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Testing the Role of Multicopy Plasmids in the Evolution of Antibiotic Resistance

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Does Antibiotic Resistance Evolve in Hospitals?

Anna Seigal¹, Portia Mira², Bernd Sturmfels³

¹Department of Mathematics, University of California, Berkeley, Berkeley, CA, USA. seigal@berkeley.edu.

Bulletin of Mathematical Biology

|December 8, 2016

Summary

Hospital antibiotic resistance trends are not solely driven by the hospital environment. A new statistical test, the Nosocomial Evolution of Resistance Detector (NERD), reveals resistance evolution is complex, with only three antibiotics showing significant hospital-specific trends.

Keywords:

Antibiotic resistance Infection control Negative binomial distribution Nosocomial outbreaks

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Area of Science:

Microbiology
Epidemiology
Statistical Modeling

Background:

Nosocomial bacterial outbreaks are common, leading to the assumption that antibiotic resistance primarily evolves within hospital settings due to high antibiotic use.
Understanding the specific drivers of antibiotic resistance evolution in hospitals is crucial for effective infection control and antibiotic stewardship.

Purpose of the Study:

To investigate whether antibiotic resistance phenotypes of bacteria evolve significantly within a community hospital environment over time.
To develop and validate a statistical method for detecting trends in antibiotic resistance evolution in hospitals.

Main Methods:

Analysis of bacterial resistance phenotypes from patient isolates over a 2.5-year period at a community hospital.
Development of a hospital transmission model and a statistical hypothesis test, the Nosocomial Evolution of Resistance Detector (NERD), to assess resistance trends.
Application of the NERD method to 16 different antibiotics, performing 16 hypothesis tests.

Main Results:

Graphical model analysis indicated no association between resistance and patient information, except for time of arrival, suggesting focus on time-course data.
The NERD method found no significant hospital-specific effect on resistance evolution for 13 out of 16 antibiotics studied.
Significant trends were observed for cefepime, ceftazidime, and gentamicin, with ceftazidime showing a significant decrease in resistance after adjusting for multiple hypotheses.

Conclusions:

The hospital environment is not the sole determinant of antibiotic resistance evolution; it is part of a larger picture.
The NERD tool can help hospital staff monitor antibiotic resistance trends, detect clonal outbreaks, and evaluate interventions.
Specific antibiotics like cefepime, ceftazidime, and gentamicin warrant closer monitoring and careful management within hospital practices due to observed resistance trends.