UK prevalence of underlying conditions which increase the risk of severe COVID-19 disease: a point prevalence study using electronic health records

  1. Jemma L. Walker
  2. Daniel J. Grint
  3. Helen Strongman
  4. Rosalind M. Eggo
  5. Maria Peppa
  6. Caroline Minassian
  7. Kathryn E. Mansfield
  8. Christopher T. Rentsch
  9. Ian J. Douglas
  10. Rohini Mathur
  11. Angel Y. S. Wong
  12. Jennifer K. Quint
  13. Nick Andrews
  14. Jamie Lopez Bernal
  15. J. Anthony Scott
  16. Mary Ramsay
  17. Liam Smeeth
  18. Helen I. McDonald

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Abstract

Background

Characterising the size and distribution of the population at risk of severe COVID-19 is vital for effective policy and planning. Older age, and underlying health conditions, are associated with higher risk of death from COVID-19. This study aimed to describe the population at risk of severe COVID-19 due to underlying health conditions across the United Kingdom.

Methods

We used anonymised electronic health records from the Clinical Practice Research Datalink GOLD to estimate the point prevalence on 5 March 2019 of the at-risk population following national guidance. Prevalence for any risk condition and for each individual condition is given overall and stratified by age and region with binomial exact confidence intervals. We repeated the analysis on 5 March 2014 for full regional representation and to describe prevalence of underlying health conditions in pregnancy. We additionally described the population of cancer survivors, and assessed the value of linked secondary care records for ascertaining COVID-19 at-risk status.

Results

On 5 March 2019, 24.4% of the UK population were at risk due to a record of at least one underlying health condition, including 8.3% of school-aged children, 19.6% of working-aged adults, and 66.2% of individuals aged 70 years or more. 7.1% of the population had multimorbidity. The size of the at-risk population was stable over time comparing 2014 to 2019, despite increases in chronic liver disease and diabetes and decreases in chronic kidney disease and current asthma. Separately, 1.6% of the population had a new diagnosis of cancer in the past 5 y.

Conclusions

The population at risk of severe COVID-19 (defined as either aged ≥70 years, or younger with an underlying health condition) comprises 18.5 million individuals in the UK, including a considerable proportion of school-aged and working-aged individuals. Our national estimates broadly support the use of Global Burden of Disease modelled estimates in other countries. We provide age- and region- stratified prevalence for each condition to support effective modelling of public health interventions and planning of vaccine resource allocation. The high prevalence of health conditions among older age groups suggests that age-targeted vaccination strategies may efficiently target individuals at higher risk of severe COVID-19.

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  1. Version published to 10.1186/s12889-021-10427-2
  2. ScreenIT

    SciScore for 10.1101/2020.08.24.20179192: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: 12 Secondary care (hospital) data linkage is available for approximately 75% of CPRD GOLD-registered individuals in England, based on practice-level consent.
    IACUC: Ethics approval: Approval was received from the Independent Scientific Advisory Committee of the Medicines and Healthcare Products Regulatory Agency (ISAC number: 20_062A) and the Ethics Committee of the London School of Hygiene and Tropical Medicine (reference 21851).
    IRB: Ethics approval: Approval was received from the Independent Scientific Advisory Committee of the Medicines and Healthcare Products Regulatory Agency (ISAC number: 20_062A) and the Ethics Committee of the London School of Hygiene and Tropical Medicine (reference 21851).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableFor pregnancy, the study population comprised women aged 11–49 years.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strengths and limitations: To our knowledge, these are the first prevalence estimates of the full population at risk of severe COVID-19 across the UK according to national guidelines. Strengths include the large, nationally representative cohort, risk group definitions with detailed ascertainment tailored to risk of COVID-19, and quantification of the value of linked secondary care records. To support policy and planning flexibly as evidence of the associations of different underlying conditions with COVID-19 outcomes evolves, we provide age-and region-stratified prevalence for each underlying condition separately, including separating asthma from other respiratory conditions.16, 24 A key limitation is that UK-wide estimates rely on primary care records, which may miss undiagnosed conditions and under-ascertain conditions diagnosed in secondary care. Our analysis including linked secondary care records in England suggests that estimates of the overall size of the at-risk population are robust, but that the prevalence of multimorbidity, chronic heart disease and liver disease may be underestimated from primary care records. There is likely under-ascertainment of immunosuppressing cancer treatments even using secondary care records, which could be on a scale similar to the 1·6% of the population newly diagnosed with cancer within the previous year. Second, the 2019 estimates did not include all regions in England. Although the dataset remained nationally representative in terms...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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  3. Version published to 10.1101/2020.08.24.20179192v1 on medRxiv