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Causes of delayed outbreak responses and their impacts on epidemic spread

Overview of attention for article published in Journal of The Royal Society Interface, March 2021
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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)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

news
1 news outlet
twitter
14 tweeters

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
19 Mendeley
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Title
Causes of delayed outbreak responses and their impacts on epidemic spread
Published in
Journal of The Royal Society Interface, March 2021
DOI 10.1098/rsif.2020.0933
Pubmed ID
Authors

Yun Tao, William J. M. Probert, Katriona Shea, Michael C. Runge, Kevin Lafferty, Michael Tildesley, Matthew Ferrari

Abstract

Livestock diseases have devastating consequences economically, socially and politically across the globe. In certain systems, pathogens remain viable after host death, which enables residual transmissions from infected carcasses. Rapid culling and carcass disposal are well-established strategies for stamping out an outbreak and limiting its impact; however, wait-times for these procedures, i.e. response delays, are typically farm-specific and time-varying due to logistical constraints. Failing to incorporate variable response delays in epidemiological models may understate outbreak projections and mislead management decisions. We revisited the 2001 foot-and-mouth epidemic in the United Kingdom and sought to understand how misrepresented response delays can influence model predictions. Survival analysis identified farm size and control demand as key factors that impeded timely culling and disposal activities on individual farms. Using these factors in the context of an existing policy to predict local variation in response times significantly affected predictions at the national scale. Models that assumed fixed, timely responses grossly underestimated epidemic severity and its long-term consequences. As a result, this study demonstrates how general inclusion of response dynamics and recognition of partial controllability of interventions can help inform management priorities during epidemics of livestock diseases.

Twitter Demographics

The data shown below were collected from the profiles of 14 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 21%
Other 2 11%
Student > Master 2 11%
Student > Doctoral Student 1 5%
Lecturer 1 5%
Other 1 5%
Unknown 8 42%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 5 26%
Agricultural and Biological Sciences 3 16%
Mathematics 2 11%
Earth and Planetary Sciences 1 5%
Unknown 8 42%

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 09 July 2021.
All research outputs
#1,522,421
of 21,542,809 outputs
Outputs from Journal of The Royal Society Interface
#682
of 2,952 outputs
Outputs of similar age
#38,214
of 316,276 outputs
Outputs of similar age from Journal of The Royal Society Interface
#18
of 59 outputs
Altmetric has tracked 21,542,809 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 2,952 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.9. This one has done well, scoring higher than 76% 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 316,276 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 59 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.