Oxford COVID-19 Government Response Tracker

Article
09/07/2022

The Oxford Covid-19 Government Response Tracker (OxCGRT) dataset contains systematic information on which governments have taken which measures, and when.

This information can help decision-makers and citizens understand governmental responses in a consistent way, aiding efforts to fight the pandemic. The OxCGRT systematically collects information on several different common policy responses governments have taken, records these policies on a scale to reflect the extent of government action, and aggregates these scores into a suite of policy indices.

Note

Microsoft provides Azure Open Datasets on an “as is” basis. Microsoft makes no warranties, express or implied, guarantees or conditions with respect to your use of the datasets. To the extent permitted under your local law, Microsoft disclaims all liability for any damages or losses, including direct, consequential, special, indirect, incidental or punitive, resulting from your use of the datasets.

This dataset is provided under the original terms that Microsoft received source data. The dataset may include data sourced from Microsoft.

Datasets

Modified versions of the dataset are available in CSV, JSON, JSON-Lines, and Parquet, updated daily:

All modified versions have iso_country codes and load times added, and use lower case column names with underscore separators.

Raw data: https://pandemicdatalake.blob.core.windows.net/public/raw/covid-19/covid_policy_tracker/latest/CovidPolicyTracker.csv

Previous versions of modified and raw data: https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/covid_policy_tracker/ https://pandemicdatalake.blob.core.windows.net/public/raw/covid-19/covid_policy_tracker/

Data volume

As of June 8, 2020 they contained 27,919 rows (CSV 4.9 MB, JSON 20.9 MB, JSONL 20.8 MB, Parquet 133.0 KB).

Data source

The source of this data is Thomas Hale, Sam Webster, Anna Petherick, Toby Phillips, and Beatriz Kira. (2020). Oxford COVID-19 Government Response Tracker. Blavatnik School of Government. Raw data is ingested daily from the latest OxCGRT csv file. For more information on this dataset, including how it is collected, see the Government tracker response site.

Data quality

The OxCGRT does not guarantee the accuracy or timeliness of the data. For more information, see the data quality statement.

License and use rights attribution

This data is licensed under the Creative Commons Attribution 4.0 International License.

Cite as: Thomas Hale, Sam Webster, Anna Petherick, Toby Phillips, and Beatriz Kira. (2020). Oxford COVID-19 Government Response Tracker. Blavatnik School of Government.

Contact

For any questions or feedback about this or other datasets in the COVID-19 Data Lake, contact askcovid19dl@microsoft.com.

Columns

Name	Data type	Unique	Values (sample)	Description
c1_flag	boolean	3	True	Binary flag for geographic scope. 0 - targeted 1 - general Blank - no data
c1_school_closing	double	5	3.0 2.0	Record closings of schools and universities. 0 - no measures 1 - recommend closing 2 - require closing (only some levels or categories, for example, just high school, or just public schools) 3 - require closing all levels Blank - no data
c2_flag	boolean	3	True	Binary flag for geographic scope. 0 - targeted; 1 - general; Blank - no data
c2_workplace_closing	double	5	2.0 1.0	Record closings of workplaces. 0 - no measures 1 - recommend closing (or recommend work from home) 2 - require closing (or work from home) for some sectors or categories of workers 3 - require closing (or work from home) for all-but-essential workplaces (for example, grocery stores, doctors) Blank - no data
c3_cancel_public_events	double	4	2.0 1.0	Record canceling public events. 0 - no measures 1 - recommend canceling 2 - require canceling Blank - no data
c3_flag	boolean	3	True	Binary flag for geographic scope. 0 - targeted 1 - general Blank - no data
c4_flag	boolean	3	True	Binary flag for geographic scope 0 - targeted 1 - general Blank - no data
c4_restrictions_on_gatherings	double	6	4.0 3.0	Record limits on private gatherings. 0 - no restrictions 1 - restrictions on very large gatherings (the limit is above 1000 people) 2 - restrictions on gatherings between 101-1000 people 3 - restrictions on gatherings between 11-100 people 4 - restrictions on gatherings of 10 people or less Blank - no data
c5_close_public_transport	double	4	1.0 2.0	Record closing of public transport 0 - no measures 1 - recommend closing (or significantly reduce volume/route/means of transport available) 2 - require closing (or prohibit most citizens from using it) Blank - no data
c5_flag	boolean	3	True	Binary flag for geographic scope 0 - targeted 1 - general Blank - no data
c6_flag	boolean	3	True	Binary flag for geographic scope 0 - targeted 1 - general Blank - no data
c6_stay_at_home_requirements	double	5	1.0 2.0	Record orders to “shelter-in-place” and otherwise confine to the home 0 - no measures 1 - recommend not leaving house 2 - require not leaving house with exceptions for daily exercise, grocery shopping, and ‘essential’ trips 3 - require not leaving house with minimal exceptions (for example, allowed to leave once a week, or only one person can leave at a time, etc.) Blank - no data
c7_flag	boolean	3	True	Binary flag for geographic scope 0 - targeted 1 - general Blank - no data
c7_restrictions_on_internal_movement	double	4	2.0 1.0	Record restrictions on internal movement between cities/regions 0 - no measures 1 - recommend not to travel between regions/cities 2 - internal movement restrictions in place Blank - no data
c8_international_travel_controls	double	6	3.0 4.0	Record restrictions on international travel. Note: this records policy for foreign travelers, not citizens 0 - no restrictions 1 - screening arrivals 2 - quarantine arrivals from some or all regions 3 - ban arrivals from some regions 4 - ban on all regions or total border closure Blank - no data
confirmedcases	smallint	18,238	1 2
confirmeddeaths	smallint	14,906	1 2
countrycode	string	186	USA BRA
countryname	string	186	United States Brazil
date	date	478	2020-08-25 2021-03-30
e1_flag	boolean	3	True	Binary flag for sectoral scope 0 - formal sector workers only 1 - transfers to informal sector workers to Blank - no data
e1_income_support	double	4	1.0 2.0	Record if the government is providing direct cash payments to people who lose their jobs or cannot work. Note: only includes payments to firms if explicitly linked to payroll/salaries 0 - no income support 1 - government is replacing less than 50% of lost salary (or if a flat sum, it is less than 50% median salary) 2 - government is replacing 50% or more of lost salary (or if a flat sum, it is greater than 50% median salary) Blank - no data
e2_debt/contract_relief	double	4	1.0 2.0
e3_fiscal_measures	double	819	-0.01 3.0	Announced economic stimulus spending Note: only record amount additional to previously announced spending Record monetary value in USD of fiscal stimuli, includes any spending or tax cuts NOT included in E4, H4, or H5 0 - no new spending that day Blank - no data
e4_international_support	double	113	-0.02 5000000.0	Announced offers of Covid-19-related aid spending to other countries/regions Note: only record amount additional to previously announced spending Record monetary value in USD 0 - no new spending that day Blank - no data
h1_flag	boolean	3	True	Binary flag for geographic scope 0 - targeted 1 - general Blank - no data
h1_public_information_campaigns	double	4	2.0 1.0	Record presence of public info campaigns 0 - no Covid-19 public information campaign 1 - public officials urging caution about Covid-19 2- coordinated public information campaign (for example, across traditional and social media) Blank - no data
h2_testing_policy	double	5	2.0 1.0	Record government policy on who has access to testing Note: this records policies about testing for current infection (PCR tests) not testing for immunity (antibody test) 0 - no testing policy 1 - only those who both (a) have symptoms AND (b) meet specific criteria (for example, key workers, admitted to hospital, came into contact with a known case, returned from overseas) 2 - testing of anyone showing Covid-19 symptoms 3 - open public testing (for example “drive through” testing available to asymptomatic people) Blank - no data
h3_contact_tracing	double	4	2.0 1.0	Record government policy on contact tracing after a positive diagnosis Note: we are looking for policies that would identify all people potentially exposed to Covid-19; voluntary bluetooth apps are unlikely to achieve this 0 - no contact tracing 1 - limited contact tracing; not done for all cases 2 - comprehensive contact tracing; done for all identified cases
h4_emergency_investment_in_healthcare	double	462	35.0 562.0	Announced short-term spending on healthcare system, for example, hospitals, masks, etc. Note: only record amount additional to previously announced spending Record monetary value in USD 0 - no new spending that day Blank - no data
h5_investment_in_vaccines	double	133	1.0 191.0	Announced public spending on Covid-19 vaccine development Note: only record amount additional to previously announced spending Record monetary value in USD 0 - no new spending that day Blank - no data
iso_country	string	186	US BR	ISO 3166 country or region code
load_date	timestamp	1	2021-04-26 00:06:25.157000	Date and time data was loaded from external source
stringencyindex	double	188	11.11 60.19
stringencyindexfordisplay	double	188	11.11 60.19

