Epidemiological predictive modelling of COVID-19 spread

Abstract

Since the outbreak of new coronavirus COVID-19,measures for ending the global pandemic such as social distancing and contact tracing have been proposed worldwide. We propose a SEIRD model to predict the development of epidemic,which can contribute to effective planning to control it. Based on official statistical data for Belgium,we calculated the key parameters and forward them to the epidemiological model which will predict the number of infected,dead and recovered people. SEIRD model is a compartmental epidemiological model with included components - susceptible,exposed,infected (infected group is divided into three groups - mild,severe and critical),recovered,dead. Predicted (simulated) and official curves show a good match,meaning that the model is achieving promising results. A prognostic model could help us predict epidemic peaks. In that way,we could react in a timely manner by introducing new or tightening existing measures before the health system is overloaded.