Evidence map›Paper›PMID 35734094›Full record

ArticlemedRxiv : the preprint server for health sciences2022

Global estimates of the fitness advantage of SARS-CoV-2 variant Omicron.

Christiaan van Dorp, Emma Goldberg, Ruian Ke, Nick Hengartner, Ethan Romero-Severson

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Christiaan van DorpDepartment of Pathology & Cell Biology, Columbia University Irving Medical Center, New York NY, USA.
Emma GoldbergTheoretical Biology and Biophysics (T-6), Los Alamos National Laboratory, Los Alamos NM, USA.
Ruian KeTheoretical Biology and Biophysics (T-6), Los Alamos National Laboratory, Los Alamos NM, USA.
Nick HengartnerTheoretical Biology and Biophysics (T-6), Los Alamos National Laboratory, Los Alamos NM, USA.
Ethan Romero-SeversonTheoretical Biology and Biophysics (T-6), Los Alamos National Laboratory, Los Alamos NM, USA.

Funding

Modeling the ecology of tissue-resident T cellsU01AI150680 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FARBER, DONNA L., YATES, ANDREW · 2020 to 2024
$5.0M
NIAID NIH HHS U01 AI150680
6 · The paper itself

Abstract

New variants of SARS-CoV-2 show remarkable heterogeneity in their relative fitness both over time and space. In this paper we extend a previously published model for estimating the selection strength for new SARS-CoV-2 variants to a hierarchical, mixed-effects, renewal equation model. This formulation allows us to globally estimate selection effects at different spatial levels while controlling for complex patterns of transmission and jointly inferring the effects of unit-level covariates in the spatial heterogeneity of SARS-CoV-2 selection effects. Applying this model to the spread of Omicron in 40 counties finding evidence for very strong (64%) but very heterogeneous selection effects at the country level. We further considered different measures of vaccination levels and measures of recent population-level infection as possible explanations. However, none of those variables were found to explain a significant proportion of the heterogeneity in country-level selection effects. We did find a significant positive correlation between the selection advantage of Delta and Omicron at the country level, suggesting that region-specific explanatory variables of fitness differences do exist. Our method is implemented in the Stan programming language, can be run on standard commercial-grade computing resources, and should be straightforward to apply to future variants.

Identifiers

PMID35734094
PMCPMC9216718

What OpenQuestion holds

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Registered trials

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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.