Covid-19 Medical Risk Assessment

COVID-AGE

Last updated 4th January 2022

Covid-age was developed to assist health professionals when advising workers in the UK on their personal vulnerability to COVID-19, and implications for their employment.  Vulnerability can be quantified as the probability of death should infection occur.  It varies according to age, sex, ethnicity, the presence of other health conditions (comorbidities), and immunity from vaccination or previous infection.  Covid-age summarises published evidence on the impacts of age, sex, ethnicity and comorbidities in the absence of vaccination or previous infection. It is intended for use as part of occupational health assessment of individuals’ fitness for work, and not in clinical treatment pathways.

WHAT DOES COVID-AGE MEAN?

An individual’s Covid-age is calculated by expressing the impacts of risk factors as added years of age that would carry a similar increase in vulnerability.  The values for each applicable risk factor are then added to the individual’s true age. This gives an estimate of the age of a healthy white man, who in the absence of vaccination or previous infection, would be expected to have similar vulnerability.

HOW SHOULD COVID-AGE BE USED?

When assessing a worker’s occupational risk from COVID-19, their Covid-age can be set alongside their history of vaccination and/or infection to derive an overall estimate of personal vulnerability.  That assessment can then be combined with knowledge about their job and the expected community prevalence of infection, to obtain an assessment of risk (for more detailed guidance, see section below on Management of occupational risks from COVID-19).

HOW DO I FIND A PERSON’S COVID-AGE?

The easy way is to enter risk factors into the online calculator below.

Alternatively, you can calculate Covid-age using Table 1 at the bottom of this page (see section below on Estimating Covid-age using tables).

Before using Covid-age, it is important to note the following caveats.

CAVEATS

Because each individual is different, Covid-age is not an exact measure of vulnerability.  It is an estimate consistent with the current balance of scientific evidence.

Some of the categories of comorbidity are broad-ranging, and within them, vulnerability may vary. The tool gives an overall average estimate of vulnerability, which may be individually tailored through clinical judgement of a suitably qualified health professional.

Some potentially relevant health problems are not covered by the tool, because insufficient evidence is available on them. Using clinical judgement, it may in some cases be reasonable to apply added years that have been estimated for another similar condition. For example, there is evidence that inflammatory bowel diseases and inflammatory skin diseases carry similar vulnerability to inflammatory joint diseases.

Covid-age does not assess risks from Covid-19 in pregnancy.  While there is evidence of increased vulnerability during pregnancy, it is not in a form that can be incorporated into the current risk model.  Moreover, the disease can impact adversely on obstetric outcomes as well as maternal health.  When assessing and managing occupational risks from Covid-19 during pregnancy, users should refer to https://www.rcog.org.uk/en/guidelines-research-services/guidelines/coronavirus-pregnancy/covid-19-virus-infection-and-pregnancy/ 

Covid-age is based on evidence relating to various comorbidities, but in most cases, their treatment has not been considered separately. The estimate of added years for a condition represents an average across the spectrum of treatment for that disease. This includes the effects of treatment with immunosuppressive medication, and it is not necessary to add further years of age in respect of such treatment.

The group ‘other immunosuppressive disorders’ refers to medical conditions that depress immune responses, and which are not included elsewhere in the calculator.  It does not cover immunosuppressive medication. Any immunological effects of diseases that are listed elsewhere in the calculator (e.g. diabetes, splenectomy) are covered by those categories. 

Calculations assume as a default that added years for different risk factors can be summed (i.e. that relative risks multiply). However, that assumption may not be accurate for all risk factors, especially when it leads to calculated Covid-ages greater than 85. The online calculator therefore presents Covid-ages in this upper range simply as >85. It does, however, show the years added for each risk factor so that clinicians can see the assumed impact of different conditions.

SOURCES OF EVIDENCE ON VULNERABILITY

Further details of the background evidence and methods can be found here: Methods at 211214

MANAGEMENT OF OCCUPATIONAL RISKS FROM COVID-19

CONTEXT

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.

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, and on the extent of their personal vulnerability to severe illness should they get the disease.

The level of individual risk that is considered acceptable will depend on value judgements, which can differ from person to person, and it is therefore not possible to lay down hard and fast rules.  However, we here suggest an approach that may be a useful starting point for decision-making.

