Candida auris is an emerging multidrug-resistant fungal pathogen. Since first reported in 2009, C. auris has caused healthcare outbreaks around the world, often involving high mortality. Identification of C. auris has been a major challenge as many common conventional laboratory methods cannot accurately detect it. Early detection and implementation of infection control practices can prevent its spread. The aim of this review is to describe recommendations for the detection and control of C. auris in healthcare settings.

Candida auris is a multidrug-resistant pathogen that represents a serious public health threat due to its rapid global emergence, increasing incidence of healthcare-associated outbreaks, and high rates of antifungal resistance. Whole-genome sequencing and genomic surveillance have the potential to bolster C. auris surveillance networks moving forward. Laboratories conducting genomic surveillance need to be able to compare analyses from various national and international surveillance partners to ensure that results are mutually trusted and understood. Therefore, we established an empirical outbreak benchmark dataset consisting of 23 C. auris genomes to help validate comparisons of genomic analyses and facilitate communication among surveillance networks. Our outbreak benchmark dataset represents a polyclonal phylogeny with three subclades. The genomes in this dataset are from well-vetted studies that are supported by multiple lines of evidence, which demonstrate that the whole-genome sequencing data, phylogenetic tree, and epidemiological data are all in agreement. This C. auris benchmark set allows for standardized comparisons of phylogenomic pipelines, ultimately promoting effective C. auris collaborations.