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Quantifying where human acquisition of antibiotic resistance occurs: a mathematical modelling study

Overview of attention for article published in BMC Medicine, August 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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52 X users

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34 Dimensions

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126 Mendeley
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Title
Quantifying where human acquisition of antibiotic resistance occurs: a mathematical modelling study
Published in
BMC Medicine, August 2018
DOI 10.1186/s12916-018-1121-8
Pubmed ID
Authors

Gwenan M. Knight, Céire Costelloe, Sarah R. Deeny, Luke S. P. Moore, Susan Hopkins, Alan P. Johnson, Julie V. Robotham, Alison H. Holmes

Abstract

Antibiotic-resistant bacteria (ARB) are selected by the use of antibiotics. The rational design of interventions to reduce levels of antibiotic resistance requires a greater understanding of how and where ARB are acquired. Our aim was to determine whether acquisition of ARB occurs more often in the community or hospital setting. We used a mathematical model of the natural history of ARB to estimate how many ARB were acquired in each of these two environments, as well as to determine key parameters for further investigation. To do this, we explored a range of realistic parameter combinations and considered a case study of parameters for an important subset of resistant strains in England. If we consider all people with ARB in the total population (community and hospital), the majority, under most clinically derived parameter combinations, acquired their resistance in the community, despite higher levels of antibiotic use and transmission of ARB in the hospital. However, if we focus on just the hospital population, under most parameter combinations a greater proportion of this population acquired ARB in the hospital. It is likely that the majority of ARB are being acquired in the community, suggesting that efforts to reduce overall ARB carriage should focus on reducing antibiotic usage and transmission in the community setting. However, our framework highlights the need for better pathogen-specific data on antibiotic exposure, ARB clearance and transmission parameters, as well as the link between carriage of ARB and health impact. This is important to determine whether interventions should target total ARB carriage or hospital-acquired ARB carriage, as the latter often dominated in hospital populations.

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X Demographics

The data shown below were collected from the profiles of 52 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 126 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 126 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 24%
Researcher 25 20%
Student > Master 14 11%
Student > Bachelor 10 8%
Other 6 5%
Other 16 13%
Unknown 25 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 14%
Medicine and Dentistry 15 12%
Biochemistry, Genetics and Molecular Biology 9 7%
Veterinary Science and Veterinary Medicine 6 5%
Mathematics 6 5%
Other 31 25%
Unknown 41 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 31. 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 October 2019.
All research outputs
#1,245,976
of 24,972,357 outputs
Outputs from BMC Medicine
#866
of 3,902 outputs
Outputs of similar age
#26,285
of 339,426 outputs
Outputs of similar age from BMC Medicine
#21
of 69 outputs
Altmetric has tracked 24,972,357 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,902 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 45.2. This one has done well, scoring higher than 77% 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 339,426 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 69 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 71% of its contemporaries.