Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalisation, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform

COVID-19 has disproportionately affected minority ethnic populations in the UK. Our aim was to quantify ethnic differences in SARS-CoV-2 infection and COVID-19 outcomes during the first and second waves of the COVID-19 pandemic in England. We conducted an observational cohort study of adults (aged ≥...

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Veröffentlicht in:	The Lancet (British edition) Jg. 397; H. 10286; S. 1711 - 1724
Hauptverfasser:	Mathur, Rohini, Rentsch, Christopher T, Morton, Caroline E, Hulme, William J, Schultze, Anna, MacKenna, Brian, Eggo, Rosalind M, Bhaskaran, Krishnan, Wong, Angel Y S, Williamson, Elizabeth J, Forbes, Harriet, Wing, Kevin, McDonald, Helen I, Bates, Chris, Bacon, Seb, Walker, Alex J, Evans, David, Inglesby, Peter, Mehrkar, Amir, Curtis, Helen J, DeVito, Nicholas J, Croker, Richard, Drysdale, Henry, Cockburn, Jonathan, Parry, John, Hester, Frank, Harper, Sam, Douglas, Ian J, Tomlinson, Laurie, Evans, Stephen J W, Grieve, Richard, Harrison, David, Rowan, Kathy, Khunti, Kamlesh, Chaturvedi, Nishi, Smeeth, Liam, Goldacre, Ben
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Elsevier Ltd 08.05.2021 Elsevier Limited Elsevier
Schlagworte:	Adult Adults Biobanks Blood pressure Categories Cohort analysis Cohort Studies Coronaviruses COVID-19 COVID-19 - epidemiology COVID-19 - ethnology COVID-19 - mortality Cultural differences Death Deprivation Disaggregation Disease transmission Electronic health records Electronic medical records England Ethnicity Ethnicity - statistics & numerical data Health care Heterogeneity Hospitalization Hospitalization - statistics & numerical data Hospitals Households Humans Inequalities Infections Intensive care Intensive Care Units - statistics & numerical data Medical research Minority & ethnic groups Mortality Observational studies Observational Studies as Topic Pandemics Patient Admission - statistics & numerical data Population Populations Primary care Severe acute respiratory syndrome coronavirus 2 Sociodemographics Survival Analysis Vaccination Viral diseases England United Kingdom > UK
ISSN:	0140-6736, 1474-547X, 1474-547X
Online-Zugang:	Volltext
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Abstract	COVID-19 has disproportionately affected minority ethnic populations in the UK. Our aim was to quantify ethnic differences in SARS-CoV-2 infection and COVID-19 outcomes during the first and second waves of the COVID-19 pandemic in England. We conducted an observational cohort study of adults (aged ≥18 years) registered with primary care practices in England for whom electronic health records were available through the OpenSAFELY platform, and who had at least 1 year of continuous registration at the start of each study period (Feb 1 to Aug 3, 2020 [wave 1], and Sept 1 to Dec 31, 2020 [wave 2]). Individual-level primary care data were linked to data from other sources on the outcomes of interest: SARS-CoV-2 testing and positive test results and COVID-19-related hospital admissions, intensive care unit (ICU) admissions, and death. The exposure was self-reported ethnicity as captured on the primary care record, grouped into five high-level census categories (White, South Asian, Black, other, and mixed) and 16 subcategories across these five categories, as well as an unknown ethnicity category. We used multivariable Cox regression to examine ethnic differences in the outcomes of interest. Models were adjusted for age, sex, deprivation, clinical factors and comorbidities, and household size, with stratification by geographical region. Of 17 288 532 adults included in the study (excluding care home residents), 10 877 978 (62·9%) were White, 1 025 319 (5·9%) were South Asian, 340 912 (2·0%) were Black, 170 484 (1·0%) were of mixed ethnicity, 320 788 (1·9%) were of other ethnicity, and 4 553 051 (26·3%) were of unknown ethnicity. In wave 1, the likelihood of being tested for SARS-CoV-2 infection was slightly higher in the South Asian group (adjusted hazard ratio 1·08 [95% CI 1·07–1·09]), Black group (1·08 [1·06–1·09]), and mixed ethnicity group (1·04 [1·02–1·05]) and was decreased in the other ethnicity group (0·77 [0·76–0·78]) relative to the White group. The risk of testing positive for SARS-CoV-2 infection was higher in the South Asian group (1·99 [1·94–2·04]), Black group (1·69 [1·62–1·77]), mixed ethnicity group (1·49 [1·39–1·59]), and other ethnicity group (1·20 [1·14–1·28]). Compared with the White group, the four