Evidence map›Paper›PMID 36202234›Full record

ArticleJournal of theoretical biology2023

A mathematical model of the within-host kinetics of SARS-CoV-2 neutralizing antibodies following COVID-19 vaccination.

Lisette dePillis, Rebecca Caffrey, Ge Chen, Mark D Dela, Leif Eldevik, Joseph McConnell, Shahrokh Shabahang, Stephen A Varvel

Abstract read
In one paragraph

Article in Journal of theoretical biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Lisette dePillisDepartment of Mathematics, Harvey Mudd College, 301 Platt Blvd., Claremont, CA 91711, United States. Electronic address: depillis@hmc.edu.
Rebecca CaffreyAditxt, Inc. 737 N. Fifth Street, Suite 200, Richmond, VA 23219, United States.
Ge ChenAditxt, Inc. 737 N. Fifth Street, Suite 200, Richmond, VA 23219, United States.
Mark D DelaCalifornia State Polytechnic University, Pomona, CA, United States. Electronic address: mddela@cpp.edu.
Leif EldevikAditxt, Inc. 737 N. Fifth Street, Suite 200, Richmond, VA 23219, United States.
Joseph McConnellAditxt, Inc. 737 N. Fifth Street, Suite 200, Richmond, VA 23219, United States.
Shahrokh ShabahangAditxt, Inc. 737 N. Fifth Street, Suite 200, Richmond, VA 23219, United States.
Stephen A VarvelAditxt, Inc. 737 N. Fifth Street, Suite 200, Richmond, VA 23219, United States. Electronic address: depillis@hmc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Compelling evidence continues to build to support the idea that SARS-CoV-2 Neutralizing Antibody (NAb) levels in an individual can serve as an important indicator of the strength of protective immunity against infection. It is not well understood why NAb levels in some individuals remain high over time, while in others levels decline rapidly. In this work, we present a two-state mathematical model of within-host NAb dynamics in response to vaccination. By fitting only four host-specific parameters, the model is able to capture individual-specific NAb levels over time as measured by the AditxtScore™ for NAbs. The model can serve as a foundation for predicting NAb levels in the long-term, understanding connections between NAb levels, protective immunity, and breakthrough infections, and potentially guiding decisions about whether and when a booster vaccination may be warranted.

Indexed as

COVID-19SARS-CoV-2Antibodies, NeutralizingAntibodies, ViralCOVID-19 VaccinesHumansModels, TheoreticalVaccinationAntibodies, NeutralizingAntibodies, ViralCOVID-19 VaccinesAditxtScore™COVID-19Host-specific parameter fittingMathematical modelNeutralizing antibody NAbSARS-CoV-2VaccinationWithin-host model

Identifiers

PMID36202234
PMCPMC9529354

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.