Preview

countryname	countrycode	date	m1_wildcard	iso_country	load_date
Aruba	ABW	2020-01-01	null	AW	4/26/2021 12:06:25 AM
Aruba	ABW	2020-01-02	null	AW	4/26/2021 12:06:25 AM
Aruba	ABW	2020-01-03	null	AW	4/26/2021 12:06:25 AM
Aruba	ABW	2020-01-04	null	AW	4/26/2021 12:06:25 AM
Aruba	ABW	2020-01-05	null	AW	4/26/2021 12:06:25 AM
Aruba	ABW	2020-01-06	null	AW	4/26/2021 12:06:25 AM
Aruba	ABW	2020-01-07	null	AW	4/26/2021 12:06:25 AM
Aruba	ABW	2020-01-08	null	AW	4/26/2021 12:06:25 AM
Aruba	ABW	2020-01-09	null	AW	4/26/2021 12:06:25 AM
Aruba	ABW	2020-01-10	null	AW	4/26/2021 12:06:25 AM

Data access

This notebook documents the URLs and sample code to access the Oxford Covid-19 Government Response Tracker (OxCGRT) dataset

URLs of different file formats hosted on Azure Blob Storage:

CSV: https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/covid_policy_tracker/latest/covid_policy_tracker.csv

JSON: https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/covid_policy_tracker/latest/covid_policy_tracker.json

JSONL: https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/covid_policy_tracker/latest/covid_policy_tracker.jsonl

Parquet: https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/covid_policy_tracker/latest/covid_policy_tracker.parquet

Download the dataset file using the built-in capability download from an http URL in Pandas. Pandas has readers for various file formats:

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_parquet.html

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html

Start by loading the dataset file into a pandas dataframe and view some sample rows

import pandas as pd
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt

df = pd.read_parquet("https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/covid_policy_tracker/latest/covid_policy_tracker.parquet")
df.head(10)

Lets check the data types of the various fields and verify that the updated column is datetime format

df.dtypes

This dataset contains data for the numerous countries/regions. Lets verify what countries/regions we have data for.

We will start by looking at the latest data for each country:

df.groupby('countryname').first().filter(['confirmedcases ', 'confirmeddeaths','h5_investment_in_vaccines',
    'c6_stay_at_home_requirements','h4_emergency_investment_in_healthcare','c4_restrictions_on_gatherings', 'load_date'])

Next, we will do some aggregations to make sure columns such as confirmedcases and confirmeddeaths tally with the latest data. You should see that positive and death numbers for latest date in the above table match with the aggregation of confirmedcases and confirmeddeaths.

df.groupby('countryname').agg({'countryname': 'count','confirmedcases': 'sum','confirmeddeaths': 'sum',
                               'h5_investment_in_vaccines': 'count', 'c6_stay_at_home_requirements':'sum'})

Lets do some basic visualizations for a few countries/regions

import plotly.graph_objects as go
import plotly.express as px
import matplotlib.pyplot as plt

df.loc[: , ['countryname', 'confirmedcases', 
'confirmeddeaths']].groupby(['countryname']).max().sort_values(by='confirmedcases', 
                                           ascending=False).reset_index()[:15].style.background_gradient(cmap='rainbow')

df_US = df.groupby(df.date).agg({'confirmedcases': 'sum','confirmeddeaths':'sum'}).reset_index()

df_US.plot(kind='line',x='date',y="confirmedcases",grid=True)
df_US.plot(kind='line',x='date',y="confirmeddeaths",grid=True)

Azure Databricks

azure-storage
pyspark

Sample not available for this platform/package combination.

# Azure storage access info
blob_account_name = "pandemicdatalake"
blob_container_name = "public"
blob_relative_path = "curated/covid-19/covid_policy_tracker/latest/covid_policy_tracker.parquet"
blob_sas_token = r""

# Allow SPARK to read from Blob remotely
wasbs_path = 'wasbs://%s@%s.blob.core.windows.net/%s' % (blob_container_name, blob_account_name, blob_relative_path)
spark.conf.set(
  'fs.azure.sas.%s.%s.blob.core.windows.net' % (blob_container_name, blob_account_name),
  blob_sas_token)
print('Remote blob path: ' + wasbs_path)

# SPARK read parquet, note that it won't load any data yet by now
df = spark.read.parquet(wasbs_path)
print('Register the DataFrame as a SQL temporary view: source')
df.createOrReplaceTempView('source')

# Display top 10 rows
print('Displaying top 10 rows: ')
display(spark.sql('SELECT * FROM source LIMIT 10'))

Azure Synapse

azure-storage
pyspark