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Background: Mosquitoes are very important vectors of diseases to human. We aimed to establish the first spatial database on the mosquitoes of Isfahan Province, central Iran, and to predict the geographical distribution of species with medical importance. Methods: Mosquito larvae were collected from eight counties of Isfahan Province during 2014. Collected data were transferred to a database in ArcGIS and the distribution maps were created. MaxEnt model and jackknife analysis were used to predict the geographical distribution of two medical important species, and to find the effective variables for each species. Results: Totally, 1143 larvae were collected including 6 species, Anopheles maculipennis s.l., An. superpictus s.l., An. marteri, Culex hortensis, Cx. theileri and Culiseta longiareolata. The area under curve in MaxEnt model was 0.951 and 0.873 rather 1 for An. maculipennis s.l. and Cx. theileri, respectively. Culex theileri had wider and more appropriate niches across the province, except for the eastern area. The environmental variable with highest gain was mean temperature of the wettest quarter for Cx. theileri and temperature seasonality for An. maculipennis. Culex theileri, An. maculipennis s.l. and An. superpictus, three important vectors of parasitic agents to humans, were collected in this study. Conclusion: The mosquito collected and mapped can be considered for transmission of malaria and filariasis in the region. Bearing in mind the results of niche modeling for vector species, more studies on vectorial capacity and resistance status to different insecticides of these species are recommended.

journal of arthropod-borne diseases

Using Ecological Niche Modeling to Predict the Spatial Distribution of Anoph¬eles maculipennis s.l. and Culex theileri (Diptera: Culicidae) in Central Iran