Understanding the Global Impact of COVID-19
through Data Science

OXFORD COVID-19 (OxCOVID19) PROJECT

OxCOVID19 Project aims to increase our understanding of the COVID-19 pandemic and elaborate possible strategies to reduce the impact on the society through the combined power of Statistical, Mathematical Modelling and Machine Learning techniques.

OxCOVID19 Database is a large, single-centre, multimodal relational database consisting of information (using acknowledged Sources) related to COVID-19 pandemic. OxCOVID19 Database is currenlty comprised of six tables: EPIDEMIOLOGY, GOVERNMENT_RESPONSE, COUNTRY_STATISTICS, MOBILITY, WEATHER and ADMINISTRATIVE_DIVISION. Read more about the Data Structure and Sources; and how to access the data below.


If you find OxCOVID19 Database useful please cite+:

Adam Mahdi, Piotr Błaszczyk, Paweł Dłotko, Dario Salvi, Tak-Shing Chan, John Harvey, Davide Gurnari, Yue Wu, Ahmad Farhat, Niklas Hellmer, Alexander Zarebski, Bernie Hogan, Lionel Tarassenko, Oxford COVID-19 Database: a multimodal data repository for better understanding the global impact of COVID-19. University of Oxford, 2020.

+ The OxCOVID19 Database is the result of many hours of volunteer efforts and generous contributions of many organisations. If you use a specific table please also cite the underlying source (see Sources).

Who are we?

The project is coordinated by researchers from the University of Oxford; however, contributions from around the world are welcome and much appreciated. If you would like to help, please get in touch: Adam Mahdi (adam.mahdi@eng.ox.ac.uk).

Accessing the OxCOVID19 Database

The interfaces with a are recommended for accessing the latest and most complete data. The whole database is available via the PostgreSQL database with only a subset available as CSV files on GitHub and in the FigShare snapshot.

Examples of how to use OxCOVID19 Database

Examples of how to load and query OxCOVID19 Database and make simple visualisations in Jupyter notebook (Python). For more examples see our GitHub example repository. Feel free to get in touch if you would like to suggest or send us an informative visualisation usign OxCOVID19 Database.



Comparing different countries. An example of how to use EPIDEMIOLOGY table within OxCOVID19 Database to plot a simple comparison of confirmed cases and mortality between different countries.

Gradient map of the world. An example of how to use EPIDEMIOLOGY table within OxCOVID19 Database to build a simple gradient map for confirmed cases for the countries of the world.

Gradient map for different regions. An example of how to use EPIDEMIOLOGY table within OxCOVID19 Database to build a simple gradient map for confirmed for different regions in Italy.

Government action against confirmed cases. An example of how to use GOVERNMENT_RESPONSE table within OxCOVID19 Database to build a plot comparing government actions taken due to COVID-19 aginst confirmed cases from the EPIDEMIOLOGY table for the UK.

Multimodal Covid-19 data. An example of how to use GOVERNMENT_RESPONSE, MOBILITY and EPIDEMIOLOGY tables within OxCOVID19 Database to build a multimodal plot comparing government actions taken due to COVID-19 aginst confirmed cases and mobility.

Disclaimer

Some regions have undergone name changes since the last release of the GADM database. In our database we follow exactly the GID and names as given in GADM. This is merely to guarantee a standard way of relating data. In no case is this choice a manifestation of any political views by us or our universities.