The approach entails first using Covid-age to assess the individual’s vulnerability to COVID-19 in the absence of previous infection or vaccination.  That assessment is then modified to account for any previous infection or vaccination.  Finally, a matrix is applied to guide decisions according to the nature of the job and local prevalence of infection.

VULNERABILITY LEVELS

It may be convenient to stratify vulnerability into ranges. We have used a lower bound of Covid-age 85 to define a stratum of ‘very high vulnerability’. In the absence of vaccination or previous infection, this may correspond to infection fatality rates in excess of around one in twenty, and could be considered equivalent to being ‘clinically extremely vulnerable’.

To define a second stratum of ‘high vulnerability’, we suggest a lower bound at Covid-age 70 (which in those with no vaccination or previous infection has carried an infection fatality rate of around one in a hundred). This corresponds approximately to the threshold for the Government’s category of ‘clinically vulnerable’.

To account for differences in vulnerability below that level, we suggest a further cut-point at Covid-age 50, which distinguishes ‘moderate vulnerability’ from ‘low vulnerability’.

Covid-age will determine the stratum of vulnerability to which an individual is initially assigned, but in some cases clinical judgement may indicate that a different stratum is appropriate because of individual circumstances.

ACCOUNTING FOR SPECIFIC IMMUNITY

Specific immunity from previous infection and/or vaccination may reduce both the risk of becoming infected by SARS-CoV-2 and personal vulnerability should infection occur. The level of protection will vary according to time interval(s) since infection/vaccination, number of vaccinations, type(s) of vaccine administered, and the variant(s) of the virus to which the individual is subsequently exposed. It may also differ in the presence of comorbidities, and particularly those which impair immune responses.

Currently available data do not allow detailed quantitative assessment of how reductions in risk differ according to these variables, or how they are apportioned between lower rates of infection and lower vulnerability once infection has occurred.  It appears, however, that on average among people of working age, previous infection or vaccination will provide protection in excess of 80% against mortality from variants of SARS-CoV-2 that are currently dominant in the UK.  Moreover, that protection will last for months or longer, and can be enhanced by further vaccination.

The table below shows relative risks corresponding to different levels of vaccine protection against death from Covid-19, and reductions in Covid-age that would give an equivalent reduction in risk.

Level of vaccine protection (%) against death from Covid-19 Relative risk of death from Covid-19 Reduction in Covid-age (years) that would give equivalent relative risk
97.5 0.025 36
95 0.05 29
90 0.1 22
85 0.15 18
80 0.2 16
75 0.25 13
70 0.3 12
65 0.35 10
60 0.4 9
50 0.5 7
40 0.6 5
30 0.7 3

We suggest that to account for reduced risk from vaccination, it would be reasonable in many cases to shift a previously infected/vaccinated individual down by one stratum of vulnerability – for example, from ‘very high’ to ‘high’ or from ‘high’ to ‘moderate’.

An exception might be individuals on immune suppressant medication or with conditions affecting immunity such as HIV or cancer, who may not respond so well to vaccines. Particularly in such cases, clinical judgement should be applied when considering adjustments to assessed vulnerability.

ACCOUNTING FOR VIRAL PREVALENCE

A major determinant of risk is local prevalence of infection by SARS-CoV-2, Other things being equal, in occupations that do not involve selective contact with people more likely to be carrying the virus (as occurs for example in healthcare), risk of exposure can be expected to vary in proportion to the local prevalence of infection.

A MATRIX FOR RISK MANAGEMENT

Based on the above considerations, we set out below a matrix combining what we know about vulnerability, immunity, and viral prevalence to classify individuals according to the type of work that they might reasonably undertake.  It should be viewed as a rough guide and tailored to account for special circumstances and the views of the worker.

Matrix guide for estimation of a worker’s overall risk pre-and post-vaccination

Overall risk is very high, avoid this activity
Overall risk is high, only undertake this activity if it is essential and cannot be avoided
Overall risk is moderate, avoid if the activity is unnecessary
Overall risk is low, no requirement for any additional adjustments or controls

 

70-84

Viral prevalence per weekα
Workplace risk Covid-age
Adjusted for immunity
1-9/​100,000 10-99/​100,000 100-999/​100,000 1000+/​100,000
Very High
In rooms, wards or vehicles caring for Covid-positive patients where full PPE cannot be worn reliably.
85 & above
70-84
50-69
Under 50
High
In rooms, wards, accommodation buildings or vehicles in close proximity to people with suspected Covid-19.
85 & above
70-84
50-69
Under 50
Medium
High number of different face-to-face contacts. e.g. healthcare, care homes, social care, hairdressing, teaching, police, probation work, supermarket staff.
Public transport staff and passengers
85 & above
70-84
50-69
Under 50
Low
Good social distancing, ventilation and hygiene measures e.g. call centre work, office work, in-home utility and repair work.
Commuting by car, bicycle and walking.
85 & above
70-84
50-69
Under 50
Working from home All ages

