Climate change and its effect on the vulnerability to zoonotic cutaneous leishmaniasis in Iran.

Zoonotic cutaneous leishmaniasis (ZCL) is an important vector-borne disease with an incidence of 15.8 cases per 100,000 people in Iran in 2019. Despite all efforts to control the disease, ZCL has expanded into new areas during the last decades. The aim of this study was to predict the best ecological niches for both vectors and reservoirs of ZCL under climate change scenarios in Iran. Several online scientific databases were searched. In this study, various scientific sources (Google Scholar, PubMed, SID, Ovid Medline, Web of Science, Irandoc, Magiran) were searched. The inclusion criteria for this study included all records with spatial information about vectors and reservoirs of ZCL which were published between 1980 and 2019. The bioclimatic data were downloaded from online databases. MaxEnt model was used to predict the ecological niches for each species under two climate change scenarios in two periods: the 2030s and 2050s. The results obtained from the model were analysed in ArcMap to find the vulnerability of different provinces for the establishment of ZCL foci. The area under the curve (AUC) for all models was >0.8, which suggests the models are able to make an accurate prediction. The distribution of all studied species in different climatic conditions showed changes. The variables affecting each of the studied species are introduced in the article. The predicted maps show that by 2050 there will be more suitable areas for the co-occurrence of vector and reservoir(s) of ZCL in Iran compared to the current climate condition and RCP2.6 scenario. An area in the northwest of Iran is predicted to have suitable environmental conditions for both vectors and reservoirs of ZCL, although the disease has not yet been reported in this area. These areas should be considered for field studies to confirm these results and to prevent the establishment of new ZCL foci in Iran.

Global warming, environmental security and its geo-economic dimensions case study: Caspian Sea level changes on the balance of transit channels.

BACKGROUND: Global warming and climate change are considered as important environmental problems. Environmental security is more pronounced with regard to the Caspian Sea. Due to the geopolitical and geo-economic dimensions on the one hand, and its unique characteristics on the other, this large lake is considerably fragile against environmental challenges. In fact, the innate isolation of the Caspian Sea makes its conditions with regard to global warming unique. Using a descriptive-analytical method and library and valid article references, this study seeks to answer the question: "what are the effects of global warming on environmental security and what challenges does it pose to the Caspian Sea from the geo-economic point of view?" METHODS: And Also maps and charts related to the research topic were collected and plotted in the GIS. In the next step, using a descriptive-analytical method based on geopolitical perspectives, especially environmental geopolitical studies and internet searches, we analyze the spatial effects of this universal phenomenon in the context of environmental geopolitical systems. RESULTS: The findings indicate that global warming will pose a large spectrum of challenges and problems to the Caspian Sea from the destruction of its ecosystems to the complete transformation of its nature. This research has studied global warming and its effects on the sea level changes of the Caspian Sea and particularly the level of water in the transit channels of the Caspian Sea from the geo-economic point of view. CONCLUSION: The results show that fluctuations in the water level of the Caspian Sea, in addition to environmental challenges, narrow the balance of its transit channels and threaten the geo-economics and environmental security of the Caspian Sea.

Prone Regions of Zoonotic Cutaneous Leishmaniasis in Southwest of Iran: Combination of Hierarchical Decision Model (AHP) and GIS.

BACKGROUND: Cutaneous leishmaniasis due to Leishmania major is an important public health problem in the world. Khuzestan Province is one of the main foci of zoonotic cutaneous leishmaniasis (ZCL) in the southwest of Iran. We aimed to predict the spatial distribution of the vector and reservoir(s) of ZCL using decision-making tool and to prepare risk map of the disease using integrative GIS, RS and AHP methods in endemic foci in Shush (plain area) and Khorramshahr (coastal area) counties of Khuzestan Province, southern Iran from Mar 2012 to Jan 2013. METHODS: Thirteen criteria including temperature, relative humidity, rainfall, soil texture, soil organic matter, soil pH, soil moisture, altitude, land cover, land use, underground water depth, distance from river, slope and distance from human dwelling with the highest chance of the presence of the main vector and reservoir of the disease were chosen for this study. Weights of the criteria classes were determined using the Expert choice 11 software. The presence probability maps of the vector and reservoir of the disease were prepared with the combination of AHP method and Arc GIS 9.3. RESULTS: Based on the maps derived from the AHP model, in Khorramshahr study area, the highest probability of ZCL is predicted in Gharb Karoon rural district. The presence probability of ZCL was high in Hossein Abad and Benmoala rural districts in the northeast of Shush. CONCLUSION: Prediction maps of ZCL distribution pattern provide valuable information which can guide policy makers and health authorities to be precise in making appropriate decisions before occurrence of a possible disease outbreak.

Potential Risk Areas of Aedes albopictus in South-Eastern Iran: A Vector of Dengue Fever, Zika, and Chikungunya.

The possibility of the rapid and global spread of Zika, chikungunya, yellow fever, and dengue fever by Aedes albopictus is well documented and may be facilitated by changes in climate. To avert and manage health risks, climatic and topographic information can be used to model and forecast which areas may be most prone to the establishment of Ae. albopictus. We aimed to weigh and prioritize the predictive value of various meteorological and climatic variables on distributions of Ae. albopictus in south-eastern Iran using the Analytical Hierarchy Process. Out of eight factors used to predict the presence of Ae. albopictus, the highest weighted were land use, followed by temperature, altitude, and precipitation. The inconsistency of this analysis was 0.03 with no missing judgments. The areas predicted to be most at risk of Ae. albopictus-borne diseases were mapped using Geographic Information Systems and remote sensing data. Five-year (2011-2015) meteorological data was collected from 11 meteorological stations and other data was acquired from Landsat and Terra satellite images. Southernmost regions were at greatest risk of Ae. albopictus colonization as well as more urban sites connected by provincial roads. This is the first study in Iran to determine the regional probability of Ae. albopictus establishment. Monitoring and collection of Ae. albopictus from the environment confirmed our projections, though on-going field work is necessary to track the spread of this vector of life-threatening disease.

Modeling the Distribution of Cutaneous Leishmaniasis Vectors (Psychodidae: Phlebotominae) in Iran: A Potential Transmission in Disease Prone Areas.

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.

Spatio-temporal distribution of malaria vectors (Diptera: Culicidae) across different climatic zones of Iran.

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.