Species Composition of Sand Flies (Diptera: Psychodidae) and Modeling the Spatial Distribution of Main Vectors of Cutaneous Leishmaniasis in Hormozgan Province, Southern Iran

Species Composition of Sand Flies (Diptera: Psychodidae) and Modeling the Spatial Distribution of... Abstract Cutaneous Leishmaniasis (CL) is one of the main neglected vector-borne diseases in the Middle East, including Iran. This study aimed to map the spatial distribution and species composition of sand flies in Hormozgan Province and to predict the best ecological niches for main CL vectors in this area. A database that included all earlier studies on sand flies in Hormozgan Province was established. Sand flies were also collected from some localities across the province. Prediction maps for main vectors were developed using MaxEnt model. A total of 27 sand fly species were reported from the study area. Phlebotomus papatasi Scopoli, Phlebotomus sergenti s.l. Parrot, Phlebotomus alexandri Sinton, Sergentomyia sintoni Pringle, Sergentomyia clydei Sinton, Sergentomyia tiberiadis Adler, and Sergentomyia baghdadis Adler (Diptera: Psychodidae) had the widest distribution range. The probability of their presence as the main vectors of CL was calculated to be 0.0003–0.9410 and 0.0031–0.8880 for P. papatasi and P. sergenti s.l., respectively. The best ecological niches for P. papatasi were found in the central south, southeast, and a narrow area in southwest, whereas central south to northern area had better niches for P. sergenti s.l. The endemic areas are in Bandar-e Jask, where transmission occurs, whereas in Bastak, the cases were imported from endemic foci of Fars province. In conclusion, proven and suspected vectors of CL and VL were recorded in this study. Due to the existence of endemic foci of CL, and favorite ecological niches for its vectors, there is potential risk of emerging CL in new areas. Sand fly, Psychodidae, Leishmaniasis, Niche Modeling Cutaneous Leishmaniasis (CL) is one of the most important vector-borne diseases in some parts of the world, including Iran. The endemic foci of the disease are in 18 out of 31 provinces of Iran and about 80% are due to Zoonotic Cutaneous Leishmaniasis (ZCL). Anthroponotic Cutaneous Leishmaniasis (ACL) is responsible for the remaining percentage (Yaghoobi-Ershadi 2012). Phlebotomine sand flies (Diptera: Psychodidae) are well known to be the vectors of Leishmaniasis. Previous studies have reported 50 species of sand flies from different parts of Iran (Karimi et al. 2014). Two out of these species, i.e., Phlebotomus papatasi Scopoli and Phlebotomus sergenti s.l. Parrot are considered to be the main vectors of CL. Phlebotomus salehi Mesghali is the suspected/secondary vector in some endemic foci of the disease in south and southeast parts of Iran (Kasiri and Javadian 2000, Davami et al. 2011, Azizi et al. 2012). There are few studies on species composition and spatial distribution of sand flies in Hormozgan Province, southern Iran. Study on sand flies of this province dated back to 1954–1964, when 18 species were recorded and reported for the first time by Mesghali (Mesghali 1965). During the campaign toward malaria elimination in this province, two rounds of indoor residual spraying were conducted annually, resulted in reduced cases of CL as well. Malaria elimination in most areas of the country and stopping of sprays against it increased the population of vectors of other diseases, such as leishmaniasis. Also, climate change, land use changes, and urbanization development led to an increase in leishmaniasis in Iran. Following the above study that established a base line data for sand flies in Hormozgan, there was another study on Phlebotominae in Hormozgan during 1988–1989 (Oshaghi 1989) and reported 16 species, from which three species were found to be new to the fauna of that area. After the successful implementation of malaria elimination program, insecticide applications were reduced and limited to some parts of Iran. Due to the reduction and restriction of insecticide use in some areas, the incidence of CL was noticed to have increased, and some epidemics were recorded. Different studies were conducted to find the epidemiological aspects of CL in three foci of the disease in Bandar Abbas (Soleimani Ahmadi et al. 1998), Hajiabad (Hanafi-Bojd et al. 2006), and Bandar-e Jask (Azizi et al. 2012) Counties. Due to the strategic location of Hormozgan Province and wide implementation of developmental projects, especially in its sea ports, it is necessary to clarify the potentials of CL transmission. So, periodic studies are necessary to update the fauna and species richness of sand flies in different parts of this province, to find the transmission potential and for preparation to combat the disease when needed. The aim of this study was to establish a database on sand flies in Hormozgan Province, to determine their geographical species composition, and to model the spatial distribution of the main vector(s) of CL in the area. Materials and Methods Study Area The study was conducted in Hormozgan Province, in the northern parts of Persian Gulf, Iran. It covers an area of 68,476 km2 with coordinates of 25.4–28.95° N, 53.68–59.25° E (Fig. 1). The population was 1,676,000, of which 51.2% are living in urban areas and 48.8% in rural areas. North of the province is a mountains area whereas the southern part is lowland and bordered with Persian Gulf and Oman Sea. The regional climate is generally arid and semiarid. The weather in coastal line is very hot and humid in summer and mild in winter, with low precipitation. Fig. 1. View largeDownload slide An altitudinal perspective from the Study area, Hormozgan Province, Southern Iran. Fig. 1. View largeDownload slide An altitudinal perspective from the Study area, Hormozgan Province, Southern Iran. Data Collection and Analysis To update the data on the fauna of sand flies in the study area, sampling was conducted monthly in Qeshm Island and seasonally in Bashagard County during spring and summer of 2014. Site selection was constrained by the potential and productivity of various areas for breeding sand flies. A GPS device was used to record the sand fly collection sites. Sand flies from each station were collected from both indoors and outdoors using sticky paper traps coated with castor oil. The traps were installed before sunset and picked up in the next early morning before sunrise. The captured sand flies were kept in 70% ethyl alcohol until they were mounted in Puri’s medium (Smart et al. 1965) and were identified morphologically (Theodor and Mesghali 1964, Seyedi-Rashti and Nadim 1992). The results of this study were added to the former data on sand flies of Hormozgan Province in a geodatabase created in ArcMap 10.3. Disease Data Passive data recorded in Hormozgan Province health center were collected for 11 years during 2005–2015 at the County level. A CL database was developed in ArcGIS 10.3 and a quantitative map was created to show the mean of cases in this period. Modeling the Distribution of Sand Flies Model Variables Bioclimatic variables and altitude layers were obtained from the WorldClim global climate database (http://www.worldclim.org/current) at a spatial resolution of 1 km2. These variables were derived from the long term (1950–2000) monthly temperature and rainfall values to generate more biologically meaningful variables. The bioclimatic variables represent annual trends, seasonality, and extreme or limiting environmental factors (Table 1). Spatial analyst of ArcGIS 10.3 was used to prepare Slope and Aspect (the compass direction that a slope faces) layers from Altitude. Then, layers were changed to ASCII raster using ArcMap 10.3conversion tool for their subsequent use in MaxEnt model. Table 1. Variables used to predict the potential distribution of Phlebotomus papatasi and P. sergenti s.l., as vectors of Cutaneous Leishmaniasis in Hormozgan Province, Southern Iran Variable  Description  Contribution (%)  P. papatasi  P. sergenti s.l.  Altitude  Elevation above the sea level (m)  67.2  1.2  BIO1  Annual Mean Temperature (oC)  2.2  0  BIO2  Mean Diurnal Range (Mean of monthly (max temp - min temp)) (oC)  2.6  0  BIO3  Isothermality (BIO2/BIO7) (×100)  9.3  9.5  BIO4  Temperature Seasonality (standard deviation ×100)  0.6  7.2  BIO5  Max Temperature of Warmest Month (°C)  0.8  12.6  BIO6  Min Temperature of Coldest Month (°C)  0.5  3.9  BIO7  Temperature Annual Range (BIO5-BIO6) (°C)  0.3  0  BIO8  Mean Temperature of Wettest Quarter (°C)  0  0  BIO9  Mean Temperature of Driest Quarter (°C)  8.1  4  BIO10  Mean Temperature of Warmest Quarter (°C)  0  4.2  BIO11  Mean Temperature of Coldest Quarter (°C)  0.2  0  BIO12  Annual Precipitation (mm)  0  1.2  BIO13  Precipitation of Wettest Month (mm)  5.1  29  BIO14  Precipitation of Driest Month (mm)  0.6  0.2  BIO15  Precipitation Seasonality (Coefficient of Variation)  1.8  0  BIO16  Precipitation of Wettest Quarter (mm)  0  0.1  BIO17  Precipitation of Driest Quarter (mm)  0  2  BIO18  Precipitation of Warmest Quarter (mm)  0.6  0  BIO19  Precipitation of Coldest Quarter (mm)  0  24.9  Variable  Description  Contribution (%)  P. papatasi  P. sergenti s.l.  