Evidence map›Paper›PMID 41694691›Full record

ArticleThe Lancet regional health. Europe2026

Ethnic differences in Long COVID diagnosed in primary care in England (2020-2022): an observational cohort study using OpenSAFELY.

Poppy Ac Mallinson, Nick Birk, Alasdair D Henderson, Alex Lewin, Anoop Sv Shah, Amir Mehrkar, Ben Goldacre, Giridhar R Babu, Santosh Kumar Banjara, OpenSAFELY collaborative and 3 more

Abstract read
In one paragraph

Article in The Lancet regional health. Europe, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Poppy Ac MallinsonDepartment of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Nick BirkDepartment of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Alasdair D HendersonDepartment of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Alex LewinDepartment of Medical Statistics, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Anoop Sv ShahDepartment of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Amir MehrkarBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK.
Ben GoldacreBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK.
Giridhar R BabuDepartment of Population Medicine, College of Medicine, QU Health, Qatar University, Qatar.
Santosh Kumar BanjaraICMR-National Institute of Nutrition, Hyderabad, India.
OpenSAFELY collaborative
Laurie A TomlinsonDepartment of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Sanjay KinraDepartment of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Rohini MathurDepartment of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Background: Long COVID continues to affect millions of adults and contribute to substantial economic burden across Europe. Ethnic inequalities in Long COVID, and the reasons underlying these, are poorly understood. We aimed to investigate ethnic differences in the incidence of diagnosed Long COVID in England using linked national primary care data. Methods: With approval from NHS England, we used linked health record data from England, 2020-2022, accessed through the OpenSAFELY platform. We applied Cox regression to compare incidence of diagnosed Long COVID in primary care across self-reported ethnicity in five groups. We explored potential explanations for these differences by 1) adjusting for sociodemographic and health-related factors, 2) restricting to those tested or hospitalised with COVID-19, 3) stratifying into 16 ethnic sub-groups. Findings: Our sample comprised 17,848,825 adults, of whom 16,970 (0.1%) had a diagnosis of Long COVID recorded in primary care. Hazard ratios (95% confidence intervals) for Long COVID compared with the white group were 1.04 (0.98-1.11) for the South Asian group, 0.84 (0.75-0.94) for the Black group, 0.97 (0.84-1.13) for the Mixed Ethnicity group, and 0.63 (0.55-0.72) for Other ethnic groups, which remained similar when adjusting for sociodemographic and health-related factors and among those tested or hospitalised for COVID-19. Disaggregating into 16 ethnic sub-groups revealed heterogeneity within groups, for example, compared with the White British group, hazard ratios were 1.21 (1.00-1.47) for the Bangladeshi group and 1.09 (0.99-1.21) for the Pakistani group, but 0.77 (0.70-0.86) for the Indian group; and 1.15 (0.95-1.40) for the Black Caribbean group but 0.61 (0.51-0.72) for the Black African group. Interpretation: Differences in Long COVID diagnoses across broad ethnic groups mask important sub-group inequalities, offering insight into underlying mechanisms and approaches to better target Long COVID services. Funding: The OpenSAFELY platform is principally funded by grants from: NHS England [2023-2025]; The Wellcome Trust (222097/Z/20/Z) [2020-2024]; MRC (MR/V015737/1) [2020-2021]. Additional contributions to OpenSAFELY and this analysis have been funded by grants from: MRC via the National Core Study programme, Longitudinal Health and Wellbeing strand (MC_PC_20030, MC_PC_20059) [2020-2022] and the Data and Connectivity strand (MC_PC_20058) [2021-2022]; NHS England via the Primary Care Medicines Analytics Unit [2021-2024]; NIHR and MRC via the CONVALESCENCE programme (COV-LT-0009, MC_PC_20051) [2021-2024] and MRC (MR/V040235/1) [2021-24].

Indexed as

EthnicityHealth inequalitiesLong COVIDPrimary care

Identifiers

PMID41694691
PMCPMC12906119

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.