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COVID-19 Population Risk Assessment

We've used the University of Oxford’s QCovid® risk prediction model to identify additional people to be added to the Shielded Patient List (SPL).

Read about shielding letters and what to do if you think you should not have been identified as high risk.


If you have a question about the COVID-19 Population Risk Assessment that is not answered here, please email

We have used QCovid® to develop the COVID-19 Population Risk Assessment. This combines a number of factors such as age, sex registered at birth, ethnicity, body mass index (BMI) and specific health conditions and treatments to estimate the risk of a person catching coronavirus and becoming seriously unwell. 

We have used patient data held centrally to identify people who might be at high risk and generated risk assessment results for these people. People whose results are above the agreed threshold for high risk (clinically extremely vulnerable) of severe illness from coronavirus have been added to the Shielded Patient List (SPL) in England.

Coronavirus information can be found on GOV.UK, including guidance for high risk (clinically extremely vulnerable) people.

Our use of QCovid® in the COVID-19 Population Risk Assessment using patient data held centrally has been registered by NHS Digital as a Class 1 medical device with the Medicines and Healthcare products Regulatory Agency (MHRA).

Read more about QCovid®, how it works and how the NHS is using it.

How we've identified people as being potentially at high risk (clinically extremely vulnerable)

We worked with the University of Oxford to identify the pieces of information about people and their health that are needed by the risk assessment model to generate as accurate risk assessment results as possible.

We identified where this information could be found in existing datasets held by NHS Digital. We then gathered the specific pieces of information from the records of people who could potentially be considered high risk (clinically extremely vulnerable). As the national information and technology partner to the health and social care system in England, we have legal permission to securely collect and analyse this data.

The relevant coded data was found to be recorded in 7 national datasets:

We then ran this data securely through QCovid® to generate risk assessment results. The people whose risk assessment results were above the agreed threshold for high risk (clinically extremely vulnerable) were then added to the SPL.

Read more about how QCovid® works and the risk factors used to estimate risk assessment results.

More detailed information about the datasets used, the information we’ve used from those datasets and processing rules is now available. 

Health conditions and treatments

We have used data about the following conditions and treatments to generate population risk assessments.

Cardiovascular diseases

Respiratory diseases and treatment


Taking anti-leukotriene or long acting beta2-agonists (LABA)

Chronic obstructive pulmonary disease (COPD)

Cystic fibrosisbronchiectasis or alveolitis

Pulmonary hypertension or pulmonary fibrosis

Metabolic (diabetes), renal and liver conditions

Gestational diabetes is high blood sugar (glucose) that develops during pregnancy and can resolve after giving birth. People who have had gestational diabetes are at increased risk of developing type 2 diabetes or having undiagnosed diabetes.  

Some people with past gestational diabetes have been identified in combination with other factors by the QCovid® model as being potentially at high risk from coronavirus.

People with a history of gestational diabetes who have been advised to shield, but feel this is no longer relevant, are able to contact their GP for further advice. GPs can evaluate a patient’s risk with the most up to date information using the clinical tool, and remove them from the SPL if necessary.

More detailed information about gestational diabetes.

Neurological and psychiatric conditions

Immune and haematological conditions

Rheumatoid arthritis, SLE (systemic lupus erythematosus, more commonly known as lupus) or a seronegative arthritis such as ankylosing spondylitis

Sickle cell disease, HIV or severe combined immunodeficiency

Thrombosis or pulmonary embolus

Immunosuppressants, cancer conditions and treatments

Lung or oral cancer (such as laryngeal (larynx)nasopharyngeal or mouth cancer)

Solid organ transplant (such as lungliverstomachpancreasspleenheart or thymus)

Cancer of the blood or bone marrow (such as leukaemia, myelodysplastic syndromes, lymphoma or myeloma)

Chemotherapy in the last 12 months

Oral prednisolone (prescribed by a clinician 4 or more times in the last 6 months)

Immunosuppressants (prescribed by a clinician 4 or more times in the last 6 months)

Gestational diabetes

Some people with previous gestational diabetes have been identified by the QCovid® model as being at high risk. This will be appropriate for many as the model performs an individual assessment based on a wide range of risk factors, and also considers a person's risk in comparison to others of the same age and sex.  

However, because the risk assessment is based on routinely coded data from multiple systems, some people may have been identified as having diabetes when in fact they had gestational diabetes. Others may have incomplete data, in which case the risk assessment may have defaulted, on a precautionary basis, to a higher level of risk for that category and this may influence the overall assessment results. 

If a person has been identified as being at high risk due to previous gestational diabetes only (no other significant conditions) and both:

  • has a Body Mass Index (BMI) between 16 and 41
  • has had a HbA1c (a test to check average blood glucose/sugar levels) since delivery and within the last 12 months which is normal or in the pre-diabetes or non-diabetic hyperglycaemia range

they do not need to be included in the Shielded Patient List (SPL) and can be removed if they request this. They will still be called for an earlier vaccine. Shielding is advisory and people who have received a letter can choose whether or not to shield. Clinicians should always use their clinical judgement and discuss any decision to remove a patient from the SPL.

Where a person with previous gestational diabetes, and a normal HbA1c in the previous 12 months, has a BMI below 16 or above 41, the COVID-19 Clinical Risk Assessment Tool can be used to generate the patient’s risk assessment results. These results should be used to inform an individual assessment of risk to determine, in consultation with the patient, whether they should remain on the Shielded Patient List (SPL) or be removed.

Importantly, people with previous gestational diabetes have an increased risk of developing Type 2 diabetes (which would put them at higher risk from coronavirus) and they should continue to undergo the recommended annual checks for this.