Altitude  Elevation above the sea level (m)  67.2  1.2  BIO1  Annual Mean Temperature (oC)  2.2  0  BIO2  Mean Diurnal Range (Mean of monthly (max temp - min temp)) (oC)  2.6  0  BIO3  Isothermality (BIO2/BIO7) (×100)  9.3  9.5  BIO4  Temperature Seasonality (standard deviation ×100)  0.6  7.2  BIO5  Max Temperature of Warmest Month (°C)  0.8  12.6  BIO6  Min Temperature of Coldest Month (°C)  0.5  3.9  BIO7  Temperature Annual Range (BIO5-BIO6) (°C)  0.3  0  BIO8  Mean Temperature of Wettest Quarter (°C)  0  0  BIO9  Mean Temperature of Driest Quarter (°C)  8.1  4  BIO10  Mean Temperature of Warmest Quarter (°C)  0  4.2  BIO11  Mean Temperature of Coldest Quarter (°C)  0.2  0  BIO12  Annual Precipitation (mm)  0  1.2  BIO13  Precipitation of Wettest Month (mm)  5.1  29  BIO14  Precipitation of Driest Month (mm)  0.6  0.2  BIO15  Precipitation Seasonality (Coefficient of Variation)  1.8  0  BIO16  Precipitation of Wettest Quarter (mm)  0  0.1  BIO17  Precipitation of Driest Quarter (mm)  0  2  BIO18  Precipitation of Warmest Quarter (mm)  0.6  0  BIO19  Precipitation of Coldest Quarter (mm)  0  24.9  View Large Modeling Potential Occurrence of Sand Flies MaxEnt software Ver. 3.3.3 was used to predict the most appropriate ecological niches for targeted species (Phillips et al. 2006).The contribution of the environmental variables was calculated by Jackknife analysis. Table 1 shows estimates of relative contributions of the environmental variables to the MaxEnt model for CL vectors. Variables with no contribution were omitted from the final analysis. Eighty percent of sand fly collection points were used for model training and 20% kept for testing the results. Point selection process was done by MaxEnt in random. Results In our present entomological studies in Qeshm Island, just two species, i.e., 809 P. papatasi (96.2%) and 32 Sergentomyia baghdadis Adler (3.8%) were collected and identified. Out of these species, 75% were collected from indoors and 25% from outdoors. There were two peaks of activity observed in this island during the collection, the first and biggest was between March and April whereas the second and smallest was between September and October (Fig. 2). Efforts made for sand fly collection in Abu Musa, Greater Tunb, and Lesser Tunb islands yielded no results, despite installing 1440 sticky paper traps during the study period. Fig. 2. View largeDownload slide Monthly activity of sand flies in Qeshm Island, Hormozgan Province, 2014. Fig. 2. View largeDownload slide Monthly activity of sand flies in Qeshm Island, Hormozgan Province, 2014. In Bashagard County 427 specimens were collected in three occasions and 15 species were identified: P. papatasi (4), Phlebotomus bergeroti Parrot (9), P. sergenti s.l. (6), Phlebotomus alexandri (20), Sergentomyia mervynae Pringle (28), Sergentomyia tiberiadis Adler (250), Sergentomyia baghdadis (43), Sergentomyia hodgsoni Sinton (2), Sergentomyia africana Newstead (2), Sergentomyia squamipleuris Newstead (36), Sergentomyia dentata Sinton (3), Sergentomyia clydei Sinton (11), Sergentomyia sintoni Pringle (7), Sergentomyia iranica Lewis and Mesghali (4), and Sergentomyia pawlowskyi Perfiliev (2). This is the first study on the sand fly fauna of Bashagard. Overall, based on the results of our field study and other earlier works (Mesghali 1965; Oshaghi 1989; Soleimani Ahmadi et al. 1998; Hanafi-Bojd et al. 2006; Azizi and Fekri 2011; Azizi et al. 2011a, 2011b, 2012), 27 sand fly species have been reported from the Hormozgan Province including 12 Phlebotomus and 15 Sergentomyia. Phlebotomus alexandri, P. bergeroti, Phlebotomus eleanorae Sinton, Phlebotomus kazeruni Theodor and Mesghali, Phlebotomus keshishiani Shchurenkova, Phlebotomus longiductus Parrot, Phlebotomus jacusieli Theodor, Phlebotomus major (P. neglectus Tonnoir), Phlebotomus mongolensis