A Multimodal COVID-19 Database for Research

Lead Research Organisation: University of Oxford
Department Name: Engineering Science

Abstract

The proposed project addresses one of the key UKRI priority areas of preparing data sets to defined quality standards by delivering a Multimodal Database for COVID-19 Research, a comprehensive and easy-to-use database for creating and validating epidemiological models.

Modelling, machine learning, digital and data approaches to understanding the COVID-19 pandemic will shape policy decisions over the coming year. Such research requires rich and standardised data at a fine geographical level and of multiple modalities: epidemiological, mobility, socioeconomic and more. Large quantities of COVID-19 data are collected both in the UK and around the world. However, sourcing and linking data of different modalities are major burdens for researchers, owing to the lack of standardisation. There is a clear need to establish a central repository to facilitate world-class research immediately and in coming years.

Building on our extensive voluntary work on the OxCOVID19 Database (https://covid19.eng.ox.ac.uk/), we seek funding to expand our global coverage, deepen our focus on the UK, design new interfaces for diverse users, develop stronger infrastructure for increasing demand, and grow our user numbers. This database will enable data linkage for research, delivering consolidated, well-formatted data in a way that avoids duplication of effort by multiple research groups and accelerates research by removing barriers to entry.

Publications

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