IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v637y2024ics0378437124000888.html
   My bibliography  Save this article

Effectiveness of vaccination and quarantine policies to curb the spread of COVID-19

Author

Listed:
  • Jang, Gyeong Hwan
  • Kim, Sung Jin
  • Lee, Mi Jin
  • Son, Seung-Woo

Abstract

A pandemic, the worldwide spread of a disease, can threaten human beings from both social and biological perspectives and paralyze existing living habits. To stave off the more devastating disaster and return to normal life, people make tremendous efforts at multiscale levels, from individuals to the global population: paying attention to hand hygiene, developing social policies such as wearing masks, practicing social distancing, quarantine, and inventing vaccines and remedies. Regarding the current severe pandemic, namely the coronavirus disease 2019, we explore the spreading-suppression effect when adopting the aforementioned efforts. In this numerical study, we especially consider quarantine and vaccination since they are representative primary treatments for blocking the spread and preventing the disease at the government level. We establish a compartment model consisting of susceptible (S), vaccinated (V), exposed (E), infected (I), quarantined (Q), and recovered (R) compartments, called the SVEIQR model. We examine the number of infected cases in Seoul and consider three kinds of vaccines: Pfizer, Moderna, and AstraZeneca. The values of the relevant parameters are obtained from empirical data from Seoul and clinical data for the vaccines and estimated through Bayesian inference. After confirming the plausibility of our SVEIQR model, we test various scenarios by adjusting the associated parameters with the quarantine and vaccination policies around the current values. The quantitative results obtained from our model could suggest guidelines for policy making on effective vaccination and social policies.

Suggested Citation

  • Jang, Gyeong Hwan & Kim, Sung Jin & Lee, Mi Jin & Son, Seung-Woo, 2024. "Effectiveness of vaccination and quarantine policies to curb the spread of COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
  • Handle: RePEc:eee:phsmap:v:637:y:2024:i:c:s0378437124000888
    DOI: 10.1016/j.physa.2024.129580
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124000888
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2024.129580?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. Turkyilmazoglu, Mustafa, 2022. "A restricted epidemic SIR model with elementary solutions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    2. Saha, Sangeeta & Samanta, Guruprasad & Nieto, Juan J., 2022. "Impact of optimal vaccination and social distancing on COVID-19 pandemic," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 200(C), pages 285-314.
    3. Turkyilmazoglu, Mustafa, 2022. "An extended epidemic model with vaccination: Weak-immune SIRVI," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    Full references (including those not matched with items on IDEAS)

    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. Saha, Sangeeta & Dutta, Protyusha & Samanta, Guruprasad, 2022. "Dynamical behavior of SIRS model incorporating government action and public response in presence of deterministic and fluctuating environments," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    2. González-Parra, Gilberto & Villanueva-Oller, Javier & Navarro-González, F.J. & Ceberio, Josu & Luebben, Giulia, 2024. "A network-based model to assess vaccination strategies for the COVID-19 pandemic by using Bayesian optimization," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    3. Li, Tingting & Guo, Youming, 2022. "Optimal control and cost-effectiveness analysis of a new COVID-19 model for Omicron strain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    4. Kaniadakis, G., 2024. "Novel class of susceptible–infectious–recovered models involving power-law interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    5. Fehaid Salem Alshammari & Fahir Talay Akyildiz, 2023. "Epidemic Waves in a Stochastic SIRVI Epidemic Model Incorporating the Ornstein–Uhlenbeck Process," Mathematics, MDPI, vol. 11(18), pages 1-15, September.
    6. Chakir, Yassine, 2023. "Global approximate solution of SIR epidemic model with constant vaccination strategy," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    7. Ahmed, Marzia & Sulaiman, Mohd Herwan & Mohamad, Ahmad Johari & Rahman, Mostafijur, 2024. "Gooseneck barnacle optimization algorithm: A novel nature inspired optimization theory and application," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 218(C), pages 248-265.
    8. Haque, Mainul & Basir, Fahad Al & Venturino, Ezio & Saeed, Abdulhalim & Smith?, Stacey R., 2023. "Mathematical modelling of clonorchiasis with human treatment and fish vaccination versus snail control," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).

    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:eee:phsmap:v:637:y:2024:i:c:s0378437124000888. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.