Date of Award


Document Type


Degree Name

Bachelor of Science



First Advisor

Dr. Lester F. Caudill, Jr


The rise of antibiotic resistance has created a significant burden on healthcare systems around the world. Antibiotic resistance arises from the increased use of antibiotic drugs and antimicrobial agents, which kill susceptible bacterial strains, but have little effect on strains that have a mutation allowing them to survive antibiotic treatment, defined as “resistant” strains. With no non-resistant bacteria to compete for resources, the resistant bacteria thrives in this environment, continuing to reproduce and infect the host with an infection that does not respond to traditional antibiotic treatment.

A number of strategies have been proposed to tackle the problem of antibiotic resistance, such as replacing broad-spectrum antibiotic (those that are generalized to kill non-specific strains of bacteria) treatments with pathogen-specific antibiotics and immunotherapies. However, testing these strategies with clinical experiments presents a significant time and financial burden, and are limited by ethical considerations for the human test subjects. Mathematical models, and their implementation as computer simulation tools, can provide researchers with the means to simulate controlled experiments designed to assess the effectiveness of these strategies.