Evidence map›Paper›PMID 32295920›Full record

ArticleJournal of virology2020

Inferring Transmission Bottleneck Size from Viral Sequence Data Using a Novel Haplotype Reconstruction Method.

Mahan Ghafari, Casper K Lumby, Daniel B Weissman, Christopher J R Illingworth

Abstract read
In one paragraph

Article in Journal of virology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

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  13. The evolution of SARS-CoV-2.Nature reviews. Microbiology · 2023
    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.

Mahan Ghafari *Department of Genetics, University of Cambridge, Cambridge, United Kingdom.
Casper K Lumby *Department of Genetics, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0001-8329-9228
Daniel B WeissmanDepartment of Physics, Emory University, Atlanta, Georgia, USA.
Christopher J R IllingworthDepartment of Genetics, University of Cambridge, Cambridge, United Kingdom chris.illingworth@gen.cam.ac.uk.ORCID 0000-0002-0030-2784

Funding

Wellcome TrustWellcome Trust 101239/Z/13/ZWellcome Trust 105365/Z/14/Z
6 · The paper itself

Abstract

The transmission bottleneck is defined as the number of viral particles that transmit from one host to establish an infection in another. Genome sequence data have been used to evaluate the size of the transmission bottleneck between humans infected with the influenza virus; however, the methods used to make these estimates have some limitations. Specifically, viral allele frequencies, which form the basis of many calculations, may not fully capture a process which involves the transmission of entire viral genomes. Here, we set out a novel approach for inferring viral transmission bottlenecks; our method combines an algorithm for haplotype reconstruction with maximum likelihood methods for bottleneck inference. This approach allows for rapid calculation and performs well when applied to data from simulated transmission events; errors in the haplotype reconstruction step did not adversely affect inferences of the population bottleneck. Applied to data from a previous household transmission study of influenza A infection, we confirm the result that the majority of transmission events involve a small number of viruses, albeit with slightly looser bottlenecks being inferred, with between 1 and 13 particles transmitted in the majority of cases. While influenza A transmission involves a tight population bottleneck, the bottleneck is not so tight as to universally prevent the transmission of within-host viral diversity.

Indexed as

Evolution, MolecularGenetic VariationGenome, ViralHaplotypesHumansInfluenza A virusInfluenza, HumanModels, TheoreticalSequence Analysis, DNAVirusesinfluenza Apopulation bottlenecktransmission

Identifiers

PMID32295920
PMCPMC7307158

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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.