remaining high-level ethnic groups had an increased risk of COVID-19-related hospitalisation (South Asian group 1·48 [1·41–1·55], Black group 1·78 [1·67–1·90], mixed ethnicity group 1·63 [1·45–1·83], other ethnicity group 1·54 [1·41–1·69]), COVID-19-related ICU admission (2·18 [1·92–2·48], 3·12 [2·65–3·67], 2·96 [2·26–3·87], 3·18 [2·58–3·93]), and death (1·26 [1·15–1·37], 1·51 [1·31–1·71], 1·41 [1·11–1·81], 1·22 [1·00–1·48]). In wave 2, the risks of hospitalisation, ICU admission, and death relative to the White group were increased in the South Asian group but attenuated for the Black group compared with these risks in wave 1. Disaggregation into 16 ethnicity groups showed important heterogeneity within the five broader categories. Some minority ethnic populations in England have excess risks of testing positive for SARS-CoV-2 and of adverse COVID-19 outcomes compared with the White population, even after accounting for differences in sociodemographic, clinical, and household characteristics. Causes are likely to be multifactorial, and delineating the exact mechanisms is crucial. Tackling ethnic inequalities will require action across many fronts, including reducing structural inequalities, addressing barriers to equitable care, and improving uptake of testing and vaccination. Medical Research Council.
AbstractList	COVID-19 has disproportionately affected minority ethnic populations in the UK. Our aim was to quantify ethnic differences in SARS-CoV-2 infection and COVID-19 outcomes during the first and second waves of the COVID-19 pandemic in England.BACKGROUNDCOVID-19 has disproportionately affected minority ethnic populations in the UK. Our aim was to quantify ethnic differences in SARS-CoV-2 infection and COVID-19 outcomes during the first and second waves of the COVID-19 pandemic in England.We conducted an observational cohort study of adults (aged ≥18 years) registered with primary care practices in England for whom electronic health records were available through the OpenSAFELY platform, and who had at least 1 year of continuous registration at the start of each study period (Feb 1 to Aug 3, 2020 [wave 1], and Sept 1 to Dec 31, 2020 [wave 2]). Individual-level primary care data were linked to data from other sources on the outcomes of interest: SARS-CoV-2 testing and positive test results and COVID-19-related hospital admissions, intensive care unit (ICU) admissions, and death. The exposure was self-reported ethnicity as captured on the primary care record, grouped into five high-level census categories (White, South Asian, Black, other, and mixed) and 16 subcategories across these five categories, as well as an unknown ethnicity category. We used multivariable Cox regression to examine ethnic differences in the outcomes of interest. Models were adjusted for age, sex, deprivation, clinical factors and comorbidities, and household size, with stratification by geographical region.METHODSWe conducted an observational cohort study of adults (aged ≥18 years) registered with primary care practices in England for whom electronic health records were available through the OpenSAFELY platform, and who had at least 1 year of continuous registration at the start of each study period (Feb 1 to Aug 3, 2020 [wave 1], and Sept 1 to Dec 31, 2020 [wave 2]). Individual-level primary care data were linked to data from other sources on the outcomes of interest: SARS-CoV-2 testing and positive test results and COVID-19-related hospital admissions, intensive care unit (ICU) admissions, and death. The exposure was self-reported ethnicity as captured on the primary care record, grouped into five high-level census categories (White, South Asian, Black, other, and mixed) and 16 subcategories across these five categories, as well as an unknown ethnicity category. We used multivariable Cox regression to examine ethnic differences in the outcomes of interest. Models were adjusted for age, sex, deprivation, clinical factors and comorbidities, and household size, with stratification by geographical region.Of 17 288 532 adults included in the study (excluding care home residents), 10 877 978 (62·9%) were White, 1 025 319 (5·9%) were South Asian, 340 912 (2·0%) were Black, 170 484 (1·0%) were of mixed ethnicity, 320 788 (1·9%) were of other ethnicity, and 4 553 051 (26·3%) were of unknown ethnicity. In wave 1, the likelihood of being tested for SARS-CoV-2 infection was slightly higher in the South Asian group (adjusted hazard ratio 1·08 [95% CI 1·07-1·09]), Black group (1·08 [1·06-1·09]), and mixed ethnicity group (1·04 [1·02-1·05]) and