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Neutralizing antibody levels are highly predictive of immune protection from symptomatic SARS-CoV-2 infection.
Khoury, David S; Cromer, Deborah; Reynaldi, Arnold; Schlub, Timothy E; Wheatley, Adam K; Juno, Jennifer A; Subbarao, Kanta; Kent, Stephen J; Triccas, James A; Davenport, Miles P.
  • Khoury DS; Kirby Institute, University of New South Wales, Sydney, New South Wales, Australia.
  • Cromer D; Kirby Institute, University of New South Wales, Sydney, New South Wales, Australia.
  • Reynaldi A; Kirby Institute, University of New South Wales, Sydney, New South Wales, Australia.
  • Schlub TE; Kirby Institute, University of New South Wales, Sydney, New South Wales, Australia.
  • Wheatley AK; Sydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.
  • Juno JA; Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia.
  • Subbarao K; Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia.
  • Kent SJ; Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia.
  • Triccas JA; WHO Collaborating Centre for Reference and Research on Influenza, Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia.
  • Davenport MP; Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia.
Nat Med ; 27(7): 1205-1211, 2021 07.
Article in English | MEDLINE | ID: covidwho-1232070
ABSTRACT
Predictive models of immune protection from COVID-19 are urgently needed to identify correlates of protection to assist in the future deployment of vaccines. To address this, we analyzed the relationship between in vitro neutralization levels and the observed protection from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using data from seven current vaccines and from convalescent cohorts. We estimated the neutralization level for 50% protection against detectable SARS-CoV-2 infection to be 20.2% of the mean convalescent level (95% confidence interval (CI) = 14.4-28.4%). The estimated neutralization level required for 50% protection from severe infection was significantly lower (3% of the mean convalescent level; 95% CI = 0.7-13%, P = 0.0004). Modeling of the decay of the neutralization titer over the first 250 d after immunization predicts that a significant loss in protection from SARS-CoV-2 infection will occur, although protection from severe disease should be largely retained. Neutralization titers against some SARS-CoV-2 variants of concern are reduced compared with the vaccine strain, and our model predicts the relationship between neutralization and efficacy against viral variants. Here, we show that neutralization level is highly predictive of immune protection, and provide an evidence-based model of SARS-CoV-2 immune protection that will assist in developing vaccine strategies to control the future trajectory of the pandemic.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antibodies, Neutralizing / COVID-19 Vaccines / SARS-CoV-2 / COVID-19 / Antibodies, Viral Type of study: Cohort study / Observational study / Prognostic study Topics: Vaccines / Variants Limits: Humans Language: English Journal: Nat Med Journal subject: Molecular Biology / Medicine Year: 2021 Document Type: Article Affiliation country: S41591-021-01377-8

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antibodies, Neutralizing / COVID-19 Vaccines / SARS-CoV-2 / COVID-19 / Antibodies, Viral Type of study: Cohort study / Observational study / Prognostic study Topics: Vaccines / Variants Limits: Humans Language: English Journal: Nat Med Journal subject: Molecular Biology / Medicine Year: 2021 Document Type: Article Affiliation country: S41591-021-01377-8