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Mathematical Analysis of Viral Replication Dynamics and Antiviral Treatment Strategies: From Basic Models to Age-Based Multi-Scale Modeling

Overview of attention for article published in Frontiers in Microbiology, July 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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14 X users

Citations

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66 Dimensions

Readers on

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167 Mendeley
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Title
Mathematical Analysis of Viral Replication Dynamics and Antiviral Treatment Strategies: From Basic Models to Age-Based Multi-Scale Modeling
Published in
Frontiers in Microbiology, July 2018
DOI 10.3389/fmicb.2018.01546
Pubmed ID
Authors

Carolin Zitzmann, Lars Kaderali

Abstract

Viral infectious diseases are a global health concern, as is evident by recent outbreaks of the middle east respiratory syndrome, Ebola virus disease, and re-emerging zika, dengue, and chikungunya fevers. Viral epidemics are a socio-economic burden that causes short- and long-term costs for disease diagnosis and treatment as well as a loss in productivity by absenteeism. These outbreaks and their socio-economic costs underline the necessity for a precise analysis of virus-host interactions, which would help to understand disease mechanisms and to develop therapeutic interventions. The combination of quantitative measurements and dynamic mathematical modeling has increased our understanding of the within-host infection dynamics and has led to important insights into viral pathogenesis, transmission, and disease progression. Furthermore, virus-host models helped to identify drug targets, to predict the treatment duration to achieve cure, and to reduce treatment costs. In this article, we review important achievements made by mathematical modeling of viral kinetics on the extracellular, intracellular, and multi-scale level for Human Immunodeficiency Virus, Hepatitis C Virus, Influenza A Virus, Ebola Virus, Dengue Virus, and Zika Virus. Herein, we focus on basic mathematical models on the population scale (so-called target cell-limited models), detailed models regarding the most important steps in the viral life cycle, and the combination of both. For this purpose, we review how mathematical modeling of viral dynamics helped to understand the virus-host interactions and disease progression or clearance. Additionally, we review different types and effects of therapeutic strategies and how mathematical modeling has been used to predict new treatment regimens.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 167 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 167 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 13%
Student > Master 21 13%
Student > Ph. D. Student 17 10%
Student > Doctoral Student 14 8%
Student > Bachelor 11 7%
Other 30 18%
Unknown 52 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 14%
Agricultural and Biological Sciences 14 8%
Medicine and Dentistry 14 8%
Mathematics 12 7%
Pharmacology, Toxicology and Pharmaceutical Science 8 5%
Other 30 18%
Unknown 65 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 July 2022.
All research outputs
#4,366,679
of 26,325,711 outputs
Outputs from Frontiers in Microbiology
#3,861
of 30,164 outputs
Outputs of similar age
#75,060
of 342,837 outputs
Outputs of similar age from Frontiers in Microbiology
#144
of 743 outputs
Altmetric has tracked 26,325,711 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 30,164 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has done well, scoring higher than 87% of its peers.
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 342,837 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 743 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.