Ecological distribution modeling of two malaria mosquito vectors using geographical information system in Al-Baha Province, Kingdom of Saudi Arabia

Malaria is considered as an endemic mosquito borne disease in the Kingdom of Saudi Arabia (KSA). Previous investigations addressed the diseases incidences in KSA, however few studies highlighted the mosquito vectors habitats characterization in regards to ecological variables. Ecological models of mosquito vectors will help in defining potential suitable habitats for their spatial distribution and understanding how much the ecological variables contribute in delineating these suitable habitats. This information will help in developing targeted surveillance and control strategies. Ecological niche modeling was carried out using the evolutionary algorithms implemented in maximum entropy (MaxEnt) to predict the suitable larval habitats of two malaria vectors, Anopheles gambiae s.l. and An. sergentii (Theobald) in Al-Baha Province, KSA. Climatic and topographical data layers from Worldclim databases and larval occurrence records were used to model the two malaria vectors. Six topographical and four bioclimatic variables were significantly predict An. gambiae larval suitable habitat. Both streams covered with vegetation and algae and elevation above sea level were strong predictors of distribution of this mosquito vector. However, for An. sergentii, four topographical and ten bioclimatic variables were found to be significant predictors of suitable habitat distribution. Soil and altitude were strong predictors of An. sergentii distribution. Also, the linear regression statistical analysis (LM) indicates non linear correlation between TDS/pH and abundance of these two mosquito species.