Methods for cost-efficient, whole genome sequencing surveillance for enhanced detection of outbreaks in a hospital setting
6 affiliations
- 1Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- 2Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- 3Department of Infectious Diseases and Microbiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- 4Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- 5Center for Evolutionary Biology and Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- 6Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
Abstract
Introduction: Outbreaks of healthcare-associated infections (HAI) result in substantial patient morbidity and mortality; mitigation efforts by infection prevention teams have the potential to curb outbreaks and prevent transmission to additional patients. The incorporation of whole genome sequencing (WGS) surveillance of suspected high-risk pathogens often identifies outbreaks that are not detected by traditional infection prevention methods and provides evidence for transmission. Our approach to real-time WGS surveillance, the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT), has 1) identified serious outbreaks that were otherwise undetected and 2) shown the potential to be cost saving. Methods: We describe our cost-efficient methods to perform WGS surveillance and data analysis of pathogens for institutions that are interested in expanding infection prevention surveillance. We provide an overview of the weekly workflow of EDS-HAT during two distinct phases over three years. Results: In an average week at our tertiary healthcare system, we sequenced 60 samples at a cost of less than $100 each during Phase 1, and 80 samples for less than $70 each in Phase 2, inclusive of laboratory reagents and staff salaries. The average turnaround time, from sample collection to reporting data to infection prevention, was nine days. Conclusions: Performing EDS-HAT in real-time can be both feasible and time-efficient. Providing such timely information to aid in outbreak detection could identify transmission events sooner and thus could increase patient safety.
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BibTeX
@article{waggle2026methods,
title = {{Methods for cost-efficient, whole genome sequencing surveillance for enhanced detection of outbreaks in a hospital setting}},
author = {Kady D. Waggle and Marissa Pacey Griffith and Alecia B. Rokes and Vatsala Rangachar Srinivasa and Erin M. Nawrocki and Deena Ereifej and Rose Patrick and Hunter Coyle and Shurmin Chaudhary and Nathan J. Raabe and Kathleen Shutt and Alexander J. Sundermann and Vaughn S. Cooper and Lee H. Harrison and Lora Lee Pless},
journal = {PLOS One},
year = {2026},
month = sep,
doi = {10.1371/journal.pone.0355550},
url = {https://doi.org/10.1371/journal.pone.0355550},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Methods for cost-efficient, whole genome sequencing surveillance for enhanced detection of outbreaks in a hospital setting
AU - Kady D. Waggle
AU - Marissa Pacey Griffith
AU - Alecia B. Rokes
AU - Vatsala Rangachar Srinivasa
AU - Erin M. Nawrocki
AU - Deena Ereifej
AU - Rose Patrick
AU - Hunter Coyle
AU - Shurmin Chaudhary
AU - Nathan J. Raabe
AU - Kathleen Shutt
AU - Alexander J. Sundermann
AU - Vaughn S. Cooper
AU - Lee H. Harrison
AU - Lora Lee Pless
PY - 2026
DA - 2026/09/01
JO - PLOS One
DO - 10.1371/journal.pone.0355550
UR - https://doi.org/10.1371/journal.pone.0355550
AB - Introduction: Outbreaks of healthcare-associated infections (HAI) result in substantial patient morbidity and mortality; mitigation efforts by infection prevention teams have the potential to curb outbreaks and prevent transmission to additional patients. The incorporation of whole genome sequencing (WGS) surveillance of suspected high-risk pathogens often identifies outbreaks that are not detected by traditional infection prevention methods and provides evidence for transmission. Our approach to real-time WGS surveillance, the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT), has 1) identified serious outbreaks that were otherwise undetected and 2) shown the potential to be cost saving. Methods: We describe our cost-efficient methods to perform WGS surveillance and data analysis of pathogens for institutions that are interested in expanding infection prevention surveillance. We provide an overview of the weekly workflow of EDS-HAT during two distinct phases over three years. Results: In an average week at our tertiary healthcare system, we sequenced 60 samples at a cost of less than $100 each during Phase 1, and 80 samples for less than $70 each in Phase 2, inclusive of laboratory reagents and staff salaries. The average turnaround time, from sample collection to reporting data to infection prevention, was nine days. Conclusions: Performing EDS-HAT in real-time can be both feasible and time-efficient. Providing such timely information to aid in outbreak detection could identify transmission events sooner and thus could increase patient safety.
SN - 1932-6203
ER -