Evidence map›Paper›PMID 37875109›Full record

ArticleCell2023

Population immunity predicts evolutionary trajectories of SARS-CoV-2.

Matthijs Meijers, Denis Ruchnewitz, Jan Eberhardt, Marta Łuksza, Michael Lässig

Open access · hybridAbstract read
In one paragraph

Article in Cell, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
16.3field-weighted citation impact, top 1% of its field
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

50 citing papers in PubMed, 85 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Constrained Evolutionary Funnels Shape Viral Immune Escape.bioRxiv : the preprint server for biology · 2025
    Article
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

5 authors at 2 institutions in 2 countries.

Matthijs MeijersInstitute for Biological Physics, University of Cologne, Zülpicherstr. 77, 50937 Köln, Germany.
Denis RuchnewitzInstitute for Biological Physics, University of Cologne, Zülpicherstr. 77, 50937 Köln, Germany.
Jan EberhardtInstitute for Biological Physics, University of Cologne, Zülpicherstr. 77, 50937 Köln, Germany.
Marta ŁukszaTisch Cancer Institute, Departments of Oncological Sciences and Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Michael LässigInstitute for Biological Physics, University of Cologne, Zülpicherstr. 77, 50937 Köln, Germany. Electronic address: mlaessig@uni-koeln.de.
University of Cologne · DEIcahn School of Medicine at Mount Sinai · US

Funding

NIAID Centers of Excellence for Influenza Research and Response: Universal Influenza Vaccine Research Activities75N93021C00014 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI GARCIA-SASTRE, ADOLFO · 2021 to 2025
$62.6M
NIAID NIH HHS 75N93021C00014
6 · The paper itself

Abstract

The large-scale evolution of the SARS-CoV-2 virus has been marked by rapid turnover of genetic clades. New variants show intrinsic changes, notably increased transmissibility, and antigenic changes that reduce cross-immunity induced by previous infections or vaccinations. How this functional variation shapes global evolution has remained unclear. Here, we establish a predictive fitness model for SARS-CoV-2 that integrates antigenic and intrinsic selection. The model is informed by tracking of time-resolved sequence data, epidemiological records, and cross-neutralization data of viral variants. Our inference shows that immune pressure, including contributions of vaccinations and previous infections, has become the dominant force driving the recent evolution of SARS-CoV-2. The fitness model can serve continued surveillance in two ways. First, it successfully predicts the short-term evolution of circulating strains and flags emerging variants likely to displace the previously predominant variant. Second, it predicts likely antigenic profiles of successful escape variants prior to their emergence.

Indexed as

COVID-19SARS-CoV-2Epidemiological MonitoringHumansModels, GeneticVaccinationEvolutionFitness modelPopulation immunitySARS-CoV-2

Identifiers

PMID37875109
PMCPMC10964984
OpenAlexW4387882041

What OpenQuestion holds

Textmetadata
LicenceTDM
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.