αIndividual Government websites provide current viral prevalence rates, although this can also be accessed via: https://www.bbc.co.uk/news/uk-51768274

A guide to using this matrix can also be downloaded from

https://www.som.org.uk/sites/som.org.uk/files/COVID-19_return_to_work_in_the_roadmap_out_of_lockdown_March_2021.pdf

ESTIMATING COVID-AGE USING TABLES

Use these tables by starting with the person’s actual age and then adding or subtracting years for each risk factor that applies, using Table 1 below.

First find their actual age in the top line of the table, then follow the column down to find the estimated impact (i.e. years to add or subtract from their actual age) for each risk factor that applies to that person. For example:

  1. A healthy white woman, aged 40, has a Covid-age of (40-5) = 35 years
  2. A white man aged 45, BMI 36 with severe asthma, has a Covid-age of (45+13+11) = 69 years.
  3. An Asian woman aged 50 with Type 2 diabetes, unknown HbA1c, has a Covid-age of (50-5+5+20) = 70 years.

Whether a person’s Covid-age is obtained from the online calculator or using Table 1, minor modification may be warranted to account for the specific circumstances of the individual (e.g. the severity of relevant comorbidities). If you judge that to be appropriate, you should make the adjustment using your clinical judgement,

Table 1.  Vulnerability from risk factors expressed as equivalence to added years of age

True age (years) 20 21 22 23 24 25 26 27 28 29
 
Female sex -5 -5 -5 -5 -5 -5 -5 -5 -5 -5
 
Ethnicity
Asian or Asian British 5 5 5 5 5 5 5 5 5 5
Black 7 7 7 7 7 7 7 7 7 7
Mixed 5 5 5 5 5 5 5 5 5 5
Other non-white 4 4 4 4 4 4 4 4 4 4
                     
Body mass index (Kg/m2)                    
30-34.9 7 7 7 7 7 6 6 6 6 6
35-39.9 19 19 19 18 18 18 18 17 17 17
≥40 25 25 24 24 24 23 23 23 22 22
                     
Hypertension 12 12 12 12 12 12 12 11 11 11
                     
Heart failure 25 25 25 25 25 25 24 24 24 24
                     
Other chronic heart disease 20 20 20 20 20 20 19 19 19 19
                     
Cerebrovascular disease 17 17 17 16 16 16 16 16 16 16
 
Asthma
Mild 1 1 1 1 1 1 1 1 1 1
Severe 15 15 15 15 15 15 14 14 14 14
                     
Other chronic respiratory disease 17 17 17 17 17 16 16 16 16 16
                     
Diabetes                    
Type 1                    
HbA1≤58 mmol/mol in past year 24 24 24 24 24 24 23 23 23 23
HbA1>58 mmol/mol in past year 27 27 27 27 27 27 26 26 26 26
HbA1c unknown 29 29 29 29 29 28 28 28 28 28
                     
Type 2 and other                    
HbA1≤58 mmol/mol in past year 21 21 21 21 21 20 20 20 20 20
HbA1>58 mmol/mol in past year 23 23 23 23 23 22 22 22 22 22
HbA1c unknown 22 22 22 22 22 21 21 21 21 21
 
Chronic kidney disease
Estimated GFR 30-60 mL/min 42 41 40 39 38 37 37 36 35 34
Estimated GFR < 30 mL/min 53 52 51 50 50 49 48 47 46 46
                     
Non-haematological cancer                    
Diagnosed <1 year ago 34 33 33 32 32 31 31 30 30 29
Diagnosed 1-4.9 years ago 25 25 25 24 24 24 23 23 22 22
Diagnosed ≥5 years ago 18 18 18 18 17 17 17 16 16 16
                     
Haematological malignancy                    
Diagnosed <1 year ago 33 33 32 32 32 32 31 31 31 31
Diagnosed 1-4.9 years ago 32 31 31 31 30 30 30 29 29 29
Diagnosed ≥5 years ago 21 21 21 21 21 20 20 20 20 20
                     
Liver disease 32 31 31 30 30 29 29 28 28 27
                     
Chronic neurological disease other than stroke or dementia* 23 23 22 22 22 22 22 22 22 22
                     
Organ transplant 25 25 24 24 24 24 24 24 24 24
                     
Spleen diseases† 14 14 13 13 13 13 13 13 13 13
                     
Rheumatoid/lupus/psoriasis 2 2 2 2 2 2 2 2 2 2
                     
Other immunosuppressive condition‡ 30 30 29 29 28 28 27 27 26 26
True age (years) 30 31 32 33 34 35 36 37 38 39
 
Female sex -5 -5 -5 -5 -5 -5 -5 -5 -5 -5
 
Ethnicity
Asian or Asian British 5 5 5 5 5 5 5 5 5 5
Black 7 7 7 7 7 7 7 7 7 7
Mixed 5 5 5 5 5 5 5 5 5 5
Other non-white 4 4 4 4 4 4 4 4 4 4
                     
Body mass index (Kg/m2)                    
30-34.9 6 6 6 6 6 6 6 6 5 5
35-39.9 17 16 16 16 16 15 15 15 15 15
≥40 22 21 21 21 20 20 19 19 19 18
                     
Hypertension 11 11 11 11 10 10 10 10 10 10
                     
Heart failure 24 23 23 23 22 22 22 22 21 21
                     
Other chronic heart disease 19 18 18 18 17 17 17 17 16 16
                     
Cerebrovascular disease 16 16 16 16 16 16 16 15 15 15
 
Asthma
Mild 1 1 1 1 1 1 1 1 1 1
Severe 14 14 14 13 13 13 13 13 12 12
                     
Other chronic respiratory disease 16 15 15 15 15 15 14 14 14 14
                     
Diabetes                    
Type 1                    
HbA1≤58 mmol/mol in past year 23 23 22 22 22 22 22 21 21 21
HbA1>58 mmol/mol in past year 26 26 25 25 25 25 25 25 24 24
HbA1c unknown 28 28 28 27 27 27 27 27 26 26
                     
Type 2 and other                    
HbA1≤58 mmol/mol in past year 20 20 20 19 19 19 19 19 19 19
HbA1>58 mmol/mol in past year 22 22 22 21 21 21 21 21 21 21
HbA1c unknown 21 21 21 21 21 21 21 21 20 20
 
Chronic kidney disease
Estimated GFR 30-60 mL/min 33 32 32 31 30 29 28 27 26 26
Estimated GFR < 30 mL/min 45 44 44 43 42 41 40 39 38 37
                     
Non-haematological cancer                    
Diagnosed <1 year ago 29 28 28 27 27 26 26 25 25 24
Diagnosed 1-4.9 years ago 22 21 21 21 20 20 19 19 18 18
Diagnosed ≥5 years ago 15 15 15 14 14 13 13 12 12 11
                     
Haematological malignancy                    
Diagnosed <1 year ago 30 30 30 30 29 29 29 29 28 28
Diagnosed 1-4.9 years ago 28 28 28 27 27 27 26 26 25 25
Diagnosed ≥5 years ago 20 19 19 19 19 18 18 18 18 17
                     
Liver disease 27 26 26 25 25 24 24 23 23 22
                     
Chronic neurological disease other than stroke or dementia* 22 22 21 21 21 21 21 21 21 20
                     
Organ transplant 23 23 23 23 23 23 22 22 22 22
                     
Spleen diseases† 13 13 13 12 12 12 12 12 12 12
                     
Rheumatoid/lupus/psoriasis 2 2 2 2 2 2 2 2 2 2
                     
Other immunosuppressive condition‡ 25 25 24 24 23 23 22 22 21 21
True age (years) 40 41 42 43 44 45 46 47 48 49
 
Female sex -5 -5 -5 -5 -5 -5 -5 -5 -5 -5
 
Ethnicity
Asian or Asian British 5 5 5 5 5 5 5 5 5 5
Black 7 7 7 7 7 7 7 7 7 7
Mixed 5 5 5 5 5 5 5 5 5 5
Other non-white 4 4 4 4 4 4 4 4 4 4
                     
Body mass index (Kg/m2)                    
30-34.9 5 5 5 5 5 5 5 4 4 4
35-39.9 14 14 14 14 13 13 13 13 12 12
≥40 18 17 17 17 16 16 16 15 15 14
                     
Hypertension 9 9 9 9 9 8 8 8 8 8
                     
Heart failure 21 20 20 20 19 19 19 18 18 18
                     
Other chronic heart disease 16 15 15 15 14 14 14 13 13 13
                     
Cerebrovascular disease 15 15 15 15 15 15 15 14 14 14
 
Asthma
Mild 1 1 1 1 1 1 1 1 1 1
Severe 12 12 12 11 11 11 11 10 10 10
                     
Other chronic respiratory disease 14 13 13 13 13 13 13 12 12 12
                     
Diabetes                    
Type 1                    
HbA1≤58 mmol/mol in past year 21 21 20 20 20 20 20 19 19 18
HbA1>58 mmol/mol in past year 24 24 24 23 23 23 23 22 22 22
HbA1c unknown 26 26 25 25 25 25 24 24 24 23
                     
Type 2 and other                    
HbA1≤58 mmol/mol in past year 19 18 18 18 18 18 17 17 17 16
HbA1>58 mmol/mol in past year 21 20 20 20 20 20 19 19 19 18
HbA1c unknown 20 20 20 20 20 20 19 19 19 18
                     
Chronic kidney disease                    
Estimated GFR 30-60 mL/min 25 24 23 22 21 20 19 19 18 18
Estimated GFR < 30 mL/min 36 35 35 34 33 33 32 32 31 30
                     
Non-haematological cancer                    
Diagnosed <1 year ago 24 23 23 22 22 21 21 20 20 19
Diagnosed 1-4.9 years ago 18 17 17 16 16 16 15 15 14 13
Diagnosed ≥5 years ago 11 11 10 10 10 9 9 9 8 8
                     
Haematological malignancy                    
Diagnosed <1 year ago 28 28 27 27 27 26 26 26 25 25
Diagnosed 1-4.9 years ago 25 24 24 23 23 22 22 22 22 22
Diagnosed ≥5 years ago 17 17 17 16 16 16 15 15 14 14
 
Liver disease 22 21 21 20 20 19 19 18 17 17
                     
Chronic neurological disease other than stroke or dementia* 20 20 20 20 20 20 19 19 19 19
                     
Organ transplant 22 22 21 21 21 21 21 20 20 20
                     
Spleen diseases† 11 11 11 11 11 11 10 10 10 10
                     
Rheumatoid/lupus/psoriasis 2 2 2 2 2 2 2 2 2 2
                     
Other immunosuppressive condition‡ 20 20 19 19 18 17 17 16 16 15
True age (years) 50 51 52 53 54 55 56 57 58 59
 
Female sex -5 -5 -5 -5 -5 -5 -5 -5 -5 -5
 
Ethnicity
Asian or Asian British 5 5 5 5 5 5 5 5 5 5
Black 7 7 7 7 7 7 7 7 7 7
Mixed 5 5 5 5 5 5 5 5 5 5
Other non-white 4 4 4 4 4 4 4 4 4 4
                     
Body mass index (Kg/m2)                    
30-34.9 4 4 4 3 3 3 3 3 3 3
35-39.9 12 11 11 11 10 10 10 10 9 9
≥40 14 14 13 13 12 12 12 11 11 11
                     
Hypertension 7 7 7 7 7 6 6 6 5 5
                     
Heart failure 17 17 17 16 16 16 15 15 14 14
                     
Other chronic heart disease 13 12 12 12 12 11 11 10 10 9
                     
Cerebrovascular disease 14 14 14 13 13 13 13 13 12 12
 
Asthma
Mild 1 1 1 1 1 1 1 1 1 1
Severe 9 9 9 9 8 8 8 7 7 7
                     
Other chronic respiratory disease 12 12 11 11 11 11 10 10 10 9
                     
Diabetes                    
Type 1                    
HbA1≤58 mmol/mol in past year 18 18 17 17 16 16 16 15 15 14
HbA1>58 mmol/mol in past year 21 21 20 20 19 19 19 18 18 17
HbA1c unknown 23 23 22 22 21 21 20 20 19 19
                     
Type 2 and other                    
HbA1≤58 mmol/mol in past year 16 16 15 15 14 14 14 13 13 12
HbA1>58 mmol/mol in past year 18 18 17 17 16 16 16 15 15 14
HbA1c unknown 18 18 17 17 16 16 16 15 15 14
                     
