Oxford COVID-19 Government Response Tracker
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:
- https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/covid_policy_tracker/latest/covid_policy_tracker.csv
- https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/covid_policy_tracker/latest/covid_policy_tracker.json
- https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/covid_policy_tracker/latest/covid_policy_tracker.jsonl
- https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/covid_policy_tracker/latest/covid_policy_tracker.parquet
All modified versions have iso_country codes and load times added, and use lower case column names with underscore separators.
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 | c1_school_closing | c2_workplace_closing | c3_cancel_public_events | c4_restrictions_on_gatherings | c5_close_public_transport | c6_stay_at_home_requirements | c7_restrictions_on_internal_movement | c8_international_travel_controls | e1_income_support | e2_debt/contract_relief | e3_fiscal_measures | e4_international_support | h1_public_information_campaigns | h2_testing_policy | h3_contact_tracing | h4_emergency_investment_in_healthcare | h5_investment_in_vaccines | m1_wildcard | stringencyindex | stringencyindexfordisplay | iso_country | load_date |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Aruba | ABW | 2020-01-01 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | AW | 4/26/2021 12:06:25 AM |
| Aruba | ABW | 2020-01-02 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | AW | 4/26/2021 12:06:25 AM |
| Aruba | ABW | 2020-01-03 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | AW | 4/26/2021 12:06:25 AM |
| Aruba | ABW | 2020-01-04 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | AW | 4/26/2021 12:06:25 AM |
| Aruba | ABW | 2020-01-05 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | AW | 4/26/2021 12:06:25 AM |
| Aruba | ABW | 2020-01-06 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | AW | 4/26/2021 12:06:25 AM |
| Aruba | ABW | 2020-01-07 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | AW | 4/26/2021 12:06:25 AM |
| Aruba | ABW | 2020-01-08 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | AW | 4/26/2021 12:06:25 AM |
| Aruba | ABW | 2020-01-09 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | AW | 4/26/2021 12:06:25 AM |
| Aruba | ABW | 2020-01-10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | AW | 4/26/2021 12:06:25 AM |
Data access
Azure Notebooks
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:
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
Sample not available for this platform/package combination.
Azure Synapse
Sample not available for this platform/package combination.
Next steps
View the rest of the datasets in the Open Datasets catalog.