Describing the population experiencing COVID-19 vaccine breakthrough following second vaccination in England: a cohort study from OpenSAFELY.


Journal

BMC medicine
ISSN: 1741-7015
Titre abrégé: BMC Med
Pays: England
ID NLM: 101190723

Informations de publication

Date de publication:
05 07 2022
Historique:
received: 09 11 2021
accepted: 30 05 2022
entrez: 5 7 2022
pubmed: 6 7 2022
medline: 8 7 2022
Statut: epublish

Résumé

While the vaccines against COVID-19 are highly effective, COVID-19 vaccine breakthrough is possible despite being fully vaccinated. With SARS-CoV-2 variants still circulating, describing the characteristics of individuals who have experienced COVID-19 vaccine breakthroughs could be hugely important in helping to determine who may be at greatest risk. With the approval of NHS England, we conducted a retrospective cohort study using routine clinical data from the OpenSAFELY-TPP database of fully vaccinated individuals, linked to secondary care and death registry data and described the characteristics of those experiencing COVID-19 vaccine breakthroughs. As of 1st November 2021, a total of 15,501,550 individuals were identified as being fully vaccinated against COVID-19, with a median follow-up time of 149 days (IQR: ​107-179). From within this population, a total of 579,780 (<4%) individuals reported a positive SARS-CoV-2 test. For every 1000 years of patient follow-up time, the corresponding incidence rate (IR) was 98.06 (95% CI 97.93-98.19). There were 28,580 COVID-19-related hospital admissions, 1980 COVID-19-related critical care admissions and 6435 COVID-19-related deaths; corresponding IRs 4.77 (95% CI 4.74-4.80), 0.33 (95% CI 0.32-0.34) and 1.07 (95% CI 1.06-1.09), respectively. The highest rates of breakthrough COVID-19 were seen in those in care homes and in patients with chronic kidney disease, dialysis, transplant, haematological malignancy or who were immunocompromised. While the majority of COVID-19 vaccine breakthrough cases in England were mild, some differences in rates of breakthrough cases have been identified in several clinical groups. While it is important to note that these findings are simply descriptive and cannot be used to answer why certain groups have higher rates of COVID-19 breakthrough than others, the emergence of the Omicron variant of COVID-19 coupled with the number of positive SARS-CoV-2 tests still occurring is concerning and as numbers of fully vaccinated (and boosted) individuals increases and as follow-up time lengthens, so too will the number of COVID-19 breakthrough cases. Additional analyses, to assess vaccine waning and rates of breakthrough COVID-19 between different variants, aimed at identifying individuals at higher risk, are needed.

Sections du résumé

BACKGROUND
While the vaccines against COVID-19 are highly effective, COVID-19 vaccine breakthrough is possible despite being fully vaccinated. With SARS-CoV-2 variants still circulating, describing the characteristics of individuals who have experienced COVID-19 vaccine breakthroughs could be hugely important in helping to determine who may be at greatest risk.
METHODS
With the approval of NHS England, we conducted a retrospective cohort study using routine clinical data from the OpenSAFELY-TPP database of fully vaccinated individuals, linked to secondary care and death registry data and described the characteristics of those experiencing COVID-19 vaccine breakthroughs.
RESULTS
As of 1st November 2021, a total of 15,501,550 individuals were identified as being fully vaccinated against COVID-19, with a median follow-up time of 149 days (IQR: ​107-179). From within this population, a total of 579,780 (<4%) individuals reported a positive SARS-CoV-2 test. For every 1000 years of patient follow-up time, the corresponding incidence rate (IR) was 98.06 (95% CI 97.93-98.19). There were 28,580 COVID-19-related hospital admissions, 1980 COVID-19-related critical care admissions and 6435 COVID-19-related deaths; corresponding IRs 4.77 (95% CI 4.74-4.80), 0.33 (95% CI 0.32-0.34) and 1.07 (95% CI 1.06-1.09), respectively. The highest rates of breakthrough COVID-19 were seen in those in care homes and in patients with chronic kidney disease, dialysis, transplant, haematological malignancy or who were immunocompromised.
CONCLUSIONS
While the majority of COVID-19 vaccine breakthrough cases in England were mild, some differences in rates of breakthrough cases have been identified in several clinical groups. While it is important to note that these findings are simply descriptive and cannot be used to answer why certain groups have higher rates of COVID-19 breakthrough than others, the emergence of the Omicron variant of COVID-19 coupled with the number of positive SARS-CoV-2 tests still occurring is concerning and as numbers of fully vaccinated (and boosted) individuals increases and as follow-up time lengthens, so too will the number of COVID-19 breakthrough cases. Additional analyses, to assess vaccine waning and rates of breakthrough COVID-19 between different variants, aimed at identifying individuals at higher risk, are needed.

Identifiants

pubmed: 35791013
doi: 10.1186/s12916-022-02422-0
pii: 10.1186/s12916-022-02422-0
pmc: PMC9255436
doi:

Substances chimiques

COVID-19 Vaccines 0
Chickenpox Vaccine 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

243

Subventions

Organisme : Medical Research Council
ID : MR/S003975/1
Pays : United Kingdom
Organisme : Department of Health
Pays : United Kingdom

Informations de copyright

© 2022. The Author(s).

Références

BMJ. 2021 Mar 19;372:n783
pubmed: 33741565
JAMA. 2022 Jan 11;327(2):179-181
pubmed: 34914825
Lancet. 2021 Oct 9;398(10308):1377-1380
pubmed: 34534516
N Engl J Med. 2021 Aug 12;385(7):585-594
pubmed: 34289274
BMJ. 2021 Sep 17;374:n2244
pubmed: 34535466
Lancet Infect Dis. 2022 Jan;22(1):43-55
pubmed: 34480857
Ann Rheum Dis. 2022 Feb;81(2):289-291
pubmed: 34489304
N Engl J Med. 2021 Sep 30;385(14):1330-1332
pubmed: 34469645
BMJ. 2021 May 13;373:n1088
pubmed: 33985964
JAMA Netw Open. 2021 Sep 1;4(9):e2125394
pubmed: 34468758

Auteurs

Amelia Green (A)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Helen Curtis (H)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

William Hulme (W)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Elizabeth Williamson (E)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Helen McDonald (H)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Krishnan Bhaskaran (K)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Christopher Rentsch (C)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Anna Schultze (A)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Brian MacKenna (B)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Viyaasan Mahalingasivam (V)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Laurie Tomlinson (L)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Alex Walker (A)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Louis Fisher (L)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Jon Massey (J)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Colm Andrews (C)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Lisa Hopcroft (L)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Caroline Morton (C)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Richard Croker (R)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Jessica Morley (J)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Amir Mehrkar (A)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Seb Bacon (S)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

David Evans (D)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Peter Inglesby (P)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

George Hickman (G)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Tom Ward (T)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Simon Davy (S)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Rohini Mathur (R)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

John Tazare (J)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Rosalind Eggo (R)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Kevin Wing (K)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Angel Wong (A)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Harriet Forbes (H)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Chris Bates (C)

TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.

Jonathan Cockburn (J)

TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.

John Parry (J)

TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.

Frank Hester (F)

TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.

Sam Harper (S)

TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.

Ian Douglas (I)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Stephen Evans (S)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Liam Smeeth (L)

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Ben Goldacre (B)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK. ben.goldacre@phc.ox.ac.uk.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH