Mathematical Modeling and Simulation of Viral Infections

A special issue of Microorganisms (ISSN 2076-2607). This special issue belongs to the section "Virology".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 1542

Special Issue Editors


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Guest Editor
Department of Physics and Astronomy, Texas Christian University (TCU), Fort Worth, TX 76129, USA
Interests: mathematical modeling; infectious diseases; viral dynamics; epidemics
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Guest Editor
Department of Mathematics and Statistical Science, University of Idaho, Moscow, ID, USA
Interests: mathematical modeling; COVID-19; human influenza; influenza A virus
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Mathematics, New Mexico Tech, Socorro, NM 87801, USA
Interests: mathematical modeling; infectious diseases; epidemics; viral dynamics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Although often dismissed as a minor nuisance, viruses can cause severe illness and death on a global scale. Understanding viral interactions within a host, as well as viral propagation at the population level, is crucial to preventing the next pandemic. Mathematical models can play an important role in advancing our understanding of viral interactions at multiple scales, allowing researchers to study and manipulate biological processes that are difficult to study experimentally or clinically. The increasing complexity and reliability of mathematical models makes it possible to use mathematical modeling to help guide antiviral development, simulate patient treatment regimens, and inform public policy decisions.

To explore viral dynamics, a variety of mathematical modeling approaches can be applied, including discrete systems, differential equations, and agent-based methodologies. In this Special Issue, we welcome submissions of manuscripts incorporating mathematical modeling of any aspect of viral dynamics.

Keywords: viral dynamics; mathematical models; immune response; antivirals; differential equations; agent-based models; viral evolution

Dr. Hana Dobrovolny
Dr. Esteban A. Hernandez-Vargas
Dr. Gilberto Gonzalez-Parra
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Microorganisms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • viral dynamics
  • mathematical models
  • immune response
  • antivirals
  • differential equations
  • agent-based models
  • viral evolution

Published Papers (1 paper)

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Review

18 pages, 2378 KiB  
Review
Mathematical Modeling of the Lethal Synergism of Coinfecting Pathogens in Respiratory Viral Infections: A Review
by Ericka Mochan and T. J. Sego
Microorganisms 2023, 11(12), 2974; https://0-doi-org.brum.beds.ac.uk/10.3390/microorganisms11122974 - 13 Dec 2023
Viewed by 1018
Abstract
Influenza A virus (IAV) infections represent a substantial global health challenge and are often accompanied by coinfections involving secondary viruses or bacteria, resulting in increased morbidity and mortality. The clinical impact of coinfections remains poorly understood, with conflicting findings regarding fatality. Isolating the [...] Read more.
Influenza A virus (IAV) infections represent a substantial global health challenge and are often accompanied by coinfections involving secondary viruses or bacteria, resulting in increased morbidity and mortality. The clinical impact of coinfections remains poorly understood, with conflicting findings regarding fatality. Isolating the impact of each pathogen and mechanisms of pathogen synergy during coinfections is challenging and further complicated by host and pathogen variability and experimental conditions. Factors such as cytokine dysregulation, immune cell function alterations, mucociliary dysfunction, and changes to the respiratory tract epithelium have been identified as contributors to increased lethality. The relative significance of these factors depends on variables such as pathogen types, infection timing, sequence, and inoculum size. Mathematical biological modeling can play a pivotal role in shedding light on the mechanisms of coinfections. Mathematical modeling enables the quantification of aspects of the intra-host immune response that are difficult to assess experimentally. In this narrative review, we highlight important mechanisms of IAV coinfection with bacterial and viral pathogens and survey mathematical models of coinfection and the insights gained from them. We discuss current challenges and limitations facing coinfection modeling, as well as current trends and future directions toward a complete understanding of coinfection using mathematical modeling and computer simulation. Full article
(This article belongs to the Special Issue Mathematical Modeling and Simulation of Viral Infections)
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