Evidence map›Paper›PMID 35459859›Full record

ReviewNature reviews. Genetics2022

Phylogenetic and phylodynamic approaches to understanding and combating the early SARS-CoV-2 pandemic.

Stephen W Attwood, Sarah C Hill, David M Aanensen, Thomas R Connor, Oliver G Pybus

Abstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
102citing papers in PubMed, 1 pooled it
–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

102 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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  10. Toward AI foundation models for epidemics: Promise, challenges, and paths forward.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
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42 more citing papers are in PubMed but not listed here.

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.

Stephen W AttwoodDepartment of Zoology, University of Oxford, Oxford, UK. stephen.attwood@zoo.ox.ac.uk.ORCID http://orcid.org/0000-0003-1717-1677
Sarah C HillDepartment of Pathobiology and Population Sciences, Royal Veterinary College, University of London, London, UK.ORCID http://orcid.org/0000-0002-2995-2596
David M AanensenCentre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, UK.ORCID http://orcid.org/0000-0001-6688-0854
Thomas R ConnorPathogen Genomics Unit, Public Health Wales NHS Trust, Cardiff, UK.
Oliver G PybusDepartment of Zoology, University of Oxford, Oxford, UK. oliver.pybus@zoo.ox.ac.uk.ORCID http://orcid.org/0000-0002-8797-2667

Funding

Wellcome Trust 220414/Z/20/Z
6 · The paper itself

Abstract

Determining the transmissibility, prevalence and patterns of movement of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is central to our understanding of the impact of the pandemic and to the design of effective control strategies. Phylogenies (evolutionary trees) have provided key insights into the international spread of SARS-CoV-2 and enabled investigation of individual outbreaks and transmission chains in specific settings. Phylodynamic approaches combine evolutionary, demographic and epidemiological concepts and have helped track virus genetic changes, identify emerging variants and inform public health strategy. Here, we review and synthesize studies that illustrate how phylogenetic and phylodynamic techniques were applied during the first year of the pandemic, and summarize their contributions to our understanding of SARS-CoV-2 transmission and control.

Indexed as

COVID-19PandemicsHumansPhylogenySARS-CoV-2

Identifiers

PMID35459859
PMCPMC9028907

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.