IDEAS home Printed from https://ideas.repec.org/a/spr/eurphb/v95y2022i11d10.1140_epjb_s10051-022-00457-z.html
   My bibliography  Save this article

Strain-stream model of epidemic spread in application to COVID-19

Author

Listed:
  • S. A. Trigger

    (Joint Institute for High Temperatures, Russian Academy of Sciences
    Humboldt-Universität zu Berlin)

  • A. M. Ignatov

    (Prokhorov General Physics Institute of the Russian Academy of Sciences)

Abstract

The recently developed model of the epidemic spread of two virus strains in a closed population is generalized to the situation typical for the couple of strains delta and omicron, when there is a high probability of omicron infection soon enough after recovering from delta infection. This model can be considered as a kind of combination of SIR and SIS models for the case of competition of two strains of the same virus with different contagiousness in a population. The obtained equations and results can be directly implemented for practical calculations of the replacement of strains of the SARS-CoV-2 virus. A comparison between the estimated replacement time and the corresponding statistics shows reasonable agreement. Graphic abstract

Suggested Citation

  • S. A. Trigger & A. M. Ignatov, 2022. "Strain-stream model of epidemic spread in application to COVID-19," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(11), pages 1-8, November.
    • Handle: RePEc:spr:eurphb:v:95:y:2022:i:11:d:10.1140_epjb_s10051-022-00457-z
    DOI: 10.1140/epjb/s10051-022-00457-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1140/epjb/s10051-022-00457-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1140/epjb/s10051-022-00457-z?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.

    References listed on IDEAS

    as
    1. Postnikov, Eugene B., 2020. "Estimation of COVID-19 dynamics “on a back-of-envelope”: Does the simplest SIR model provide quantitative parameters and predictions?," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
    2. Xiao-Jie Li & Xiang Li, 2020. "Vaccinating SIS epidemics under evolving perception in heterogeneous networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 93(10), pages 1-7, October.
    3. Juliet Bedford & Jeremy Farrar & Chikwe Ihekweazu & Gagandeep Kang & Marion Koopmans & John Nkengasong, 2019. "A new twenty-first century science for effective epidemic response," Nature, Nature, vol. 575(7781), pages 130-136, November.
    4. Carol Y. Lin, 2008. "Modeling Infectious Diseases in Humans and Animals by KEELING, M. J. and ROHANI, P," Biometrics, The International Biometric Society, vol. 64(3), pages 993-993, September.
    5. Simón A. Rella & Yuliya A. Kulikova & Emmanouil T. Dermitzakis & Fyodor A. Kondrashov, 2021. "Rates of SARS-COV-2 transmission and vaccination impact the fate of vaccine-resistant strains," Working Papers 2129, Banco de España.
    6. Khadija Khan & Farina Karim & Sandile Cele & Kajal Reedoy & James Emmanuel San & Gila Lustig & Houriiyah Tegally & Yuval Rosenberg & Mallory Bernstein & Zesuliwe Jule & Yashica Ganga & Nokuthula Ngcob, 2022. "Omicron infection enhances Delta antibody immunity in vaccinated persons," Nature, Nature, vol. 607(7918), pages 356-359, July.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Shnip, A.I. & Trigger, S.A., 2024. "On the repeated epidemic waves," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shnip, A.I. & Trigger, S.A., 2024. "On the repeated epidemic waves," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    2. Wei Zhong, 2017. "Simulating influenza pandemic dynamics with public risk communication and individual responsive behavior," Computational and Mathematical Organization Theory, Springer, vol. 23(4), pages 475-495, December.
    3. De Martino, Giuseppe & Spina, Serena, 2015. "Exploiting the time-dynamics of news diffusion on the Internet through a generalized Susceptible–Infected model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 634-644.
    4. Guido M. Kuersteiner & Ingmar R. Prucha, 2020. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," Econometrica, Econometric Society, vol. 88(5), pages 2109-2146, September.
    5. Ofosuhene O Apenteng & Noor Azina Ismail, 2014. "The Impact of the Wavelet Propagation Distribution on SEIRS Modeling with Delay," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-9, June.
    6. M Gabriela M Gomes & Marc Lipsitch & Andrew R Wargo & Gael Kurath & Carlota Rebelo & Graham F Medley & Antonio Coutinho, 2014. "A Missing Dimension in Measures of Vaccination Impacts," PLOS Pathogens, Public Library of Science, vol. 10(3), pages 1-3, March.
    7. Saba Wajeeh & Abhishek Lal & Naseer Ahmed & Md. Ibrahim Khalil & Afsheen Maqsood & Akram Mojidea M Alshammari & Abdulelah Zaid Alshammari & Meshari Musallam Mohammed Alsharari & Abdulelah Hamdan Alrus, 2021. "Operational Implications and Risk Assessment of COVID-19 in Dental Practices," IJERPH, MDPI, vol. 18(22), pages 1-13, November.
    8. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "Dynamic tracking with model-based forecasting for the spread of the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    9. Sterck, Olivier, 2016. "Natural resources and the spread of HIV/AIDS: Curse or blessing?," Social Science & Medicine, Elsevier, vol. 150(C), pages 271-278.

    More about this item

    Statistics

    Access and download statistics

    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:spr:eurphb:v:95:y:2022:i:11:d:10.1140_epjb_s10051-022-00457-z. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.