Persistent COVID-19 symptoms in a community study of 606,434 people in England
Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3–5 of the REACT-2 study ( n = 508,707; September 2020 – February 2021), a representative community survey of adults in England, and replication data from round 6 ( n ...
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| Veröffentlicht in: | Nature communications Jg. 13; H. 1; S. 1957 - 10 |
|---|---|
| Hauptverfasser: | , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
London
Nature Publishing Group UK
12.04.2022
Nature Publishing Group Nature Portfolio |
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| ISSN: | 2041-1723, 2041-1723 |
| Online-Zugang: | Volltext |
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| Abstract | Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3–5 of the REACT-2 study (
n
=
508,707; September 2020 – February 2021), a representative community survey of adults in England, and replication data from round 6 (
n
=
97,717; May 2021) to estimate the prevalence and identify predictors of persistent symptoms lasting 12 weeks or more; and unsupervised learning to cluster individuals by reported symptoms. At 12 weeks in rounds 3–5, 37.7% experienced at least one symptom, falling to 21.6% in round 6. Female sex, increasing age, obesity, smoking, vaping, hospitalisation with COVID-19, deprivation, and being a healthcare worker are associated with higher probability of persistent symptoms in rounds 3–5, and Asian ethnicity with lower probability. Clustering analysis identifies a subset of participants with predominantly respiratory symptoms. Managing the long-term sequelae of COVID-19 will remain a major challenge for affected individuals and their families and for health services.
This study characterises Long COVID using data from the REACT-2 community-based study in England. It estimates that 38% (in autumn/winter 2020/21) and 22% (in spring 2021) of people reported at least one symptom 12 weeks after symptom onset; identifies risk factors for persistent symptoms; and finds evidence of symptom clustering. |
|---|---|
| AbstractList | Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3–5 of the REACT-2 study (n = 508,707; September 2020 – February 2021), a representative community survey of adults in England, and replication data from round 6 (n = 97,717; May 2021) to estimate the prevalence and identify predictors of persistent symptoms lasting 12 weeks or more; and unsupervised learning to cluster individuals by reported symptoms. At 12 weeks in rounds 3–5, 37.7% experienced at least one symptom, falling to 21.6% in round 6. Female sex, increasing age, obesity, smoking, vaping, hospitalisation with COVID-19, deprivation, and being a healthcare worker are associated with higher probability of persistent symptoms in rounds 3–5, and Asian ethnicity with lower probability. Clustering analysis identifies a subset of participants with predominantly respiratory symptoms. Managing the long-term sequelae of COVID-19 will remain a major challenge for affected individuals and their families and for health services.This study characterises Long COVID using data from the REACT-2 community-based study in England. It estimates that 38% (in autumn/winter 2020/21) and 22% (in spring 2021) of people reported at least one symptom 12 weeks after symptom onset; identifies risk factors for persistent symptoms; and finds evidence of symptom clustering. This study characterises Long COVID using data from the REACT-2 community-based study in England. It estimates that 38% (in autumn/winter 2020/21) and 22% (in spring 2021) of people reported at least one symptom 12 weeks after symptom onset; identifies risk factors for persistent symptoms; and finds evidence of symptom clustering. Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3-5 of the REACT-2 study (n = 508,707; September 2020 - February 2021), a representative community survey of adults in England, and replication data from round 6 (n = 97,717; May 2021) to estimate the prevalence and identify predictors of persistent symptoms lasting 12 weeks or more; and unsupervised learning to cluster individuals by reported symptoms. At 12 weeks in rounds 3-5, 37.7% experienced at least one symptom, falling to 21.6% in round 6. Female sex, increasing age, obesity, smoking, vaping, hospitalisation with COVID-19, deprivation, and being a healthcare worker are associated with higher probability of persistent symptoms in rounds 3-5, and Asian ethnicity with lower probability. Clustering analysis identifies a subset of participants with predominantly respiratory symptoms. Managing the long-term sequelae of COVID-19 will remain a major challenge for affected individuals and their families and for health services. Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3–5 of the REACT-2 study ( n = 508,707; September 2020 – February 2021), a representative community survey of adults in England, and replication data from round 6 ( n = 97,717; May 2021) to estimate the prevalence and identify predictors of persistent symptoms lasting 12 weeks or more; and unsupervised learning to cluster individuals by reported symptoms. At 12 weeks in rounds 3–5, 37.7% experienced at least one symptom, falling to 21.6% in round 6. Female sex, increasing age, obesity, smoking, vaping, hospitalisation with COVID-19, deprivation, and being a healthcare worker are associated with higher probability of persistent symptoms in rounds 3–5, and Asian ethnicity with lower probability. Clustering analysis identifies a subset of participants with predominantly respiratory symptoms. Managing the long-term sequelae of COVID-19 will remain a major challenge for affected individuals and their families and for health services. Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3-5 of the REACT-2 study (n = 508,707; September 2020 - February 2021), a representative community survey of adults in England, and replication data from round 6 (n = 97,717; May 2021) to estimate the prevalence and identify predictors of persistent symptoms lasting 12 weeks or more; and unsupervised learning to cluster individuals by reported symptoms. At 12 weeks in rounds 3-5, 37.7% experienced at least one symptom, falling to 21.6% in round 6. Female sex, increasing age, obesity, smoking, vaping, hospitalisation with COVID-19, deprivation, and being a healthcare worker are associated with higher probability of persistent symptoms in rounds 3-5, and Asian ethnicity with lower probability. Clustering analysis identifies a subset of participants with predominantly respiratory symptoms. Managing the long-term sequelae of COVID-19 will remain a major challenge for affected individuals and their families and for health services.Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3-5 of the REACT-2 study (n = 508,707; September 2020 - February 2021), a representative community survey of adults in England, and replication data from round 6 (n = 97,717; May 2021) to estimate the prevalence and identify predictors of persistent symptoms lasting 12 weeks or more; and unsupervised learning to cluster individuals by reported symptoms. At 12 weeks in rounds 3-5, 37.7% experienced at least one symptom, falling to 21.6% in round 6. Female sex, increasing age, obesity, smoking, vaping, hospitalisation with COVID-19, deprivation, and being a healthcare worker are associated with higher probability of persistent symptoms in rounds 3-5, and Asian ethnicity with lower probability. Clustering analysis identifies a subset of participants with predominantly respiratory symptoms. Managing the long-term sequelae of COVID-19 will remain a major challenge for affected individuals and their families and for health services. Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3–5 of the REACT-2 study ( n = 508,707; September 2020 – February 2021), a representative community survey of adults in England, and replication data from round 6 ( n = 97,717; May 2021) to estimate the prevalence and identify predictors of persistent symptoms lasting 12 weeks or more; and unsupervised learning to cluster individuals by reported symptoms. At 12 weeks in rounds 3–5, 37.7% experienced at least one symptom, falling to 21.6% in round 6. Female sex, increasing age, obesity, smoking, vaping, hospitalisation with COVID-19, deprivation, and being a healthcare worker are associated with higher probability of persistent symptoms in rounds 3–5, and Asian ethnicity with lower probability. Clustering analysis identifies a subset of participants with predominantly respiratory symptoms. Managing the long-term sequelae of COVID-19 will remain a major challenge for affected individuals and their families and for health services. This study characterises Long COVID using data from the REACT-2 community-based study in England. It estimates that 38% (in autumn/winter 2020/21) and 22% (in spring 2021) of people reported at least one symptom 12 weeks after symptom onset; identifies risk factors for persistent symptoms; and finds evidence of symptom clustering. |
| ArticleNumber | 1957 |
| Author | Elliott, Paul Ward, Helen Whitaker, Matthew Chadeau-Hyam, Marc Elliott, Joshua Riley, Steven Cooke, Graham Darzi, Ara |
| Author_xml | – sequence: 1 givenname: Matthew orcidid: 0000-0003-1363-6537 surname: Whitaker fullname: Whitaker, Matthew organization: School of Public Health, Imperial College London, MRC Centre for Environment and Health, Imperial College London – sequence: 2 givenname: Joshua surname: Elliott fullname: Elliott, Joshua organization: Imperial College Healthcare NHS Trust, Department of Infectious Disease, Imperial College London – sequence: 3 givenname: Marc orcidid: 0000-0001-8341-5436 surname: Chadeau-Hyam fullname: Chadeau-Hyam, Marc organization: School of Public Health, Imperial College London, MRC Centre for Environment and Health, Imperial College London – sequence: 4 givenname: Steven surname: Riley fullname: Riley, Steven organization: School of Public Health, Imperial College London, MRC Centre for Global Infectious Disease Analysis, Imperial College London, Abdul Latif Jameel Institute for Disease & Emergency Analytics, Imperial College London – sequence: 5 givenname: Ara orcidid: 0000-0001-7815-7989 surname: Darzi fullname: Darzi, Ara organization: Imperial College Healthcare NHS Trust, Institute of Global Health Innovation at Imperial College London – sequence: 6 