Impact of Network Topology on the Spread of Infectious Diseases

Authors

  • Eduardo R. Pinto Programa de Pós-Graduação em Biometria do Instituto de Biociências. UNESP. Campus de Botucatu, São Paulo.
  • Erivelton G. Nepomuceno Departamento de Engenharia Elétrica. Universidade de São João Del Rei (UFSJ), Minas Gerais https://orcid.org/0000-0002-5841-2193
  • Andriana S. L. O. Campanharo Departamento de Bioestatística do Instituto de Biociências de Botucatu. UNESP, São Paulo. https://orcid.org/0000-0002-0501-5303

DOI:

https://doi.org/10.5540/tema.2020.021.01.95

Keywords:

Scientific Computing, Complex Networks, Individual Based Model, Epidemic Infectious Diseases

Abstract

The complex network theory constitutes a natural support for the study of a disease propagation. In this work, we present a study of an infectious disease spread with the use of this theory in combination with the Individual Based Model. More specifically, we use several complex network models widely known in the literature to verify their topological effects in the propagation of the disease. In general, complex networks with different properties result in curves of infected individuals with different behaviors, and thus, the growth of a given disease is highly sensitive to the network model used. The disease eradication is observed when the vaccination strategy of 10% of the population is used in combination with the random, small world or modular network models, which opens an important space for control actions that focus on changing the topology of a complex network as a form of reduction or even elimination of an infectious disease.

Downloads

Published

2020-03-27

How to Cite

Pinto, E. R., Nepomuceno, E. G., & Campanharo, A. S. L. O. (2020). Impact of Network Topology on the Spread of Infectious Diseases. Trends in Computational and Applied Mathematics, 21(1), 95. https://doi.org/10.5540/tema.2020.021.01.95

Issue

Vol. 21 No. 1 (2020)

Section

Original Article

License

Copyright

Authors of articles published in the journal Trends in Computational and Applied Mathematics retain the copyright of their work. The journal uses Creative Commons Attribution (CC-BY) in published articles. The authors grant the TCAM journal the right to first publish the article.

Intellectual Property and Terms of Use

The content of the articles is the exclusive responsibility of the authors. The journal uses Creative Commons Attribution (CC-BY) in published articles. This license allows published articles to be reused without permission for any purpose as long as the original work is correctly cited.

The journal encourages Authors to self-archive their accepted manuscripts, publishing them on personal blogs, institutional repositories, and social media, as long as the full citation is included in the journal's website version.