Chronic kidney disease                    
Estimated GFR 30-60 mL/min 17 16 16 15 14 14 13 13 12 11
Estimated GFR < 30 mL/min 30 29 28 28 27 26 26 25 24 23
                     
Non-haematological cancer                    
Diagnosed <1 year ago 19 18 18 17 16 16 15 15 14 14
Diagnosed 1-4.9 years ago 13 12 11 11 10 10 9 9 8 8
Diagnosed ≥5 years ago 8 7 7 7 6 6 6 5 5 4
                     
Haematological malignancy                    
Diagnosed <1 year ago 24 24 23 23 22 22 21 21 20 20
Diagnosed 1-4.9 years ago 21 21 21 21 20 20 20 19 19 18
Diagnosed ≥5 years ago 13 12 12 11 11 10 10 10 9 9
 
Liver disease 16 15 15 14 14 13 13 12 12 11
                     
Chronic neurological disease other than stroke or dementia* 18 18 18 18 17 17 17 16 16 16
                     
Organ transplant 19 19 19 18 18 18 17 17 16 16
                     
Spleen diseases† 9 9 9 8 8 8 8 7 7 7
                     
Rheumatoid/lupus/psoriasis 2 2 2 2 2 2 2 2 2 2
                     
Other immunosuppressive condition‡ 15 15 14 14 13 13 13 12 12 11
True age (years) 60 61 62 63 64 65 66 67 68 69
 
Female sex -5 -5 -5 -5 -5 -5 -5 -5 -5 -5
 
Ethnicity
Asian or Asian British 5 5 5 5 5 5 5 5 5 5
Black 7 7 7 7 7 7 7 7 7 7
Mixed 5 5 5 5 5 5 5 5 5 5
Other non-white 4 4 4 4 4 4 4 4 4 4
                     
Body mass index (Kg/m2)                    
30-34.9 3 2 2 2 2 2 2 2 2 2
35-39.9 9 8 8 8 7 7 7 6 6 5
≥40 10 10 10 9 9 9 8 8 7 7
                     
Hypertension 5 5 4 4 4 3 3 3 2 2
                     
Heart failure 13 13 12 12 11 11 11 10 10 10
                     
Other chronic heart disease 9 8 8 7 7 6 6 5 5 5
                     
Cerebrovascular disease 12 12 12 11 11 11 11 11 10 10
 
Asthma
Mild 1 1 1 1 1 1 1 1 1 1
Severe 6 6 5 5 4 4 4 4 3 3
 
Other chronic respiratory disease 9 9 8 8 8 7 7 7 7 7
 
Diabetes
Type 1
HbA1≤58 mmol/mol in past year 14 13 13 12 12 11 11 11 10 10
HbA1>58 mmol/mol in past year 17 16 16 15 15 14 14 14 13 13
HbA1c unknown 18 18 17 17 16 16 15 15 14 14
                     
Type 2 and other                    
HbA1≤58 mmol/mol in past year 12 11 11 10 10 9 9 8 8 7
HbA1>58 mmol/mol in past year 14 13 13 12 12 11 11 11 10 10
HbA1c unknown 14 13 13 12 12 11 11 11 10 10
                     
Chronic kidney disease                    
Estimated GFR 30-60 mL/min 11 10 9 9 8 8 7 7 6 6
Estimated GFR < 30 mL/min 23 22 22 21 20 20 19 19 18 18
                     
Non-haematological cancer
Diagnosed <1 year ago 13 13 12 12 11 11 10 10 9 9
Diagnosed 1-4.9 years ago 8 7 7 7 6 6 6 5 5 4
Diagnosed ≥5 years ago 4 3 3 2 2 1 1 1 1 0
                     
Haematological malignancy                    
Diagnosed <1 year ago 19 19 18 17 17 16 16 15 15 14
Diagnosed 1-4.9 years ago 18 17 17 16 16 15 15 14 14 13
Diagnosed ≥5 years ago 9 8 8 8 7 7 7 7 6 6
                     
Liver disease 11 10 10 9 9 8 8 7 7 6
                     
Chronic neurological disease other than stroke or dementia* 16 15 15 15 14 14 14 14 13 13
                     
Organ transplant 15 15 14 14 13 13 12 12 11 11
                     
Spleen diseases† 6 6 6 5 5 5 5 4 4 3
                     
Rheumatoid/lupus/psoriasis 2 2 2 2 2 2 2 2 2 2
                     
Other immunosuppressive condition‡ 11 11 10 10 9 9 9 8 8 7
True age (years) 70 71 72 73 74 75
 
