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We investigated whether and how infection prevention programs monitor for health disparities as part of healthcare-associated infection (HAI) surveillance through a survey of healthcare epidemiology leaders. Most facilities are not assessing for disparities in HAI rates. Professional society and national guidance should focus on addressing this gap.
Two independent temporal-spatial clusters of hospital-onset Rhizopus infections were evaluated using whole-genome sequencing (WGS). Phylogenetic analysis confirmed that isolates within each cluster were unrelated despite epidemiological suspicion of outbreaks. The ITS1 region alone was insufficient for accurate analysis. WGS has utility for rapid rule-out of suspected nosocomial Rhizopus outbreaks.
Methicillin-resistant Staphylococcus aureus (MRSA) is an important pathogen in neonatal intensive care units (NICU) that confers significant morbidity and mortality.
Improving our understanding of MRSA transmission dynamics, especially among high-risk patients, is an infection prevention priority.
We investigated a cluster of clinical MRSA cases in the NICU using a combination of epidemiologic review and whole-genome sequencing (WGS) of isolates from clinical and surveillance cultures obtained from patients and healthcare personnel (HCP).
Phylogenetic analysis identified 2 genetically distinct phylogenetic clades and revealed multiple silent-transmission events between HCP and infants. The predominant outbreak strain harbored multiple virulence factors. Epidemiologic investigation and genomic analysis identified a HCP colonized with the dominant MRSA outbreak strain who cared for most NICU patients who were infected or colonized with the same strain, including 1 NICU patient with severe infection 7 months before the described outbreak. These results guided implementation of infection prevention interventions that prevented further transmission events.
Silent transmission of MRSA between HCP and NICU patients likely contributed to a NICU outbreak involving a virulent MRSA strain. WGS enabled data-driven decision making to inform implementation of infection control policies that mitigated the outbreak. Prospective WGS coupled with epidemiologic analysis can be used to detect transmission events and prompt early implementation of control strategies.