Quantifying the role of naturally- and vaccine-derived neutralizing antibodies as a correlate of protection against COVID-19 variants
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
The functional relationship between neutralizing antibodies (NAbs) and protection against SARS-CoV-2 infection and disease remains unclear. We jointly estimated protection against infection and disease progression following natural infection and vaccination from meta-study data. We find that NAbs are strongly correlated with prevention of infection and that any history of NAbs will stimulate immune memory to moderate disease progression. We also find that natural infection provides stronger protection than vaccination for the same level of NAbs, noting that infection itself, unlike vaccination, carries risk of morbidity and mortality, and that our most potent vaccines induce much higher NAb levels than natural infection. These results suggest that while sterilizing immunity may decay, we expect protection against severe disease to be robust over time and in the face of immune-evading variants.
Article activity feed
-
-
SciScore for 10.1101/2021.05.31.21258018: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Model overview: Covasim is an open-source agent-based model developed by the Institute for Disease Modeling with source code and documentation available at https://covasim.org. Covasimsuggested: NoneResults from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our modeling approach has several limitations. Although we explicitly account for the fact that individuals with some neutralizing antibodies from prior infection or vaccination are less likely to develop symptomatic or severe …
SciScore for 10.1101/2021.05.31.21258018: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Model overview: Covasim is an open-source agent-based model developed by the Institute for Disease Modeling with source code and documentation available at https://covasim.org. Covasimsuggested: NoneResults from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our modeling approach has several limitations. Although we explicitly account for the fact that individuals with some neutralizing antibodies from prior infection or vaccination are less likely to develop symptomatic or severe disease, we do not account for the possibility that the duration of disease may also be reduced or that secondary infections may have a reduced viral load, although there is some evidence to this effect (Gouma et al., 2021; Levine-Tiefenbrun et al., 2021). We do not model the emergence of new variants, although previous studies have attempted this for influenza (Bush et al., 1999; Gupta et al., 1998; Bedford et al., 2012; Koelle and Rasmussen, 2015; Wen et al., 2020) and similar approaches could possibly be applied for SARS-CoV-2. Our modeling approach relies on estimating a relationship between neutralizing antibodies and different correlates of protection, and the data used to establish these estimates are scarce and uncertain, especially for low levels of neutralizing antibodies. We do not specifically model cellular immune responses, although they are likely to also influence disease symptomaticity and severity (Tarke et al., 2021; McMahan et al., 2021). We have modeled antibody kinetics based upon studies of immune decay in patients up to 8 months after SARS-CoV-2 infection, using a two-part exponential decay. An alternative approach taken by (Pelleau et al., 2021) uses a mathematical model of the immunological process underlying the generation and...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
-