Mathematical Epidemiology : A study of the COVID-19 pandemic using compartmental models

Abstract: The sudden occurrence of a global pandemic brought an imbalance to each of our ways of living. Prediction of the COVID-19 progresses is crucial for governments and is deemed essential for the healthcare industry to solve which indicates how mathematical modelling becomes in dire need of use This master thesis aims to use well-established compartmental models like SEIR and modifications of SEIR to simulate scenarios like introducing different restrictions (i.e. isolation of elders, closing schools) by first fitting parameters of the SEIR models to official data. An estimation of the true calculated number of COVID-19 cases in Denmark, Germany, Spain, Sweden and the United Kingdom is made by comparing the number of deceased cases with the number of confirmed cases between the first and second waves of the virus spread. A simulation showing the effect of the British variant B.1.1.7 had on the Swedish third wave is also made. The estimation made from comparing the first and second waves shows that the number of confirmed cases underestimates the true calculated number of cases with a factor between 7.57 and 36.5 depending on the country in consideration. The restriction simulations show that isolating elders decreases the number of elders that contract the disease but no significant change is seen in the total number of infected individuals. When restrictions like closing schools are simulated the total number of infected decreases significantly but the change in decreased cases among elders is not that high. The simulations also show that the British mutation B.1.1.7 with its increased infectiousness is responsible for the third wave of the virus spread. Without the existence of the British mutation, the Swedish third wave of virus spread would have been less severe.