was decreased in the other ethnicity group (0·77 [0·76-0·78]) relative to the White group. The risk of testing positive for SARS-CoV-2 infection was higher in the South Asian group (1·99 [1·94-2·04]), Black group (1·69 [1·62-1·77]), mixed ethnicity group (1·49 [1·39-1·59]), and other ethnicity group (1·20 [1·14-1·28]). Compared with the White group, the four remaining high-level ethnic groups had an increased risk of COVID-19-related hospitalisation (South Asian group 1·48 [1·41-1·55], Black group 1·78 [1·67-1·90], mixed ethnicity group 1·63 [1·45-1·83], other ethnicity group 1·54 [1·41-1·69]), COVID-19-related ICU admission (2·18 [1·92-2·48], 3·12 [2·65-3·67], 2·96 [2·26-3·87], 3·18 [2·58-3·93]), and death (1·26 [1·15-1·37], 1·51 [1·31-1·71], 1·41 [1·11-1·81], 1·22 [1·00-1·48]). In wave 2, the risks of hospitalisation, ICU admission, and death relative to the White group were increased in the South Asian group but attenuated for the Black group compared with these risks in wave 1. Disaggregation into 16 ethnicity groups showed important heterogeneity within the five broader categories.FINDINGSOf 17 288 532 adults included in the study (excluding care home residents), 10 877 978 (62·9%) were White, 1 025 319 (5·9%) were South Asian, 340 912 (2·0%) were Black, 170 484 (1·0%) were of mixed ethnicity, 320 788 (1·9%) were of other ethnicity, and 4 553 051 (26·3%) were of unknown ethnicity. In wave 1, the likelihood of being tested for SARS-CoV-2 infection was slightly higher in the South Asian group (adjusted hazard ratio 1·08 [95% CI 1·07-1·09]), Black group (1·08 [1·06-1·09]), and mixed ethnicity group (1·04 [1·02-1·05]) and was decreased in the other ethnicity group (0·77 [0·76-0·78]) relative to the White group. The risk of testing positive for SARS-CoV-2 infection was higher in the South Asian group (1·99 [1·94-2·04]), Black group (1·69 [1·62-1·77]), mixed ethnicity group (1·49 [1·39-1·59]), and other ethnicity group (1·20 [1·14-1·28]). Compared with the White group, the four remaining high-level ethnic groups had an increased risk of COVID-19-related hospitalisation (South Asian group 1·48 [1·41-1·55], Black group 1·78 [1·67-1·90], mixed ethnicity group 1·63 [1·45-1·83], other ethnicity group 1·54 [1·41-1·69]), COVID-19-related ICU admission (2·18 [1·92-2·48], 3·12 [2·65-3·67], 2·96 [2·26-3·87], 3·18 [2·58-3·93]), and death (1·26 [1·15-1·37], 1·51 [1·31-1·71], 1·41 [1·11-1·81], 1·22 [1·00-1·48]). In wave 2, the risks of hospitalisation, ICU admission, and death relative to the White group were increased in the South Asian group but attenuated for the Black group compared with these risks in wave 1. Disaggregation into 16 ethnicity groups showed important heterogeneity within the five broader categories.Some minority ethnic populations in England have excess risks of testing positive for SARS-CoV-2 and of adverse COVID-19 outcomes compared with the White population, even after accounting for differences in sociodemographic, clinical, and household characteristics. Causes are likely to be multifactorial, and delineating the exact mechanisms is crucial. Tackling ethnic inequalities will require action across many fronts, including reducing structural inequalities, addressing barriers to equitable care, and improving uptake of testing and vaccination.INTERPRETATIONSome minority ethnic populations in England have excess risks of testing positive for SARS-CoV-2 and of adverse COVID-19 outcomes compared with the White population, even after accounting for differences in sociodemographic, clinical, and household characteristics. Causes are likely to be multifactorial, and delineating the exact mechanisms is crucial. Tackling ethnic inequalities will require action across many fronts, including reducing structural inequalities, addressing barriers to equitable care, and improving uptake of testing and vaccination.Medical Research Council.FUNDINGMedical Research Council. Summary Background COVID-19 has disproportionately affected minority ethnic populations in the UK. Our aim was to quantify ethnic differences in SARS-CoV-2 infection and COVID-19 outcomes during the first and second waves of the COVID-19 pandemic in England. Methods We conducted an observational cohort study of adults (aged ≥18 years) registered with primary care practices in England for whom electronic health records were available through the OpenSAFELY platform, and who had at least 1 year of continuous registration at the start of each study period (Feb 1 to Aug 3, 2020 [wave 1], and Sept 1 to Dec 31, 2020 [wave 2]). Individual-level primary care data