{
  "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.",
  "abstract_shown": true,
  "affiliations": [
    "Microbial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America",
    "Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America",
    "Department of Infectious Diseases and Microbiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America",
    "Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America",
    "Center for Evolutionary Biology and Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America",
    "Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America"
  ],
  "article_type": "Lab Protocol",
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  "author_total": 15,
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      "name": "Kady D. Waggle"
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      "name": "Vatsala Rangachar Srinivasa"
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      "name": "Erin M. Nawrocki"
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      "name": "Deena Ereifej"
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    {
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    {
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    {
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    {
      "name": "Kathleen Shutt"
    },
    {
      "name": "Alexander J. Sundermann"
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    {
      "name": "Vaughn S. Cooper"
    },
    {
      "name": "Lee H. Harrison"
    },
    {
      "name": "Lora Lee Pless"
    }
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  "bibtex": "https://research.draconitic.com/paper/1n0wr3qrjvh9n.bib",
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  "doi": "10.1371/journal.pone.0355550",
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  "pmcid": null,
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  "published": "2026-09-01",
  "publisher": "Public Library of Science",
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  "title": "Methods for cost-efficient, whole genome sequencing surveillance for enhanced detection of outbreaks in a hospital setting",
  "title_text": "Methods for cost-efficient, whole genome sequencing surveillance for enhanced detection of outbreaks in a hospital setting",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:02Z",
  "url": "https://research.draconitic.com/paper/1n0wr3qrjvh9n",
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