Methods for cost-efficient, whole genome sequencing surveillance for enhanced detection of outbreaks in a hospital setting

Abstract

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 to expand 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 ten 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. Impact statement Whole genome sequencing (WGS) surveillance to confirm or refute suspected outbreaks of potential healthcare-associated infections (HAI) is a highly effective approach for outbreak detection. Since November 2021, we have conducted WGS surveillance in real-time through a program called the Enhanced Detection System for Hospital-Associated Transmission (EDS-HAT), to assist our hospital infection prevention and control (IP&C) team to identify and stop outbreaks. Our laboratory has successfully implemented real-time WGS surveillance of multiple pathogens in the hospital setting continuously for over four years. Our weekly workflow included identifying HAI pathogens and performing WGS, followed by bioinformatic analyses that included species confirmation, determination of sequence type, and genetic relatedness comparisons. Based on this information, transmission clusters were identified, and the electronic health record was reviewed to determine probable transmission routes. Finally, IP&C implemented appropriate interventions to mitigate the spread of infection. The focus of this manuscript is to provide the details of our laboratory and analytical methods, along with the cost associated with laboratory materials and staff salary, for successful implementation of real-time WGS surveillance. Data Summary The whole genome sequencing data generated in this study are deposited in the United States National Institutes of Health, National Library of Medicine ( https://www.ncbi.nlm.nih.gov/bioproject ), and are publicly available under BioProject accession PRJNA475751. All supporting data and protocols are provided within the article or through supplementary data files.

The authors' abstract, as published at the source. PLoS ONE, 2026 · DOI ↗