IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v50y2023i2p231-246.html
   My bibliography  Save this article

Monitoring SEIRD model parameters using MEWMA for the COVID-19 pandemic with application to the state of Qatar

Author

Listed:
  • Edward L. Boone
  • Abdel-Salam G. Abdel-Salam
  • Indranil Sahoo
  • Ryad Ghanam
  • Xi Chen
  • Aiman Hanif

Abstract

During the current COVID-19 pandemic, decision-makers are tasked with implementing and evaluating strategies for both treatment and disease prevention. In order to make effective decisions, they need to simultaneously monitor various attributes of the pandemic such as transmission rate and infection rate for disease prevention, recovery rate which indicates treatment effectiveness as well as the mortality rate and others. This work presents a technique for monitoring the pandemic by employing an Susceptible, Exposed, Infected, Recovered, Death model regularly estimated by an augmented particle Markov chain Monte Carlo scheme in which the posterior distribution samples are monitored via Multivariate Exponentially Weighted Average process monitoring. This is illustrated on the COVID-19 data for the State of Qatar.

Suggested Citation

  • Edward L. Boone & Abdel-Salam G. Abdel-Salam & Indranil Sahoo & Ryad Ghanam & Xi Chen & Aiman Hanif, 2023. "Monitoring SEIRD model parameters using MEWMA for the COVID-19 pandemic with application to the state of Qatar," Journal of Applied Statistics, Taylor & Francis Journals, vol. 50(2), pages 231-246, January.
    • Handle: RePEc:taf:japsta:v:50:y:2023:i:2:p:231-246
    DOI: 10.1080/02664763.2021.1985091
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2021.1985091
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2021.1985091?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.

    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:taf:japsta:v:50:y:2023:i:2:p:231-246. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.