The use of GIS in the Predictive Ecological Niche Modeling of Vector Species of the American Trypanosomiasis Disease (Chagas), in Ecuador

In recent years Ecuador has suffered from the Zika virus. Geo-software and statistical software allowed the probabilistic identification of suitable ecological niche species, such as the vector Aedes aegypti, which is the leading cause of the Zika virus transmission, depending on the dependent and independent variables. These models require pre-weighted input, normalized, and rasterized inputs to continue the validation process to estimate their predictive performance through several statistics such as the confusion matrix or the Receiver Operating Characteristic Curve (ROC). It resulted that the Maxent method has been with the higher predictive performance with a value of Area Under Curve (AUC) = 0.998, which describes the areas of Zika with a greater probability of the transmission vector resembling the actual distribution of the species as a function of the presence data and the predictor variables. A large part of the Ecuadorian coastal territory yielded a statistical-based, probabilistic presence of the vector, being the most vulnerable before a possible epidemiological risk.

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The use of GIS in the Predictive Ecological Niche Modeling of Vector Species of the American Trypanosomiasis Disease (Chagas), in Ecuador

Cited by 2 publications

References 71 publications

Trypanosoma Cruzi: An Ancient and Successful Enzootic Parasite

Trypanosoma Cruzi: An Ancient and Successful Enzootic Parasite

Modeling of the spatial distribution of the vector Aedes Aegypti, transmitter of the Zika Virus in continental Ecuador by the application of GIS tools

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