Modelling, machine learning and data science approaches to understanding the COVID-19 pandemic will shape policy decisions over the coming years. This research requires rich and standardised databases at a fine geographical level: epidemiological, mobility, socioeconomic and more. Despite the massive data collection efforts in the UK and around the world, sourcing and linking data of different modalities create major burdens for researchers.
The OxCOVID19 Project collects data of different types from multiple sources worldwide. This allows researchers to work with a broad focus, for example, allowing for studies aimed at estimating the global effects of non-pharmaceutical interventions on COVID-19. The resulting database is unique in its scope, both in the variety of data collected and in the focus on sub-national geographies.
Director of Graduate Studies, Departmental Research Lecturer
Project role: Project Lead
Adam Mahdi’s research focuses on digital health and application of machine learning in social sciences. He is the director of the UKRI-funded OxCOVID19 Project and a fellow at Wolfson College, University of Oxford.
Associate Professor, Senior Research Fellow
Project role: Co-Investigator
Bernie Hogan examines how to capture, represent and think about social networks, especially personal social networks. His work focuses on the role of design in social media, network capture techniques and theories of relationships.
Senior Research Officer, Mathematics, University of Swansea
Project role: Co-Investigator
John Harvey is a a research mathematician with interests in geometry and topology, and in how these subjects can be applied in topological data analysis.
Former Research Associate
Project role: Tech Lead
Dr Blaszczyk was a Postdoctoral Researcher at the Oxford Internet Institute. He is a computer scientist with experience in academia and years of leadership positions in the technology sector.
