Pinto, E. R,, Nepomuceno, Erivelton and Campanharo, A. S. L. O. (2020) Impact of network topology on the spread of infectious diseases. Tema : têndencias em matemática aplicada e computacional. pp. 95-115.
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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.
Item Type: | Article |
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Keywords: | scientific computing; complex networks; Individual Based Model; epidemic infectious diseases; |
Academic Unit: | Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: | 16707 |
Identification Number: | 10.5540/tema.2020.021.01.0095 |
Depositing User: | Erivelton Nepomuceno |
Date Deposited: | 15 Nov 2022 16:47 |
Journal or Publication Title: | Tema : têndencias em matemática aplicada e computacional |
Publisher: | Sociedade Brasileira de Matematica Aplicada e Computacional |
Refereed: | Yes |
Related URLs: | |
URI: | https://mu.eprints-hosting.org/id/eprint/16707 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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