Sinton, P. papatasi, P. salehi, P. sergenti s.l., S. africana, Sergentomyia antennata Newstead, S. baghdadis, Sergentomyia christophersi Sinton, S. clydei, S. dentata, S. hodgsoni Sinton, S. iranica, S. mervynae, Sergentomyia palestinensis Adler and Theodor, S. pawlowskyi, S. sintoni, S. squamipleuris, Sergentomyia theodori Parrot and S. tiberiadis Adler were reported in the study area. The spatial distributions of different species are mapped in Figs. 3 and 4. Red circles show the collection record(s) for each species, whereas green ones are collection sites with no record for that sand fly. Fig. 3. View largeDownload slide Spatial distribution of genus Phlebotomus in Hormozgan Province, South of Iran. Fig. 3. View largeDownload slide Spatial distribution of genus Phlebotomus in Hormozgan Province, South of Iran. Fig. 4. View largeDownload slide Spatial distribution of genus Sergentomyia in Hormozgan Province, South of Iran. Fig. 4. View largeDownload slide Spatial distribution of genus Sergentomyia in Hormozgan Province, South of Iran. Results of MaxEnt model showed the probability of presence for P. papatasi ranges from 0.0003 to 0.9410. This species was more active in Bandar-e Jask, Sirik, Bandar Abbas, Qesham, and Parsian Counties, compared to other areas (Fig. 5). For P. sergenti s.l., this range was found to be 0.0031–0.8880. This sand fly has more suitable ecological niches in Hajiabad, Bandar Abbas, Qeshm, Bashagard, Parsian, and Bastak Counties (Fig. 5). The area under curve (AUC) for P. papatasi and P. sergenti s.l. was 0.870 and 0.886, respectively. The area under the receiver operator characteristic (ROC) curve (AUC) is the statistic most frequently used to characterize model performance. This value is a number between 0 and 1, with the explanation that the closer to 1, the prediction of the model is more credible. Fig. 5. View largeDownload slide Presence probability of P. papatasi (left) and P. sergenti s.l.(right) in Hormozgan Province, Southern Iran. Fig. 5. View largeDownload slide Presence probability of P. papatasi (left) and P. sergenti s.l.(right) in Hormozgan Province, Southern Iran. Jackknife analysis for P. sergenti s.l. showed that the environmental variable with the highest gain when used in isolation was bio16, whereas bio5 decreased the gain the most when it was omitted. For P. papatasi, the environmental variable with both the highest and the lowest gain on the model was altitude (Fig. 6). Figure 7 shows the response of these two sand fly species to the variables used for modeling. Fig. 6. View largeDownload slide Jackknife of regulated training gains for P. papatasi (left) and P. sergenti s.l. (right) in Hormozgan Province, Southern Iran. Fig. 6. View largeDownload slide Jackknife of regulated training gains for P. papatasi (left) and P. sergenti s.l. (right) in Hormozgan Province, Southern Iran. Fig. 7. View largeDownload slide Most effective environmental variables in modeling niches of P. papatasi and P. sergenti s.l. in Hormozgan Province, South of Iran. Fig. 7. View largeDownload slide Most effective environmental variables in modeling niches of P. papatasi and P. sergenti s.l. in Hormozgan Province, South of Iran. During 2005–2015, a total of 2531 CL cases were reported from the study area. The disease was more prevalent in Bandar-e Jask and Bastak Counties, followed by Hajiabad and Bandar Abbas (Fig. 8). Fig. 8. View largeDownload slide Average number of Cutaneous Leishmaniasis cases during 2005–2015. Fig. 8. View largeDownload slide Average number of Cutaneous Leishmaniasis cases during 2005–2015. Discussion This study has found a new fauna of sand flies in Bashagard County located in northeastern part of Hormozgan Province. Earlier studies in Iran confirmed records of 50 species (Karimi et al. 2014), out of them 27 species are reported in Hormozgan Province. Considering report of CL cases from different Counties of this province (Soleimani Ahmadi et al. 1998, 2004, Hanafi-Bojd et al. 2006, Azizi and Fekri 2011, Azizi et al. 2011a, 2011b), it is important to predict the distribution of confirmed/potential vector species. P. papatasi is mostly distributed in semiarid and arid regions of the old world from Morocco to Indian subcontinent, whereas P. sergenti s.l. is a Mediterranean species, reported from south of Europe and north of Africa to north of the Indian subcontinent. These