RIVOIRARD Vincent

< Back to ILB Patrimony
Topics of productions
Affiliations
  • 2012 - 2020
    Centre de recherches en mathématiques de la décision
  • 2014 - 2015
    Université Paris-Dauphine
  • 2014 - 2015
    Communauté d'universités et établissements Université de Recherche Paris Sciences et Lettres
  • 2001 - 2002
    Université Paris Diderot
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
  • 2014
  • 2013
  • 2002
  • Simple discrete-time self-exciting models can describe complex dynamic processes: A case study of COVID-19.

    Raiha BROWNING, Deborah SULEM, Kerrie MENGERSEN, Vincent RIVOIRARD, Judith ROUSSEAU
    PLOS ONE | 2021
    Hawkes processes are a form of self-exciting process that has been used in numerous applications, including neuroscience, seismology, and terrorism. While these self-exciting processes have a simple formulation, they can model incredibly complex phenomena. Traditionally Hawkes processes are a continuous-time process, however we enable these models to be applied to a wider range of problems by considering a discrete-time variant of Hawkes processes. We illustrate this through the novel coronavirus disease (COVID-19) as a substantive case study. While alternative models, such as compartmental and growth curve models, have been widely applied to the COVID-19 epidemic, the use of discrete-time Hawkes processes allows us to gain alternative insights. This paper evaluates the capability of discrete-time Hawkes processes by modelling daily mortality counts as distinct phases in the COVID-19 outbreak. We first consider the initial stage of exponential growth and the subsequent decline as preventative measures become effective. We then explore subsequent phases with more recent data. Various countries that have been adversely affected by the epidemic are considered, namely, Brazil, China, France, Germany, India, Italy, Spain, Sweden, the United Kingdom and the United States. These countries are all unique concerning the spread of the virus and their corresponding response measures. However, we find that this simple model is useful in accurately capturing the dynamics of the process, despite hidden interactions that are not directly modelled due to their complexity, and differences both within and between countries. The utility of this model is not confined to the current COVID-19 epidemic, rather this model could explain many other complex phenomena. It is of interest to have simple models that adequately describe these complex processes with unknown dynamics. As models become more complex, a simpler representation of the process can be desirable for the sake of parsimony.
Affiliations are detected from the signatures of publications identified in scanR. An author can therefore appear to be affiliated with several structures or supervisors according to these signatures. The dates displayed correspond only to the dates of the publications found. For more information, see https://scanr.enseignementsup-recherche.gouv.fr