Evidence map›Paper›PMID 35775026›Full record

ReviewVirus evolution2022

Epidemiological inference from pathogen genomes: A review of phylodynamic models and applications.

Leo A Featherstone, Joshua M Zhang, Timothy G Vaughan, Sebastian Duchene

Abstract readReview
In one paragraph

Review in Virus evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Review
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  4. Hidden Burden of a Measles Outbreak Revealed by Genomic and Transmission Models.medRxiv : the preprint server for health sciences · 2026
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  6. Review
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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

4 authors.

Leo A FeatherstonePeter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia.
Joshua M ZhangPeter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia.
Timothy G VaughanDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland.
Sebastian DuchenePeter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Phylodynamics requires an interdisciplinary understanding of phylogenetics, epidemiology, and statistical inference. It has also experienced more intense application than ever before amid the SARS-CoV-2 pandemic. In light of this, we present a review of phylodynamic models beginning with foundational models and assumptions. Our target audience is public health researchers, epidemiologists, and biologists seeking a working knowledge of the links between epidemiology, evolutionary models, and resulting epidemiological inference. We discuss the assumptions linking evolutionary models of pathogen population size to epidemiological models of the infected population size. We then describe statistical inference for phylodynamic models and list how output parameters can be rearranged for epidemiological interpretation. We go on to cover more sophisticated models and finish by highlighting future directions.

Indexed as

birth-death modelcoalescent modelepidemiological modelsphylodynamics

Identifiers

PMID35775026
PMCPMC9241095

What OpenQuestion holds

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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.