Analysis of COVID-19 Disease Transmission: A Blended Appraisal of Quarantine and Vaccination Effects in Bangladesh

A precise understanding of infectious disease transmission patterns is critical for developing effective control methods and reducing the negative effect on public health. In this study, we introduce SEQIRVP, a unique mathematical epidemic model that incorporates the effects of quarantine, vaccination and death by dividing the population into distinct epidemiological compartments. A full stability analysis is performed in which equilibrium conditions are systematically analyzed and the calculation of basic reproduction number to determine whether the disease will persist or decline. Numerical simulations are used to study how the disease spreads across different groups in the population. Furthermore, a sensitivity analysis is performed to identify which parameters most influence the outbreak's dynamics. Using COVID-19 data from Bangladesh, we simulate the model in MATLAB to see the disease progression under varying vaccination rates, quarantine effectiveness, and healthcare interventions. The results indicate that while vaccination alone may not lead to an immediate reduction in transmission, its combination with vaccination and quarantine and enhanced healthcare significantly lowers both transmission rates and mortality. This study strengthens the importance of strategic epidemic control and provides a strong foundation for influencing public health policy, enhancing social resilience, and ensuring economic stability.