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A Review of Quantitative Tools Used to Assess the Epidemiology of Porcine Reproductive and Respiratory Syndrome in U.S. Swine Farms Using Dr. Morrison’s Swine Health Monitoring Program Data

Overview of attention for article published in Frontiers in Veterinary Science, June 2017
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Title
A Review of Quantitative Tools Used to Assess the Epidemiology of Porcine Reproductive and Respiratory Syndrome in U.S. Swine Farms Using Dr. Morrison’s Swine Health Monitoring Program Data
Published in
Frontiers in Veterinary Science, June 2017
DOI 10.3389/fvets.2017.00094
Pubmed ID
Authors

Carles Vilalta, Andreia G. Arruda, Steven J. P. Tousignant, Pablo Valdes-Donoso, Petra Muellner, Ulrich Muellner, Moh A. Alkhamis, Robert B. Morrison, Andres M. Perez

Abstract

Porcine reproductive and respiratory syndrome (PRRS) causes far-reaching financial losses to infected countries and regions, including the U.S. The Dr. Morrison's Swine Health Monitoring Program (MSHMP) is a voluntary initiative in which producers and veterinarians share sow farm PRRS status weekly to contribute to the understanding, in quantitative terms, of PRRS epidemiological dynamics and, ultimately, to support its control in the U.S. Here, we offer a review of a variety of analytic tools that were applied to MSHMP data to assess disease dynamics in quantitative terms to support the decision-making process for veterinarians and producers. Use of those methods has helped the U.S. swine industry to quantify the cyclical patterns of PRRS, to describe the impact that emerging pathogens has had on that pattern, to identify the nature and extent at which environmental factors (e.g., precipitation or land cover) influence PRRS risk, to identify PRRS virus emerging strains, and to assess the influence that voluntary reporting has on disease control. Results from the numerous studies reviewed here provide important insights into PRRS epidemiology that help to create the foundations for a near real-time prediction of disease risk, and, ultimately, will contribute to support the prevention and control of, arguably, one of the most devastating diseases affecting the North American swine industry. The review also demonstrates how different approaches to analyze and visualize the data may help to add value to the routine collection of surveillance data and support infectious animal disease control.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 15%
Other 5 13%
Student > Ph. D. Student 5 13%
Student > Bachelor 3 8%
Professor > Associate Professor 3 8%
Other 10 25%
Unknown 8 20%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 14 35%
Agricultural and Biological Sciences 6 15%
Computer Science 3 8%
Biochemistry, Genetics and Molecular Biology 2 5%
Medicine and Dentistry 2 5%
Other 3 8%
Unknown 10 25%
Attention Score in Context

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 27 June 2017.
All research outputs
#17,900,930
of 22,982,639 outputs
Outputs from Frontiers in Veterinary Science
#3,500
of 6,295 outputs
Outputs of similar age
#226,551
of 315,729 outputs
Outputs of similar age from Frontiers in Veterinary Science
#37
of 58 outputs
Altmetric has tracked 22,982,639 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,295 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one is in the 33rd percentile – i.e., 33% of its peers scored the same or lower than it.
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 315,729 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.