ROCOVE

Summary (Research in a nutshell)

The Omicron COVID-19 variant is sweeping the UK. As well as being easier to transmit, it appears that existing monoclonal antibody (mAb) and antiviral treatments may be less effective against this variant. These medicines are in limited supply, and need to be offered to the people who need them the most, but also for whom the treatment is most likely to work. 

It is crucial that we can work out who is most likely to benefit from the treatment, and how many people might be suitable for treatment, so that we can stock up enough medicine.  At the same time, we use data from the whole Scottish population to monitor if there are any new side-effects being reported, as rare side-effects can be difficult to pick up in smaller clinical trials.

We are fortunately able to analyse this using existing research datasets, which contain data from vaccination records, COVID-19 test results, GP records, hospital records and more, for the national population. This data is pseudonymised, which means all the data that could be used to identify a particular person has been removed. 

We are also able to connect this with the registry of everyone taking these mAb and antiviral treatments, so we can keep an eye on how many people have received the treatment, and how everyone is getting on with their recovery from the virus. All the data is looked after in a secure computer system within Public Health Scotland (PHS) so that everyone’s privacy is protected. 

In terms of how well the treatment is working, the main outcomes we will be looking at are COVID-19 mortality, hospital admission, and intensive care unit (ICU) admission.

These outcomes will be assessed using ‘time-to-event’ analyses. In these analysis methods, we look at:

• If and when an outcome occurred within a specific time-frame (e.g. within a year of the treatment being administered) 
• The duration of admissions in the subset of people who had to go to hospital and/or ICU.

All these analyses will take into account whether outcomes are more likely because of certain factors called ‘confounders’: demographic, socio-economic and geographic factors, vaccination status, smoking status, body mass, history of COVID-19 infections prior to the infection resulting in treatment eligibility, other health conditions, and more. 

For assessing potential treatment side effects, we will investigate the causes of any hospital admissions or GP visits, report their frequency, and investigate when these side effects are commonly reported, relative to treatment.  For example, we might find that a percentage of people report some muscle aches, and that they are most commonly reported a certain number of days after the medicine was administered. 

This means that we might be able to target the treatment in the future to the people it is most likely to help recover, and who are less likely to have side effects. 

Publications

Key people

Contact

Holly Tibble: holly.tibble@ed.ac.uk

Key collaborators

Albasoft Ltd 

BREATHE – Health Data Research Hub for Respiratory Health 

Long COVID Scotland 

Public Health Scotland 

University of Strathclyde

Website

ROCOVE is a connected project of EAVE II.

More information about EAVE II Connected Projects

Partners and Funders

National Institute for Health Research

This research used data assets made available as part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20058).

Timeline

Start date: 1 January 2022

End date: 31 March 2022