givenname: Graham orcidid: 0000-0001-6475-5056 surname: Cooke fullname: Cooke, Graham organization: Imperial College Healthcare NHS Trust, Department of Infectious Disease, Imperial College London, National Institute for Health Research Imperial Biomedical Research Centre – sequence: 7 givenname: Helen orcidid: 0000-0001-8238-5036 surname: Ward fullname: Ward, Helen organization: Imperial College Healthcare NHS Trust, MRC Centre for Global Infectious Disease Analysis, Imperial College London, National Institute for Health Research Imperial Biomedical Research Centre – sequence: 8 givenname: Paul orcidid: 0000-0002-7511-5684 surname: Elliott fullname: Elliott, Paul email: p.elliott@imperial.ac.uk organization: School of Public Health, Imperial College London, MRC Centre for Environment and Health, Imperial College London, Imperial College Healthcare NHS Trust, National Institute for Health Research Imperial Biomedical Research Centre, Health Data Research (HDR) UK London at Imperial College, UK Dementia Research Institute at Imperial College |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35413949$$D View this record in MEDLINE/PubMed |
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| References_xml | – reference: LinzerDALewisJBpoLCA: an R package for polytomous variable latent class analysisJ. Stat. Softw.20114212910.18637/jss.v042.i10 – reference: HennigCCluster-wise assessment of cluster stabilityComput. Stat. Data Anal.200752258271240998010.1016/j.csda.2006.11.025 – reference: Living with Covid19. https://evidence.nihr.ac.uk/themedreview/living-with-covid19/, https://doi.org/10.3310/themedreview_41169 (Accessed 31 March 2022). – reference: Huang, Y. et al. COVID symptoms, symptom clusters, and predictors for becoming a long-hauler: looking for clarity in the haze of the pandemic. Preprint at medRxivhttps://doi.org/10.1101/2021.03.03.21252086 (2021). – reference: Hennig, C. fpc: Flexible Procedures for Clustering. 2020. https://cran.r-project.org/web/packages/fpc/index.html. – reference: Imperial College London. Real-time Assessment of Community Transmission (REACT) study. https://www.imperial.ac.uk/medicine/research-and-impact/groups/react-study/ (accessed 31 March 2022). – reference: Evans, R. A. et al. Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study. Lancet Respir. Med. https://doi.org/10.1016/S2213-2600(21)00383-0 (2021). – reference: MichelenMCharacterising long COVID: a living systematic reviewBMJ Glob. Health20216e00542710.1136/bmjgh-2021-005427 – reference: Overview | COVID-19 rapid guideline: managing the long-term effects of COVID-19 | Guidance (NICE). – reference: Blomberg, B. et al. Long COVID in a prospective cohort of home-isolated patients. Nat. Med. https://doi.org/10.1038/s41591-021-01433-3 (2021). – reference: Prokhorenkova, L., Gusev, G., Vorobev, A., Dorogush, A. V. & Gulin, A. CatBoost: unbiased boosting with categorical features. Preprint at arXiv [cs.LG]: 1706.09516 (2017). – reference: Cirulli, E. T. et al. Long-term COVID-19 symptoms in a large unselected population. Preprint at bioRxivhttps://doi.org/10.1101/2020.10.07.20208702 (2020). – reference: SudreCHAttributes and predictors of long COVIDNat. Med.2021276266311:CAS:528:DC%2BB3MXmt1entb0%3D10.1038/s41591-021-01292-y – reference: Timeline of UK government coronavirus lockdowns. https://www.instituteforgovernment.org.uk/charts/uk-government-coronavirus-lockdowns (accessed 31 March 2022). – reference: SykesDLPost-COVID-19 symptom burden: what is long-COVID and how should we manage it?Lung20211991131191:CAS:528:DC%2BB3MXktlWrtb8%3D10.1007/s00408-021-00423-z – reference: TomasoniDAnxiety and depression symptoms after virological clearance of COVID-19: A cross-sectional study in Milan, ItalyJ. Med. Virol.202193117511791:CAS:528:DC%2BB3cXhvFCrurzK10.1002/jmv.26459 – reference: ElliottJPredictive symptoms for COVID-19 in the community: REACT-1 study of over 1 million peoplePLoS Med.202118e10037771:CAS:528:DC%2BB3MXit1eitrbP10.1371/journal.pmed.1003777 – reference: DaviesBCommunity factors and excess mortality in first wave of the COVID-19 pandemic in EnglandNat. Commun.2021122021NatCo..12.3755D1:CAS:528:DC%2BB3MXhtl2jsrzJ10.1038/s41467-021-23935-x – reference: Sorensen & Julius, T. A Method of Establishing Groups of Equal Amplitude in Plant Sociology Based on Similarity of Species Content and Its Application to Analyses of the Vegetation on Danish Commons (I kommission hos E. Munksgaard, 1948). – reference: EFS Survey. 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| Snippet | Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3–5 of the REACT-2 study (
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... Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3-5 of the REACT-2 study (n =... Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3–5 of the REACT-2 study (n =... This study characterises Long COVID using data from the REACT-2 community-based study in England. It estimates that 38% (in autumn/winter 2020/21) and 22% (in... |
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| Title | Persistent COVID-19 symptoms in a community study of 606,434 people in England |
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