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Optimal control of vaccination rate in an epidemiological model of Clostridium difficile transmission

Overview of attention for article published in Journal of Mathematical Biology, May 2017
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Title
Optimal control of vaccination rate in an epidemiological model of Clostridium difficile transmission
Published in
Journal of Mathematical Biology, May 2017
DOI 10.1007/s00285-017-1133-6
Pubmed ID
Authors

Brittany Stephenson, Cristina Lanzas, Suzanne Lenhart, Judy Day

Abstract

The spore-forming, gram-negative bacteria Clostridium difficile can cause severe intestinal illness. A striking increase in the number of cases of C. difficile infection (CDI) among hospitals has highlighted the need to better understand how to prevent the spread of CDI. In our paper, we modify and update a compartmental model of nosocomial C. difficile transmission to include vaccination. We then apply optimal control theory to determine the time-varying optimal vaccination rate that minimizes a combination of disease prevalence and spread in the hospital population as well as cost, in terms of time and money, associated with vaccination. Various hospital scenarios are considered, such as times of increased antibiotic prescription rate and times of outbreak, to see how such scenarios modify the optimal vaccination rate. By comparing the values of the objective functional with constant vaccination rates to those with time-varying optimal vaccination rates, we illustrate the benefits of time-varying controls.

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Mendeley readers

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 %
Student > Bachelor 3 16%
Researcher 3 16%
Professor > Associate Professor 2 11%
Professor 2 11%
Student > Ph. D. Student 2 11%
Other 2 11%
Unknown 5 26%
Readers by discipline Count As %
Mathematics 5 26%
Veterinary Science and Veterinary Medicine 2 11%
Chemical Engineering 1 5%
Nursing and Health Professions 1 5%
Immunology and Microbiology 1 5%
Other 4 21%
Unknown 5 26%
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 11 May 2017.
All research outputs
#18,547,867
of 22,971,207 outputs
Outputs from Journal of Mathematical Biology
#447
of 658 outputs
Outputs of similar age
#236,654
of 310,587 outputs
Outputs of similar age from Journal of Mathematical Biology
#12
of 19 outputs
Altmetric has tracked 22,971,207 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 658 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.