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

Abstract

Vaccination is the most effective measure for preventing infectious diseases. Developing an appropriate mathematical model facilitates quantitative research into the activation of adaptive immune responses in the human body by vaccines, thereby providing better guidance for vaccine development. In this study, we have constructed a novel mathematical model to simulate the dynamics of antibody levels following vaccination. Based on principles from immunology, our model provides a concise and accurate representation of the kinetics of antibody response. We have compared the 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 model explains the crucial role of booster shots in enhancing IgG antibody levels and provides a detailed discussion on the advantages and disadvantages of different vaccine types. From a mathematical standpoint, our model systematically 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 model contributes to the understanding of vaccine design and its application by explaining various phenomena and providing positive guidance in comprehending the interactions between antibodies and antigenic substances during the immune process.