A Mathematical Model Simulating the Adaptive Immune Response in Various Vaccines and Vaccination Strategies

Abstract

Vaccination has been widely recognized as an effective measure for preventing infectious diseases. To facilitate quantitative research into the activation of adaptive immune responses in the human body by vaccines, it is important to develop an appropriate mathematical model, which can provide valuable guidance for vaccine development. In this study, we constructed a novel mathematical model to simulate the dynamics of antibody levels following vaccination, based on principles from immunology. Our model offers a concise and accurate representation of the kinetics of antibody response. We conducted a comparative analysis of antibody dynamics within the body after administering several common vaccines, including traditional inactivated vaccines, mRNA vaccines, and future attenuated vaccines based on defective interfering viral particles (DVG). Our findings suggest that booster shots play a crucial role in enhancing IgG antibody levels, and we provide a detailed discussion on the advantages and disadvantages of different vaccine types. From a mathematical standpoint, our model proposes four essential approaches to guide vaccine design: enhancing antigenic T-cell immunogenicity, directing the production of high-affinity antibodies, reducing the rate of IgG decay, and lowering the peak level of vaccine antigen-antibody complexes. Our study contributes to the understanding of vaccine design and its application by explaining various phenomena and providing guidance in comprehending the interactions between antibodies and antigens during the immune process.