Coccidioidomycosis is an infection caused by inhalation of spores from the soil-dwelling fungi Coccidioides immitis or C. posadasii, and can lead to chronic lung infection, meningitis, or death. Southwestern states are currently experiencing among the highest incidence rates of coccidioidomycosis ever recorded. The disease has levied a substantial human and economic burden throughout the southwest, totaling an estimated $2.2 billion in charges in California alone for coccidioidomycosis-associated hospitalizations from 2000-2011. Critical gaps in understanding have hindered the public health response, including how dust, pathogen, and individual risk factors interact to determine disease incidence, as well as how environmental factors influence the distribution of the pathogen and dust. To address these gaps, this project investigates the impacts of dust exposure, environmental variability, and sociodemographic change on Coccidioides spp. proliferation, dispersion, and coccidioidomycosis infection rates in California. The research focuses on three main aims: 1) investigate the influence of climate variation and dust exposure on the spatiotemporal distribution of cocci incidence using >65,000 geolocated surveillance records from 2000 to 2018 and a case-crossover design; 2) identify environmental sources of C. immitis at high spatial and temporal resolution in disturbed and undisturbed soil, and determine how wind, rainfall, soil disturbance and other factors influence spore dispersion through longitudinal sampling of C. immitis in air and soil; and 3) predict changes in pathogen density over space and time and estimate the exposure-response relationship between pathogen density and risk of infection using a case-crossover approach with prospective surveillance for incident cases. In pursuit of these aims, the research will combine georeferenced coccidioidomycosis case data across California since 2000 at an unprecedented spatial resolution with fine-scale dust concentration estimates and environmental data from a combination of remote sensing, modeling and ground monitors. We will use novel field and laboratory methods to conduct longitudinal sampling of C. immitis in air and soil, determining how microenvironmental conditions and cyclical patterns of rainfall and drought determine pathogen source dynamics, and identifying conditions that support pathogen dispersion through the air. Through these activities, we will identify the specific dust conditions that pose the greatest risk for infection, estimate pathogen exposure and the dose- response relationship, and evaluate heterogeneity in this relationship across risk groups and regions. The results will elucidate drivers of the current epidemic, enhance understanding of the distribution and dispersion of Coccidioides spp. in the environment, and identify high risk regions and subpopulations. The knowledge gained will support decision-makers in targeting, designing and implementing protective measures for vulnerable populations.