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Risk factors and prediction models for long COVID: analysis of longitudinal cohort studies with linked NHS data
Safe People
Organisation name
University of Plymouth
Applicant name(s)
Yinghui Wei
Dylan Williams
Claire Steves
Anika Knuppel
Funders/ Sponsors
Medical Research Council
DEA accredited researcher?
Yes
Safe Projects
Project ID
618D-62F0-03B0-5AFF-3CA8-DEBA
Lay summary
Patients with long COVID have symptoms over a long time. Some patients do not receive a diagnosis by their doctors, and do not receive support for recovery from long COVID. With the requested data, we will compare two sources of information on long COVID, reported by patients and by their doctors. We will identify who are more likely to miss a diagnosis by doctors. The data on patients are needed to find who are at higher risk of having long COVID. The benefit to patients include the improved diagnosis of long COVID. More patients will receive a diagnosis by doctors. They will have better chance to have healthcare support for recovery.
Public benefit statement
The project will help to identify risk factors and develop risk scores to predict the likelihood of developing long lasting symptoms post COVID infection. Findings could help to guide clinical practice and heath care management through prioritisation of patient care for high risk groups.
Latest approval date
21/01/2022
Safe Data
Legal basis for provision of data under Article 6
(e) processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;
Lawful conditions for provision of data under Article 9
(j) processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.
Safe Setting
Access type
Secure e-Research Platform (SeRP)