Analyzing the stability of the SEIR model under various vaccination scenarios and coverage rates

The “SEIR (S-Susceptible, E-Exposed, I-Infectious, R-Recovered)” epidemic model which is used to represent the population as ‘Susceptible, Exposed, Infectious, and Recovered individuals’ occupies a crucial place in epidemiology. Through the vaccination campaigns gaining more size in addressing the global health issues, the modelling of stability under different scenarios of vaccination campaigns and coverage rates has become crucial. The focus of this study is on the complex homeostatic process between the continuation and extinction of a disease in the SEIR model. It attempts to measure the lowest vaccination coverage needed for a disease stability through trying different vaccination methods. Even though outbreaks can be contained in such a case, they can either be prevented or limited and controlled. The role of main parameters, like transfer rates, recovery times, and vaccine immunity loss, will be examined to see their effect on the stability threshold. The scope of this investigation is not limited to just defining the minimal coverage threshold. Against the background of mutations, interaction with next pathogen, it focuses on the quantification of modelling methods as either vaccination strategies, mixture models or their combination influence the model stability. The goal of the study is to illustrate how incomprehensible elements mentioned above indicate a more profound and comprehensive view of the connection between vaccination methods and control of chronic diseases. Such results of the study ensure that the health policy makers may make these decisions based on factual information. It can be used to determine the different vaccination effects on disease equilibrium. This prediction can help to direct optimal resource allocation, identify the risks of resurgence, and ultimately guide efforts for achieving sustainable disease control through effective vaccination strategies.