Modeling and System Identification of Epidemics with Application to COVID-19

Master Thesis Defense

Naya Baslan

Monday, June 28, 2021, 10:00 - 11:00


Abtract of the thesis: In the end of 2019, a novel coronavirus, the SARS-COV-2 started a global pandemic crisis. The virus caused respiratory infections and its transmission rate was very high that it forced lock down policies to be implemented throughout the world in an attempt to keep it under control. Statisticians and mathematicians have been working diligently on modeling the spread of the virus and trying to predict its future progression. In this master’s thesis, we do model fitting based on publicly available COVID-19 data to study the dynamics of the transmission and mortality of the virus. We use the deterministic SIRD model, which divides the population into four compartments: Susceptible (S), Infected (I), Recovered (R) and Dead (D). Furthermore, we quantify the mortality rate of the disease by using standard methods such as the Case fatality Ratio (CFR) and compare
our results to similar research. Since the probability of dying from the disease increases with age, we use an age-stratified version of the SIRD which includes data based on the age distribution of the German population.
Meeting-ID: 627 9173 7415
Password: syscop2021