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Data-driven predictions and novel hypotheses about zoonotic tick vectors from the genus Ixodes

Overview of attention for article published in BMC Ecology, February 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 (87th percentile)

Mentioned by

twitter
22 tweeters
facebook
2 Facebook pages
wikipedia
1 Wikipedia page

Citations

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11 Dimensions

Readers on

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58 Mendeley
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Title
Data-driven predictions and novel hypotheses about zoonotic tick vectors from the genus Ixodes
Published in
BMC Ecology, February 2018
DOI 10.1186/s12898-018-0163-2
Pubmed ID
Authors

Laura Hyesung Yang, Barbara A. Han

Abstract

With the resurgence of tick-borne diseases such as Lyme disease and the emergence of new tick-borne pathogens such as Powassan virus, understanding what distinguishes vectors from non-vectors, and predicting undiscovered tick vectors is a crucial step towards mitigating disease risk in humans. We aimed to identify intrinsic traits that predict which Ixodes tick species are confirmed or strongly suspected to be vectors of zoonotic pathogens. We focused on the well-studied tick genus Ixodes from which many species are known to transmit zoonotic diseases to humans. We apply generalized boosted regression to interrogate over 90 features for over 240 species of Ixodes ticks to learn what intrinsic features distinguish zoonotic vectors from non-vector species. In addition to better understanding the biological underpinnings of tick vectorial capacity, the model generates a per species probability of being a zoonotic vector on the basis of intrinsic biological similarity with known Ixodes vector species. Our model predicted vector status with over 91% accuracy, and identified 14 Ixodes species with high probabilities (80%) of transmitting infections from animal hosts to humans on the basis of their traits. Distinguishing characteristics of zoonotic tick vectors of Ixodes tick species include several anatomical structures that influence host seeking behavior and blood-feeding efficiency from a greater diversity of host species compared to non-vectors. Overall, these results suggest that zoonotic tick vectors are most likely to be those species where adult females hold a fecundity advantage by producing more eggs per clutch, which develop into larvae that feed on a greater diversity of host species compared to non-vector species. These larvae develop into nymphs whose anatomy are well suited for more efficient and longer feeding times on soft-bodied hosts compared to non-vectors, leading to larger adult females with greater fecundity. In addition to identifying novel, testable hypotheses about intrinsic features driving vectorial capacity across Ixodes tick species, our model identifies particular Ixodes species with the highest probability of carrying zoonotic diseases, offering specific targets for increased zoonotic investigation and surveillance.

Twitter Demographics

The data shown below were collected from the profiles of 22 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 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 58 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 26%
Researcher 10 17%
Student > Ph. D. Student 8 14%
Professor 4 7%
Other 3 5%
Other 5 9%
Unknown 13 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 26%
Veterinary Science and Veterinary Medicine 5 9%
Immunology and Microbiology 4 7%
Medicine and Dentistry 4 7%
Biochemistry, Genetics and Molecular Biology 4 7%
Other 10 17%
Unknown 16 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 September 2021.
All research outputs
#1,580,376
of 20,555,893 outputs
Outputs from BMC Ecology
#74
of 421 outputs
Outputs of similar age
#37,332
of 294,438 outputs
Outputs of similar age from BMC Ecology
#1
of 1 outputs
Altmetric has tracked 20,555,893 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 421 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one has done well, scoring higher than 82% 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 294,438 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 87% 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