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Comparison of covariate adjustment methods using space-time scan statistics for food animal syndromic surveillance.

Overview of attention for article published in BMC Veterinary Research, November 2013
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (57th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

Mentioned by

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2 tweeters

Citations

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8 Dimensions

Readers on

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39 Mendeley
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Title
Comparison of covariate adjustment methods using space-time scan statistics for food animal syndromic surveillance.
Published in
BMC Veterinary Research, November 2013
DOI 10.1186/1746-6148-9-231
Pubmed ID
Authors

Gillian D Alton, David L Pearl, Ken G Bateman, Bruce McNab, Olaf Berke

Abstract

Abattoir condemnation data show promise as a rich source of data for syndromic surveillance of both animal and zoonotic diseases. However, inherent characteristics of abattoir condemnation data can bias results from space-time cluster detection methods for disease surveillance, and may need to be accounted for using various adjustment methods. The objective of this study was to compare the space-time scan statistics with different abilities to control for covariates and to assess their suitability for food animal syndromic surveillance. Four space-time scan statistic models were used including: animal class adjusted Poisson, space-time permutation, multi-level model adjusted Poisson, and a weighted normal scan statistic using model residuals. The scan statistics were applied to monthly bovine pneumonic lung and "parasitic liver" condemnation data from Ontario provincial abattoirs from 2001-2007.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 3%
Unknown 38 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 28%
Researcher 7 18%
Student > Master 5 13%
Student > Bachelor 2 5%
Other 2 5%
Other 5 13%
Unknown 7 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 21%
Veterinary Science and Veterinary Medicine 7 18%
Medicine and Dentistry 6 15%
Computer Science 5 13%
Psychology 3 8%
Other 4 10%
Unknown 6 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 28 November 2013.
All research outputs
#2,087,857
of 4,507,509 outputs
Outputs from BMC Veterinary Research
#290
of 795 outputs
Outputs of similar age
#48,064
of 115,931 outputs
Outputs of similar age from BMC Veterinary Research
#19
of 48 outputs
Altmetric has tracked 4,507,509 research outputs across all sources so far. This one has received more attention than most of these and is in the 52nd percentile.
So far Altmetric has tracked 795 research outputs from this source. They receive a mean Attention Score of 2.1. This one has gotten more attention than average, scoring higher than 62% 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 115,931 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 57% of its contemporaries.
We're also able to compare this research output to 48 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 56% of its contemporaries.