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Impact of the shedding level on transmission of persistent infections in Mycobacterium avium subspecies paratuberculosis (MAP)

Overview of attention for article published in Veterinary Research, February 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

twitter
4 tweeters

Citations

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10 Dimensions

Readers on

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48 Mendeley
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Title
Impact of the shedding level on transmission of persistent infections in Mycobacterium avium subspecies paratuberculosis (MAP)
Published in
Veterinary Research, February 2016
DOI 10.1186/s13567-016-0323-3
Pubmed ID
Authors

Noa Slater, Rebecca Mans Mitchell, Robert H. Whitlock, Terry Fyock, Abani Kumar Pradhan, Elena Knupfer, Ynte Hein Schukken, Yoram Louzoun

Abstract

Super-shedders are infectious individuals that contribute a disproportionate amount of infectious pathogen load to the environment. A super-shedder host may produce up to 10 000 times more pathogens than other infectious hosts. Super-shedders have been reported for multiple human and animal diseases. If their contribution to infection dynamics was linear to the pathogen load, they would dominate infection dynamics. We here focus on quantifying the effect of super-shedders on the spread of infection in natural environments to test if such an effect actually occurs in Mycobacterium avium subspecies paratuberculosis (MAP). We study a case where the infection dynamics and the bacterial load shed by each host at every point in time are known. Using a maximum likelihood approach, we estimate the parameters of a model with multiple transmission routes, including direct contact, indirect contact and a background infection risk. We use longitudinal data from persistent infections (MAP), where infectious individuals have a wide distribution of infectious loads, ranging upward of three orders of magnitude. We show based on these parameters that the effect of super-shedders for MAP is limited and that the effect of the individual bacterial load is limited and the relationship between bacterial load and the infectiousness is highly concave. A 1000-fold increase in the bacterial contribution is equivalent to up to a 2-3 fold increase in infectiousness.

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 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 6%
Unknown 45 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 27%
Student > Ph. D. Student 9 19%
Student > Bachelor 7 15%
Student > Master 6 13%
Other 4 8%
Other 7 15%
Unknown 2 4%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 14 29%
Agricultural and Biological Sciences 13 27%
Medicine and Dentistry 4 8%
Computer Science 3 6%
Biochemistry, Genetics and Molecular Biology 2 4%
Other 5 10%
Unknown 7 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 24 April 2020.
All research outputs
#8,354,753
of 15,496,877 outputs
Outputs from Veterinary Research
#461
of 941 outputs
Outputs of similar age
#109,322
of 268,590 outputs
Outputs of similar age from Veterinary Research
#4
of 13 outputs
Altmetric has tracked 15,496,877 research outputs across all sources so far. This one is in the 45th percentile – i.e., 45% of other outputs scored the same or lower than it.
So far Altmetric has tracked 941 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 50% 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 268,590 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.