Mathematical modelling to predict COVID-19 dynamics

In the context of 2019 coronavirus disease (COVID-19), considerable attention has been paid to mathematical models for predicting country- or region-specific future pandemic developments. In this project, we will discuss the different modelling approach, different reproduction numbers and their approximations, different equilibrium points and their asymptotic stability properties and interpret these mathematical terms.
Next, we will consider as an example an SVICDR model, i.e. an ODE system, that includes a susceptible, an all-or-nothing vaccinated, an infected, an intensive care, a deceased, and a recovered compartment.
We will take taking into account recent data for the pandemic from a country the students selected, an exponential increasing vaccination rate in the considered time window and trigonometric contact and quarantine rate functions. For the calibration process and the numerical solution of the ODE systems we will use a standard solver (ODE45 in Matlab/Octave)  and as an alternative a model-specific non-standard finite difference (NSFD), that preserves the positivity of solutions and yields the correct asymptotic behaviour. The obtained predictions will (hopefully) underline the usability of the proposed method.

Instructor: Matthias Ehrhardt (Wuppertal University, DE)


  • Domenico Di Grazia, University of Verona
  • Nikolina Miholjcic, University of Novi Sad
  • Sara Heikkinen, LUT University
  • Roozbeh Jozeranjbar, University of Verona
  • Luka Đurović, University of Novi Sad


Room Messedaglia, Veronetta – Chiostro Santa Maria delle Vittorie, Lungadige Porta Vittoria, 37129 Verona