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Animal health syndromic surveillance: a systematic literature review of the progress in the last 5 years (2011–2016)

Overview of attention for article published in Veterinary Medicine : Research and Reports, November 2016
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Title
Animal health syndromic surveillance: a systematic literature review of the progress in the last 5 years (2011–2016)
Published in
Veterinary Medicine : Research and Reports, November 2016
DOI 10.2147/vmrr.s90182
Pubmed ID
Authors

Fernanda C Dórea, Flavie Vial

Abstract

This review presents the current initiatives and potential for development in the field of animal health surveillance (AHSyS), 5 years on from its advent to the front of the veterinary public health scene. A systematic review approach was used to document the ongoing AHSyS initiatives (active systems and those in pilot phase) and recent methodological developments. Clinical data from practitioners and laboratory data remain the main data sources for AHSyS. However, although not currently integrated into prospectively running initiatives, production data, mortality data, abattoir data, and new media sources (such as Internet searches) have been the objective of an increasing number of publications seeking to develop and validate new AHSyS indicators. Some limitations inherent to AHSyS such as reporting sustainability and the lack of classification standards continue to hinder the development of automated syndromic analysis and interpretation. In an era of ubiquitous electronic collection of animal health data, surveillance experts are increasingly interested in running multivariate systems (which concurrently monitor several data streams) as they are inferentially more accurate than univariate systems. Thus, Bayesian methodologies, which are much more apt to discover the interplay among multiple syndromic data sources, are foreseen to play a big part in the future of AHSyS. It has become clear that early detection of outbreaks may not be the principal expected benefit of AHSyS. As more systems will enter an active prospective phase, following the intensive development stage of the last 5 years, the study envisions AHSyS, in particular for livestock, to significantly contribute to future international-, national-, and local-level animal health intelligence, going beyond the detection and monitoring of disease events by contributing solid situation awareness of animal welfare and health at various stages along the food-producing chain, and an understanding of the risk management involving actors in this value chain.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 2%
Unknown 51 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 37%
Student > Ph. D. Student 11 21%
Student > Master 8 15%
Professor > Associate Professor 2 4%
Other 2 4%
Other 10 19%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 17 33%
Agricultural and Biological Sciences 17 33%
Unspecified 5 10%
Mathematics 4 8%
Computer Science 3 6%
Other 6 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 29 July 2018.
All research outputs
#10,587,258
of 13,297,120 outputs
Outputs from Veterinary Medicine : Research and Reports
#44
of 61 outputs
Outputs of similar age
#200,383
of 268,280 outputs
Outputs of similar age from Veterinary Medicine : Research and Reports
#2
of 3 outputs
Altmetric has tracked 13,297,120 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 61 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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