Evidence on risk factors associated with COVID-19 death
There are often difficulties when trying to understand the meaning of COVID-19 daily death rates. To make sense of the data more relevant information is needed and these numbers need to be placed in context. For example, what are the expected death rates due to factors such as prescribed medications, other underlying complications and age? What other factors are there? In this way we have a better grasp on the true impact of this infection on our population and therefore how we might be able to manage the situation.
World’s largest COVID-19 analysis to date
Academics at the University of Oxford and the London School of Hygiene & Tropical Medicine (LSHTM), have therefore analysed the health data of over 17.4 million UK adults to discover the key factors associated with death from COVID-19 . This gives the strongest evidence on risk factors associated with COVID-19 death to date.
The major risk factors in no particular order include the following:
- being male,
- older age,
- uncontrolled diabetes and
- severe asthma
- Asian and Black ethnic origin
- deprived social backgrounds
The findings are summarised as follows:
- Among the 17.4 million adults, from 1st February 2020 to 25th April 2020 there were 5,707 deaths in hospitals attributed to COVID-19.
- People of Asian and Black ethnic backgrounds are at a higher risk of death and, contrary to prior speculation, this is only partially attributable to pre-existing clinical risk factors or deprivation.
- Key factors related to COVID-19 death included being male, older age, uncontrolled diabetes and severe asthma.
- A deprived background was also found to be a major risk factor: this was also only partially attributable to other clinical risk factors.
Asian and Black ethnic origin at higher risk
The academics go onto report that compared to white people, people of Asian and Black ethnic origin were found to be at a higher risk of death. Previously, commentators and researchers have reasonably speculated that this might be due to higher prevalence of medical problems such as cardiovascular disease or diabetes among BME communities, or higher deprivation. The findings, based on detailed data, show that this only accounts for a small part of the excess risk. Consequently, further work must be done to fully understand why BME people are at such increased risk of death.
Results confirmed that men are at increased risk from COVID-19 death, as well as people of older ages and those with uncontrolled diabetes. People with more severe asthma were also found to be at increased risk of death from COVID-19.
There has already been some discussion around the potential benefits of female hormones such as oestrogen and HRT for protecting against the virus, although studies will be needed to prove this.
Professor Liam Smeeth, Professor of Clinical Epidemiology at LSHTM, NHS doctor and co-lead on the study, says: "We need highly accurate data on which patients are most at risk in order to manage the pandemic and improve patient care. The answers provided by this OpenSAFELY analysis are of crucial importance to countries around the world. For example, it is very concerning to see that the higher risks faced by people from BME backgrounds are not attributable to identifiable underlying health conditions".
Dr Ben Goldacre (pictured), in the Nuffield Department of Primary Care Health Sciences at the University of Oxford, NHS doctor and co-lead on the study, says:
"During a global health emergency we need answers quickly and accurately. That means we need very large, very current datasets. The UK has phenomenal coverage and quality of data. We owe it to patients to keep their data secure; and we owe it to the global community to make good use of this data. That’s why we have developed a new highly secure model, taking the analytics to where the data already resides."
Further analyses are already underway, including investigation into the effects of specific drugs routinely prescribed in primary care. The platform can also be used to evaluate COVID-19 spread with innovative approaches to modelling; predict local health service needs; assess the indirect health impacts of the pandemic; track the impact of national interventions; and inform exit from lockdown.
