The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
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
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Factors associated with COVID-19-related death using OpenSAFELY
Williamson, E. J., Walker, A. J., Bhaskaran, K., Bacon, S., Bates, C., Morton, C. E., Curtis, H. J., Mehrkar, A., Evans, D., Inglesby, P., et al. (2020) · Nature · doi:10.1038/s41586-020-2521-4 · Cited by 6,674
Self-citationGarg, S., Kim, L., Whitaker, M., O’Halloran, A., Cummings, C., Holstein, R., Prill, M., Chai, S. J., Kirley, P. D., Alden, N. B., et al. (2020) · MMWR. Morbidity and Mortality Weekly Report · doi:10.15585/mmwr.mm6915e3 · Cited by 2,335
Laster Pirtle, W. N. (2020) · Health Education & Behavior · doi:10.1177/1090198120922942 · Cited by 619
The Read clinical classification.
Chisholm, J. (1990) · BMJ · doi:10.1136/bmj.300.6732.1092 · Cited by 504
Ethnicity and COVID-19: an urgent public health research priority
Pareek, M., Bangash, M. N., Pareek, N., Pan, D., Sze, S., Minhas, J. S., Hanif, W., & Khunti, K. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30922-3 · Cited by 426
Self-citationRimmer, A. (2020) · BMJ · doi:10.1136/bmj.m1562 · Cited by 62
Cited by
Menni, C., Valdes, A. M., Polidori, L., Antonelli, M., Penamakuri, S., Nogal, A., Louca, P., May, A., Figueiredo, J. C., Hu, C., et al. (2022) · The Lancet · doi:10.1016/s0140-6736(22)00327-0 · Cited by 854
Global seroprevalence of SARS-CoV-2 antibodies: A systematic review and meta-analysis
Bobrovitz, N., Arora, R. K., Cao, C., Boucher, E., Liu, M., Donnici, C., Yanes-Lane, M., Whelan, M., Perlman-Arrow, S., Chen, J., et al. (2021) · PLOS ONE · doi:10.1371/journal.pone.0252617 · Cited by 246
Gozzi, N., Tizzoni, M., Chinazzi, M., Ferres, L., Vespignani, A., & Perra, N. (2021) · Nature Communications · doi:10.1038/s41467-021-22601-6 · Cited by 142
Riou, J., Panczak, R., Althaus, C. L., Junker, C., Perisa, D., Schneider, K., Criscuolo, N. G., Low, N., & Egger, M. (2021) · The Lancet Public Health · doi:10.1016/s2468-2667(21)00160-2 · Cited by 136
Nab, L., Parker, E. P. K., Andrews, C. D., Hulme, W. J., Fisher, L., Morley, J., Mehrkar, A., MacKenna, B., Inglesby, P., Morton, C. E., et al. (2023) · The Lancet Public Health · doi:10.1016/s2468-2667(23)00079-8 · Cited by 97
Self-citation
Metadata
- Authors
- Mathur, R., Rentsch, C. T., Morton, C. E., Hulme, W. J., Schultze, A., MacKenna, B., Eggo, R. M., Bhaskaran, K., Wong, A. Y. S., Williamson, E. J., Forbes, H., Wing, K., McDonald, H. I., Bates, C., Bacon, S., Walker, A. J., Evans, D., Inglesby, P., Mehrkar, A., Curtis, H. J., DeVito, N. J., Croker, R., Drysdale, H., Cockburn, J., Parry, J., Hester, F., Harper, S., Douglas, I. J., Tomlinson, L., Evans, S. J. W., Grieve, R., Harrison, D., Rowan, K., Khunti, K., Chaturvedi, N., Smeeth, L., & Goldacre, B.
- Venue
- The Lancet
- Publisher
- Elsevier BV
- Published
- 2021-05
- Volume
- 397
- Issue
- 10286
- Pages
- 1711-1724
- ISSN
- 0099-5355 (ISSN-L)
- 0140-6736
- OpenAlex
- W3158323486
- Cited by
- 501
- References
- 6
- FWCI
- 31.76
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: 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. https://app.cochat.ai/papers/10.1016/s0140-6736(21)00634-6
- The paper
- Mathur, R., Rentsch, C. T., Morton, C. E., Hulme, W. J., Schultze, A., MacKenna, B., Eggo, R. M., Bhaskaran, K., Wong, A. Y. S., Williamson, E. J., Forbes, H., Wing, K., McDonald, H. I., Bates, C., Bacon, S., Walker, A. J., Evans, D., Inglesby, P., Mehrkar, A., . . . Goldacre, B. (2021). 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. The Lancet. https://doi.org/10.1016/s0140-6736(21)00634-6
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.