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The human viral challenge model: accelerating the evaluation of respiratory antivirals, vaccines and novel diagnostics

Overview of attention for article published in Respiratory Research, June 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)

Mentioned by

1 news outlet
1 blog
4 tweeters
1 Wikipedia page


14 Dimensions

Readers on

63 Mendeley
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The human viral challenge model: accelerating the evaluation of respiratory antivirals, vaccines and novel diagnostics
Published in
Respiratory Research, June 2018
DOI 10.1186/s12931-018-0784-1
Pubmed ID

Rob Lambkin-Williams, Nicolas Noulin, Alex Mann, Andrew Catchpole, Anthony S. Gilbert


The Human Viral Challenge (HVC) model has, for many decades, helped in the understanding of respiratory viruses and their role in disease pathogenesis. In a controlled setting using small numbers of volunteers removed from community exposure to other infections, this experimental model enables proof of concept work to be undertaken on novel therapeutics, including vaccines, immunomodulators and antivirals, as well as new diagnostics.Crucially, unlike conventional phase 1 studies, challenge studies include evaluable efficacy endpoints that then guide decisions on how to optimise subsequent field studies, as recommended by the FDA and thus licensing studies that follow. Such a strategy optimises the benefit of the studies and identifies possible threats early on, minimising the risk to subsequent volunteers but also maximising the benefit of scarce resources available to the research group investing in the research. Inspired by the principles of the 3Rs (Replacement, Reduction and Refinement) now commonly applied in the preclinical phase, HVC studies allow refinement and reduction of the subsequent development phase, accelerating progress towards further statistically powered phase 2b studies. The breadth of data generated from challenge studies allows for exploration of a wide range of variables and endpoints that can then be taken through to pivotal phase 3 studies.We describe the disease burden for acute respiratory viral infections for which current conventional development strategies have failed to produce therapeutics that meet clinical need. The Authors describe the HVC model's utility in increasing scientific understanding and in progressing promising therapeutics through development.The contribution of the model to the elucidation of the virus-host interaction, both regarding viral pathogenicity and the body's immunological response is discussed, along with its utility to assist in the development of novel diagnostics.Future applications of the model are also explored.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 30%
Student > Ph. D. Student 7 11%
Other 5 8%
Student > Master 5 8%
Student > Postgraduate 3 5%
Other 9 14%
Unknown 15 24%
Readers by discipline Count As %
Medicine and Dentistry 10 16%
Biochemistry, Genetics and Molecular Biology 9 14%
Pharmacology, Toxicology and Pharmaceutical Science 6 10%
Agricultural and Biological Sciences 5 8%
Immunology and Microbiology 5 8%
Other 9 14%
Unknown 19 30%

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 June 2020.
All research outputs
of 15,284,323 outputs
Outputs from Respiratory Research
of 1,909 outputs
Outputs of similar age
of 276,591 outputs
Outputs of similar age from Respiratory Research
of 1 outputs
Altmetric has tracked 15,284,323 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,909 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has done particularly well, scoring higher than 96% of its peers.
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 276,591 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them