Modelling the second wave of COVID-19 infections in France and Italy via a Stochastic SEIR model 2

Davide Faranda (1, 2, 3) , Tommaso Alberti (4)

1 ESTIMR - Extrèmes : Statistiques, Impacts et Régionalisation
2 London Mathematical Laboratory
3 LMD - Laboratoire de Météorologie Dynamique (UMR 8539)
4 IAPS - Istituto di Astrofisica e Planetologia Spaziali - INAF

COVID-19 has forced quarantine measures in several countries across the world. These measures have proven to be effective in significantly reducing the prevalence of the virus. To date, no effective treatment or vaccine is available. In the effort of preserving both public health as well as the economical and social textures, France and Italy governments have partially released lockdown measures. Here we extrapolate the long-term behavior of the epidemics in both countries using a Susceptible-Exposed-Infected-Recovered (SEIR) model where parameters are stochastically perturbed to handle the uncertainty in the estimates of COVID-19 prevalence. Our results suggest that uncertainties in both parameters and initial conditions rapidly propagate in the model and can result in different outcomes of the epidemics leading or not to a second wave of infections. Using actual knowledge, asymptotic estimates of COVID-19 prevalence can fluctuate of order of ten millions units in both countries.

Domaines: Santé publique et épidémiologie; Biophysique [physics.bio-ph]

Davide Faranda, Tommaso Alberti. Modelling the second wave of COVID-19 infections in France and Italy via a Stochastic SEIR model 2. 2020. ⟨hal-02668318v1⟩