IDEAS home Printed from https://ideas.repec.org/a/wsi/ijmpcx/v31y2020i10ns0129183120501351.html
   My bibliography  Save this article

Modeling the early evolution of the COVID-19 in Brazil: Results from a Susceptible–Infectious–Quarantined–Recovered (SIQR) model

Author

Listed:
  • Nuno Crokidakis

    (Instituto de Física, Universidade Federal Fluminense, Niterói/RJ, Brazil)

Abstract

The world evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-Cov2 or simply COVID-19) led the World Health Organization to declare it a pandemic. The disease appeared in China in December 2019, and it has spread fast around the world, especially in European countries like Italy and Spain. The first reported case in Brazil was recorded in February 26, and after that the number of cases grew fast. In order to slow down the initial growth of the disease through the country, confirmed positive cases were isolated to not transmit the disease. To better understand the early evolution of COVID-19 in Brazil, we apply a Susceptible–Infectious–Quarantined–Recovered (SIQR) model to the analysis of data from the Brazilian Department of Health, obtained from February 26, 2020 through March 25, 2020. Based on analytical and numerical results, as well on the data, the basic reproduction number is estimated to R0=5.25. In addition, we estimate that the ratio between unidentified infectious individuals and confirmed cases at the beginning of the epidemic is about 10, in agreement with previous studies. We also estimated the epidemic doubling time to be 2.72 days.

Suggested Citation

  • Nuno Crokidakis, 2020. "Modeling the early evolution of the COVID-19 in Brazil: Results from a Susceptible–Infectious–Quarantined–Recovered (SIQR) model," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 31(10), pages 1-7, October.
    • Handle: RePEc:wsi:ijmpcx:v:31:y:2020:i:10:n:s0129183120501351
    DOI: 10.1142/S0129183120501351
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0129183120501351
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0129183120501351?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alexey I. Borovkov & Marina V. Bolsunovskaya & Aleksei M. Gintciak, 2022. "Intelligent Data Analysis for Infection Spread Prediction," Sustainability, MDPI, vol. 14(4), pages 1-11, February.
    2. Esperanza Lozada & Carolina Guerrero-Ortiz & Aníbal Coronel & Rigoberto Medina, 2023. "Proposal of a Mathematical Modelling Activity to Facilitate Students’ Learning of Ordinary Differential Equation Concepts," Sustainability, MDPI, vol. 15(16), pages 1-22, August.
    3. Katarzyna Czech & Michał Wielechowski, 2021. "Is the Alternative Energy Sector COVID-19 Resistant? Comparison with the Conventional Energy Sector: Markov-Switching Model Analysis of Stock Market Indices of Energy Companies," Energies, MDPI, vol. 14(4), pages 1-17, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wsi:ijmpcx:v:31:y:2020:i:10:n:s0129183120501351. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijmpc/ijmpc.shtml .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.