were linked to data from other sources on the outcomes of interest: SARS-CoV-2 testing and positive test results and COVID-19-related hospital admissions, intensive care unit (ICU) admissions, and death. The exposure was self-reported ethnicity as captured on the primary care record, grouped into five high-level census categories (White, South Asian, Black, other, and mixed) and 16 subcategories across these five categories, as well as an unknown ethnicity category. We used multivariable Cox regression to examine ethnic differences in the outcomes of interest. Models were adjusted for age, sex, deprivation, clinical factors and comorbidities, and household size, with stratification by geographical region. Findings Of 17 288 532 adults included in the study (excluding care home residents), 10 877 978 (62·9%) were White, 1 025 319 (5·9%) were South Asian, 340 912 (2·0%) were Black, 170 484 (1·0%) were of mixed ethnicity, 320 788 (1·9%) were of other ethnicity, and 4 553 051 (26·3%) were of unknown ethnicity. In wave 1, the likelihood of being tested for SARS-CoV-2 infection was slightly higher in the South Asian group (adjusted hazard ratio 1·08 [95% CI 1·07–1·09]), Black group (1·08 [1·06–1·09]), and mixed ethnicity group (1·04 [1·02–1·05]) and was decreased in the other ethnicity group (0·77 [0·76–0·78]) relative to the White group. The risk of testing positive for SARS-CoV-2 infection was higher in the South Asian group (1·99 [1·94–2·04]), Black group (1·69 [1·62–1·77]), mixed ethnicity group (1·49 [1·39–1·59]), and other ethnicity group (1·20 [1·14–1·28]). Compared with the White group, the four remaining high-level ethnic groups had an increased risk of COVID-19-related hospitalisation (South Asian group 1·48 [1·41–1·55], Black group 1·78 [1·67–1·90], mixed ethnicity group 1·63 [1·45–1·83], other ethnicity group 1·54 [1·41–1·69]), COVID-19-related ICU admission (2·18 [1·92–2·48], 3·12 [2·65–3·67], 2·96 [2·26–3·87], 3·18 [2·58–3·93]), and death (1·26 [1·15–1·37], 1·51 [1·31–1·71], 1·41 [1·11–1·81], 1·22 [1·00–1·48]). In wave 2, the risks of hospitalisation, ICU admission, and death relative to the White group were increased in the South Asian group but attenuated for the Black group compared with these risks in wave 1. Disaggregation into 16 ethnicity groups showed important heterogeneity within the five broader categories. Interpretation Some minority ethnic populations in England have excess risks of testing positive for SARS-CoV-2 and of adverse COVID-19 outcomes compared with the White population, even after accounting for differences in sociodemographic, clinical, and household characteristics. Causes are likely to be multifactorial, and delineating the exact mechanisms is crucial. Tackling ethnic inequalities will require action across many fronts, including reducing structural inequalities, addressing barriers to equitable care, and improving uptake of testing and vaccination. Funding Medical Research Council. COVID-19 has disproportionately affected minority ethnic populations in the UK. Our aim was to quantify ethnic differences in SARS-CoV-2 infection and COVID-19 outcomes during the first and second waves of the COVID-19 pandemic in England. We conducted an observational cohort study of adults (aged ≥18 years) registered with primary care practices in England for whom electronic health records were available through the OpenSAFELY platform, and who had at least 1 year of continuous registration at the start of each study period (Feb 1 to Aug 3, 2020 [wave 1], and Sept 1 to Dec 31, 2020 [wave 2]). Individual-level primary care data were linked to data from other sources on the outcomes of interest: SARS-CoV-2 testing and positive test results and COVID-19-related hospital admissions, intensive care unit (ICU) admissions, and death. The exposure was self-reported ethnicity as captured on the primary care record, grouped into five high-level census categories (White, South Asian, Black, other, and mixed) and 16 subcategories across these five categories, as well as an unknown ethnicity category. We used multivariable Cox regression to examine ethnic differences in the outcomes of interest. Models were adjusted for age, sex, deprivation, clinical factors and comorbidities, and household size, with stratification by geographical region. Of 17 288 532 adults included in the study (excluding care home residents), 10 877 978 (62·9%) were White, 1 025 319 (5·9%) were South Asian, 340 912 (2·0%) were Black, 170 484 (1·0%) were of mixed ethnicity, 320 788 (1·9%) were of other ethnicity, and 4 553 051 (26·3%) were