Abstract
The continuous increase of Coccidioidomycosis cases requires reliable detection methods of the causal agent, Coccidioides spp., in its natural environment. This has proven challenging because of our limited knowledge on the distribution of this soil-dwelling fungus. Knowing the pathogen’s geographic distribution and its relationship with the environment is crucial to identify potential areas of risk and to prevent disease outbreaks. The maximum entropy (Maxent) algorithm, Geographic Information System (GIS) and bioclimatic variables were combined to obtain current and future potential distribution models (DMs) of Coccidioides and its putative rodent reservoirs for Arizona, California and Baja California. We revealed that Coccidioides DMs constructed with presence records from one state are not well suited to predict distribution in another state, supporting the existence of distinct phylogeographic populations of Coccidioides. A great correlation between Coccidioides DMs and United States counties with high Coccidioidomycosis incidence was found. Remarkably, under future scenarios of climate change and high concentration of greenhouse gases, the probability of habitat suitability for Coccidioides increased. Overlap analysis between the DMs of rodents and Coccidioides, identified Neotoma lepida as one of the predominant co-occurring species in all three states. Considering rodents DMs would allow to implement better surveillance programs to monitor disease spread.
Highlights
Coccidioidomycosis (CM), a reemerging disease known as Valley Fever, is endemic to arid and semi-arid regions of the American continent
Species distribution models (DMs) were generated for Coccidioides spp., C. fallax, C. penicillatus, D. simulans, D. merriami, N. lepida and P. maniculatus using maximum entropy (Maxent) version 3.3.3.k with default parameters, other than splitting occurrence points randomly for model calibration and testing (80% and 20%, respectively)
Jackknife results for rodent models indicated as important variables, when used individually: precipitation of driest month (BIO14), temperature seasonality (BIO4), precipitation of warmest quarter (BIO18) and precipitation seasonality (BIO15) for C. fallax, D. simulans and N. lepida respectively, as well as annual mean temperature (BIO1) for D. merriami, C. penicillatus and P. maniculatus
Summary
Coccidioidomycosis (CM), a reemerging disease known as Valley Fever, is endemic to arid and semi-arid regions of the American continent. Southern Arizona and California in the United States, and Sonora, Nuevo Leon, Coahuila and Baja California in Mexico, are considered important endemic regions based on the high prevalence of the disease they present [1]. //www.cdc.gov/fungal/diseases/coccidioidomycosis/statistics.html), represent a great concern both in terms of public health and economically [2]. Coccidioides spp. distribution in soils is very irregular, and this hinders the detection of positive sites even in highly endemic areas [1,3]. Great efforts to characterize Coccidioides habitat and elucidate the basis for this scattered distribution have been made. Sandy-textured and high-salinity soils, have been correlated with the presence of Coccidioides spp.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
