Background: Cryptococcus gattii emerged on Vancouver Island, British Columbia (BC), Canada, in 1999, causing human and animal illness. Environmental sampling for C.gattii in southwestern BC has isolated the fungal organism from native vegetation, soil, air, and water.
Objectives: Our aim was to help public health officials in BC delineate where C.gattii is currently established and forecast areas that could support C.gattii in the future. We also examined the utility of ecological niche modeling (ENM) based on human and animal C.gattii disease surveillance data.
Methods: We performed ENM using the Genetic Algorithm for Rule-set Prediction (GARP) to predict the optimal and potential ecological niche areas of C.gattii in BC. Human and animal surveillance and environmental sampling data were used to build and test the models based on 15 predictor environmental data layers.
Results: ENM provided very accurate predictions (> 98% accuracy, p-value < 0.001) for C.gattii in BC. The models identified optimal C.gattii ecological niche areas along the central and south eastern coast of Vancouver Island and within the Vancouver Lower Mainland. Elevation, biogeoclimatic zone, and January temperature were good predictors for identifying the ecological niche of C.gattii in BC.
Conclusions: The use of human and animal case data for ENM proved useful and effective in identifying the ecological niche of C.gattii in BC. These results are shared with public health to increase public and physician awareness of cryptococcal disease in regions at risk of environmental colonization of C.gattii.