Last updated 1 Jun 2020
This website provides information about personal vulnerability to Covid-19 according to age, sex, ethnicity and comorbidities. Its purpose is to assist health professionals in the UK who are asked to advise about patients’ medical fitness for work that may entail exposure to coronavirus. It is not intended for, or suitable for use as a clinical practice guideline.
In managing occupational risks of Covid-19, employers must control exposure to the virus so far as is reasonably practicable, taking into account the possibility that some workers will be more vulnerable than others should they contract the disease. Guidance on the overall approach to risk management can be found at Returning_to_the_workplace_COVID-19_toolkit_FINAL and specifically for healthcare workers at Risk-Reduction-Framework-for-NHS-staff-at-risk-of-COVID-19-infection-12-05-20 and SOM_RTW_guide_health_professionals_COVID-19_FINAL.
Strategies may include changes to the way in which work is carried out, use of barriers and personal protective equipment (PPE), and in some cases, exclusion or redeployment of individuals who are more vulnerable.
The need for selective exclusion/redeployment of vulnerable workers will depend on the likelihood of their contracting Covid-19 through their work (which will vary according to the job and the prevalence of infection in the local community), and on the extent of their personal vulnerability to severe illness should they get the disease.
The best evidence on vulnerability to Covid-19 comes from epidemiological research. From analysis of epidemiological data for the UK, the contributions to vulnerability from sex, ethnicity and some of the most common comorbidities among people of working age have been summarised in terms of their equivalence to added years of age (see Table 1 below). This allows calculation of a person’s “Covid-age” – a simple summary measure indicating the age of a healthy white male with equivalent vulnerability . We start with the individual’s biological age, then add/subtract the age adjustments from the table. For example:
A healthy white woman, age 40, has a Covid-age of (40-8) = 32 years
A white man age 45, BMI 36, severe asthma, has a Covid-age of (45+5+4) = 54 years.
An Asian woman age 50, Type 2 diabetes HbA1c>58, has a Covid-age of (50-8+5+10) = 57 years.
To give the measure context, we also provide estimates of case fatality rates in healthy white men by age. (see Table 2 below). As relevant new evidence becomes available, evidence-based assessment of vulnerability will be updated and refined, with extension to other categories of comorbidity where that becomes possible.
The background evidence and methods can be found here: Methods at 200526
and the original paper was placed on the medRxiv pre-print server: 2020.05.21.20108969v1.full
Table 1. Vulnerability from risk factors expressed as equivalence to added years of age
|Risk factor||Relative risk||Equivalent added years of age||Robustness of risk estimate|
|Asian or Asian British||1.5||4||Moderately robust|
|Body mass index (Kg/m2)|
|Mild (no requirement for oral corticosteroids in past year)||1.1||1||Moderately robust|
|Severe (requiring oral corticosteroids in past year)||1.4||4||Moderately robust|
|HbA1c≤58 mmol/mol in past year||2.0||8||Moderately robust|
|HbA1c>58 mmol/mol in past year||2.7||11||Moderately robust|
|HbA1c unknown||3.3||13||Moderately robust|
|Type 2 and other|
|HbA1c≤58 mmol/mol in past year||1.5||4||Moderately robust|
|HbA1c>58 mmol/mol in past year||2.0||8||Moderately robust|
|HbA1c unknown||2.3||9||Moderately robust|
|Other chronic heart disease||1.3||3||Provisional|
|Chronic respiratory disease (excluding asthma)||1.9||7||Moderately robust|
|Chronic kidney disease*||1.7||6||Moderately robust|
|Diagnosed <1 year ago||1.6||5||Provisional|
|Diagnosed 1-4.9 years ago||1.2||2||Provisional|
|Diagnosed ≥5 years ago||1||0||Provisional|
|Diagnosed <1 year ago||3.5||14||Provisional|
|Diagnosed 1-4.9 years ago||3.1||13||Provisional|
|Diagnosed ≥5 years ago||1.9||7||Provisional|
|Chronic neurological disease other than stroke or dementia**||2.5||10||Provisional|
|Other immunosuppressive condition‡||1.8||7||Provisional|
*Glomerular filtration rate <60mL/min/1.73m2, as estimated from the most recent serum creatinine measurement.
**Includes motor neurone disease, myasthenia gravis, multiple sclerosis, Parkinson’s disease, cerebral palsy, quadriplegia, hemiplegia, malignant primary brain tumour and progressive cerebellar disease.
†Includes splenectomy, or spleen dysfunction (e.g. from sickle cell disease).
‡Includes HIV, conditions inducing permanent immunodeficiency (ever diagnosed), aplastic anaemia, and temporary immunodeficiency recorded within the past year.
Table 2. Relative risks of mortality from Covid-19 and estimated case fatality rates in healthy white males by age
|Age (years)||Estimated risk relative to that at age 47 years (healthy white males)||Estimated case-fatality rate per 1000 in cases of Covid-19 infection (healthy white males)|
Meanwhile, qualitative guidance on predicted vulnerability from comorbidities that have not yet been studied epidemiologically is provided in risk tables that were compiled by clinical experts soon after Covid-19 emerged (see separate pages listed at the bottom of this page). Although compiled by expert clinicians, this qualitative guidance is inevitably much less reliable than that based on epidemiological data. It may change substantially as further information becomes available. When compiled, it stratified vulnerability into ‘very high’, ‘high’, ‘moderate’ and ‘low’ in accordance to the likely effect of Covid-19 on the individual. Clinical judgement will be required when considering how this relates to Covid-age.
As this qualitative guidance was based on what is known about respiratory infections generally, it may change substantially as further information becomes available on the specific effects of Covid-19.
The work has been undertaken by the Joint Occupational Health COVID-19 Group:
Prof David Coggon, Southampton, Prof Peter Croft, Keele, Prof Paul Cullinan, Imperial College, Dr Tony Williams, Working Fit Ltd
Prof Ewan MacDonald, Glasgow, Prof Raymond Agius, Manchester, Prof Mike Pearson, Liverpool, Dr Anne de Bono, Faculty of Occupational Medicine, Dr Will Ponsonby, Society of Occupational Medicine, Dr Blandina Blackburn, NHS Health at Work Network, Dr Alastair Leckie, NHS Lothian
Working Group for Tables:
Dr Jacqui Bollman, Dr Pam Collins, Dr Andrew Dickson, Dr Emma McCollum, Dr Kerry McNeil, Dr Pam Mellors, Dr Peter Noone, Dr Chris Valentine, Dr Eugene Waclawski, Dr Tony Williams
Dr Tony Williams, Working Fit Ltd