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Describing the population experiencing COVID-19 vaccine breakthrough following second vaccination in England: a cohort study from OpenSAFELY.
Green, Amelia; Curtis, Helen; Hulme, William; Williamson, Elizabeth; McDonald, Helen; Bhaskaran, Krishnan; Rentsch, Christopher; Schultze, Anna; MacKenna, Brian; Mahalingasivam, Viyaasan; Tomlinson, Laurie; Walker, Alex; Fisher, Louis; Massey, Jon; Andrews, Colm; Hopcroft, Lisa; Morton, Caroline; Croker, Richard; Morley, Jessica; Mehrkar, Amir; Bacon, Seb; Evans, David; Inglesby, Peter; Hickman, George; Ward, Tom; Davy, Simon; Mathur, Rohini; Tazare, John; Eggo, Rosalind; Wing, Kevin; Wong, Angel; Forbes, Harriet; Bates, Chris; Cockburn, Jonathan; Parry, John; Hester, Frank; Harper, Sam; Douglas, Ian; Evans, Stephen; Smeeth, Liam; Goldacre, Ben.
  • Green A; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Curtis H; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Hulme W; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Williamson E; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • McDonald H; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • Bhaskaran K; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • Rentsch C; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • Schultze A; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • MacKenna B; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Mahalingasivam V; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • Tomlinson L; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • Walker A; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Fisher L; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Massey J; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Andrews C; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Hopcroft L; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Morton C; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Croker R; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Morley J; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Mehrkar A; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Bacon S; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Evans D; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Inglesby P; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Hickman G; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Ward T; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Davy S; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
  • Mathur R; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • Tazare J; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • Eggo R; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • Wing K; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • Wong A; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • Forbes H; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • Bates C; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.
  • Cockburn J; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.
  • Parry J; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.
  • Hester F; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.
  • Harper S; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.
  • Douglas I; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • Evans S; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • Smeeth L; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
  • 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.
BMC Med ; 20(1): 243, 2022 07 05.
Artigo em Inglês | MEDLINE | ID: covidwho-2214584
ABSTRACT

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.
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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Assunto principal: Vacinas contra COVID-19 / COVID-19 Tipo de estudo: Estudo de coorte / Estudo experimental / Estudo observacional / Estudo prognóstico / Ensaios controlados aleatorizados Tópicos: Vacinas / Variantes Limite: Humanos País/Região como assunto: Europa Idioma: Inglês Revista: BMC Med Assunto da revista: Medicina Ano de publicação: 2022 Tipo de documento: Artigo País de afiliação: S12916-022-02422-0

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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Assunto principal: Vacinas contra COVID-19 / COVID-19 Tipo de estudo: Estudo de coorte / Estudo experimental / Estudo observacional / Estudo prognóstico / Ensaios controlados aleatorizados Tópicos: Vacinas / Variantes Limite: Humanos País/Região como assunto: Europa Idioma: Inglês Revista: BMC Med Assunto da revista: Medicina Ano de publicação: 2022 Tipo de documento: Artigo País de afiliação: S12916-022-02422-0