of unknown ethnicity. In wave 1, the likelihood of being tested for SARS-CoV-2 infection was slightly higher in the South Asian group (adjusted hazard ratio 1·08 [95% CI 1·07-1·09]), Black group (1·08 [1·06-1·09]), and mixed ethnicity group (1·04 [1·02-1·05]) and was decreased in the other ethnicity group (0·77 [0·76-0·78]) relative to the White group. The risk of testing positive for SARS-CoV-2 infection was higher in the South Asian group (1·99 [1·94-2·04]), Black group (1·69 [1·62-1·77]), mixed ethnicity group (1·49 [1·39-1·59]), and other ethnicity group (1·20 [1·14-1·28]). Compared with the White group, the four remaining high-level ethnic groups had an increased risk of COVID-19-related hospitalisation (South Asian group 1·48 [1·41-1·55], Black group 1·78 [1·67-1·90], mixed ethnicity group 1·63 [1·45-1·83], other ethnicity group 1·54 [1·41-1·69]), COVID-19-related ICU admission (2·18 [1·92-2·48], 3·12 [2·65-3·67], 2·96 [2·26-3·87], 3·18 [2·58-3·93]), and death (1·26 [1·15-1·37], 1·51 [1·31-1·71], 1·41 [1·11-1·81], 1·22 [1·00-1·48]). In wave 2, the risks of hospitalisation, ICU admission, and death relative to the White group were increased in the South Asian group but attenuated for the Black group compared with these risks in wave 1. Disaggregation into 16 ethnicity groups showed important heterogeneity within the five broader categories. Some minority ethnic populations in England have excess risks of testing positive for SARS-CoV-2 and of adverse COVID-19 outcomes compared with the White population, even after accounting for differences in sociodemographic, clinical, and household characteristics. Causes are likely to be multifactorial, and delineating the exact mechanisms is crucial. Tackling ethnic inequalities will require action across many fronts, including reducing structural inequalities, addressing barriers to equitable care, and improving uptake of testing and vaccination. Medical Research Council.
Author	Curtis, Helen J Evans, David Grieve, Richard Mehrkar, Amir Hester, Frank Cockburn, Jonathan Khunti, Kamlesh Williamson, Elizabeth J Evans, Stephen J W Rowan, Kathy Inglesby, Peter Mathur, Rohini Tomlinson, Laurie Wong, Angel Y S DeVito, Nicholas J Douglas, Ian J Bhaskaran, Krishnan MacKenna, Brian McDonald, Helen I Chaturvedi, Nishi Forbes, Harriet Goldacre, Ben Croker, Richard Morton, Caroline E Bacon, Seb Bates, Chris Wing, Kevin Smeeth, Liam Eggo, Rosalind M Hulme, William J Schultze, Anna Walker, Alex J Harper, Sam Harrison, David Drysdale, Henry Rentsch, Christopher T Parry, John
Author_xml	– sequence: 1 givenname: Rohini surname: Mathur fullname: Mathur, Rohini email: rohini.mathur@lshtm.ac.uk organization: Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK – sequence: 2 givenname: Christopher T surname: Rentsch fullname: Rentsch, Christopher T organization: Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK – sequence: 3 givenname: Caroline E surname: Morton fullname: Morton, Caroline E organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK – sequence: 4 givenname: William J surname: Hulme fullname: Hulme, William J organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK – sequence: 5 givenname: Anna surname: Schultze fullname: Schultze, Anna organization: Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK – sequence: 6 givenname: Brian surname: MacKenna fullname: MacKenna, Brian organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK – sequence: 7 givenname: Rosalind M surname: Eggo fullname: Eggo, Rosalind M organization: Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK – sequence: 8 givenname: Krishnan surname: Bhaskaran fullname: Bhaskaran, Krishnan organization: Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK – sequence: 9 givenname: Angel Y S surname: Wong fullname: Wong, Angel Y S organization: Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK – sequence: 10 givenname: Elizabeth J surname: Williamson fullname: Williamson, Elizabeth J organization: Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK – sequence: 11 givenname: Harriet surname: Forbes fullname: Forbes, Harriet organization: Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK – sequence: 12 givenname: Kevin surname: Wing fullname: Wing, Kevin organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK – sequence: 13 givenname: Helen I surname: McDonald fullname: McDonald, Helen I organization: Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK – sequence: 14 givenname: Chris surname: Bates fullname: Bates, Chris organization: TPP, Leeds, UK – sequence: 15 givenname: Seb