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Neutralizing antibody levels are highly predictive of immune protection from symptomatic SARS-CoV-2 infection

Published: 17 May 2021
Nature Medicine , Volume 27, pp 1205-1211; doi:10.1038/s41591-021-01377-8

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. Estimates of the levels of neutralizing antibodies necessary for protection against symptomatic SARS-CoV-2 or severe COVID-19 are a fraction of the mean level in convalescent serum and will be useful in guiding vaccine rollouts.
Keywords: Computational biology and bioinformatics / Vaccines / Viral infection / Biomedicine / general / Cancer Research / Metabolic Diseases / Infectious Diseases / Molecular Medicine / Neurosciences
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