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1000 Titel
  • UK prevalence of underlying conditions which increase the risk of severe COVID-19 disease: a point prevalence study using electronic health records
1000 Autor/in
  1. Walker, Jemma L. |
  2. Grint, Daniel J. |
  3. Strongman, Helen |
  4. Eggo, Rosalind M. |
  5. Peppa, Maria |
  6. Minassian, Caroline |
  7. Mansfield, Kathryn E. |
  8. Rentsch, Christopher T. |
  9. Douglas, Ian J. |
  10. Mathur, Rohini |
  11. Wong, Angel Y. S. |
  12. Quint, Jennifer K. |
  13. Andrews, Nick |
  14. Bernal, Jamie Lopez |
  15. Scott, J. Anthony |
  16. Ramsay, Mary |
  17. Smeeth, Liam |
  18. McDonald, Helen |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-03-11
1000 Erschienen in
1000 Quellenangabe
  • 21(1):484
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s12889-021-10427-2 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7948667/ |
1000 Ergänzendes Material
  • https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-021-10427-2#Sec24 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • 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.
1000 Sacherschließung
gnd 1206347392 COVID-19
lokal Prevalence
lokal Electronic health records
lokal United Kingdom
lokal Risk factors
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/V2Fsa2VyLCBKZW1tYSBMLg==|https://frl.publisso.de/adhoc/uri/R3JpbnQsIERhbmllbCBKLg==|https://frl.publisso.de/adhoc/uri/U3Ryb25nbWFuLCBIZWxlbg==|https://frl.publisso.de/adhoc/uri/RWdnbywgUm9zYWxpbmQgTS4=|https://frl.publisso.de/adhoc/uri/UGVwcGEsIE1hcmlh|https://frl.publisso.de/adhoc/uri/TWluYXNzaWFuLCBDYXJvbGluZQ==|https://frl.publisso.de/adhoc/uri/TWFuc2ZpZWxkLCBLYXRocnluIEUu|https://frl.publisso.de/adhoc/uri/UmVudHNjaCwgQ2hyaXN0b3BoZXIgVC4=|https://frl.publisso.de/adhoc/uri/RG91Z2xhcywgSWFuIEou|https://frl.publisso.de/adhoc/uri/TWF0aHVyLCBSb2hpbmk=|https://frl.publisso.de/adhoc/uri/V29uZywgQW5nZWwgWS4gUy4=|https://frl.publisso.de/adhoc/uri/UXVpbnQsIEplbm5pZmVyIEsu|https://frl.publisso.de/adhoc/uri/QW5kcmV3cywgTmljaw==|https://frl.publisso.de/adhoc/uri/QmVybmFsLCBKYW1pZSBMb3Bleg==|https://frl.publisso.de/adhoc/uri/U2NvdHQsIEouIEFudGhvbnk=|https://frl.publisso.de/adhoc/uri/UmFtc2F5LCBNYXJ5|https://frl.publisso.de/adhoc/uri/U21lZXRoLCBMaWFt|https://orcid.org/0000-0003-0576-2015
1000 Label
1000 Förderer
  1. National Institute for Health and Care Research |
  2. Health Protection Research Unit |
  3. London School of Hygiene and Tropical Medicine |
  4. Public Health England |
1000 Fördernummer
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1000 Förderprogramm
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1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer National Institute for Health and Care Research |
    1000 Förderprogramm -
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer Health Protection Research Unit |
    1000 Förderprogramm -
    1000 Fördernummer -
  3. 1000 joinedFunding-child
    1000 Förderer London School of Hygiene and Tropical Medicine |
    1000 Förderprogramm -
    1000 Fördernummer -
  4. 1000 joinedFunding-child
    1000 Förderer Public Health England |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
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1000 @id frl:6428447.rdf
1000 Erstellt am 2021-07-02T16:55:12.969+0200
1000 Erstellt von 218
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1000 Zuletzt bearbeitet 2022-08-18T11:39:20.830+0200
1000 Objekt bearb. Thu Aug 18 11:39:10 CEST 2022
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1000 Oai Id
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