  With the present highly infectious dominant SARS-CoV-2 strain of B1.1.529 or
Omicron spreading around the globe, there is concern that the COVID-19 pandemic
will not end soon and that it will be a race against time until a more
contagious and virulent variant emerges. One of the most promising approaches
for preventing virus propagation is to maintain continuous high vaccination
efficacy among the population, thereby strengthening the population protective
effect and preventing the majority of infection in the vaccinated population,
as is known to occur with the Omicron variant frequently. Countries must
structure vaccination programs in accordance with their populations'
susceptibility to infection, optimizing vaccination efforts by delivering
vaccines progressively enough to protect the majority of the population. We
present a feasibility study proposal for maintaining optimal continuous
vaccination by assessing the susceptible population, the decline of vaccine
efficacy in the population, and advising booster dosage deployment to maintain
the population's protective efficacy through the use of a predictive model.
Numerous studies have been conducted in the direction of analyzing vaccine
utilization; however, very little study has been conducted to substantiate the
optimal deployment of booster dosage vaccination with the help of a predictive
model based on machine learning algorithms.
