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

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 because HAIs are expensive to treat and WGS has become relatively inexpensive. Methods We describe a cost-efficient method to perform WGS surveillance and data analysis of pathogens for hospitals that are interested in incorporating WGS surveillance. We provide an overview of the weekly workflow of EDS-HAT, discussing both the laboratory and bioinformatics methods utilized, as well as the costs associated with performing these methods. Results In an average week at our tertiary healthcare system, we sequenced 48 samples at a cost of less than $100 per sample, inclusive of laboratory reagents and staff salaries. The average turnaround time, from sample collection to data reporting to the infection prevention and control team, was ten days. Conclusions Our findings demonstrate that performing EDS-HAT in real-time can be both affordable and time-efficient. Providing such timely information to aid in outbreak investigations can identify transmission events sooner and thus 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 been conducting 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. To our knowledge, our laboratory is the only group in the United States that has successfully implemented real-time WGS surveillance of multiple pathogens in the hospital setting. Our weekly workflow includes identifying HAI pathogens and performing WGS, followed by a variety of bioinformatic analyses that include species confirmation, determination of sequence type, and genetic relatedness comparisons. Based on this information, transmission clusters are identified, and the electronic health record is reviewed to determine probable transmission routes. Finally, IP&C implements appropriate interventions to mitigate the spread of infection. We detail the laboratory and analytical methods, along with the cost associated for laboratory materials and staff salary, for successful implementation of WGS surveillance in real-time establishing EDS-HAT as a unique and effective tool to detect HAI outbreaks. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by the National Institutes of Health (grant numbers R01AI127472 and R21AI109459). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The University of Pittsburgh Institutional Review Board provided ethics approval for EDS-HAT (Protocol: STUDY21040126). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as [ClinicalTrials.gov][1]. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors. [1]: http://ClinicalTrials.gov