Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 269

The DOI matches its Crossref record; 233 of the 233 references it cites were found in a registry or an index.

Immunological memory to SARS‐CoV‐2 infection and COVID‐19 vaccines

Open access
Sette, Alessandro, Crotty, Shane·2022·Immunological Reviews

Abstract

Immunological memory is the basis of protective immunity provided by vaccines and previous infections. Immunological memory can develop from multiple branches of the adaptive immune system, including CD4 T cells, CD8 T cells, B cells, and long‐lasting antibody responses. Extraordinary progress has been made in understanding memory to SARS‐CoV‐2 infection and COVID‐19 vaccines, addressing development; quantitative and qualitative features of different cellular and anatomical compartments; and durability of each cellular component and antibodies. Given the sophistication of the measurements; the size of the human studies; the use of longitudinal samples and cross‐sectional studies; and head‐to‐head comparisons between infection and vaccines or between multiple vaccines, the understanding of immune memory for 1 year to SARS‐CoV‐2 infection and vaccines already supersedes that of any other acute infectious disease. This knowledge may help inform public policies regarding COVID‐19 and COVID‐19 vaccines, as well as the scientific development of future vaccines against SARS‐CoV‐2 and other diseases.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1111/imr.13089

Cites

233 of 233 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 233 references

Cited by

See all 269

Metadata

Authors
Sette, A., & Crotty, S.
Venue
Immunological Reviews
Publisher
Wiley
Published
2022-06-22
Volume
310
Issue
1
Pages
27-46
ISSN
  • 0105-2896 (ISSN-L)
  • 1600-065X
OpenAlex
W4283331044
Cited by
269
References
233
FWCI
11.89
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Immunological memory to SARS‐CoV‐2 infection and COVID‐19 vaccines. https://app.cochat.ai/papers/10.1111/imr.13089
The paper
Sette, A., & Crotty, S. (2022). Immunological memory to SARS‐CoV‐2 infection and COVID‐19 vaccines. Immunological Reviews. https://doi.org/10.1111/imr.13089

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.