IDEAS home Printed from https://ideas.repec.org/p/cor/louvco/2020022.html
   My bibliography  Save this paper

Online prediction of COVID19 dynamics. Belgian case study

Author

Listed:
  • NESTEROV Yurii,

    (CORE, Université catholique de Louvain)

Abstract

In this paper, we present a new axiomatic model of epidemic development, called HIT, which is consistent with the very special features of COVID19. This is a discrete-time linear switching model for predicting the dynamics of total number of infected persons and concentration of the asymptomatic virus holders in the population. A small number of its parameters can be tuned using the available real-time dynamic data on virus propagation. This model provides us with a rare possibility of online prediction of the future. As an example, we describe an application of this model to the online analysis of COVID19 epidemic in Belgium for eighty days in the period March - May, 2020. During this time, our predictions were exact, typically, within the accuracy of 0.5%. To the best of our knowledge, this is the fi rst mathematical model predicting the evolution of epidemics under containment measures, which prevent development of immunity in the population.

Suggested Citation

  • NESTEROV Yurii,, 2020. "Online prediction of COVID19 dynamics. Belgian case study," LIDAM Discussion Papers CORE 2020022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvco:2020022
    as

    Download full text from publisher

    File URL: https://sites.uclouvain.be/core/publications/coredp/coredp2020.html
    Download Restriction: no
    ---><---

    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:cor:louvco:2020022. 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: Alain GILLIS (email available below). General contact details of provider: https://edirc.repec.org/data/coreebe.html .

    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.