020 on the eve of the second wave of the pandemic. The data is collected in a general Microsoft Excel table. Dataset is a unique database that combines COVID-19 statistics and entrepreneurship statistics. The dataset is flexible data that can be supplemented with data from other countries and newer statistics on the COVID-19 pandemic. Due to the fact that the data in the dataset are not ready-made numbers, but formulas, when adding and / or changing the values in the original table at the beginning of the dataset, most of the subsequent tables will be automatically recalculated and the graphs will be updated. This allows the dataset to be used not just as an array of data, but as an analytical tool for automating scientific research on the impact of the COVID-19 pandemic and crisis on international entrepreneurship. The dataset includes not only tabular data, but also charts that provide data visualization. The dataset contains not only actual, but also forecast data on morbidity and mortality from COVID-19 for the period of the second wave of the pandemic in 2020. The forecasts are presented in the form of a normal distribution of predicted values and the probability of their occurrence in practice. This allows for a broad scenario analysis of the impact of the COVID-19 pandemic and crisis on international entrepreneurship, substituting various predicted morbidity and mortality rates in risk assessment tables and obtaining automatically calculated consequences (changes) on the characteristics of international entrepreneurship. It is also possible to substitute the actual values identified in the process and following the results of the second wave of the pandemic to check the reliability of pre-made forecasts and conduct a plan-fact analysis. The dataset contains not only the numerical values of the initial and predicted values of the set of studied indicators, but also their qualitative interpretation, reflecting the presence and level of risks of a pandemic and COVID-19 crisis for international entrepreneurship.

As part of an ongoing partnership with the Census Bureau, the National Center for Health Statistics (NCHS) recently added questions to assess the prevalence of post-COVID-19 conditions (long COVID), on the experimental Household Pulse Survey. This 20-minute online survey was designed to complement the ability of the federal statistical system to rapidly respond and provide relevant information about the impact of the coronavirus pandemic in the U.S. Data collection began on April 23, 2020. Beginning in Phase 3.5 (on June 1, 2022), NCHS included questions about the presence of symptoms of COVID that lasted three months or longer. Phase 3.5 will continue with a two-weeks on, two-weeks off collection and dissemination approach.

Estimates on this page are derived from the Household Pulse Survey and show the percentage of adults aged 18 and over who a) as a proportion of the U.S. population, the percentage of adults who EVER experienced post-COVID conditions (long COVID). These adults had COVID and had some symptoms that lasted three months or longer; b) as a proportion of adults who said they ever had COVID, the percentage who EVER experienced post-COVID conditions; c) as a proportion of the U.S. population, the percentage of adults who are CURRENTLY experiencing post-COVID conditions. These adults had COVID, had long-term symptoms, and are still experiencing symptoms; d) as a proportion of adults who said they ever had COVID, the percentage who are CURRENTLY experiencing post-COVID conditions; and e) as a proportion of the U.S. population, the percentage of adults who said they ever had COVID.

This 20MB download is a zip file containing 1 docx document and 2 xlsx spreadsheets.Waka Kotahi has been running an ongoing study across New Zealand for the effects of COVID-19 on transport choices. The study started on 3 April 2020 and runs for 28 waves, with the final wave scheduled to take place in late 2021. This market research analysis was conducted by Ipsos, with the results data kept in the Harmoni application by Infotools, an external vendor.

We have created summarised tables from this data, in the form of an Excel spreadsheet, for release as open data. The data records how New Zealanders felt, behaved and travelled under the different COVID-19 alert levels.The data tables from the study, to allow you to do your own analysis. We have already made analysed data from this study available as reports on the Waka Kotahi website.Read 'covid-19 impacts on transport' reportsComplete open dataset: click on the download button for a .zip file containing this item.

Watch our video about the impacts of COVID-19 on New Zealanders' transport choices

Data reuse caveats: as per license. Additionally, this data is from research currently being undertaken by Ipsos on behalf of Waka Kotahi NZ Transport Agency. While Waka Kotahi provided investment, the research was undertaken independently, and the resulting findings should not be regarded as being the opinion, responsibility or policy of Waka Kotahi or indeed of any NZ Government agency. We have removed the data for sample sizes of fewer than 60 people, to protect privacy. Data quality statement: high level of confidence.

Data quality caveats: none known.

Other metadata: technical report - click on the download button for a .zip file containing this itemquestionnaire changes tracking log - click on the download button for a .zip file containing this item.

The data contained in the table describes COVID-19 in Canada in terms of number of cases and deaths at the provincial and national levels from January 31, 2020 to present time. It also describes the number of tests performed and the number of people recovered. The values displayed in the table are provided by the Public Health Infobase, managed by the Health Promotion and Chronic Disease Prevention Branch (HPCDPB) of the Public Health Agency of Canada (PHAC). The values are updated daily.

We are unable to share the transcripts due to ethical restrictions. The dataset that can be requested contains a list of participants' quotes and their ID, and demographics (parent gender and age range of children) in a excel spreadsheet. The quotes have been anonymised, therefore, they do not contain any information that can identify the participant, such as locations, parent and child names, parent and child ages, employment information, specific medical information have all been removed. Additional information has been removed for some participants where their quotes provide potentially identifiable information due to what has been disclosed in their interview. Between 40 and 75 quotes are listed for each participant, and 997 in total.

In July and August 2020, Malala Fund and our Education Champions Network conducted a rapid assessment survey of girls' experiences of COVID-19 school closures in Ethiopia, India, Nigeria and Pakistan. Our team distributed questionnaires that we administered using both door-to-door and telephonic interviews in compliance with the various regulations imposed by national governments. These were structured around three critical areas of inquiry for parents: i) social and demographic profile of the household, ii) economic status of the family, and iii) the kind of support the household received from the education department, governments and civil society — and three for children: i) educational profile of the child, ii) access to and use of technology, and iii) time use.

This repository contains the raw dataset associated to the scientific article "Stable psychological traits predict psychological perceived stress to COVID-19 outbreak”, by L. Flesia, V. Fietta, B. Segatto, M. Monaro. Data are contained in the excel file and organized as follows:

- the entire dataset used by the authors to perform statistical analysis

- the training set used by the authors to train and validate ML models

- the test set used by the authors to test the ML models

The "Legend" file contains the description of each variable in the excel file.

The step by step instructions to replicate the results of ML classification models, which are reported in the paper, including two .arff files containing the training and test set od data that can be directly run in WEKA software 3.9.

The "COVID-19 QUESTIONNAIRE" file contains the English version of the questions administered to participants.

Cameroon recorded 125036 Coronavirus Cases since the epidemic began, according to the World Health Organization (WHO). In addition, Cameroon reported 1972 Coronavirus Deaths. This dataset includes a chart with historical data for Cameroon Coronavirus Cases.

Data files related to the manuscript Perspectives and experiences of Covid-19: Two Irish studies of families in disadvantaged communities. The manuscript includes two studies. The following materials are shared below.

Study 1:

- Qualitative data (Microsoft Office Excel file)

- Codebook for coding the qualitative data developed through content analysis (pdf file)

Study 2:

- Qualitative data (Microsoft Office Excel file)

Data are named using the following naming convention: Project acronym_Date (YYYYMMDD)_Study_Type of data_Type of participant_Version number of the file.

Both studies in the manuscript were developed by the Childhood Development Initiative (CDI), Dublin, Ireland. Study 1 was conducted within the project PEAR_EC, that has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 890925. Study 2 was conducted within the Child Poverty research project, funded by Tusla under the Area Based Childhood funding and the Child and Youth Participation Initiatives grant.

Description

This repository includes: 1) Data scraper of Google, Apple and Waze Mobility data 2) Preprocessed mobility reports in different formats 3) Merged mobility reports in summary files

About data

About Google COVID-19 Community Mobility Reports

About Apple COVID-19 Mobility Trends Reports

About Waze COVID-19 local driving trends

Description of data files

Google reports (located in google_reports directory):

The raw report in ZIP format: Global_Mobility_Report.zip Data for the worldwide (only 1st level of subregions): mobility_report_countries (CSV and Excel formats available) Data for Brazil: mobility_report_brazil (CSV and Excel formats available) Data for Europe: mobility_report_europe (CSV and Excel formats available) Data for Asia + Africa: mobility_report_asia_africa (CSV and Excel formats available) Data for North and South America + Oceania (Brazil and US excluded): mobility_report_america_oceania (CSV and Excel formats available)

Apple reports (located in apple_reports directory):

Raw report: applemobilitytrends.csv Data for the worldwide: apple_mobility_report (Google Sheets, CSV and Excel formats available) Data for the US: apple_mobility_report_US (CSV and Excel formats available)

Waze reports (located in waze_reports directory):

Raw CSV files: Waze_Country-Level_Data.csv, Waze_City-Level_Data.csv Preprocessed report: waze_mobility (Google Sheets, CSV and Excel formats available)

Summary reports (located in summary_reports directory)

These are merged Apple and Google reports.

Report by regions: summary_report_regions (CSV and Excel formats available) Report by countries: summary_report_countries (Google Sheets, CSV and Excel formats available) Report for the US: summary_report_US (CSV and Excel formats available)

License

See LICENSE.txt

Credits

If you use this dataset, please also cite the original data sources:

1. Google LLC "Google COVID-19 Community Mobility Reports". https://www.google.com/covid19/mobility/ Accessed:

2. Apple Inc. "Apple COVID-19 Mobility Trends Reports". https://www.apple.com/covid19/mobility Accessed:

3. Waze Ltd "Waze COVID-19 Impact Dashboard". https://www.waze.com/covid19 Accessed:

Submitted data as of the week ending 11/28/2021. The Nursing Home COVID-19 Public File includes data reported by nursing homes to the CDC’s National Healthcare Safety Network (NHSN) Long Term Care Facility (LTCF) COVID-19 Module: Surveillance Reporting Pathways and COVID-19 Vaccinations. For resources and ways to explore and visualize the data, please see the links to the left, as well as the buttons at the top of the page. Please note: Starting with week ending 9/12/2021, the full downloadable file has become too large to open in most spreadsheet programs, including Microsoft Excel. If you require smaller files, you can use the links below to download 2020 and 2021 data separately: Dataset for 2020 Dataset for 2021

Downloadable Excel file of COVID data summary tables. Managed by the State of Alaska Department of Health and Social Services.

This data package includes the sources, underlying data, and Excel files to replicate the charts and tables presented in How COVID-19 vaccine supply chains emerged in the midst of a pandemic, PIIE Working Paper 21-12.

If you use the data, please cite as: Bown, Chad P., and Thomas J. Bollyky, How COVID-19 vaccine supply chains emerged in the midst of a pandemic, PIIE Working Paper 21-12, August 2021, Peterson Institute for International Economics.

The COVID Analysis and Mapping of Policies (AMP) dataset is a research effort performed by researchers at the Georgetown University Center for Global Health Science and Security. This pre-print version of the COVID AMP database is an Excel file (.xlsx) which includes a library of nearly 50,000 policies from January 2020 - June 2022, collected from U.S. states and the District of Columbia, US local governments (counties, cities) and national governments globally.

In addition to the policies themselves, the COVID-AMP policy database contains a comprehensive set of metadata describing the governing authority, the type of policy measure, the policy's intentions, and an analysis of the legal authority under which the policy is enacted. A Data Dictionary is included in the file download.

Raw, original data and fits data set for "A Simple Model to Predict Future SARS-CoV-2 Infections on a National Level" by Blanco et al. in EXCEL and GraphPad Prism file formats.

Note: In these datasets, a person is defined as up to date if they have received at least one dose of an updated COVID-19 vaccine. The Centers for Disease Control and Prevention (CDC) recommends that certain groups, including adults ages 65 years and older, receive additional doses.

On 6/16/2023 CDPH replaced the booster measures with a new “Up to Date” measure based on CDC’s new recommendations, replacing the primary series, boosted, and bivalent booster metrics The definition of “primary series complete” has not changed and is based on previous recommendations that CDC has since simplified. A person cannot complete their primary series with a single dose of an updated vaccine. Whereas the booster measures were calculated using the eligible population as the denominator, the new up to date measure uses the total estimated population. Please note that the rates for some groups may change since the up to date measure is calculated differently than the previous booster and bivalent measures.

This data is from the same source as the Vaccine Progress Dashboard at https://covid19.ca.gov/vaccination-progress-data/ which summarizes vaccination data at the county level by county of residence. Where county of residence was not reported in a vaccination record, the county of provider that vaccinated the resident is included. This applies to less than 1% of vaccination records. The sum of county-level vaccinations does not equal statewide total vaccinations due to out-of-state residents vaccinated in California.

These data do not include doses administered by the following federal agencies who received vaccine allocated directly from CDC: Indian Health Service, Veterans Health Administration, Department of Defense, and the Federal Bureau of Prisons.

Totals for the Vaccine Progress Dashboard and this dataset may not match, as the Dashboard totals doses by Report Date and this dataset totals doses by Administration Date. Dose numbers may also change for a particular Administration Date as data is updated.

Previous updates:

• On March 3, 2023, with the release of HPI 3.0 in 2022, the previous equity scores have been updated to reflect more recent community survey information. This change represents an improvement to the way CDPH monitors health equity by using the latest and most accurate community data available. The HPI uses a collection of data sources and indicators to calculate a measure of community conditions ranging from the most to the least healthy based on economic, housing, and environmental measures.

• Starting on July 13, 2022, the denominator for calculating vaccine coverage has been changed from age 5+ to all ages to reflect new vaccine eligibility criteria. Previously the denominator was changed from age 16+ to age 12+ on May 18, 2021, then changed from age 12+ to age 5+ on November 10, 2021, to reflect previous changes in vaccine eligibility criteria. The previous datasets based on age 16+ and age 5+ denominators have been uploaded as archived tables.

• Starting on May 29, 2021 the methodology for calculating on-hand inventory in the shipped/delivered/on-hand dataset has changed. Please see the accompanying data dictionary for details. In addition, this dataset is now down to the ZIP code level.

Subject: EducationSpecific: Online Learning and FunType: Questionnaire survey data (csv / excel)Date: February - March 2020Content: Students' views about online learning and fun Data Source: Project OLAFValue: These data provide students' beliefs about how learning occurs and correlations with fun. Participants were 206 students from the OU

Analysis of ‘COVID-19 Hospital Data Coverage Report’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/ab731f27-6d4a-4ad5-b31b-84f0e2cebbb1 on 11 February 2022.

--- Dataset description provided by original source is as follows ---

This report shows data completeness information on data submitted by hospitals for the previous week, from Friday to Thursday. The U.S. Department of Health and Human Services requires all hospitals licensed to provide 24-hour care to report certain data necessary to the all-of-America COVID-19 response. The report includes the following information for each hospital:

• The percentage of mandatory fields reported.
• The number of days in the preceding week where 100% of the fields were completed.
• Whether a hospital is required to report on Wednesdays only.
• A cell for each required field with the number of days that specific field was reported for the week.