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. 2018 Jul 3;11(1):382.
doi: 10.1186/s13071-018-2973-7.

Predicting environmentally suitable areas for Anopheles superpictus Grassi (s.l.), Anopheles maculipennis Meigen (s.l.) and Anopheles sacharovi Favre (Diptera: Culicidae) in Iran

Ahmad Ali Hanafi-Bojd  1   2 , Mohammad Mehdi Sedaghat  3 , Hassan Vatandoost  3   4 , Shahyad Azari-Hamidian  5 , Kamran Pakdad  3   6
Affiliations

Predicting environmentally suitable areas for Anopheles superpictus Grassi (s.l.), Anopheles maculipennis Meigen (s.l.) and Anopheles sacharovi Favre (Diptera: Culicidae) in Iran

Ahmad Ali Hanafi-Bojd et al. Parasit Vectors. .

Abstract

Background: Malaria is an important mosquito-borne disease, transmitted to humans by Anopheles mosquitoes. The aim of this study was to gather all records of three main malaria vectors in Iran during the last decades, and to predict the current distribution and the environmental suitability for these species across the country.

Methods: All published documents on An. superpictus Grassi (s.l.), An. maculipennis Meigen (s.l.) and An. sacharovi Favre during 1970-2016 in Iran were obtained from different online data bases and academic libraries. A database was created in ArcMap 10.3. Ecology of these species was analyzed and the ecological niches were predicted using MaxEnt model.

Results: Anopheles superpictus (s.l.) is the most widespread malaria vector in Iran, and exists in both malaria endemic and non-endemic areas. Whereas An. maculipennis (s.l.) is reported from the northern and northwestern parts, Anopheles sacharovi is mostly found in the northwestern Iran, although there are some reports of this species in the western, southwestern and eastern parts. The area under receiver operating characteristic (ROC) curve (AUC) for training and testing data was calculated as 0.869 and 0.828, 0.939 and 0.915, and 0.921 and 0.979, for An. superpictus (s.l.), An. maculipennis (s.l.) and An. sacharovi, respectively. Jackknife test showed the environmental variable with highest gain in the predicting power of the model when used in isolation was annual precipitation for An. superpictus (s.l.) and An. maculipennis (s.l.), and precipitation of the driest quarter for An. sacharovi.

Conclusions: Despite this range, global warming may increase the potential risk for malaria transmission in some cleared-up areas, where these proven vectors are active. Mapping and prediction of spatial/temporal distribution of these vectors will be beneficial for decision makers to be aware of malaria transmission risk, especially in the western parts of the country.

Keywords: An. maculipennis (s.l.); An. sacharovi; Anopheles superpictus (s.l.); Ecology; Iran; Modeling; Spatial distribution.

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The authors declare that they have no competing interests.

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Figures

Fig. 1
Fig. 1
Iran climate map (Koppen climate classification) and its neighboring countries
Fig. 2
Fig. 2
Spatial distribution of Anopheles superpictus (s.l.), An. maculipennis (s.l.) and An. sacharovi in Iran at the county (left) and village scales (right), 1970–2016.
Fig. 3
Fig. 3
Representation of MaxEnt model (left) and receiver operating characteristic (ROC) curve (right) for three malaria vectors in Iran: Anopheles superpictus (s.l.) (a), Anopheles maculipennis (s.l.) (b) and Anopheles sacharovi (c)
Fig. 4
Fig. 4
Result of the jackknife test of variable importance (left) and the curve of the most important variable in the model (right) for three malaria vectors in Iran. a Anopheles superpictus (s.l.). b Anopheles maculipennis (s.l.). c Anopheles sacharovi
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