Efficacy of vaccine and face mask in a COVID-19 enlarged SEIAQR model

Abstract

As a result of its rapid spread throughout the world on a huge scale in a very short period of time, the current COVID-19 infection has triggered a global emergency scenario. Vaccination and antiviral medicine are not available, however, for this particular virus. The question of how to control this pandemic is currently a major global concern at the present time. India, on the other hand, is a country with a high population density, and the COVID-19 infection sickness has been active from the first day of March 2020. The rate of human to human social contact in India is extremely high as a result of the country's dense population. As a result, controlling the COVID-19 pandemic at an early stage is a very critical and difficult matter for India. Mathematical models are used to investigate the dynamics of the disease, identify the characteristics that are important, and determine the most effective prevention techniques for reducing the magnitude of outbreaks. In this study, we present an improved SEIAQR mathematical model and conduct an analysis of it in order to better understand the transmission dynamics of the COVID-19 pandemic outbreak in India. It is subdivided into nine compartmental classifications, which are as follows: susceptible (S), exposed (E), symptomatically infected (I), asymptomatically infected (A), quarantined (Q), recovered (R), hospitalized (H), died (D), and vaccinated (V). The fundamental reproduction number of the suggested model, designated as R (COVID-19), was computed using the next-generation matrix technique, which was developed by the researchers. Face masks and vaccines have also been proved to be effective in reducing viral transmission, which has been demonstrated to be substantial. In addition, using MATLAB-7.0, certain effective preventive actions and their influence on the environment were investigated numerically and graphically.