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SARS-CoV-2 antibodies and breakthrough infections in the Virus Watch cohort.
Aldridge, Robert W; Yavlinsky, Alexei; Nguyen, Vincent; Eyre, Max T; Shrotri, Madhumita; Navaratnam, Annalan M D; Beale, Sarah; Braithwaite, Isobel; Byrne, Thomas; Kovar, Jana; Fragaszy, Ellen; Fong, Wing Lam Erica; Geismar, Cyril; Patel, Parth; Rodger, Alison; Johnson, Anne M; Hayward, Andrew.
Afiliación
  • Aldridge RW; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK. r.aldridge@ucl.ac.uk.
  • Yavlinsky A; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.
  • Nguyen V; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.
  • Eyre MT; Institute of Epidemiology and Health Care, University College London, London, UK.
  • Shrotri M; Centre of Health Informatics, Computing and Statistics, Lancaster Medical School, Lancaster University, Lancaster, UK.
  • Navaratnam AMD; Liverpool School of Tropical Medicine, Liverpool, UK.
  • Beale S; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.
  • Braithwaite I; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.
  • Byrne T; Institute of Epidemiology and Health Care, University College London, London, UK.
  • Kovar J; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.
  • Fragaszy E; Institute of Epidemiology and Health Care, University College London, London, UK.
  • Fong WLE; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.
  • Geismar C; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.
  • Patel P; Institute of Epidemiology and Health Care, University College London, London, UK.
  • Rodger A; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.
  • Johnson AM; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
  • Hayward A; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.
Nat Commun ; 13(1): 4869, 2022 08 18.
Article en En | MEDLINE | ID: mdl-35982056
ABSTRACT
A range of studies globally demonstrate that the effectiveness of SARS-CoV-2 vaccines wane over time, but the total effect of anti-S antibody levels on risk of SARS-CoV-2 infection and whether this varies by vaccine type is not well understood. Here we show that anti-S levels peak three to four weeks following the second dose of vaccine and the geometric mean of the samples is nine fold higher for BNT162b2 than ChAdOx1. Increasing anti-S levels are associated with a reduced risk of SARS-CoV-2 infection (Hazard Ratio 0.85; 95%CIs 0.79-0.92). We do not find evidence that this antibody relationship with risk of infection varies by second dose vaccine type (BNT162b2 vs. ChAdOx1). In keeping with our anti-S antibody data, we find that people vaccinated with ChAdOx1 had 1.64 times the odds (95% confidence interval 1.45-1.85) of a breakthrough infection compared to BNT162b2. We anticipate our findings to be useful in the estimation of the protective effect of anti-S levels on risk of infection due to Delta. Our findings provide evidence about the relationship between antibody levels and protection for different vaccines and will support decisions on optimising the timing of booster vaccinations and identifying individuals who should be prioritised for booster vaccination, including those who are older, clinically extremely vulnerable, or received ChAdOx1 as their primary course. Our finding that risk of infection by anti-S level does not interact with vaccine type, but that individuals vaccinated with ChAdOx1 were at higher risk of infection, provides additional support for the use of using anti-S levels for estimating vaccine efficacy.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Vacunas Virales / COVID-19 Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Vacunas Virales / COVID-19 Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido