Between February 2020 and March 2022, Indonesia had the longest overall duration of school closures among the selected Southeast Asian countries, *** days, *** of which were full closures. At *** days, the Philippines had the highest amount of full school closure days during this period.

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.

Context

World Bank Education COVID-19 School Closures

https://www.worldbank.org/en/data/interactive/2020/03/24/world-bank-education-and-covid-19

Content

Number of countries by information status as of 15/03/2021 09:51:25 Number of Students in countries with fully closed schools Number of Students in countries with partially closed schools

https://www.worldbank.org/en/data/interactive/2020/03/24/world-bank-education-and-covid-19

Acknowledgements

https://www.worldbank.org/en/data/interactive/2020/03/24/world-bank-education-and-covid-19

Photo by Nathan Dumlao on Unsplash

Inspiration

School closures during the Covid-19 Pandemic.

As of February 2021, there were *** days of full school closures due to the coronavirus (COVID-19) in Myanmar, more than in any other country in the Asia-Pacific region. With a total of *** days, India had the highest amount of full and partial school closures in that same period. Countries with comparatively longer school closures such as Myanmar, Indonesia, and the Philippines performed rather poorly in a survey on satisfaction rate with local education conducted in 2020 and early 2021.

As of March 2021, nearly 682 million students all across the globe lived in countries with closed schools due to the outbreak of the coronavirus (COVID-19). Furthermore, schools were partially open for around 92 millions students worldwide. In 57 countries schools were closed during that same, while in 95 countries schools remained open with limitations.

This article discusses the question of data, and our perspective on the importance of public, accessible, and contemporaneous data in the face of public crisis. Then, we present data on the extent of school closures, both globally and within the United States. We describe the available data on the degree of these closures, which will provide a set of resources for studying longer-term consequences as they emerge. We also highlight what we know about the demographic patterns of school closures. We then discuss the emerging estimates of the short-term impacts of school closures. A central finding throughout our discussion is that school closures during the pandemic tended to increase inequality, both within and across countries. We also emphasize that fully understanding the long-run impact of COVID-related school closures on students will take time and will surely be influenced by events and policies in the next few years.

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.

According to a survey from 2021, 76 percent of the respondents in Singapore were accepting of the school closures in order to prevent COVID-19 transmissions. In comparison, 38 percent of the respondents in South Korea accepted the school closures due to COVID-19.

In many high-income economies, the recession caused by the Covid-19 pandemic has resulted in unprecedented declines in women’s employment. We examine how the forces that underlie this observation play out in developing countries, with a specific focus on Nigeria, the most populous country in Africa. A force affecting high- and low-income countries alike are increased childcare needs during school closures; in Nigeria, mothers of school-age children experience the largest declines in employment during the pandemic, just as in high-income countries. A key difference is the role of the sectoral distribution of employment: whereas in high-income economies reduced employment in contact-intensive services had a large impact on women, this sector plays a minor role in low-income countries. Another difference is that women’s employment rebounded much more quickly in low-income countries. We conjecture that large income losses without offsetting government transfers drive up labor supply in low-income countries during the recovery.

Temporal data on school closures in response to the COVID-19 pandemic at the country and country region levels.

The COVID-19 pandemic has been a major health concern in Bangladesh until very recently. Although the Bangladesh government has employed various infection control strategies, more targeted Non-Pharmaceutical interventions (NPIs), including school closure, mask-wearing, hand washing, and social distancing have gained special attention. Despite significant long-term adverse effects of school closures, authorities have opted to keep schools closed to curb the spread of COVID-19 infection. However, there is limited knowledge about the impact of reopening schools alongside other NPI measures on the course of the epidemic. In this study, we implemented a mathematical modeling framework developed by the CoMo Consortium to explore the impact of NPIs on the dynamics of the COVID-19 outbreak and deaths for Bangladesh. For robustness, the results of prediction models are then validated through model calibration with incidence and mortality data and using external sources. Hypothetical projections are made under alternative NPIs where we compare the impact of current NPIs with school closures versus enhanced NPIs with school openings. Results suggest that enhanced NPIs with schools opened may have lower COVID-19 related prevalence and deaths. This finding indicates that enhanced NPIs and school openings may mitigate the long-term negative impacts of COVID-19 in low- and middle-income countries. Potential shortcomings and ways to improve the research are also discussed.

Across South Asian countries, the average length of partial or full school closures during the coronavirus (COVID-19) pandemic amounted to 84 weeks as of April 2022. In comparison, schools across East Asia and the Pacific were partially or fully closed for 43 weeks on average.

Abstract

COVID-19 caused significant disruption to the global education system. A thorough analysis of recorded learning loss evidence documented since the beginning of the school closures between March 2020 and March 2022 finds even evidence of learning loss. Most studies observed increases in inequality where certain demographics of students experienced more significant learning losses than others. But there are also outliers, countries that managed to limit the amount of loss. This review consolidates all the available evidence and documents the empirical findings. Data for 41 countries is included, together with other variables related to the pandemic experience. This data is publicly available and will be updated regularly.

