Patient-level dataset to study the effect of COVID-19 in people with Multiple Sclerosis

Abstract

Multiple Sclerosis (MS) is an inflammatory autoimmune disease of the central nervous system, causing increased vulnerability to infections and disability among young adults. Ever since the coronavirus disease 2019 (COVID-19) outbreak, caused by severe acute respiratory syndrome coronavirus 2 infections, there have been concerns among people with MS (PwMS) about the potential interactions between various disease-modifying therapies and COVID-19. The COVID-19 in MS Global Data Sharing Initiative (GDSI) was initiated in 2020 to address these concerns. This paper focuses on the anonymisation and open-sourcing of a GDSI sub-dataset, comprising data entered by people with MS and clinicians using a fast data entry tool. The dataset includes demographics, comorbidities, hospital stay, and COVID-19 symptoms of PwMS. The dataset can be used to perform different statistical analyses to improve our understanding of COVID-19 in MS. Furthermore, this dataset can also be used within the context of educational activities to educate different stakeholders on the complex data science topics that were used within the GDSI.