The Royal College of General Practitioners (RCGP) has developed a flow chart to support GPs when considering risk for patients with a history of gestational diabetes.

Who has been risk assessed

Risk assessment results have only been generated for:

  • people who could potentially meet the threshold for being considered at high risk (clinically extremely vulnerable)
  • people who have not previously been identified by existing SPL processes

This means we have not generated risk assessment results for some people, including:

  • people who are already on the SPL
  • people who were previously on the SPL, but have been removed by a clinician involved in their care
  • people whose combined risk factors could not possibly meet the agreed threshold
  • people who have already been assessed individually by a clinician and identified as low or medium risk
  • people under the age of 19, or over 100, because QCovid® is not designed for use on these groups
  • people coded with Down’s syndrome in their record who had not already been identified through the national SPL. This is due to Down’s syndrome already being included in the national SPL ruleset and a known coding issue.

Agreed threshold for adding people to the Shielded Patient List

England’s Chief Medical Officer (CMO), in consultation with senior clinicians, looked at the results of the QCovid® research conducted by the University of Oxford to work out what risk threshold should be used to decide if someone may be high risk (clinically extremely vulnerable) and added to the SPL as a result.

The research showed that most people included in the study who died from coronavirus would have had risk assessment results that placed them in approximately the top 2% of the population in England that are at the highest risk. For the combined risk of catching and dying of coronavirus, most results were higher than or equal to:

  • an absolute risk of 0.5% (or 5 in 1,000)
  • a relative risk of 10 (or 10 times the baseline risk)

The CMO and senior clinicians decided that these thresholds should be used to help protect people who may be high risk.

Absolute risk is the overall risk, based on what happened to other people with the same characteristics and risk factors who caught coronavirus and went to hospital or died as a result.


Relative risk is the level of risk compared to a person who is the same age and sex registered at birth, but without any other risk factors.

Missing or unknown data

If certain information is missing from a record held by NHS Digital or has been recorded as unknown, then default values are used by the COVID-19 Population Risk Assessment as a substitute.

We have taken a precautionary approach to how we handle information which might be missing from records. This is to make sure that we do not underestimate people’s risk and exclude them from the high risk (clinically extremely vulnerable) group who will be added to the SPL.

Where data is missing, we have used some default values that have higher than average risk associated with them, according to QCovid®. This means that we are likely to be overestimating the level of risk for some people with information missing from their records and therefore identifying more people as potentially high risk (clinically extremely vulnerable). 

As a result, some people may be advised to shield based on these default values. Based on advice from clinical advisors, the Department of Health and Social Care has determined that this precautionary approach is clinically the most appropriate. 

The patient’s GP record will indicate that they have been added to the SPL using the COVID-19 Population Risk Assessment, and whether a default value was applied. Read more about how this is shown in GP IT systems.


Default values

Body Mass Index (BMI)

If a person’s BMI is not available, a BMI of 31 is used by default. This is the midpoint BMI in the population data that was available when we analysed it.

If BMI is more than 47, then a BMI of 47 will be used to generate the results. If BMI is less than 15, then a BMI of 15 will be used to generate the results. This is because almost all (99.9%) BMIs in the UK are between 15 and 47. BMIs calculated as being lower than 15 or higher than 47 are likely to be a mistake which would affect the accuracy of the result.

Sex registered at birth

If a person’s sex registered at birth is not available from GP data, and gender is not available from the Patient Demographic Service (PDS), a value equal to the sex with the highest risk is used by default. This is in line with the precautionary approach to overestimate rather than underestimate risk.


If a person’s ethnicity is not available, a value equal to the ethnicity with the highest risk is used by default. This is in line with the precautionary approach to overestimate rather than underestimate risk.


If a person’s postcode (used to identify a Townsend deprivation score) is not available, the average UK score for the Townsend deprivation index is used. This is in line with the defaults used in QCovid®.

Validating additions to the SPL generated by the population risk assessment

To act as quickly as possible and reduce GP workload, patients identified as potentially high risk have been added directly to the SPL. Clinicians can follow existing processes to review, add and remove patients from the SPL where this is appropriate at any time.

Clinicians should continue to review individual patients on an ongoing basis, according to clinical judgement and patient request. Guidance about how to identify this cohort of patients in IT systems is available for general practice and hospital trusts.

Clinicians can use the COVID-19 Clinical Risk Assessment Tool to validate additions to the SPL from the COVID-19 Population Risk Assessment. The tool uses the same QCovid® model used in the COVID-19 Population Risk Assessment and can be used to generate results for individual patients. Because the population risk assessment uses data from a number of national datasets and may include different default values, there may be some variation between results. Detailed guidance for clinicians is available within the online tool.

Patients not added to the SPL

GP practices can access details of their patients who were risk assessed, but whose risk assessment results did not meet the agreed threshold to be added to the SPL. Some of these patients may have been close to the threshold for addition to the SPL and GPs may wish to review these individually. The information will reflect whether default values were used. 

Clinicians can use the COVID-19 Clinical Risk Assessment Tool to review these patients, alongside their clinical judgement, as they may have access to more up-to-date information.

This list will not include every patient registered at the practice that may be close to the threshold because we did not risk assess all patients. GPs should therefore still consider using the risk assessment tool on an individual basis for patients they believe may be at risk.

GP practices can use the COVID-19 Population Risk Assessment Viewer to view these patients.

Transparency notice

This explains how personal information may be used by NHS Digital in relation to the COVID-19 Population Risk Assessment.

View the COVID-19 Population Risk Assessment transparency notice

Last edited: 19 April 2021 8:52 am