Prolonged silent carriage, genomic virulence potential and transmission between staff and patients characterize a neonatal intensive care unit (NICU) outbreak of methicillin-resistant Staphylococcus aureus (MRSA)

Author:

Madera SharlineORCID,McNeil Nicole,Serpa Paula Hayakawa,Kamm JackORCID,Pak Christy,Caughell Carolyn,Nichols Amy,Dynerman David,Li Lucy M.ORCID,Sanchez-Guerrero Estella,Phelps Maira S.,Detweiler Angela M.,Neff Norma,Reyes Helen,Miller Steve A.,Yokoe Deborah S.,DeRisi Joseph L.,Ramirez-Avila Lynn,Langelier Charles R.ORCID

Abstract

AbstractBackground:Methicillin-resistant Staphylococcus aureus (MRSA) is an important pathogen in neonatal intensive care units (NICU) that confers significant morbidity and mortality.Objective:Improving our understanding of MRSA transmission dynamics, especially among high-risk patients, is an infection prevention priority.Methods: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).Results: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.Conclusions: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.

Publisher

Cambridge University Press (CUP)

Subject

Infectious Diseases,Microbiology (medical),Epidemiology

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