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Criteria for judging the immune markers of COVID‐19 disease vaccines

Authors: Nan Lin; Haoxuan Fu; Dan Pu; Yuxin Quan; Yueyi Li; Xiaomeng Yin; Yuhao Wei; +3 Authors

Criteria for judging the immune markers of COVID‐19 disease vaccines

Abstract

AbstractAs severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) sweeping the world, effective and affordable vaccines are in urgent need. A reliable system for the assessment of SARS‐CoV‐2 vaccines would boost the development of vaccines and reduce the research cost. We constructed a logistic regression model and analyzed the relationship between antibody (Ab) level and efficacy of different vaccine types. The relationship between assessment dates and Ab levels was depicted by plotting the mean of Ab levels evolved over time and a fitted cubic polynomial model. Anti‐spike immunoglobulin G (IgG) could best estimate the vaccine efficacy (VE) (adjusted R2 = 0.731) and neutralizing Ab to live SARS‐CoV‐2 also explained a fine relationship (adjusted R2 = 0.577). Neutralizing Abs to live SARS‐CoV‐2 in inactivated virus vaccines reached a peak during days 40–60, and their receptor‐binding domain (RBD)‐IgG peaked during days 40–50. For messenger RNA (mRNA) and viral vector vaccines, their neutralizing Ab to live SARS‐CoV‐2 peaked later than day 40, and for RBD‐IgG during days 30–50. For mRNA and viral vector vaccines, their peak time of Abs was later than that in inactivated virus vaccines. RBD‐IgG peaked earlier than Ab to live SARS‐CoV‐2. Anti‐spike IgG and Ab to live SARS‐CoV‐2 may be good immune markers for VE assessment.

Keywords

assessment, vaccine, R, Medicine, neutralizing antibodies, Original Articles, SARS‐CoV‐2

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
gold