During an online survey, *** percent of surveyed small businesses in the United States said they had temporarily closed a location due to the COVID-19 pandemic during the week ending April 17, 2022. Another *** percent of respondents said that they had opened a previously closed location during the same week.

Almost one quarter of all businesses have temporarily closed or paused trading due to the Coronavirus (COVID-19) pandemic in the United Kingdom as of April 2020. The sector with the highest share of business closures were those in the arts, entertainment, and recreation sector, with over ** percent of them currently closed, compared with just *** percent of human health, and social work businesses.

According to a survey fielded in Mexico in ***********, ** percent of respondents stated having to close their businesses as a result of the COVID-19 pandemic. This represents a noticeable decrease compared to April, when ** percent of participants said they had to shut down their businesses.

Up to ** percent of businesses were completely closed in January 2021, of which only *** percent remained shut down since the outbreak of the coronavirus (COVID-19). Up to ** percent of those also closed for at least *** month between June and December of the previous year, while the rest opened in December but closed again in January.

A substantial fraction of k-12 schools in the United States closed their in-person operations during the COVID-19 pandemic. These closures may have altered the labor supply decisions of parents of affected children due to a need to be at home with children during the school day. In this paper, we examine the impact of school closures on parental labor market outcomes. We test whether COVID-19 school closures have a disproportionate impact on parents of school-age children (ages 5-17 years old). Our results show that both women’s and men’s work lives were affected by school closures, with both groups seeing a reduction in work hours and the likelihood of working full-time but only women being less likely to work at all. We also find that closures had a corresponding negative effect on the earnings of parents of school-aged children. These effects are concentrated among parents without a college degree and parents working in occupations that do not lend themselves to telework, suggesting that such individuals had a more difficult time adjusting their work lives to school closures.

This layer is part of SDGs Today. Please see sdgstoday.orgAs the UN agency mandated to coordinate and lead on global education, UNESCO is tracking the evolution of COVID-19 caused closures of educational institutions and monitoring the policy responses deployed to mitigate impact. This includes tracking the timing and duration of closures and the number of students affected by level of education and sex. The data on closures and re-openings, as well as the number of impacted learners, are displayed on an interactive map. Updated on a monthly basis, the map shows the evolution of closures since mid-February 2020. Data on the evolution of school closures and re-openings is available for download. The map complements other efforts to collect timely data on educational disruption and response during the pandemic. These data have been widely cited in the media and are being used by partners in their responses to the COVID-19 crisis.For more information: ERF@unesco.org

Unplanned public K-12 school district and individual school closures due to COVID-19 in the United States from February 18–June 30, 2020.

This dataset records when and how Washington state's public library systems changed or suspended certain services at the beginning of the COVID-19 pandemic in the United States, culminating with the closure of library buildings to the public. The data reflects responses to an emerging public health emergency by institutions dedicated to public service and accessibility. Information comes primarily from library websites and social media accounts, and occasional communication with library staff.

Every day, schools, child care centres and licensed home child care agencies report to the Ministry of Education on children, students and staff that have positive cases of COVID-19.

If there is a discrepancy between numbers reported here and those reported publicly by a Public Health Unit, please consider the number reported by the Public Health Unit to be the most up-to-date.

Schools and school boards report when a school is closed to the Ministry of Education. Data is current as of 2:00 pm the previous day.

This dataset is subject to change.

Data is only updated on weekdays excluding provincial holidays

Effective June 15, 2022, board and school staff will not be expected to report student/staff absences and closures in the Absence Reporting Tool. The ministry will no longer report absence rates or school/child care closures on Ontario.ca for the remainder of the school year.

Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak.

Summary of school closures

This is a summary of school closures in Ontario.

Data includes:

• Number of schools closed
• Total number of schools
• Percentage of schools closed

School Absenteeism

This report provides a summary of schools and school boards that have reported staff and student absences.

Data includes:

• School board
• School
• City or Town
• Percentage of staff and students who are absent

Summary of cases in schools

This report provides a summary of COVID-19 activity in publicly-funded Ontario schools.

Data includes:

• School-related cases (total)
• School-related student cases
• School-related staff cases
• Current number of schools with a reported case
• Current number of schools closed

Note: In some instances the type of cases are not identified due to privacy considerations.

Schools with active COVID-19 cases

This report lists schools and school boards that have active cases of COVID-19.

Data includes :

• School Board
• School
• Municipality
• Confirmed Student Cases
• Confirmed Staff Cases
• Total Confirmed Cases

Cases in school board partners

This report lists confirmed active cases of COVID-19 for other school board partners (e.g. bus drivers, authorized health professionals etc.) and will group boards if there is a case that overlaps.

