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Advances in Difference Equations
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Advances in Difference Equations
Article
License: CC BY
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Advances in Difference Equations
Article . 2021
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Modeling bacterial resistance to antibiotics: bacterial conjugation and drug effects

Authors: Pirommas Techitnutsarut; Farida Chamchod;

Modeling bacterial resistance to antibiotics: bacterial conjugation and drug effects

Abstract

AbstractAntibiotic resistance is a major burden in many hospital settings as it drastically reduces the successful probability of treating bacterial infections. Generally, resistance is associated with bacterial fitness reduction and selection pressure from antibiotic usage. Here, we investigate the effects of bacterial conjugation, plasmid loss, and drug responses on the population dynamics of sensitive and resistant bacteria by using a mathematical model. Two types of drugs are considered here: antibiotic M that kills only sensitive bacteria and antibiotic N that kills both bacteria. Our results highlight that larger dose and longer dosing interval of antibiotic M may result in the higher prevalence of resistant bacteria while they do the opposite for antibiotic N. When delays in administering initial and second doses are incorporated, the results demonstrate that the delays may lead to the higher prevalence of resistant bacteria when antibiotic M or N is administered with the longer time of bacteria remaining at the lower prevalence of the latter. Our results highlight that switching antibiotic agents during a treatment course and different bacterial strain characteristics result in a significant impact on the prevalence of resistant bacteria.

Related Organizations
Keywords

Bacterial conjugation, Therapeutic strategies, QA1-939, Mathematical modeling, Antimicrobial resistance, Mathematics

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    8
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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
gold