species are proven vectors of CL in the old world (Maroli 2013) and different foci of the disease in Iran (Karimi et al. 2014). MaxEnt is a modeling approach for predicting the ecological niches for different species of insects, animals, and plants. This model has been used for sand flies modeling in Iran as well. Modeling the distribution of sand flies has been done for both visceral and CL vectors in the country (Hanafi-Bojd et al. 2015a, 2015b), and the endemic areas for the disease as well (Abedi-Astaneh et al. 2015, Sofizadeh et al. 2017). In this investigation, bio16 (Precipitation of the Wettest Quarter) and altitude had the highest gain when used in isolation for P. sergenti and P. papatasi, respectively. On the other hand, for P. papatasi, there was a positive gain in the areas with an altitude of 0–100 m, and then it sharply dropped, whereas increasing bio16 had a negative effect on its gain in the model for P. sergenti s.l. (Fig. 7). These variables were bio8 (Mean Temperature of the Wettest Quarter) in the Country level study (Hanafi-Bojd et al. 2015a), bio16 in central Iran (Abedi-Astaneh et al. 2015) and slope in northeastern endemic area for CL (Sofizadeh et al. 2017). In other studies, there was a clear association between low elevations and CL incidence in northeastern Iran (Mollalo et al. 2015). This variable had the most effect on the distribution of sand flies in some recent investigations (Simsek et al. 2007, Ozbel et al. 2011, Kassem et al. 2012, Abdel-Dayem et al. 2012). Land cover have had a strong contribution in the distribution of sand flies and a survey raised that the urban area was correlated with high probability of sand flies (Colacicco-Mayhugh et al. 2010). Mean monthly temperature range of 16–44°C was determined to be favorable for P. papatasi (Cross et al. 1996). The area under curve (AUC) for P. papatasi and P. sergenti s.l. was 0.870 and 0.886, respectively. Although this value was reported to be more than 0.9 in recent studies in Iran (Hanafi-Bojd et al. 2015a, Abedi-Astaneh et al. 2015, Sofizadeh et al. 2017), our results also showed enough validity of the model. Prediction of the model for ecological niches of CL vectors in this study showed the most favorable niche to be the same as the spatial distribution of the disease based on the data provided by health centers. Among other sand fly species recorded from Hormozgan Province, there were three vectors of Visceral Leishmaniasis (VL), i.e., P. major, P. keshishiani, and P. alexandri. The latter was confirmed to be infected with Leishmania infantum Nicolle (Trypanosomatida: Trypanosomatidae) in Fars province, northwest of the study area (Azizi et al. 2006). Although the number of collection sites was not enough to be used for modeling these species, an earlier study conducted in the Country level predicted very low probability of presence for P. major and P. alexandri in Hormozgan Province (Hanafi-Bojd et al. 2015b). So, it is unlikely to establish foci of VL in Hormozgan Province. There were no reported cases of the disease to confirm our assertion in this regard. Activity of sand flies in Qeshm Island also included two peaks, the first and biggest one took place in October, whereas the activity in the environment stopped during December–February. During these months, the average of minimum monthly temperature dropped below 16°C (12.4–15.7). This shows the same temporal trend as other studies in tropical areas of southern Iran (Azizi and Fekri 2011, Karimi et al. 2014). Other studies on sand flies in Iran showed a short active season with one peak in August in northwestern foci of Leishmaniasis (Hazratian et al. 2011), as well as seven to eight months of activity including two peaks in May and September; the latter being the biggest (Karimi et al. 2014, Abedi-Astaneh et al. 2015). Temperature can be considered as the most important environmental variable with critical effect on the length of seasonal activity. In a study conducted in central Iran (Abedi-Astaneh et al. 2015), the minimum threshold of temperature was found to have a monthly average of 16°C. In this study, we found that the sand fly population dropped during July–August, the warmest period of the time in Qeshm Island. The mean monthly average of maximum temperature in these months was recorded as 37–38°C. This value can be considered as a