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A qualitatively validated mathematical-computational model of the immune response to the yellow fever vaccine

Overview of attention for article published in BMC Immunology, May 2018
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Title
A qualitatively validated mathematical-computational model of the immune response to the yellow fever vaccine
Published in
BMC Immunology, May 2018
DOI 10.1186/s12865-018-0252-1
Pubmed ID
Authors

Carla R. B. Bonin, Guilherme C. Fernandes, Rodrigo W. dos Santos, Marcelo Lobosco

Abstract

Although a safe and effective yellow fever vaccine was developed more than 80 years ago, several issues regarding its use remain unclear. For example, what is the minimum dose that can provide immunity against the disease? A useful tool that can help researchers answer this and other related questions is a computational simulator that implements a mathematical model describing the human immune response to vaccination against yellow fever. This work uses a system of ten ordinary differential equations to represent a few important populations in the response process generated by the body after vaccination. The main populations include viruses, APCs, CD8+ T cells, short-lived and long-lived plasma cells, B cells and antibodies. In order to qualitatively validate our model, four experiments were carried out, and their computational results were compared to experimental data obtained from the literature. The four experiments were: a) simulation of a scenario in which an individual was vaccinated against yellow fever for the first time; b) simulation of a booster dose ten years after the first dose; c) simulation of the immune response to the yellow fever vaccine in individuals with different levels of naïve CD8+ T cells; and d) simulation of the immune response to distinct doses of the yellow fever vaccine. This work shows that the simulator was able to qualitatively reproduce some of the experimental results reported in the literature, such as the amount of antibodies and viremia throughout time, as well as to reproduce other behaviors of the immune response reported in the literature, such as those that occur after a booster dose of the vaccine.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 16%
Researcher 6 16%
Professor 4 11%
Student > Postgraduate 3 8%
Student > Master 3 8%
Other 7 19%
Unknown 8 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 16%
Mathematics 3 8%
Immunology and Microbiology 3 8%
Agricultural and Biological Sciences 3 8%
Computer Science 2 5%
Other 9 24%
Unknown 11 30%
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 25 May 2018.
All research outputs
#18,625,558
of 23,073,835 outputs
Outputs from BMC Immunology
#426
of 590 outputs
Outputs of similar age
#255,661
of 330,748 outputs
Outputs of similar age from BMC Immunology
#8
of 11 outputs
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So far Altmetric has tracked 590 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
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We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.