Abstract

Understanding how antibiotic use drives resistance is crucial for guiding effective strategies to limit the spread of resistance, but the use–resistance relationship across pathogens and antibiotics remains unclear. We applied sinusoidal models to evaluate the seasonal use–resistance relationship across 3 species (Staphylococcus aureus, Escherichia coli, and Klebsiella pneumoniae) and 5 antibiotic classes (penicillins, macrolides, quinolones, tetracyclines, and nitrofurans) in Boston, Massachusetts. Outpatient use of all 5 classes and resistance in inpatient and outpatient isolates in 9 of 15 species–antibiotic combinations showed statistically significant amplitudes of seasonality (false discovery rate (FDR) < 0.05). While seasonal peaks in use varied by class, resistance in all 9 species–antibiotic combinations peaked in the winter and spring. The correlations between seasonal use and resistance thus varied widely, with resistance to all antibiotic classes being most positively correlated with use of the winter peaking classes (penicillins and macrolides). These findings challenge the simple model of antibiotic use independently selecting for resistance and suggest that stewardship strategies will not be equally effective across all species and antibiotics. Rather, seasonal selection for resistance across multiple antibiotic classes may be dominated by use of the most highly prescribed antibiotic classes, penicillins and macrolides.

Highlights

  • Antibiotic resistance is a growing threat to society, with important public health [1] and economic consequences [2]

  • Macrolide and penicillin use peaked in the winter, around late January and early February, respectively

  • We found that resistance to all antibiotics, including those with summer and biannual peaks in use, best correlated temporally with use of winter peaking antibiotics—penicillins and macrolides—at a 0- to 1-month lag

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Summary

Introduction

Antibiotic resistance is a growing threat to society, with important public health [1] and economic consequences [2]. These findings reflect the complexity of the antibiotic use–resistance relationship, underscoring the need to characterize this relationship across a wide range of bacterial species and antibiotics and identify factors that influence the strength of this association

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