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Data

School closures during the COVID-19 pandemic

See all data and research on:
COVID-19

What you should know about this indicator

Possible categories:

  • 0: no measures
  • 1: recommend closing or all schools open with alterations resulting in significant differences compared to non-Covid-19 operations
  • 2: require closing (only some levels or categories, eg just high school, or just public schools)
  • 3: require closing all levels
School closures during the COVID-19 pandemic
Record closings of schools and universities.
Source
Blavatnik School of Government, University of Oxford (2023) – with minor processing by Our World in Data
Last updated
August 1, 2024

Sources and processing

This data is based on the following sources

Blavatnik School of Government, University of Oxford – Government Response Tracker (OxCGRT)

The Oxford Covid-19 Government Response Tracker (OxCGRT) collected information on which pandemic response measures were enacted by governments, and when. During the pandemic this helped decision-makers and citizens understand governmental responses in a consistent way, aiding efforts to fight the pandemic. Now that covid-19 is no longer designated a public health emergency of international concern, the data can be used for research purposes and to prepare for future pandemics.

The OxCGRT systematically collected information on several different common policy responses governments took over 2020, 2021, and 2022, recorded these policies on a scale to reflect the extent of government action, and aggregates these scores into a suite of policy indices. We also collected differentiated policies data where different policies apply to people who were vaccinated and non-vaccinated.

The OxCGRT reports publicly available information on 24 policy indicators and a miscellaneous notes field of government response organised into four groups:

  • C: containment and closure policies
  • E: economic policies
  • H: health system policies
  • V: vaccination policies

To help make sense of the data, we have produced four indices that aggregate the data into a single number. For more details about how the indices are comprised, see the section 'Calculation of policy indices' in our documentation. Each of these indices reports a number between 0 to 100 that reflects the level of the government's response along certain dimensions:

  • overall government response index (all indicators)
  • containment and health index (all C and H indicators)
  • stringency index (all C indicators, plus H1 which records public information campaigns)
  • economic support index (all E indicators)

These indices are a measure of how many of the relevant policy types a government has acted upon, and to what degree. The index cannot say whether a government's policy has been implemented effectively.

Because of the complexity of the dataset, it is published across 27 CSV files. Our technical documentation (https://github.com/OxCGRT/covid-policy-dataset/blob/main/documentation_and_codebook.md) contains all the information users need to navigate and use the data.

Retrieved on
August 1, 2024
Retrieved from
https://github.com/OxCGRT/covid-policy-dataset
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Thomas Hale, Noam Angrist, Rafael Goldszmidt, Beatriz Kira, Anna Petherick, Toby Phillips, Samuel Webster, Emily Cameron-Blake, Laura Hallas, Saptarshi Majumdar, and Helen Tatlow. (2021). “A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker).” Nature Human Behaviour. https://doi.org/10.1038/s41562-021-01079-8

The Oxford Covid-19 Government Response Tracker (OxCGRT) collected information on which pandemic response measures were enacted by governments, and when. During the pandemic this helped decision-makers and citizens understand governmental responses in a consistent way, aiding efforts to fight the pandemic. Now that covid-19 is no longer designated a public health emergency of international concern, the data can be used for research purposes and to prepare for future pandemics.

The OxCGRT systematically collected information on several different common policy responses governments took over 2020, 2021, and 2022, recorded these policies on a scale to reflect the extent of government action, and aggregates these scores into a suite of policy indices. We also collected differentiated policies data where different policies apply to people who were vaccinated and non-vaccinated.

The OxCGRT reports publicly available information on 24 policy indicators and a miscellaneous notes field of government response organised into four groups:

  • C: containment and closure policies
  • E: economic policies
  • H: health system policies
  • V: vaccination policies

To help make sense of the data, we have produced four indices that aggregate the data into a single number. For more details about how the indices are comprised, see the section 'Calculation of policy indices' in our documentation. Each of these indices reports a number between 0 to 100 that reflects the level of the government's response along certain dimensions:

  • overall government response index (all indicators)
  • containment and health index (all C and H indicators)
  • stringency index (all C indicators, plus H1 which records public information campaigns)
  • economic support index (all E indicators)

These indices are a measure of how many of the relevant policy types a government has acted upon, and to what degree. The index cannot say whether a government's policy has been implemented effectively.

Because of the complexity of the dataset, it is published across 27 CSV files. Our technical documentation (https://github.com/OxCGRT/covid-policy-dataset/blob/main/documentation_and_codebook.md) contains all the information users need to navigate and use the data.

Retrieved on
August 1, 2024
Retrieved from
https://github.com/OxCGRT/covid-policy-dataset
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Thomas Hale, Noam Angrist, Rafael Goldszmidt, Beatriz Kira, Anna Petherick, Toby Phillips, Samuel Webster, Emily Cameron-Blake, Laura Hallas, Saptarshi Majumdar, and Helen Tatlow. (2021). “A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker).” Nature Human Behaviour. https://doi.org/10.1038/s41562-021-01079-8

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: School closures during the COVID-19 pandemic”, part of the following publication: Edouard Mathieu, Hannah Ritchie, Lucas Rodés-Guirao, Cameron Appel, Daniel Gavrilov, Charlie Giattino, Joe Hasell, Bobbie Macdonald, Saloni Dattani, Diana Beltekian, Esteban Ortiz-Ospina, and Max Roser (2020) - “COVID-19 Pandemic”. Data adapted from Blavatnik School of Government, University of Oxford. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/school-closures-covid.html [online resource] (archived on March 4, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Blavatnik School of Government, University of Oxford (2023) – with minor processing by Our World in Data

Full citation

Blavatnik School of Government, University of Oxford (2023) – with minor processing by Our World in Data. “School closures during the COVID-19 pandemic” [dataset]. Blavatnik School of Government, University of Oxford, “Government Response Tracker (OxCGRT)” [original data]. Retrieved March 31, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/school-closures-covid.html (archived on March 4, 2026).

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Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

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Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/school-closures-covid.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/school-closures-covid.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/school-closures-covid.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/school-closures-covid.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/school-closures-covid.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/school-closures-covid.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/school-closures-covid.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/school-closures-covid.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear