Abstract Cryptococcal disease, caused by basidiomycete yeasts of the genus Cryptococcus, represents a sub- stantial global health burden. Cryptococcus neoformans, the most common infectious agent, is ubiq- uitous in the environment and it is likely that most people are exposed to multiple genetically and phenotypically diverse Cryptococcus strains throughout their lifetimes. Despite this, human cryptococcosis has historically been studied under the assumption that a majority of infections are caused by single pathogenic strains. As a result, little is known about the incidence and prevalence of multi-strain or mixed-species cryptococcal infections or their clinical impact. In a preliminary study of patient samples from the Duke University Hospital System we de- tected a surprisingly high number of mixed Cryptococcus infections. We now propose to charac- terize the population genomic structure and epidemiological correlates of mixed Cryptococcus in- fections, using a set of more than 500 patient samples from the southeastern US collected over the last 30 years. We will analyze phenotypic and genomic heterogeneity within these patient samples to identify mixed infections, and combine these data with with population genomic and phyloge- netic analyses of environmental isolates from the same geographic region to understand the en- vironmental origins of mixed infections. Information on the frequency and population structure of mixed infections will be correlated with epidemiological analyses of patient demographics and health outcomes to understand who is likely to get mixed Cryptococcus infections and what such infections mean for health outcomes. We will also explore the impact of phenotypic heterogeneity, a key characteristic of mixed infections, on sensitivity to antifungal drugs and interactions with the host immune system.