(untitled) (The Review of Diabetic Studies, 2025)
Background Healthcare-associated infections (HAIs) represent a persistent and formidable challenge to global health security, significantly contributing to patient morbidity, mortality, and the escalation of healthcare costs. As antimicrobial resistance (AMR) accelerates, the precision of outbreak detection methodologies becomes paramount. Traditional epidemiological surveillance, reliant on temporal-spatial clustering and phenotypic typing methods such as pulsed-field gel electrophoresis (PFGE), often lacks the discriminatory power necessary to distinguish true transmission events from sporadic cases in real-time. This resolution gap frequently leads to delayed interventions, uncontained transmission, and the misallocation of infection prevention resources. Whole-genome sequencing (WGS) has emerged as a transformative technology, offering single-nucleotide resolution that can definitively link or exonerate pathogen isolates. This systematic review evaluates the efficacy, economic viability, and operational integration of real-time genomic epidemiology in the containment of nosocomial outbreaks. Methods A comprehensive review of the literature from 2015 to 2025 was conducted, targeting studies that implemented prospective or real-time WGS surveillance in hospital settings. The review prioritized data focusing on high-consequence pathogens, including methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococci (VRE), Clostridioides difficile, multidrug-resistant Gram-negative bacilli, and SARS-CoV-2. Outcomes of interest included outbreak detection rates, cessation of transmission following intervention, turnaround times (TAT), economic return on investment (ROI), and the elucidation of cryptic transmission pathways. Risk of bias was assessed utilizing the ROBINS-I and ROBINS-E tools to evaluate non-randomized intervention studies, ensuring a rigorous synthesis of the available evidence. Results The synthesis of data indicates a paradigm shift in infection control efficacy. Prospective WGS surveillance demonstrated a superior capacity to detect outbreaks compared to standard of care (SoC), with studies such as the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT) revealing that traditional methods miss a substantial proportion of transmission events. WGS surveillance was associated with a 95.6% cessation of transmission in intervened outbreaks and demonstrated a 3.2-fold return on investment through averted infections and the reduction of unnecessary bed closures. The technology proved particularly adept at identifying "cryptic" transmission routes—such as those mediated by asymptomatic carriers or environmental reservoirs—that defy conventional epidemiological logic. Furthermore, WGS provided critical "rule-out" capabilities, differentiating between relapse and reinfection in C. difficile cases and preventing futile investigations into temporally clustered but genetically unrelated infections. However, the review also identified significant barriers to widespread adoption, including the high costs of bioinformatic infrastructure, the need for specialized workforce training, and the logistical challenges of integrating genomic data into routine clinical microbiology workflows. Conclusions Real-time genomic epidemiology is not merely a refinement of existing tools but a fundamental restructuring of nosocomial surveillance. By transitioning from reactive investigation to prospective monitoring, healthcare institutions can achieve significant clinical and economic benefits. The successful integration of this technology requires a coordinated effort to standardize bioinformatic pipelines, enhance laboratory capacity, and foster regional data-sharing networks. As sequencing costs decline and automation improves, WGS is poised to become the new standard of care for infection prevention, offering a robust defense against the spreading threat of hospital-acquired pathogens.