Shahirah Atikah Binti Mohamad Husnin creator author. text my 2024 2024 monographic eng xii, 137 pages : illustrations (some color) ; 30 cm. + 1 CD-ROM Due to the ongoing Coronavirus Disease 2019 (COVID-19) endemic, proper mathematical modelling to capture disease transmission is an essential tool for developing control methods and identifying driving factors in disease dynamics. However, COVID-19 modelling is not a one-size-fits-all approach, as it varies depending on many factors such as vaccination, intervention measures, social distancing and population. In this study, an improved mathematical model was proposed with time-dependent epidemiological parameters for COVID-19 by considering the factors of lockdown and vaccination for a university in Malaysia. The model is based on Susceptible-Infected-Recovered-Dead (SIRD) framework and in the form of a set of Ordinary Differential Equations. The model development involved three stages. It begins with the simplest setting of the model which used constant epidemiological parameters known as Model I that neglect the vaccination factor. Then, the model's complexity was increased to Model II, utilizing the time-dependent epidemiological parameters. The final stage is Model III which used time-dependent epidemiological parameters and included the vaccination factor. The models were numerically solved using the Runge Kutta fourth order method (RK4) and parameter fitting techniques namely Pattern Search and Nelder-Mead Simplex algorithm embedded in MATLAB software. In addition, a sensitivity analysis of the parameters was carried out to determine the relative influence of the model parameters on disease transmissions. To validate the results, a comparison between the model and the actual data was carried out and measured using mean absolute percentage error (MAPE) and root mean squared error (RMSE). As a result, Model III was adequately fitted to the actual data. In addition, a MATLAB-based graphical user interface (GUI) was developed to provide a better insight to the effectiveness of the vaccine in a population. The GUI is able to provide a rough percentage of vaccine effectiveness, as indicated by the good agreement of the projection and the actual data for the university. This research offers healthcare personnel a validated mathematical model along with tools for analysis and visualization which enables to make data-driven decisions and effectively manage the impact of COVID-19 within the university population. In future work, the developed mathematical model can be extended to incorporate the diversity of available vaccines, considering their varying efficacies and mechanisms of action. specialized Shahirah Atikah Binti Mohamad Husnin Centre for Mathematical Sciences Thesis (Master of Science (Mathematics)) -- Universiti Malaysia Pahang – 2024 Includes bibliographical references Centre for Mathematical Sciences Dissertations Universities and colleges Dissertations Theses Dissertations THE0009844 (Local) UMPSA 240524 20251125110857.0 eng