Geographic coverage

The data covers 41 countries.

Analysis unit

Country

Kind of data

Aggregate data [agg]

Mode of data collection

Other [oth]

The data correspond to the selected national public response measures presented in the weekly report COVID-19 Country overviews.Response measures collected include mass gathering cancellations (for specific events or a ban on gatherings of a particular size); closure of public spaces (including restaurants, entertainment venues, non-essential shops, partial or full closure of public transport etc.); closure of educational institutions (including daycare or nursery, primary schools, and secondary schools and higher education); ‘stay-at-home’ recommendations for risk groups or vulnerable populations (such as the elderly, people with underlying health conditions, physically disabled people etc.); ‘stay-athome’ recommendations for the general population (which are voluntary or not enforced); and ‘stay-at-home’ orders for the general population (these are enforced and also referred to as ‘lockdown’), use of protective masks in public spaces/on public transport (mutually exclusive voluntary recommendations and mandatory obligations shown separately) and also teleworking recommendations/closure of workplaces

It is based on data originally downloaded by the site https://www.ecdc.europa.eu/en/covid-19.

Raw data from ECDC, harmonization and homogenization of data from UNIPV - Laboratory of Geomatics

The COVID-19 pandemic has been a major health concern in Bangladesh until very recently. Although the Bangladesh government has employed various infection control strategies, more targeted Non-Pharmaceutical interventions (NPIs), including school closure, mask-wearing, hand washing, and social distancing have gained special attention. Despite significant long-term adverse effects of school closures, authorities have opted to keep schools closed to curb the spread of COVID-19 infection. However, there is limited knowledge about the impact of reopening schools alongside other NPI measures on the course of the epidemic. In this study, we implemented a mathematical modeling framework developed by the CoMo Consortium to explore the impact of NPIs on the dynamics of the COVID-19 outbreak and deaths for Bangladesh. For robustness, the results of prediction models are then validated through model calibration with incidence and mortality data and using external sources. Hypothetical projections are made under alternative NPIs where we compare the impact of current NPIs with school closures versus enhanced NPIs with school openings. Results suggest that enhanced NPIs with schools opened may have lower COVID-19 related prevalence and deaths. This finding indicates that enhanced NPIs and school openings may mitigate the long-term negative impacts of COVID-19 in low- and middle-income countries. Potential shortcomings and ways to improve the research are also discussed.

As of March 2021, schools were closed in 57 countries worldwide. In 95 countries schools remained open with limitations, while only 26 countries across the globe kept their schools open. Altogether, roughly 682 million students worldwide resided in countries where schools were fully closed.

The COVID-19 pandemic had severe impacts on almost every aspect of life, from health via economy to education. School closures around the world caused disruptions in learning development of children and youth. South Asia as well as Latin America and the Caribbean had the highest number of weeks where schools were either partially or fully closed. In the former, a total of 84 weeks of education were conducted either partially or completely remote. On the other hand, Europe and Central Asia saw just above 30 weeks of some form of remote learning. Infrastructure and remote learning It may not come as a surprise, then, that South Asia and Latin America and the Caribbean were the two regions with the highest levels of learning delays caused by the COVID-19 pandemic. Moreover, different countries in different regions have different infrastructures that make remote learning possible. For instance, Sub-Saharan Africa, where many countries have a poor internet infrastructure, was the region with the highest number of academic weeks held in person as remote learning was impossible in many areas. Economic impact
The learning disruptions caused by the pandemic could also have severe economic impacts in the future if counter measures are not taken. Estimates show that globally, *** trillion U.S. dollars of GDP could be lost annually by 2040 due to the educational disruptions caused by COVID-19.

The Oxford COVID-19 Government Response Tracker (OxCGRT) systematically collects information on several different common policy responses that governments have taken to respond to the pandemic on 18 indicators such as school closures and travel restrictions. It now has data from more than 180 countries. The data is also used to inform a Risk of Openness Index which aims to help countries understand if it is safe to ‘open up’ or whether they should ‘close down’ in their fight to tackle the coronavirus.

The COVID-19 pandemic triggered a globally spread—but differently timed—implementation of school closures and other disruptive containment measures as governments worldwide intervened to curb transmission of disease. This study argues that the timing of such disruptive interventions reflects how governments balance the principles of precaution and proportionality in their pandemic decision-making. A theory is proposed of how their trade-off is impacted by two interacting institutional factors: electoral democratic institutions, which incentivize political leaders to increasingly favor precaution, and high state administrative capacity, which instead makes a proportional strategy involving later containment measures more administratively and politically feasible. Global patterns consistent with this theory are documented among 170 countries in early 2020, using Cox models of school closures and other non-pharmaceutical interventions. Corroborating the theorized mechanisms, additional results indicate that electoral competition prompts democratic leaders’ faster response, and that this mechanism is weaker where professional state agencies have more influence over policy-making.

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