Author(s)

Chongrong Tan

Corresponding Author

Chongrong Tan

Abstract

This study systematically analyzed the influencing factors of Pfizer vaccine immunogenicity through Bayesian method. Data collection covers multiple public databases, and the accuracy of the analysis is ensured through data cleaning and preprocessing. We first constructed a Bayesian network model to identify age, gender, health status and vaccine dose as key factors affecting immune response. Subsequently, the specific effects of these factors on immune response were quantified through a Bayesian regression model. The results showed that the older the age, the slightly lower the immune response; males had a slightly higher level of response than females; the healthy person had a higher one; and high-dose vaccines, to a great extent, enhanced the level of immune responses. These conclusions provide a scientific basis for vaccination strategy optimization and a methodological reference for other vaccine immunogenicity studies.

Keywords

Pfizer vaccine, immunogenicity, Bayesian analysis, influencing factors, data processing