threshold in which the sand fly activity will be stopped. So, it was easy to model spatio-temporal distribution of P. papatasi across the areas at risk of ZCL. Earlier studies confirmed the circulation of L. major in humans, gerbils and P. papatasi in Hormozgan Province (Soleimani Ahmadi et al. 1998, Hanafi-Bojd et al. 2006, Azizi et al. 2011a, 2011b). The zoonotic form of Leishmaniasis is more prevalent in the province and should be a focus for control and prevention programs. The incidence of CL in Hormozgan Province was reported as 22/100,000 for the last 3 decades although this value has decreased significantly to 6.39/100,000 in recent years. Hot spots of the disease based on incidence are; Ilam, Fars, Khorassan-e-Razavi and Isfahan in recent years, although 17 out of 31 provinces in Iran have endemic foci (Holakouie-Naieni et al. 2016, Norouzinejad et al. 2016). Moreover, risk assessment and vulnerability analysis are necessary to make proper decision and do targeted interventions. Hormozgan Province is one of the economic poles of Iran, and so many developmental projects are running. These projects will lead to population movements from endemic areas of CL or to clear regions. Lack of attention to this issue will lead to risk of epidemics in some regions. In conclusion, proven and suspected vectors of CL and VL were recorded from Hormozgan Province. Due to existence of the endemic foci of CL, and favorite ecological niches for its vectors, there is potential risk of emerging CL in new areas. Spatio-temporal analysis of vector activity will allow authorities and stakeholders to plan and implement preventive and control programs to limit the transmission and will be a good and applicable step for towards the elimination of CL in the area. Acknowledgment The authors are grateful to the kindness and hospitability displayed by the people of Bashagard and Qeshm for their collaboration during the field study. 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S., Ozbel Y., Aytekin A. M., Kaynas S., Belen A., Kasap O. E., Yaman M., and Rastgeldi S.. 2007. Distribution and altitudinal structuring of phlebotomine sand flies (Diptera: Psychodidae) in southern Anatolia, Turkey: their relation to human cutaneous leishmaniasis. J. Vec. Ecol . 32: 269– 279. Google Scholar CrossRef Search ADS   Smart, J., Jordan K., and Whittick R. J.. 1965. Insects of Medical Importance , 4th ed. Adlen Press, Oxford. Sofizadeh, A., Rassi Y., Vatandoost H., Hanafi-Bojd A. A., Mollalo A., Rafizadeh S., and Akhavan A. A.. 2017. Predicting the distribution of Phlebotomus papatasi (Diptera: Psychodidae), the primary vector of zoonotic cutaneous leishmaniasis, in Golestan Province of Iran using ecological niche modeling: Comparison of MaxEnt and GARP models. J. Med. Entomol . 54: 32– 320. Soleimani Ahmadi, M., Javadian E., A., Raeisi, and Yaghoobi-Ershadi M. R.. 1998. Study on entomology’s fauna of psychodidae in Kahurestan area Bandar Abbas, 1998. Hormozgan Univ. Med. J . 2: 25– 31 (In Persian). Soleimani Ahmadi, M., Dindarlou K., and Zare Sh.. 2004. Study on vectors of cutaneous leishmaniasis in Bastak, Hormozgan Province, 2003. Hormozgan Univ. Med. J . 8: 85– 89 (In Persian). Theodor, O. and Mesghali A.. 1964. On the phlebotominae of Iran. J. Med. Entomol . 1: 285– 300. Google Scholar CrossRef Search ADS PubMed  Yaghoobi-Ershadi, M. R. 2012. Phlebotomine sand flies (Diptera: Psychodidae) in Iran and their role on Leishmania transmission. J. Arthropod-Borne Dis . 6: 1– 17. Google Scholar PubMed  © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Medical Entomology Oxford University Press

Species Composition of Sand Flies (Diptera: Psychodidae) and Modeling the Spatial Distribution of Main Vectors of Cutaneous Leishmaniasis in Hormozgan Province, Southern Iran

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Entomological Society of America
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0022-2585
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10.1093/jme/tjx205
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Abstract

