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Modeling Classical Swine Fever Outbreak-Related Outcomes

Overview of attention for article published in Frontiers in Veterinary Science, February 2016
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Title
Modeling Classical Swine Fever Outbreak-Related Outcomes
Published in
Frontiers in Veterinary Science, February 2016
DOI 10.3389/fvets.2016.00007
Pubmed ID
Authors

Shankar Yadav, Nicole J. Olynk Widmar, Hsin-Yi Weng

Abstract

The study was carried out to estimate classical swine fever (CSF) outbreak-related outcomes, such as epidemic duration and number of infected, vaccinated, and depopulated premises, using defined most likely CSF outbreak scenarios. Risk metrics were established using empirical data to select the most likely CSF outbreak scenarios in Indiana. These scenarios were simulated using a stochastic between-premises disease spread model to estimate outbreak-related outcomes. A total of 19 single-site (i.e., with one index premises at the onset of an outbreak) and 15 multiple-site (i.e., with more than one index premises at the onset of an outbreak) outbreak scenarios of CSF were selected using the risk metrics. The number of index premises in the multiple-site outbreak scenarios ranged from 4 to 32. The multiple-site outbreak scenarios were further classified into clustered (N = 6) and non-clustered (N = 9) groups. The estimated median (5th, 95th percentiles) epidemic duration (days) was 224 (24, 343) in the single-site and was 190 (157, 251) and 210 (167, 302) in the clustered and non-clustered multiple-site outbreak scenarios, respectively. The median (5th, 95th percentiles) number of infected premises was 323 (0, 488) in the single-site outbreak scenarios and was 529 (395, 662) and 465 (295, 640) in the clustered and non-clustered multiple-site outbreak scenarios, respectively. Both the number and spatial distributions of the index premises affected the outcome estimates. The results also showed the importance of implementing vaccinations to accommodate depopulation in the CSF outbreak controls. The use of routinely collected surveillance data in the risk metrics and disease spread model allows end users to generate timely outbreak-related information based on the initial outbreak's characteristics. Swine producers can use this information to make an informed decision on the management of swine operations and continuity of business, so that potential losses could be minimized during a CSF outbreak. Government authorities might use the information to make emergency preparedness plans for CSF outbreak control.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 26%
Student > Ph. D. Student 4 17%
Student > Doctoral Student 3 13%
Professor > Associate Professor 2 9%
Researcher 1 4%
Other 1 4%
Unknown 6 26%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 7 30%
Agricultural and Biological Sciences 5 22%
Medicine and Dentistry 2 9%
Business, Management and Accounting 1 4%
Unknown 8 35%
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 02 April 2020.
All research outputs
#17,783,561
of 22,842,950 outputs
Outputs from Frontiers in Veterinary Science
#3,472
of 6,223 outputs
Outputs of similar age
#270,503
of 397,089 outputs
Outputs of similar age from Frontiers in Veterinary Science
#23
of 31 outputs
Altmetric has tracked 22,842,950 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 6,223 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 397,089 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.