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Real-time detection of Staphylococcus aureus transmission in hospitals

Published online by Cambridge University Press:  24 September 2025

Kristine Rabii
Affiliation:
NYU Langone Health
Courtney Takats
Affiliation:
NYU Langone Health
Gregory Putzel
Affiliation:
NYU Langone
Alice Tillman
Affiliation:
NYU Langone
Magdalena Podkowik
Affiliation:
NYU School of Medicine
Julia Shenderovich
Affiliation:
N/A
Natalia Argüelles
Affiliation:
N/A
Anusha Srivastava
Affiliation:
NYU Langone Department of Microbiology
Alejandro Pironti
Affiliation:
NYU Langone Health
Sarah Hochman
Affiliation:
NYU Langone Health
Audrey Renson
Affiliation:
NYU Langone Medical Center
Bo Shopsin
Affiliation:
NYU Langone Medical Center

Abstract

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Genomic surveillance of Staphylococcus aureus in hospitals usually focuses on clinical infections, missing transmissions from asymptomatic carriers and delaying detection and timely intervention. To address the issue, we performed whole-genome sequencing (WGS) on over 5,000 S. aureus isolates obtained from colonization screens at admission, in addition to standard clinical cultures, at two interconnected urban hospitals. By integrating genomic data with timestamped location information, we identified hundreds of transmissions missed by standard methods. However, nearly 70% of transmissions were detected during readmission after the index case had been discharged. This finding indicates that even with dense genomic sampling, real-time detection remains challenging due to asymptomatic carriage. Therefore, effective monitoring of nosocomial S. aureus transmission will likely require WGS and colonization sampling at both admission and discharge. The data also highlight patient- and strain-specific factors, including methicillin resistance, as predictors of S. aureus spread, which may enable cost-effective, targeted sequencing surveillance strategies.

Information

Type
Molecular Epidemiology
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America