Malaria is a main vector-borne public health problem in Iran. The last studies on Iranian mosquitoes show 31 Anopheles species including different sibling species and genotypes, eight of them are reported to play role in malaria transmission. The objective of this study is to provide a reference for malaria vectors of Iran and to map their spatial and temporal distribution in different climatic zones. Shape files of administrative boundaries and climates of Iran were provided by National Cartographic Center. Data on distribution and seasonal activity of malaria vectors were obtained from different sources and a databank in district level was created in Excel 2003, inserted to the shape files and analyzed by ArcGIS 9.2 to provide the maps. Anopheles culicifacies Giles s.l., Anopheles dthali Patton, Anopheles fluviatilis James s.l., Anopheles maculipennis Meigen s.l., Anopheles sacharovi Favre, Anopheles stephensi Liston, and Anopheles superpictus Grassi have been introduced as primary and secondary malaria vectors and Anopheles pulcherrimus Theobald as a suspected vector in Iran. Temporal distribution of anopheline mosquitoes is restricted to April-December in northern Iran, however mosquitoes can be found during the year in southern region. Spatial distribution of malaria vectors is different based on species, thus six of them (except for Anopheles maculipennis s.l. and Anopheles sacharovi) are reported from endemic malarious area in southern and southeastern areas of Iran. The climate of this part is usually warm and humid, which makes it favorable for mosquito rearing and malaria transmission. Correlation between climate conditions and vector distribution can help to predict the potential range of activity for each species and preparedness for malaria epidemics.

Cutaneous leishmaniasis (CL) is now the main vector-borne disease in Iran. Two forms of the disease exist in the country, transmitted by Phlebotomus papatasi and Phlebotomus sergenti s.l. Modeling distribution of the vector species is beneficial for preparedness and planning to interrupt the transmission cycle. Data on sand fly distribution during 1990–2013 were used to predict the niche suitability. MaxEnt algorithm model was used for prediction using bioclimatic and environmental variables (precipitation, temperature, altitude, slope, and aspect). Regularized training, area under the curve, and unregularized training gains were 0.916, 0.915, and 1.503, respectively, for Ph. papatasi . These values were calculated as 0.987, 0.923, and 1.588 for Ph. sergenti s.l . The jackknife test showed that the environmental variable with the highest gain when used in isolation has the mean temperature of the wettest quarter for both species, while slope decreases the gain the most when it is omitted from the model. Classification of probability of presence for two studied species was performed on five classes using equal intervals in ArcGIS. More than 60% probability of presence was considered as areas with high potential of CL transmission. These areas include arid and semiarid climates, mainly located in central part of the country. Mean of altitude, annual precipitation, and temperature in these areas were calculated 990 and 1,235 m, 273 and 226 mm, and 17.5 and 16.4°C for Ph. papatasi and Ph. sergenti s.l., respectively. These findings can be used in the prediction of CL transmission potential, as well as for planning the disease control interventions.

Cutaneous leishmaniasis (CL) is among the top 10 infectious disease priorities in the world, and the leading cause of morbidity in Iran. The present study was conducted to assess the risk of CL, and to determine some epidemiological features of the disease in endemic areas of Qom Province in Central Iran during 2009 to 2013. Data regarding human cases of the disease were obtained from the Qom Province Health Center, prepared and stored in a spatial database created in ArcGIS10.3. A total of 9 out of 212 Leishmania spp. positive slides taken in 2013 from patients residing in Qom city were examined using molecular methods and the species of Leishmania was identified by PCR-RFLP. Those 9 patients had no history of travel outside the city. Spatial analysis and clustering methods were applied to find major hot spots and susceptible areas for the establishment of novel foci of the disease. Transmission patterns were examined for spatial autocorrelation using the Moran's I statistical application, and for the clustering of high or low values using the Getis-Ord Gi* statistics. During the period of study, a total of 1767 CL cases were passively reported in the area, out of which were 65% males and 35% females. The highest and lowest numbers of cases were reported in 2010 and 2013, respectively. Importantly, 979 cases were reported from urban areas, while the remainder came from rural areas. Leishmania major was detected as the causative agent of CL in the city of Qom. Remarkably, most patients recorded in Qom city were associated with a history of travel to the endemic areas of CL within the province, or to other endemic areas of the disease in Iran. Spatial distribution of CL cases revealed northeastern and southwestern quarters of the city were the major hot spots of the disease (P<0.05). Hot spot and CL transmission risk analysis across the province indicated that more than 40 villages were located in high and very high risk areas of CL transmission. Due to the existence of hot spots (P<0.05) of CL in successive years in some quarters of Qom city, along with detection of L. major from the patients without a history of travel, there may be potential of local transmission of the disease within the city. Therefore, it is necessary to conduct a comprehensive study concerning the hot spots of CL in Qom city for curtailing the incidence of the disease in the city. The methodology and the results of this study is essential in serving as a yardstick for subsequent similar studies that will be carried out in other endemic areas of CL in Iran and providing an adequate tool for the establishment of a national database of cutaneous leishmaniasis.