surname: Bacon fullname: Bacon, Seb organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK – sequence: 16 givenname: Alex J surname: Walker fullname: Walker, Alex J organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK – sequence: 17 givenname: David surname: Evans fullname: Evans, David organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK – sequence: 18 givenname: Peter surname: Inglesby fullname: Inglesby, Peter organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK – sequence: 19 givenname: Amir surname: Mehrkar fullname: Mehrkar, Amir organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK – sequence: 20 givenname: Helen J surname: Curtis fullname: Curtis, Helen J organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK – sequence: 21 givenname: Nicholas J surname: DeVito fullname: DeVito, Nicholas J organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK – sequence: 22 givenname: Richard surname: Croker fullname: Croker, Richard organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK – sequence: 23 givenname: Henry surname: Drysdale fullname: Drysdale, Henry organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK – sequence: 24 givenname: Jonathan surname: Cockburn fullname: Cockburn, Jonathan organization: TPP, Leeds, UK – sequence: 25 givenname: John surname: Parry fullname: Parry, John organization: TPP, Leeds, UK – sequence: 26 givenname: Frank surname: Hester fullname: Hester, Frank organization: TPP, Leeds, UK – sequence: 27 givenname: Sam surname: Harper fullname: Harper, Sam organization: TPP, Leeds, UK – sequence: 28 givenname: Ian J surname: Douglas fullname: Douglas, Ian J organization: Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK – sequence: 29 givenname: Laurie surname: Tomlinson fullname: Tomlinson, Laurie organization: Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK – sequence: 30 givenname: Stephen J W surname: Evans fullname: Evans, Stephen J W organization: Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK – sequence: 31 givenname: Richard surname: Grieve fullname: Grieve, Richard organization: Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK – sequence: 32 givenname: David surname: Harrison fullname: Harrison, David organization: Intensive Care National Audit and Research Centre, London, UK – sequence: 33 givenname: Kathy surname: Rowan fullname: Rowan, Kathy organization: Intensive Care National Audit and Research Centre, London, UK – sequence: 34 givenname: Kamlesh surname: Khunti fullname: Khunti, Kamlesh organization: Diabetes Research Centre, University of Leicester, Leicester, UK – sequence: 35 givenname: Nishi surname: Chaturvedi fullname: Chaturvedi, Nishi organization: Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK – sequence: 36 givenname: Liam surname: Smeeth fullname: Smeeth, Liam organization: Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK – sequence: 37 givenname: Ben surname: Goldacre fullname: Goldacre, Ben organization: The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/33939953$$D View this record in MEDLINE/PubMed
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Snippet	COVID-19 has disproportionately affected minority ethnic populations in the UK. Our aim was to quantify ethnic differences in SARS-CoV-2 infection and COVID-19... Summary Background COVID-19 has disproportionately affected minority ethnic populations in the UK. Our aim was to quantify ethnic differences in SARS-CoV-2...
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SubjectTerms	Adult Adults Biobanks Blood pressure Categories Cohort analysis Cohort Studies Coronaviruses COVID-19 COVID-19 - epidemiology COVID-19 - ethnology COVID-19 - mortality Cultural differences Death Deprivation Disaggregation Disease transmission Electronic health records Electronic medical records England Ethnicity Ethnicity - statistics & numerical data Health care Heterogeneity Hospitalization Hospitalization - statistics & numerical data Hospitals Households Humans Inequalities Infections Intensive care Intensive Care Units - statistics & numerical data Medical research Minority & ethnic groups Mortality Observational studies Observational Studies as Topic Pandemics Patient Admission - statistics & numerical data Population Populations Primary care Severe acute respiratory syndrome coronavirus 2 Sociodemographics Survival Analysis Vaccination Viral diseases
Title	Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalisation, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform
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