Online prediction of COVID19 dynamics. Belgian case study

Yurii, Nesterov ()
Additional contact information
Yurii, Nesterov: CORE, Université catholique de Louvain

No 2020022, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

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.

Date: 2020-02-11
References: Add references at CitEc
Citations:

Downloads: (external link)
https://sites.uclouvain.be/core/publications/coredp/coredp2020.html (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:2020022

Access Statistics for this paper

More papers in LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) Voie du Roman Pays 34, 1348 Louvain-la-Neuve (Belgium). Contact information at EDIRC.
Bibliographic data for series maintained by Alain GILLIS ().