Evidence map›Paper›PMID 36137003›Full record

ReviewPLoS genetics2022

Population genetic models for the spatial spread of adaptive variants: A review in light of SARS-CoV-2 evolution.

Margaret C Steiner, John Novembre

Open access · goldAbstract readReview
In one paragraph

Review in PLoS genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

9 citing papers in PubMed, 13 citations in OpenAlex.

  1. Observational
  2. Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series.Proceedings of the National Academy of Sciences of the United States of America · 2025
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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

2 authors at 1 institution in 1 country.

Margaret C SteinerDepartment of Human Genetics, University of Chicago, Chicago, Illinois, United States of America.ORCID 0000-0002-1062-1228
John NovembreDepartment of Human Genetics, University of Chicago, Chicago, Illinois, United States of America.ORCID 0000-0001-5345-0214
University of Chicago · US

Funding

Haplotype-based analysis methods for population genomicsR01HG007089 · NHGRI · UNIVERSITY OF CHICAGO · PI NOVEMBRE, JOHN · 2013 to 2017
$1.5M
Extending Tools for Visualization of Geographic Structure in Population Genomic DataR01GM132383 · NIGMS · UNIVERSITY OF CHICAGO · PI NOVEMBRE, JOHN · 2019 to 2022
$1.4M
NHGRI NIH HHS R01 HG007089NIGMS NIH HHS R01 GM132383
6 · The paper itself

Abstract

Theoretical population genetics has long studied the arrival and geographic spread of adaptive variants through the analysis of mathematical models of dispersal and natural selection. These models take on a renewed interest in the context of the COVID-19 pandemic, especially given the consequences that novel adaptive variants have had on the course of the pandemic as they have spread through global populations. Here, we review theoretical models for the spatial spread of adaptive variants and identify areas to be improved in future work, toward a better understanding of variants of concern in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) evolution and other contemporary applications. As we describe, characteristics of pandemics such as COVID-19-such as the impact of long-distance travel patterns and the overdispersion of lineages due to superspreading events-suggest new directions for improving upon existing population genetic models.

Indexed as

COVID-19SARS-CoV-2HumansPandemics

Identifiers

PMID36137003
PMCPMC9498967
OpenAlexW4296742929

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.