As of June 14, 2021, 34 states in the United States had no school closure order in effect due to the COVID-19 pandemic. Meanwhile, 13 states had ordered schools open.

School closure during COVID-19

The debate on whether to close schools during the COVID-19 pandemic has been highly contentious in the United States. As experts are unsure about the long-term effects of COVID-19 on individuals, the call to close schools has been rapidly growing. The evidence of children being asymptomatic spreaders helps support the case to close schools to decrease the risk of spreading to their parents and grandparents. Those in favor of closing schools argue that closing schools hinders children’s emotional, mental, and educational development. However, a majority of voters agree that schools should wait to reopen until all teachers are vaccinated.

Parents' worry

Regardless of income level or working status, most parents in the United States share the same fears and concerns about their children’s education and safety during COVID-19. A majority of parents were concerned about their children falling behind as a result of online schooling, as an online school does not provide the same academic and social benefits as an in-person school.

This dataset include two .csv files containing the integrated dataset used by the COVID-19 School Dashboard website to report and maps confirmed school-related cases of COVID-19 in publicly funded elementary and secondary schools in Ontario, Canada, and connects this to data on school social background characteristics. One csv file reports cases from 2020-09-10 to 2021-04-14 (2020 school year) while the other csv file reports cases from 2021-09-13 to 2021-12-22 (2021 school year). Two accompanying .doc files are included to describe the variables in the .csv files.

This dataset provides the number of weekly COVID-19 cases for staff and students in CT public and private PK-12 schools during the 2021-2022 school year. The following metrics are included: Number of student cases - total Number of student cases - fully vaccinated June 30, 2022 is the last report for the 2021 – 2022 academic school year. Number of student cases - not vaccinated Number of student cases - no vaccine information Number of staff cases - total Number of staff cases - fully vaccinated Number of staff cases - not vaccinated Number of staff cases - no vaccine information Data for the 2020-2021 school year is available here: https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-in-CT-Schools-Statewide-2020-2021-S/ehua-hw73

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.

Due to the coronavirus (COVID-19) outbreak, institutions in the United States have had to react in order to try to contain the virus. As of March 17, 2020, 489 schools or school districts in the U.S. have closed in response to COVID-19. 22 schools or school districts are scheduled to close.

This dataset includes information on school reported COVID-19 testing and case positive data from the 2021-2022 academic year. Data was collected from private schools on each operational day using the daily school survey form, which school administrators access by logging in to the NYSDOH school survey website.

The primary goal of publishing this dataset is to provide users timely information about disease spread and reporting of positive cases within schools. The data will be updated daily, reflecting data submitted by school administrators the previous day.

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.

This dataset provides the number of weekly COVID-19 cases for staff and students in CT PK-12 schools by school during the 2022-2023 school year.

Initial estimates of staff and pupils testing positive for the coronavirus (COVID-19) across a sample of schools within selected local authority areas in England.

This data table covers key socio-demographic and health indicators at the health region levels of geography to better understand the different ways that remote learning approaches and temporarily closed schools have affected children and youth during the COVID-19 pandemic.

Analysis of ‘COVID-19 Cases in CT Schools (Statewide), 2020-2021 School Year’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/3a9baef4-0eb8-44c5-93f9-13daa5576dd0 on 26 January 2022.

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

This dataset provides the number of weekly COVID-19 cases for staff and students in CT public and private PK-12 schools.

As of 6/24/2021, COVID-19 school-based surveillance activities for the 2020 – 2021 academic year has ended. The Connecticut Department of Public Health along with the Connecticut State Department of Education are planning to resume these activities at the start of the 2021 – 2022 academic year.

Data for the 2021-2022 school year is available here: https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-in-CT-Schools-Statewide-2021-2022-S/72vp-djx5

--- Original source retains full ownership of the source dataset ---

This project aims to build a model that is able to generate risk scores for schools in different areas of San Diego and provide insights for schools to take the appropriate precautionary measures when reopening for in-person instructions. We plan to utilize the 2020 synthetic population data for simulating transportation from and to schools. Combining the trips data with school information and case rates in individual census tracts, we can then assign weights to various factors and compute the final risk score for schools in each census tract. The final result can also serve as a baseline for agent-based model to simulate COVID-19 spread on campus.Notable Modules Used:Matplotlib We used matplotlib to plot some of our data into graph to better view them in a visualized way.Geopandas We used geopandas to read in the shape files in our data.Pandas We used pandas to handle dataframe and have done some preprocessing using it.Numpy We used numpy for some arithmetic operations.ArcGIS Feature Module It is mainly used for feature summarization. Using the summarize_within function provided in this module, we are able to turn our zip code based COVID data into MGRA based COVID data.

