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.
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.