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• Mosquito infections with Sindbis (SINV) and Chikungunya (CHIKV) viruses in the northwest of Iran were examined. • The presence of the SINV genome in Culex pipiens complex and Cx. theileri was confirmed. • No CHIKV infection cases were identified in the 149 examined mosquito pools. • North, northwest, south, and southeast of Iran are the probable ecological niches of SINV vectors. Sindbis virus (SINV) and Chikungunya virus (CHIKV) are among the most widely spread mosquito-borne viruses worldwide. Due to the key role of mosquitoes in the transmission cycle of vector-borne diseases, models such as Maximum Entropy (MaxEnt) have been used in recent years to predict the environmental suitability and ecological niches of mosquito vectors. Infection of three mosquito species (Anopheles maculipennis s.l., Culex tritaeniorhynchus , and Culiseta longiareolata) with CHIKV has recently been reported in Iran. However, given the importance of vector-borne diseases in the country, there is a need for extensive studies on the infection of mosquitoes with CHIKV and SINV in different areas of the country. Accordingly, the current research was conducted to investigate the infection of mosquitoes with the two aforementioned viruses in the northwestern part of Iran and also to model the ecological niches of the vectors of these mosquito-borne viruses in the country. In the current study, 4639 mosquito specimens, consisting of 2515 adults and 2124 larvae, were collected from the wetlands of West Azerbaijan Province and identified. Ten species belonging to four genera were identified in this study. The specimens were allocated to 149 pools for the determination of infection with CHIKV and SINV. The amplification pattern of five pools comprising two mosquito species (Culex pipiens complex and Cx. Theileri) corresponded to the reference strain of SINV, and the isolates were sequenced to confirm the presence of SINV genome. No cases of CHIKV infection were found among the 149 examined mosquito pools. Data on the distribution of Cx. Pipiens complex and Cx. Theileri were mapped using ArcMap 10.5. Prediction maps of the presence probability for these species revealed that they are most likely to be found in and spread to the north, northwest, south, and southeastern areas of the country and in areas with abundant water resources. For the first time in Iran, our study investigated the presence probability of SINV vectors using ecological niche modeling. Ecological niche profiling showed that the most suitable habitats for Cx. pipiens are mainly concentrated in the north and northwestern parts of the country, whereas Cx. theileri is mostly located in the northwest and western regions. However, there were some other areas of low suitability for these two species in the country. Further studies in a broader geographical area with more species of mosquitos and the determination of infection with other mosquito-borne viruses can provide a clear understanding of the potential spread of mosquito-borne diseases in various regions of Iran. [Display omitted] [ABSTRACT FROM AUTHOR]

Zoonotic cutaneous leishmaniasis (ZCL), caused by Leishmania major, is a common zoonotic vector-borne disease in Iran. Close contact with infected reservoir hosts increases the probability of transmission of Leishmania parasite infections to susceptible humans. Four gerbil species (Rodentia: Gerbillidae) serve as the main reservoir hosts for ZCL in different endemic foci of Iran. These species include Rhombomys opimus , Meriones libycus, Meriones hurrianae and Tatera indica; while notable infection has been reported in Nesokia indica as well. The purpose of this study is to model the distribution of these reservoirs to identify the risk areas of ZCL. A data bank was developed including all published data during the period of 1970–2015. Maximum entropy model was used to find the most appropriate ecological niches for each species. The areas under curve obtained were 0.961, 0.927, 0.922, 0.997 and 0.899, instead of 1, for training test in R. opimus , M. libycus , T. indica , M. hurrianae and N. indica, respectively. The environmental variable with the highest gain when used in isolation was slope for R. opimus and N. indica , annual mean temperature for M. libycus, and seasonal precipitation for T. indica and M. hurrianae . Summation of presence probabilities for three main species, i.e., R. opimus , M. libycus and T. indica revealed favorable ecological niches in wide areas of 16 provinces. This is the first study to predict the distribution of ZCL reservoir hosts in Iran. Climatology and topography variables had high contributions toward the prediction of potential distribution of the main reservoir species; therefore, as climate changes, the models should be updated periodically with novel data, and the results should be used in disease-monitoring programs. [ABSTRACT FROM AUTHOR]

• MaxEnt model was used to predict the high risk areas of fascioliasis using topographic and bioclimatic variables. • The most important predictor variables were included Precipitation of driest quarter, Precipitation of driest month, aspect and altitude. • Guilan province has a high risk of fascioliasis in livestock. The present study aimed to determine the number of cases of animal fascioliasis per district in the southern littoral of Caspian Sea and to model suitable ecological niches for Fasciola infection in the region. Stool samples (n = 2688) were collected from cattle and sheep in Guilan, Mazandaran and Golestan provinces. The samples were tested using flotation method, and the number of parasite eggs per gram (EPG) of feces was recorded for each sample. Occurrence-only data of Fasciola were collected from the field. A total of 96 points/locations were used to model the ecological niche of Fasciola in maximum entropy (MaxEnt) and geographical information system (GIS). The spatial layers were compiled from 23 bioclimatic and biophysical variables for modeling analysis. Jackknife analysis was used to determine the relative importance of all variables in the model. In the present study, the proportion of fascioliasis in both hosts was highest in Guilan province (sheep: 12.34%, cattle: 15.16%), followed by Mazandaran (sheep: 7.3%, cattle: 6.25%) and Golestan (sheep: 0%, cattle: 0.94%) provinces. The Area Under Curve (AUC) value of the model was 0.909, indicating a good predictive power of the model. Our modeling results indicate that four variables, which were markedly incorporated into the model, are the major predictors of the presence probability of Fasciola spp. in the region: Bio17 (Precipitation of driest quarter; 45.5%), Bio14 (Precipitation of driest month; 24.8%), aspect (9%), and altitude (7.2%). The data presented herein show expansion of the potential high-risk areas of fascioliasis in the northern part of Iran, located at the southern littoral of Caspian Sea, especially in Guilan province. However, the extent of the predicted risk zones varied between the different areas of the region and within provinces, such that at the present, many parts of Golestan province are less environmentally suitable for Fasciola distribution than other areas in the region. [ABSTRACT FROM AUTHOR]

Cutaneous leishmaniasis (CL) is the most important vector-borne disease in Iran. Qom Province is a very important area in the case of CL transmission, because of high traffic population from other parts of the country, or even other countries, as well as existence of confirmed foci of the disease. The aim of this study was to determine the ecology of sand flies in two different climates of this province and model the distribution of the main vector. Sand flies were collected monthly during April 2013–April 2014, at 22 urban/rural collection sites. Site selection was constrained by the geographical distribution of CL cases in recent years. Shannon–Weiner and Evenness indices were used to compare diversity in two studied climates. ArcGIS and MaxEnt were used to map and predict the appropriate ecological niches for sand flies. Totally, 5389 sand flies were collected and 12 species were identified. The most abundant species were Sergentomyia sintoni, P. papatasi , P. sergenti s.l. and Phlebotomus alexandri . Two peaks of activity were found in May and August in lowlands; while in mountainous areas they were observed in June and September. Species diversity in mountainous areas was found to be higher than in lowlands. The environmental variable with the highest gain in MaxEnt model was the monthly mean of (max temp–min temp). A big part of the lowland areas provides good ecological niches for P. papatasi and therefore higher transmission potential. These findings can be used in stratification of potential for CL transmission in Qom province. [ABSTRACT FROM AUTHOR]