Authors : Pranavi Rohit

Volume/Issue : Volume 8 - 2023, Issue 11 - November

Google Scholar : https://tinyurl.com/4xzp8bus

Scribd : https://tinyurl.com/ycxx285e

DOI : https://doi.org/10.5281/zenodo.10259116

Abstract : Antibiotic resistance poses a critical global health threat as bacteria evolve to withstand antibiotics. Apart from severely impacting individuals, often patients of antibiotic-resistant diseases, antibiotic resistance also uniquely affects communities given their relation to wastewater systems. This impact is particularly noteworthy in connection to wastewater systems, which remain integral to urban areas, where the purification of wastewater is essential. Unfortunately, these systems are acknowledged as notable reservoirs for antibiotic- resistant bacterial growth. The potential entry of a resistant pathogen into the community post-wastewater treatment can spark outbreaks, impacting thousands within a city. Recognizing the urgency to comprehend antibiotic resistance emergence in detail and work towards prevention, this study employs agent-based modeling. This approach is crucial in light of the challenges associated with collecting real-world data, including time, expense, and logistical constraints. The developed model provides valuable insights into bacterial population dynamics and the mechanisms fueling antibiotic resistance, encompassing phenomena such as horizontal gene transfer and chromosomal mutations. Multiple simulations conducted with the model confirmed previous findings and uncovered insights into the impact of bacteria population sizes at varying antibiotic concentrations. These insights have the potential to extend to applications in the real world, including added filtration systems and better legislature around the disposal and usage of antibiotics.

Keywords : Antibiotic Resistance, Agent-based Modeling, Wastewater Systems.