↓ Skip to main content

Quantifying the Fitness Advantage of Polymerase Substitutions in Influenza A/H7N9 Viruses during Adaptation to Humans

Overview of attention for article published in PLOS ONE, September 2013
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
36 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Quantifying the Fitness Advantage of Polymerase Substitutions in Influenza A/H7N9 Viruses during Adaptation to Humans
Published in
PLOS ONE, September 2013
DOI 10.1371/journal.pone.0076047
Pubmed ID
Authors

Judith M. Fonville, David F. Burke, Nicola S. Lewis, Leah C. Katzelnick, Colin A. Russell

Abstract

Adaptation of zoonotic influenza viruses towards efficient human-to-human transmissibility is a substantial public health concern. The recently emerged A/H7N9 influenza viruses in China provide an opportunity for quantitative studies of host-adaptation, as human-adaptive substitutions in the PB2 gene of the virus have been found in all sequenced human strains, while these substitutions have not been detected in any non-human A/H7N9 sequences. Given the currently available information, this observation suggests that the human-adaptive PB2 substitution might confer a fitness advantage to the virus in these human hosts that allows it to rise to proportions detectable by consensus sequencing over the course of a single human infection. We use a mathematical model of within-host virus evolution to estimate the fitness advantage required for a substitution to reach predominance in a single infection as a function of the duration of infection and the fraction of mutant present in the virus population that initially infects a human. The modeling results provide an estimate of the lower bound for the fitness advantage of this adaptive substitution in the currently sequenced A/H7N9 viruses. This framework can be more generally used to quantitatively estimate fitness advantages of adaptive substitutions based on the within-host prevalence of mutations. Such estimates are critical for models of cross-species transmission and host-adaptation of influenza virus infections.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 3%
Unknown 35 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 31%
Student > Ph. D. Student 10 28%
Student > Bachelor 2 6%
Professor 2 6%
Professor > Associate Professor 2 6%
Other 3 8%
Unknown 6 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 39%
Biochemistry, Genetics and Molecular Biology 8 22%
Immunology and Microbiology 3 8%
Computer Science 1 3%
Mathematics 1 3%
Other 2 6%
Unknown 7 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 July 2021.
All research outputs
#18,348,542
of 22,723,682 outputs
Outputs from PLOS ONE
#154,211
of 193,985 outputs
Outputs of similar age
#152,059
of 204,189 outputs
Outputs of similar age from PLOS ONE
#3,634
of 4,876 outputs
Altmetric has tracked 22,723,682 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 193,985 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 204,189 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4,876 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.