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Dose-response models for selected respiratory infectious agents: Bordetella pertussis, group a Streptococcus, rhinovirus and respiratory syncytial virus

Overview of attention for article published in BMC Infectious Diseases, February 2015
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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 (89th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

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1 news outlet
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11 X users

Citations

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18 Dimensions

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51 Mendeley
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Title
Dose-response models for selected respiratory infectious agents: Bordetella pertussis, group a Streptococcus, rhinovirus and respiratory syncytial virus
Published in
BMC Infectious Diseases, February 2015
DOI 10.1186/s12879-015-0832-0
Pubmed ID
Authors

Rachael M Jones, Yu-Min Su

Abstract

Dose-response assessment is one step in quantitative microbial risk assessment (QMRA). Four infectious microbes capable of causing respiratory diseases important to public health, and for which dose-response functions have not been available are: Bordetella pertussis (whooping cough), group A Streptococcus (pharyngitis), rhinovirus (common cold) and respiratory syncytial virus (common cold). The objective of this study was to fit dose-response functions for these microbes to published experimental data. Experimental infectivity data in human subjects and/or animal models were identified from the peer-reviewed literature. The exponential and beta-Poisson dose-response functions were fitted using the method of maximum likelihood, and models compared by Akaike's Information Criterion. Dose-response functions were identified for each appropriate data set for the four infectious microbes. Statistical and graphical measures of fit are presented. With the fitted dose-response functions it will be possible to perform QMRA for these microbes. The dose-response functions, however, have a number of limitations associated with the route of exposure, use of animal hosts, and quality of fit. As a result, thoughtfulness must be used in selecting one dose-response function for a QMRA, and the function should be recognized as a significant source of uncertainty. Nonetheless, QMRA offers a transparent, systematic framework within which to understand the mechanisms of disease transmission, and evaluate interventions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 X users 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 2%
Unknown 50 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 14%
Student > Master 6 12%
Researcher 5 10%
Other 3 6%
Professor > Associate Professor 3 6%
Other 10 20%
Unknown 17 33%
Readers by discipline Count As %
Engineering 7 14%
Medicine and Dentistry 7 14%
Agricultural and Biological Sciences 5 10%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Mathematics 1 2%
Other 6 12%
Unknown 24 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 10 June 2020.
All research outputs
#2,375,055
of 25,425,223 outputs
Outputs from BMC Infectious Diseases
#688
of 8,614 outputs
Outputs of similar age
#28,860
of 270,001 outputs
Outputs of similar age from BMC Infectious Diseases
#6
of 157 outputs
Altmetric has tracked 25,425,223 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,614 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has done particularly well, scoring higher than 92% 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 270,001 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 89% of its contemporaries.
We're also able to compare this research output to 157 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.