Abstract Cutaneous Leishmaniasis (CL) is one of the main neglected vector-borne diseases in the Middle East, including Iran. This study aimed to map the spatial distribution and species composition of sand flies in Hormozgan Province and to predict the best ecological niches for main CL vectors in this area. A database that included all earlier studies on sand flies in Hormozgan Province was established. Sand flies were also collected from some localities across the province. Prediction maps for main vectors were developed using MaxEnt model. A total of 27 sand fly species were reported from the study area. Phlebotomus papatasi Scopoli, Phlebotomus sergenti s.l. Parrot, Phlebotomus alexandri Sinton, Sergentomyia sintoni Pringle, Sergentomyia clydei Sinton, Sergentomyia tiberiadis Adler, and Sergentomyia baghdadis Adler (Diptera: Psychodidae) had the widest distribution range. The probability of their presence as the main vectors of CL was calculated to be 0.0003–0.9410 and 0.0031–0.8880 for P. papatasi and P. sergenti s.l., respectively. The best ecological niches for P. papatasi were found in the central south, southeast, and a narrow area in southwest, whereas central south to northern area had better niches for P. sergenti s.l. The endemic areas are in Bandar-e Jask, where transmission occurs, whereas in Bastak, the cases were imported from endemic foci of Fars province. In conclusion, proven and suspected vectors of CL and VL were recorded in this study. Due to the existence of endemic foci of CL, and favorite ecological niches for its vectors, there is potential risk of emerging CL in new areas. Sand fly, Psychodidae, Leishmaniasis, Niche Modeling Cutaneous Leishmaniasis (CL) is one of the most important vector-borne diseases in some parts of the world, including Iran. The endemic foci of the disease are in 18 out of 31 provinces of Iran and about 80% are due to Zoonotic Cutaneous Leishmaniasis (ZCL). Anthroponotic Cutaneous Leishmaniasis (ACL) is responsible for the remaining percentage (Yaghoobi-Ershadi 2012). Phlebotomine sand flies (Diptera: Psychodidae) are well known to be the vectors of Leishmaniasis. Previous studies have reported 50 species of sand flies from different parts of Iran (Karimi et al. 2014). Two out of these species, i.e., Phlebotomus papatasi Scopoli and Phlebotomus sergenti s.l. Parrot are considered to be the main vectors of CL. Phlebotomus salehi Mesghali is the suspected/secondary vector in some endemic foci of the disease in south and southeast parts of Iran (Kasiri and Javadian 2000, Davami et al. 2011, Azizi et al. 2012). There are few studies on species composition and spatial distribution of sand flies in Hormozgan Province, southern Iran. Study on sand flies of this province dated back to 1954–1964, when 18 species were recorded and reported for the first time by Mesghali (Mesghali 1965). During the campaign toward malaria elimination in this province, two rounds of indoor residual spraying were conducted annually, resulted in reduced cases of CL as well. Malaria elimination in most areas of the country and stopping of sprays against it increased the population of vectors of other diseases, such as leishmaniasis. Also, climate change, land use changes, and urbanization development led to an increase in leishmaniasis in Iran. Following the above study that established a base line data for sand flies in Hormozgan, there was another study on Phlebotominae in Hormozgan during 1988–1989 (Oshaghi 1989) and reported 16 species, from which three species were found to be new to the fauna of that area. After the successful implementation of malaria elimination program, insecticide applications were reduced and limited to some parts of Iran. Due to the reduction and restriction of insecticide use in some areas, the incidence of CL was noticed to have increased, and some epidemics were recorded. Different studies were conducted to find the epidemiological aspects of CL in three foci of the disease in Bandar Abbas (Soleimani Ahmadi et al. 1998), Hajiabad (Hanafi-Bojd et al. 2006), and Bandar-e Jask (Azizi et al. 2012) Counties. Due to the strategic location of Hormozgan Province and wide implementation of developmental projects, especially in its sea ports, it is necessary to clarify the potentials of CL transmission. So, periodic studies are necessary to update the fauna and species richness of sand flies in different parts of this province, to find the transmission potential and for preparation to combat the disease when needed. The aim of this study was to establish a database on sand flies in Hormozgan Province, to determine their geographical species