CCU086: A data landscape review of datasets used in the surveillance of neurological complications of COVID-19

Project lead:
Stephen McKeever, University of Liverpool

During the COVID-19 pandemic, it became apparent that COVID-19 infection caused a range of issues within the nervous system including stroke, encephalopathy and peripheral neuropathy. We have also seen similar neurological complications in previous pandemics including Spanish flu (1918) and Swine flu (2009). The neurological complications from COVID-19 have resulted in patients developing long term health problems and disabilities that can persist long after their initial infection has resolved.

In response to COVID-19, multiple datasets were created to collect data of patients with COVID-19. However, some datasets were not primarily focused on neurological outcomes and therefore collected a range of different information.  Furthermore, it is unclear how common neurological complications are in COVID-19 infection.

This project aims to review the strengths and limitations of these databases, covering the sources of data and the quality of data obtained. From identifying these strengths and weaknesses we aim to create a new platform to identify neurological complications which arise from future pandemics. The review also aims to identify how common neurological complications are in COVID-19 infection.

The potential impact from creating a new and intuitive platform will produce more detailed information quickly in the event of future pandemics. This will help guide further research and medical management.

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