Data includes :

• School Board(s)
• School Municipality
• Confirmed cases – other school board partners

Summary of targeted testing conducted in schools

This data includes all tests that have been reported to the Ministry of Education since February 1, 2021. School boards and other testing partners will report to the Ministry every Wednesday based on data from the previous seven days.

Data includes : * School boards or regions * Number of schools invited to participate in the last seven days * Total number of tests conducted in the last seven days * Cumulative number of tests conducted * Number of new cases identified in the last seven days * Cumulative number of cases identified

Summary of asymptomatic testing at conducted in pharmacies:

This is a summary of COVID-19 rapid antigen testing conducted at participating pharmacies in Ontario since March 27, 2021.

• Total number of tests conducted in the last seven days
• Cumulative number of tests conducted
• Number of new cases identified in the last seven days
• Cumulative number of cases identified

This survey by the United Nations Educational, Scientific and Cultural Organization (UNESCO), the United Nations Children's Fund (UNICEF) and the World Bank seeks to collect information on national education responses to school closures related to the COVID-19 pandemic. The questionnaire is designed for Ministry of Education officials at central or decentralized level in charge of school education. The questionnaire does not cover higher education or technical and vocational education and training. Analysis of results will allow for policy learning across the diversity of country settings in order to better inform local/national responses and prepare for the reopening of schools. The survey will be run on a regular basis to ensure that the latest impact and responses are captured. In light of the current education crisis, the COVID-19 education response coordinated by UNESCO with our partners is deemed urgent. A first wave of data collection started in May and lasted until mid-June 2020. A second wave of data collection will start at the beginning of July. A link to the online survey questionnaire, as well as other formats, will be available shortly.

The number of children, youth and adults not attending schools or universities because of COVID-19 is soaring. Governments all around the world have closed educational institutions in an attempt to contain the global pandemic.

According to UNESCO monitoring, over 100 countries have implemented nationwide closures, impacting over half of world’s student population. Several other countries have implemented localized school closures and, should these closures become nationwide, millions of additional learners will experience education disruption.

This data is compiled by the UNESCO and distributed by HDX.

According to a survey conducted in February 2022, around *** percent of small to medium-sized companies in Japan foresaw a likelihood of discontinuation of their business activities due to the impact of the coronavirus (COVID-19) outbreak. By comparison, about *** percent of large business enterprises reported the potential closing down.

This dataset is no longer being updated as of 7/1/2021. It is being retained on the Open Data Portal for its potential historical interest.

A list of retail stores, restaurants, personal services and other businesses open and closed during the COVID-19 pandemic. Also indicates if business is offering delivery, pick up or on-line sales.

Updated at least biweekly during Covid-19 Pandemic.

Updated weekly Public Health — Seattle & King County is monitoring changes in key economic, social, and other health indicators resulting from strategies to slow the spread of COVID-19. The metrics below were selected based on studies from previous outbreaks, which have linked strategies such as social distancing, school closures, and business closures to specific outcomes. Individual indicators in the grid below are updated daily, weekly, or monthly, depending on the source of data. Additional data will be added over time.

From the project page: https://covid19.uis.unesco.org/global-monitoring-school-closures-covid19/

The COVID-19 crisis has significantly affected the education sector across all regions. The closing of schools has interrupted the functioning of the system, reducing student learning, and restricting the activities of education authorities, parents, and decision-makers. As the pandemic progresses, many important decisions need to be made based on a systematic understanding of deployed policies up to date.

UNESCO has monitored in a daily basis the status of the schooling system according to the closures of school and the methods selected for delivery across the world since the outbreak of the pandemic

These dashboards present the status of school closures by region and country and the status of the delivery of classes in two dashboards, one by region and the other by country.

Changes businesses have made to adapt to the COVID-19 pandemic, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership.

The Research and Development Survey (RANDS) is a platform designed for conducting survey question evaluation and statistical research. RANDS is an ongoing series of surveys from probability-sampled commercial survey panels used for methodological research at the National Center for Health Statistics (NCHS). RANDS estimates are generated using an experimental approach that differs from the survey design approaches generally used by NCHS, including possible biases from different response patterns and sampling frames as well as increased variability from lower sample sizes. Use of the RANDS platform allows NCHS to produce more timely data than would be possible using traditional data collection methods. RANDS is not designed to replace NCHS’ higher quality, core data collections. Below are experimental estimates of loss of work due to illness with coronavirus for three rounds of RANDS during COVID-19. Data collection for the three rounds of RANDS during COVID-19 occurred between June 9, 2020 and July 6, 2020, August 3, 2020 and August 20, 2020, and May 17, 2021 and June 30, 2021. Information needed to interpret these estimates can be found in the Technical Notes. RANDS during COVID-19 included a question about the inability to work due to being sick or having a family member sick with COVID-19. The National Health Interview Survey, conducted by NCHS, is the source for high-quality data to monitor work-loss days and work limitations in the United States. For example, in 2018, 42.7% of adults aged 18 and over missed at least 1 day of work in the previous year due to illness or injury and 9.3% of adults aged 18 to 69 were limited in their ability to work or unable to work due to physical, mental, or emotional problems. The experimental estimates on this page are derived from RANDS during COVID-19 and show the percentage of U.S. adults who did not work for pay at a job or business, at any point, in the previous week because either they or someone in their family was sick with COVID-19. Technical Notes: https://www.cdc.gov/nchs/covid19/rands/work.htm#limitations

The indicators and analysis presented in this bulletin are based on responses from the new voluntary fortnightly business survey, which captures businesses responses on how their turnover, workforce prices, trade and business resilience have been affected in the two week reference period. These data relate to the period 6 April 2020 to 19 April 2020.

COVID-19 Stats & Trends

Context

This dataset seeks to provide insights into what has changed due to policies aimed at combating COVID-19 and evaluate the changes in community activities and its relation to reduced confirmed cases of COVID-19. The reports chart movement trends, compared to an expected baseline, over time (from 2020/02/15 to 2020/02/05) by geography (across 133 countries), as well as some other stats about the country that might help explain the evolution of the disease.

Content

1. Grocery & Pharmacy: Mobility trends for places like grocery markets, food warehouses, farmers' markets, specialty food shops, drug stores, and pharmacies.
2. Parks: Mobility trends for places like national parks, public beaches, marinas, dog parks, plazas, and public gardens.
3. Residential: Mobility trends for places of residence.
4. Retail & Recreation: Mobility trends for places like restaurants, cafes, shopping centers, theme parks, museums, libraries, and movie theaters.
5. Transit stations: Mobility trends for places like public transport hubs such as subway, bus, and train stations.
6. Workplaces: Mobility trends for places of work.
7. Total Cases: Total number of people infected with the SARS-CoV-2.
8. Fatalities: Total number of deaths caused by CoV-19.
9. Government Response Stringency Index: Additive score of nine indicators of government response to CoV-19: School closures, workplace closures, cancellation of public events, public information campaigns, stay at home policies, restrictions on internal movement, international travel controls, testing policy, and contact tracing.
10. COVID-19 Testing: Total number of tests performed.
11. Total Vaccinations: Total number of shots given.
12. Total People Vaccinated: Total number of people given a shot.
13. Total People Fully Vaccinated: Total number of people fully vaccinated (might require two shots of some vaccines).
14. Population: Total number of inhabitants.
15. Population Density per km2: Number of human inhabitants per square kilometer.
16. Health System Index: Overall performance of the health system.
17. Human Development Index (HDI): Summary index based on life expectancy at birth, expected years of schooling for children and mean years of schooling for adults, and GNI per capita.
18. GDP (PPP) per capita: Gross Domestic Product (GDP) per capita based on Purchasing Power Parity (PPP), taking into account the relative cost of local goods, services and inflation rates of the country, rather than using international market exchange rates, which may distort the real differences in per capita income.
19. Elderly Population (percentage): Percentage of the population above the age of 65 years old.

References & Acknowledgements

Bing COVID-19 data. Available at: https://github.com/microsoft/Bing-COVID-19-Data COVID-19 Community Mobility Report. Available at: https://www.google.com/covid19/mobility/ COVID-19: Government Response Stringency Index. Available at: https://ourworldindata.org/grapher/covid-stringency-index Coronavirus (COVID-19) Testing. Available at: https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-all-observations.csv Coronavirus (COVID-19) Vaccination. Available at: https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/vaccinations/vaccinations.csv List of countries and dependencies by population. Available at: https://www.kaggle.com/tanuprabhu/population-by-country-2020 List of countries and dependencies by population density. Available at: https://www.kaggle.com/tanuprabhu/population-by-country-2020 List of countries by Human Development Index. Available at: http://hdr.undp.org/en/data Measuring Overall Health System Performance. Available at: https://www.who.int/healthinfo/paper30.pdf?ua=1 List of countries by GDP (PPP) per capita. Available at: https://data.worldbank.org/indicator/NY.GDP.PCAP.PP.CD List of countries by age structure (65+). Available at: https://data.worldbank.org/indicator/SP.POP.65UP.TO.ZS

Authors

• Diogo Silva, up201706892@fe.up.pt