Infectious disease such as COVID-19 poses a considerable threat to public health when a pandemic strain emerges. Constructing a reliable mathematical model helps us quantitatively explain the kinetic characteristics of antibody-virus interactions, which could provide a reasonable prediction toward many sensitive concerns faced by the public, such as how to calculate protection time provided by the specific vaccine. A novel and robust model is developed to integrate antibody dynamics with virus dynamics in the host body. Our model is based on a comprehensive understanding of immunology principles rather than a simple data-fitting attempt by arbitrarily mathematical function selection. The physical-based mechanism would bring this model more reliable and broader prediction performance. This model gives quantitative insights between antibody dynamics and virus loading in the host body. Based on this model, we can estimate the antibody dynamic parameters with high fidelity. We could solve lots of critical problems, such as the calculation of vaccine protection time. We can also explain lots of mysterious phenomena such as antibody inferences, self-reinfection, chronic infection, etc. We suggest the best strategy in prolonging the vaccine protection time is not repeated inoculation but a directed induction of fast binding antibodies. Eventually, it will also inform the future construction of the mathematical model and help us fight against those infectious diseases.