When challenged with foreign macromolecules, the humoral immune system produces an efficient response of antibody production (Skerra, 2003). However, the human immunodeficiency virus (HIV) evades CD4 T helper cells, the central component of generating neutralizing antibodies that orchestrate specific responses to a wide range of viruses (Wodarz & Nowak, 2002). When understanding the dynamic between HIV pathogenesis and immune system response, verbal reasoning proves insufficient because of the inherent complexity of the interactions involved. In particular, verbal reasoning may overlook subtle nuances, intricate feedback loops, and nonlinear relationships that are fundamental to comprehending the progression of HIV infection and the host immune response. Thus, mathematical models have proven useful in understanding how virus-antibody dynamics alter the course of HIV infection by capturing a set of assumptions and deducing logical conclusions through altering key parameters. Many studies have utilized chimeric simian-human immunodeficiency virus (SHIV) as a comparable animal model for HIV pathogenesis (Ciupe et al., 2018). It has been found that broadly neutralizing monoclonal antibodies (bnMAbs) have exceptional in vitro potency against a high-dosage mucosal HIV challenge, but the strength of protection in both high-dose and low-dose challenges is dependent upon the ratio between concentration of bnMAbs and size of the viral challenge (Moldt et al., 2012; Hessell et al., 2009). In simpler terms, the effectiveness of vaccines relies heavily on the balance between the amount and strength of antibodies produced by the immune system and the size of the virus challenge; if there are not enough strong antibodies to fight off a large amount of virus, the vaccine may not be as effective. Therefore, understanding the concentration and avidity of antibodies in relation to the size of viral inoculum proves important in developing vaccines that offer robust protection against HIV.