Mathematical Modeling to Perform an Analysis of Social Isolation Periods in the Dissemination of COVID-19

Authors

  • A. Molter Federal University of Pelotas (UFPel), Pelotas, RS - Brazil.
  • R. S. Quadros
  • M. Rafikov
  • D. Buske
  • G. A. Gonçalves

DOI:

https://doi.org/10.5540/tcam.2021.022.04.00595

Abstract

The outbreak of COVID-19 has made scientists from all over the world do not measure
efforts to understand the dynamics of the disease caused by this coronavirus. Several mathematical models have been proposed to describe the dynamics and make predictions. This work proposes a mathematical model that includes social isolation of susceptible individuals as a strategy of suppression and mitigation of the disease. The Susceptible-Infectious-Isolated-Recovered-Dead (SIQRD) model is proposed to analyze three important issues about the dynamics of the disease taking into account social isolation: when the isolation should begin? How long to keep the isolation? How to get out of this isolation? To get answers, computer simulations are provided and their results discussed. The results obtained show that beginning social isolation on the 10th or 15th days, after confirmation of the 50th case, and with 70% of the population in isolation, seems to be promising, since the infected curve does not grow much until it enters the isolation and remains at a stable level during the isolation. On the other hand an abrupt release of the social isolation will imply a second peak of infected individuals above the first one, which is not desired. Therefore, the release from social isolation should be gradual.

Author Biography

A. Molter, Federal University of Pelotas (UFPel), Pelotas, RS - Brazil.

Department of Mathematics and Statistics.

Downloads

Published

2021-10-26

How to Cite

Molter, A., Quadros, R. S., Rafikov, M., Buske, D., & Gonçalves, G. A. (2021). Mathematical Modeling to Perform an Analysis of Social Isolation Periods in the Dissemination of COVID-19. Trends in Computational and Applied Mathematics, 22(4), 595–608. https://doi.org/10.5540/tcam.2021.022.04.00595

Issue

Vol. 22 No. 4 (2021)

Section

Original Article

License

Authors who publish in this journal agree to the following terms: 

  1. Authors retain copyright and grant the journal the right of first publication, with the work simultaneously licensed under the Creative Commons Attribution License that allows the sharing of the work with acknowledgment of authorship and initial publication in this journal.

  2. Authors are authorized to assume additional contracts separately, for non-exclusive distribution of the version of the work published in this journal (eg, publish in an institutional repository or as a book chapter), with acknowledgment of authorship and initial publication in this journal.
     

  3. Authors are allowed and encouraged to publish and distribute their work online (eg, in institutional repositories or on their personal page) at any point before or during the editorial process, as this can generate productive changes as well as increase impact and the citation of the published work (See The effect of open access).

  4. This is an open access journal which means that all content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, without asking prior permission from the publisher or the
    author. This is in accordance with the BOAI definition of open access

 

Intellectual Property

All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License under attribution BY.