Female sex -5 -5 -5 -5 -5 -5
 
Ethnicity
Asian or Asian British 5 5 5 5 5 5
Black 7 7 7 7 7 7
Mixed 5 5 5 5 5 5
Other non-white 4 4 4 4 4 4
             
Body mass index (Kg/m2)            
30-34.9 2 1 1 1 1 1
35-39.9 5 5 4 4 3 3
≥40 7 6 6 5 5 5
             
Hypertension 2 1 1 0 0 0
             
Heart failure 9 9 9 8 8 8
             
Other chronic heart disease 4 4 4 3 3 3
             
Cerebrovascular disease 10 10 9 9 9 9
 
Asthma
Mild 1 1 1 1 1 1
Severe 3 3 2 2 2 2
 
Other chronic respiratory disease 6 6 6 6 6 6
 
Diabetes
Type 1
HbA1≤58 mmol/mol in past year 10 9 9 8 8 8
HbA1>58 mmol/mol in past year 13 12 12 12 11 11
HbA1c unknown 14 13 13 12 12 12
             
Type 2 and other            
HbA1≤58 mmol/mol in past year 7 6 6 6 5 5
HbA1>58 mmol/mol in past year 9 9 9 8 8 8
HbA1c unknown 9 9 9 8 8 7
 
Chronic kidney disease
Estimated GFR 30-60 mL/min 5 5 4 4 3 3
Estimated GFR < 30 mL/min 17 17 16 16 15 15
             
Non-haematological cancer            
Diagnosed <1 year ago 9 8 8 8 7 7
Diagnosed 1-4.9 years ago 4 3 3 3 2 2
Diagnosed ≥5 years ago 0 0 0 0 0 0
             
Haematological malignancy            
Diagnosed <1 year ago 14 13 13 12 12 11
Diagnosed 1-4.9 years ago 13 12 12 11 11 11
Diagnosed ≥5 years ago 6 6 5 5 5 5
             
Liver disease 6 6 5 5 4 4
             
Chronic neurological disease other than stroke or dementia* 13 13 12 12 12 12
             
Organ transplant 10 10 9 9 8 8
             
Spleen diseases† 3 2 2 1 1 0
             
Rheumatoid/lupus/psoriasis 2 2 2 2 2 2
             
Other immunosuppressive condition‡ 7 7 6 6 5 5

*Chronic neurological disease other than stroke or dementia includes motor neurone disease, myasthenia gravis, multiple sclerosis, Parkinson’s disease, cerebral palsy, quadriplegia, hemiplegia and progressive cerebellar disease.

†Spleen diseases include splenectomy, or spleen dysfunction (e.g. from sickle cell disease).

‡Other immunosuppressive condition includes HIV, conditions inducing permanent immunodeficiency (ever diagnosed), aplastic anaemia, and temporary immunodeficiency recorded within the past year.

 

PROJECT PARTICIPANTS

The work has been undertaken by the Joint Occupational Health COVID-19 Group:

Principal Authors:

Prof David Coggon, Southampton, Prof Peter Croft, Keele, Prof Paul Cullinan, Imperial College London, Dr Tony Williams, Working Fit Ltd

OpenSAFELY team:

Our thanks to the OpenSAFELY team, and in particular to Prof Krishnan Bhaskharan, Professor of Statistical Epidemiology at the London School of Hygiene and Tropical Medicine, for providing the additional analyses used in the update of the Covid Age tables and Dr Elizabeth Williamson, Associate Professor of Medical Statistics at the London School of Hygiene and Tropical Medicine. These analyses are open access and can be found, with all other OpenSafely publications, at https://opensafely.org/research/

Website calculator:

Our thanks to Dr David Hodkin for developing the calculator, and for RStudio for hosting the tool on their shinyapps.io cloud.

Excel calculator:

Our thanks to Dr Mark Glover and Lalji Varsani for developing the Excel calculators.

Strategy Group:

Prof Ewan MacDonald, Glasgow (Chair), 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, Dr Drushca Lalloo, Glasgow, Dr Munna Roy, Glasgow, Dr Clare Rayner, Manchester

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

Project Manager:

Dr Tony Williams, Working Fit Ltd

covid19@workingfit.com

Pregnancy and COVID-19