A0974
Title: Dynamical modelling of COVID-19 pandemic
Authors: Francoise Anne Kemp - University of Luxembourg (Luxembourg) [presenting]
Daniele Proverbio - University of Luxembourg (Luxembourg)
Atte Aalto - Luxembourg Center for Systems Biomedicine (Luxembourg)
Christophe Ley - University of Luxembourg (Luxembourg)
Jorge Goncalves - Luxembourg Center for Systems Biomedicine (Luxembourg)
Alexander Skupin - Luxembourg Center for Systems Biomedicine (Luxembourg)
Stefano Magni - (Luxembourg)
Abstract: Worldwide 488,532,505 confirmed cases and 6,144,226 dead people have been identified to be infected with SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) by 1st April 2022. COVID-19 is a new strain of coronavirus SARS-COV-2 (severe acute respiratory syndrome coronavirus 2). The first outbreak was reported in December 2019 in Wuhan, China. COVID-19 is spreading across the globe and was declared as a pandemic by WHO in March 2020. Epidemiological modelling and forecasting of the evolution of the epidemic represent a useful tool to assist in designing better non-pharmaceutical measures and prepare for the stress on healthcare systems. We develop a new compartment-model based on Susceptible-Exposed-Infectious-Removed (SEIR) model and described by ordinary differential equations to simulate the time evolution of the number of positive cases, the number of people entering hospital and intensive care unit (ICU) and of deaths. The model is fitted to Luxembourgish time-series data and provides fruitful insights into the dynamics behind this pandemic and the evolution of immunity in the society. Overall, we show that mathematical modelling represents a powerful tool to test mechanistic hypotheses and to identify underlying principles of complex biological systems.
