Background
Candida auris is a pathogenic, drug-resistant fungus that has emerged in healthcare facilities across the world in the span of a decade. In the United States, C. auris typically affects individuals in healthcare settings. Patients who have been in a healthcare facility a long time, have a central venous catheter, or other lines or tubes entering their body, or have previously received antibiotics or antifungal medications, appear to be at highest risk of infection.
Since C. auris was first identified as a public health threat, whole genome sequencing (WGS) has helped guide public health response to control its spread. FungiNet, a network for molecular surveillance and genomic epidemiology of fungal disease, supports the generation and analysis of C. auris WGS data to support public health investigations.
Purpose
This goal of this course is to describe the basic epidemiology of C. auris and how WGS has helped public health officials learn more about its molecular epidemiology. Additionally, it provides an overview of the laboratory and analytic methods for C. auris WGS when using the data for epidemiologic purposes.
Format
This self-guided e-learning course consists of two interactive modules designed for learners to complete at their own pace. Each module consists of sub-modules, which include guides, videos, and/or knowledge checks to support learning. Each module concludes with a quiz. Results from knowledge-checks and quizzes are not recorded. The modules do not need to be completed sequentially. Additionally, there is no registration or certification for this course.
Audience
This virtual training is intended to be a primer for laboratorians, bioinformaticians, and epidemiologists interested in learning how to generate, analyze, and interpret C. auris WGS for epidemiologic purposes.
Time required
Approximately 2 hours to complete both modules. Modules do not have to be completed in one sitting. Learners can start and stop as needed but must note where to resume the course, as the place will not be saved between sessions.
Language
English
