Abstract
Antibiotic resistance remains one of the most critical challenges in global public health. Finding effective remedies requires an understanding of how resistance arises and spreads, as bacteria evolve to withstand the antibiotic intended to kill them. In this study, we simulate the growth and adaptation of bacterial populations in response to antibiotic exposure using a computational model. Both antibiotic-sensitive and antibiotic-resistant bacteria are the main subjects of the model. We investigate how these variables affect the survival and domination of resistant strains by altering variables such as the starting number of resistant bacteria, the antibiotic’s potency, and the bacterial growth rates. Our results demonstrate that, particularly when antibiotics are employed, even a few resistant bacteria can eventually take over the population. This emphasizes how crucial it is to use antibiotics sparingly and the necessity of developing plans to prevent resistance from spreading. Additionally, the model offers an adaptable instrument for researching the evolution of resistance, which may aid in directing future initiatives to counter this escalating danger.