Characterisation, prediction of complications, and safety of emergent therapies for viral outbreaks and pneumonia: a rapid network study to inform management of COVID-19

Date of ISAC Approval: 
Lay Summary: 
Scientists can learn from previous viral outbreaks like the flu to inform how we respond to the current crisis. Coronavirus COVID-19 is an ongoing viral pandemic that is placing extreme pressures on health systems including the United Kingdom National Health Service. Any evidence that can be derived from existing routinely-collected data would aid in the response to the pandemic. In our proposed research we will use existing data to characterise previous virus outbreaks, study sufferers of previous infections and viral pneumoniae, and to generate prediction tools (web apps and similar) for the prediction of severe cases of viral infection. The findings from these studies will help to immediately inform the response to COVID-19. In addition, we will investigate the use and safety of medicines being tested as antivirals for COVID-19. These results will inform ongoing and future drug development. The proposed study using primary care and linked hospital data will be part of a global collaboration using existing health care data to inform the global response to COVID-19.
Technical Summary: 
Data from previous viral outbreaks including the seasonal flu can be used to generate evidence that may help to inform the response to the current Coronavirus COVID-19 pandemic. One dataset that could provide many useful insights is the Clinical Practice Research Datalink (CPRD GOLD and AURUM) linked to Hospital Episode Statistics admitted patient care data (HES-APC). Using such data, we aim to answer the following three research questions: 1) What are the features and characteristics of the symptoms and complications of seasonal flu and Covid19 infections, with a particular focus on pneumoniae? 2) What are the predictors of adverse outcomes amongst patients with flu- or Covid19-related hospitalization? And can we, by combining them, generate algorithms that can help us identify subjects most at risk of complications and/or morbi-mortality? AND 3) What are the effects of treatments being considered/used for potential use in COVID-19, including hydroxychloroquine, antivirals, systemic steroids, and angiotensin converting enzyme inhibitors (ACEi) and angiotensin II receptor blockers (ARB)? CPRD GOLD, AURUM, and linked HES-APC will be mapped to Observational Medical Outcomes Partnership (OMOP) common data model (CDM). Performing the analysis on mapped data will allow for the study to be replicated in other data sources that have also been mapped to the OMOP CDM, including Asian data with COVID-19 cases already available from South Korea. We will update the extracted data in the coming months with new cohorts of patients and their electronic medical records during the current calendar year to include those with COVID-19 so that once mapped to the OMOP CDM, findings can be further validated. COVID19 UK cohorts are expected to be available from CPRD GOLD, AURUM and linked HES from Q3 or Q4 2020.
Health Outcomes to be Measured: 
1. Pneumonia based on hospital admission/s data from linked HES-APC 2. Adult distress respiratory syndrome based on hospital admission/s data from linked HES-APC 3. Advanced life support including ICU and/or mechanical ventilation or intubation based on hospital admission/s data from linked HES-APC 4. All-cause death based on CPRD GOLD or AURUM date of death 5. Serious adverse effects for the studied medicines based on hospital admission/s obtained from linked HES-APC

Dr Patrick Ryan - Chief Investigator - Johnson & Johnson (JnJ - USA)
Dr Albert Prats-Uribe - Collaborator - University of Oxford
Dr Antonella Delmestri - Collaborator - University of Oxford
Dr Daniel Prieto-Alhambra - Collaborator - University of Oxford
Edward Burn - Collaborator - Oxford University Hospitals
Dr Martijn Schuemie - Collaborator - Janssen US
Dr Patrick Ryan - Corresponding Applicant - Johnson & Johnson (JnJ - USA)
Sara Khalid - Collaborator - University of Oxford

HES Admitted