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.

Analysis of ‘COVID-19 Cases in CT Schools by County, 2020-2021 School Year’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/38eb039f-ca7a-4abf-a51b-142949f62475 on 26 January 2022.

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

Counts of COVID-19 Cases in CT Schools by County

As of 6/24/2021, COVID-19 school-based surveillance activities for the 2020 – 2021 academic year has ended. The Connecticut Department of Public Health along with the Connecticut State Department of Education are planning to resume these activities at the start of the 2021 – 2022 academic year.

--- Original source retains full ownership of the source dataset ---

Abstract copyright UK Data Service and data collection copyright owner.

Understanding Society (the UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex, and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

The Understanding Society COVID-19 Study is a regular survey of households in the UK. The aim of the study is to enable research on the socio-economic and health consequences of the COVID-19 pandemic, in the short and long term. The surveys started in April 2020 and took place monthly until July 2020. From September 2020 they take place every other month. They complement the annual interviews in the Understanding Society study.

This dataset contains school code variables for the Understanding Society COVID-19 study (SN 8644).

A file is provided for the fifth web wave of the Understanding Society COVID-19 study, the only one that school information has currently been gathered for. For each child it contains: state school code, country of state school, private school name and private school town variables for both mother and father responses. A child personal identification serial number (pidp_c) is also provided for matching to the main data in SN 8644.

In addition, this dataset contains a file of school code variables that can be matched to a dataset released with the main Understanding Society COVID-19 study containing data taken from waves 10 and 11 of the main Understanding Society survey specifically for the respondents in the Understanding Society COVID-19 study. Child school codes are only available for Wave 11 as they are only collected in odd-numbered waves. For each child it contains the state school code and country of state school variables as well as a personal identification serial number (pidp) and a household identification serial number for wave 11 (jk_hidp). Further details on the files in this dataset can be found in the Understanding Society COVID-19 User Guide.

Additional information can be found on the Understanding Society COVID-19 website, including Data documentation. A list of Understanding Society COVID-19 Research Outputs (regularly updated) is also available.

New edition information
For the second edition (January 2021), both previously deposited files have been revised to include a significant number of additional school codes resulting from manual coding. For further details please refer to the UKHLS COVID-19: Data Changes document, included in the main COVID-19 study (SN 8644).

Main Topics:

This study contains school code variables for the Understanding Society COVID-19 study.

Number of COVID-19 cases (PCR test) in schools by type of school A graphical representation of the numbers is available on the website Covid19 Location Picture Schools. Character separator is comma, character set is UTF-8

The emergence of the COVID-19 pandemic resulted in abrupt disruptions in teaching and learning activities in higher education, with students from diverse programs suffering varying levels of anxieties. The physical education field happens to be one of the most affected academic areas due to its experiential content as a medium of instruction. In this study, we investigated the roles of school climate and coping strategies in the relationship between COVID-19 related knowledge and anxiety. Through the census approach, a cross-sectional sample of 760 students was administered a questionnaire in two universities offering Physical Education in Ghana: the University of Education, Winneba, and University of Cape Coast. The outcome of the study found a positive and significant link between COVID-19 knowledge and anxiety. Further, school climate and coping strategies significantly moderated the relationship between students’ COVID-19 knowledge and associated anxiety. The findings have implications for creating a conducive school environment that reduces the risk of COVID-19 infection and through students’ adoption of active coping strategies in an attempt to reduce psychological distress associated with COVID-19 anxiety.

Unplanned public K-12 school district and individual school closures due to COVID-19 in the United States from August 1, 2020–June 30, 2022.

The share of K-12 schools in the United States who used hybrid teaching methods has increased since September 2020. At the beginning of September 2020, 18.2 percent of K-12 schools were teaching students with a hybrid method (both virtual and in-person instruction) due to the COVID-19 pandemic. This figure increased to 24.8 percent of K-12 schools by February 2021.

This paper presents simulations of the potential range of impacts school closures might have on schooling and learning, in both the short term and the long term.