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Understanding the global impact of COVID-19 through Data Science

Oxford COVID-19 (OxCOVID19) database and tracker is a powerful tool for understanding the pandemic and predicting its future course, using the combined power of Statistical, Mathematical Modelling and Machine Learning techniques


The OxCovid19 Tracker showing a World view of cases as at 4 October 2020

A coalition of researchers from Oxford University and other institutions has developed a comprehensive database of information relating to the COVID-19 pandemic. The data is drawn daily from dozens of sources worldwide and works alongside an interactive COVID-19 tracker which visualises the global geographic spread of the pandemic as well as giving a detailed view of the UK.

The OxCOVID19 Project was initiated by Dr Adam Mahdi at the Institute of Biomedical Engineering - part of the Department of Engineering Science - at the end of February as a response to the challenges that researchers face when modelling the spread of COVID-19, such as erratic reporting, lack of granularity and inconsistent formatting of data.

am-oxfordDr Mahdi says: ‘The main challenge we faced was to link different sources of data across small geographical regions, reported at the national and regional level. To our knowledge, this is the only database that links so many features related to COVID-19 at such high geographical resolution.’

One of the ways this challenge presented itself is in how different countries make data on COVID-19 public – some with freely accessible GitHub accounts, others only announcing cases and trends on social media. The strength of the OxCOVID19 Project is in collecting data from multiple sources, then unifying, validating and pairing it with geographical regions, before storing it in the database.

The OxCOVID19 Database forms the basis for the team’s recently developed Interactive COVID-19 Tracker, pictured above and below, which visualises the geographic spread of the pandemic globally as well as giving a more detailed view of the UK. Users can choose to view the cumulative impact by selecting the total number of cases to date or see the current state of the epidemic by selecting the average daily numbers over the last seven days, with an option to see the rate of cases adjusted in relation to the area’s population.

The underlying database is the result of hundreds of hours of combined efforts with the contributions of multiple organisations, including the Oxford Institute of Biomedical Engineering, the Blavatnik School of Government, Imperial College London, the Met Office, World Value Survey, European Value Study, the Oxford Mathematics Institute, the Oxford Internet institute, Swansea University, Dioscuri Centre in Topological Data Analysis, and AGH University of Science and Technology in Poland.


Updated daily, the database offers a freely available and relational source of information related to the COVID-19 pandemic, combining epidemiological information (confirmed cases, deaths, recoveries, hospitalisations, etc.), government responses (school closures, economic measures, etc.), mobility (for example changes in human mobility trends), weather (temperature, humidity and precipitation, etc.), socioeconomic statistics and value surveys for all countries at the national and (for more than 50 countries) at the regional level.

Several research groups are already known to be using this resource via the CoMo (COVID-19 pandemic modelling) Consortium. It contributed to the recent study on the economic impact of dexamethasone treatment for patients with COVID-19, performed in collaboration with Oxford’s RECOVERY and CoMo groups. Other independent groups are developing tools to facilitate use of the database, such as a package for the R language and a database proxy on Splitgraph. A number of research projects that use OxCOVID19 Database are currently underway, including a cross-departmental study on exploring mechanisms for occurrence of multiple waves of COVID-19. The summative essays for the Fundamentals of Social Data Science course taught at Oxford Internet Institute will also employ the OxCOVID19 Database as their primary source.

The recently introduced COVID-19 Tracker is also gaining momentum with the general public as a visual tool to track COVID-19 hotspots, with 12,000 visits recorded to the Tracker website to date.

The OxCOVID19 Project is led by Dr Adam Mahdi, the project’s technical lead is Dr Piotr Błaszczyk and other current and past team members include Dr Alex Zarebski, Dr Paweł Dłotko, Dr John Harvey, Dr Tak-Shing Chan, Davide Gurnari, Dr Yue Wu, Dr Dario Salvi, Niklas Hellmer, Ahmad Farhat, Steve Poynter, Bryan Chan, Tarun Srivastava, Dr Bernie Hogan and Professor Lionel Tarassenko.

A preprint describing the OxCOVID19 database is available on medRxiv (doi:


Further resources

Dr Adam Mahdi:

OxCOVID19 Project:

CoMo consortium

Economic impact of dexamethasone treatment for patients with COVID-19 study

R language package:

Integrated data catalog and database proxy Splitgraph: