Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
2.0
Journals
Axioms
Special Issues
Computer Methods in Mathematical Epidemiology
share announcement

Computer Methods in Mathematical Epidemiology

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 2026

Special Issue Editors

Dr. Pedro Henrique Triguis Schimit

E-Mail Website
Guest Editor
Information Technology and Knowledge Management Graduate Program, Universidade Nove de Julho, São Paulo, Brazil
Interests: mathematical epidemiology; evolutionary game theory
Dr. Yijun Lou

E-Mail Website
Guest Editor
Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Interests: applied dynamical systems; differential equations; mathematical epidemiology

Special Issue Information

Dear Colleagues,

The COVID-19 pandemic highlighted the importance of epidemiological modelling in the prediction and comprehension of disease transmission. In addition, computer methods have played a crucial role in building predictive models that can help to forecast the course of the pandemic, determining the sensitivity to modifications in parameter values, estimating key parameters from data, optimizing control measures to reduce the transmission of COVID-19, and delivering prompt results. By leveraging the power of these computer methods, epidemiologists can run simulations that account for the complexity of real-world systems. Therefore, the efficacy of mathematical epidemiology models is reliant on the complementary progress of effective computer methods. This convergence of various research domains adopts a natural interdisciplinary approach, where machine learning, metaheuristics approaches, and high-performance computing often feature in innovative studies of mathematical epidemiology. It is likely that these interdisciplinary efforts will continue to drive progress in the field of mathematical epidemiology for years to come.

Hence, the current Special Issue, entitled "Computer Methods in Mathematical Epidemiology", affiliated with the scholarly journal Axioms, invites contributions that employ novel computer-based techniques in the topic list to enhance established and contemporary mathematical epidemiological methodologies. Manuscripts will be considered for publication only if they incorporate a pertinent computational method to facilitate the utilization, tuning, analysis, and simulation of the epidemiological model, rather than solely relying on the development, investigation, and simulation of mathematical models.

Dr. Pedro Henrique Triguis Schimit
Dr. Yijun Lou
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. Axioms 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 2400 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

  • artificial intelligence
  • big data analytics
  • data mining
  • evolutionary algorithms
  • high-performance computing
  • machine learning
  • metaheuristics techniques
  • neural networks
  • population dynamics
  • soft computing

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

33 pages, 5889 KiB  
Article
Analysis of Epidemic Models in Complex Networks and Node Isolation Strategie Proposal for Reducing Virus Propagation
by Carlos Rodríguez Lucatero
Axioms 2024, 13(2), 79; https://doi.org/10.3390/axioms13020079 - 25 Jan 2024
Viewed by 903
Abstract
Many models of virus propagation in Computer Networks inspired by epidemic disease propagation mathematical models that can be found in the epidemiology field (SIS, SIR, SIRS, etc.) have been proposed in the last two decades. The purpose of these models has [...] Read more.
Many models of virus propagation in Computer Networks inspired by epidemic disease propagation mathematical models that can be found in the epidemiology field (SIS, SIR, SIRS, etc.) have been proposed in the last two decades. The purpose of these models has been to determine the conditions under which a virus becomes rapidly extinct in a network. The most common models of virus propagation in networks are SIS-type models or their variants. In such models, the conditions that lead to a rapid extinction of the spread of a computer virus have been calculated and its dependence on some parameters inherent to the mathematical model has been observed. In this article, we will try to analyze a particular SIS-type model proposed in the past by Chakrabarti as well as an SIRS-type variation of this model proposed in the past by myself. I will show through simulations the influence that the topology of a network has on the dynamics of the spread of a virus in different network types. In the recent past, there have been interesting articles that demonstrate the relationship between the eigenvalue λ1 of the adjacency matrix and the reduction in the spread of a virus in a network. From this, the minimization of the spectral radius strategies by edge suppression has been proposed. This problem is NP-complete in its general case and for this reason, heuristic algorithms have been proposed. In this article, I will perform simulations of an SIS-type model in topologies with the same number of nodes but with different structures to compare their epidemic behavior. The simulations will show that regular topologies with small node degrees, i.e., of degree 4, as is the case of the topology that I call Lattice4, have favorable behavior in terms of the fast extinction property, with respect to other denser and less regular topologies such as the binomial topologies as well as Power law topologies. Based on the results of the simulations, my contribution will consist of proposing, as a node isolation strategy, a transformation of the original topology into an approximately regular topology by edge elimination. Although such a transformed topology is not optimal in terms of reducing the propagation of a virus, it induces the rapid extinction of the virus in the network. Full article
(This article belongs to the Special Issue Computer Methods in Mathematical Epidemiology)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop