Objectives In late 2019, the novel coronavirus, known as COVID-19, emerged in Wuhan, China, and rapidly spread worldwide, including in Germany. To mitigate the pandemic’s impact, various strategies, including vaccination and non-pharmaceutical interventions, have been implemented. However, the emergence of new, highly infectious SARS-CoV-2 strains has become the primary driving force behind the disease’s spread. Mathematical models, such as deterministic compartmental models, are essential for estimating contagion rates in different scenarios and predicting the pandemic’s behavior. Methods In this study, we present a novel model that incorporates vaccination dynamics, the three most prevalent virus strains (wild-type, alpha, and delta), infected individuals’ detection status, and pre-symptomatic transmission to represent the pandemic’s course in Germany from March 2, 2020, to August 17, 2021. Results By analyzing the behavior of the German population over 534 days and 25 time intervals, we estimated various parameters, including transmission, recovery, mortality, and detection. Furthermore, we conducted an alternative analysis of vaccination scenarios under the same interval conditions, emphasizing the importance of vaccination administration and awareness. Conclusions Our 534-day analysis provides policymakers with a range of circumstances and parameters that can be used to simulate future scenarios. The proposed model can also be used to make predictions and inform policy decisions related to pandemic control in Germany and beyond.