composition, and to model the spatial distribution of the main vector(s) of CL in the area. Materials and Methods Study Area The study was conducted in Hormozgan Province, in the northern parts of Persian Gulf, Iran. It covers an area of 68,476 km2 with coordinates of 25.4–28.95° N, 53.68–59.25° E (Fig. 1). The population was 1,676,000, of which 51.2% are living in urban areas and 48.8% in rural areas. North of the province is a mountains area whereas the southern part is lowland and bordered with Persian Gulf and Oman Sea. The regional climate is generally arid and semiarid. The weather in coastal line is very hot and humid in summer and mild in winter, with low precipitation. Fig. 1. View largeDownload slide An altitudinal perspective from the Study area, Hormozgan Province, Southern Iran. Fig. 1. View largeDownload slide An altitudinal perspective from the Study area, Hormozgan Province, Southern Iran. Data Collection and Analysis To update the data on the fauna of sand flies in the study area, sampling was conducted monthly in Qeshm Island and seasonally in Bashagard County during spring and summer of 2014. Site selection was constrained by the potential and productivity of various areas for breeding sand flies. A GPS device was used to record the sand fly collection sites. Sand flies from each station were collected from both indoors and outdoors using sticky paper traps coated with castor oil. The traps were installed before sunset and picked up in the next early morning before sunrise. The captured sand flies were kept in 70% ethyl alcohol until they were mounted in Puri’s medium (Smart et al. 1965) and were identified morphologically (Theodor and Mesghali 1964, Seyedi-Rashti and Nadim 1992). The results of this study were added to the former data on sand flies of Hormozgan Province in a geodatabase created in ArcMap 10.3. Disease Data Passive data recorded in Hormozgan Province health center were collected for 11 years during 2005–2015 at the County level. A CL database was developed in ArcGIS 10.3 and a quantitative map was created to show the mean of cases in this period. Modeling the Distribution of Sand Flies Model Variables Bioclimatic variables and altitude layers were obtained from the WorldClim global climate database (http://www.worldclim.org/current) at a spatial resolution of 1 km2. These variables were derived from the long term (1950–2000) monthly temperature and rainfall values to generate more biologically meaningful variables. The bioclimatic variables represent annual trends, seasonality, and extreme or limiting environmental factors (Table 1). Spatial analyst of ArcGIS 10.3 was used to prepare Slope and Aspect (the compass direction that a slope faces) layers from Altitude. Then, layers were changed to ASCII raster using ArcMap 10.3conversion tool for their subsequent use in MaxEnt model. Table 1. Variables used to predict the potential distribution of Phlebotomus papatasi and P. sergenti s.l., as vectors of Cutaneous Leishmaniasis in Hormozgan Province, Southern Iran Variable  Description  Contribution (%)  P. papatasi  P. sergenti s.l.  Altitude  Elevation above the sea level (m)  67.2  1.2  BIO1  Annual Mean Temperature (oC)  2.2  0  BIO2  Mean Diurnal Range (Mean of monthly (max temp - min temp)) (oC)  2.6  0  BIO3  Isothermality (BIO2/BIO7) (×100)  9.3  9.5  BIO4  Temperature Seasonality (standard deviation ×100)  0.6  7.2  BIO5  Max Temperature of Warmest Month (°C)  0.8  12.6  BIO6  Min Temperature of Coldest Month (°C)  0.5  3.9  BIO7  Temperature Annual Range (BIO5-BIO6) (°C)  0.3  0  BIO8  Mean Temperature of Wettest Quarter (°C)  0  0  BIO9  Mean Temperature of Driest Quarter (°C)  8.1  4  BIO10  Mean Temperature of Warmest Quarter (°C)  0  4.2  BIO11  Mean Temperature of Coldest Quarter (°C)  0.2  0  BIO12  Annual Precipitation (mm)  0  1.2  BIO13  Precipitation of Wettest Month (mm)  5.1  29  BIO14  Precipitation of Driest Month (mm)  0.6  0.2  BIO15  Precipitation Seasonality (Coefficient of Variation)  1.8  0  BIO16  Precipitation of Wettest Quarter (mm)  0  0.1  BIO17  Precipitation of Driest Quarter (mm)  0  2  BIO18  Precipitation of Warmest Quarter (mm)  0.6  0  BIO19  Precipitation of Coldest Quarter (mm)  0  24.9  Variable  Description  Contribution (%)  P. papatasi  P. sergenti s.l.  Altitude  Elevation above the sea level (m)  67.2  1.2  BIO1  Annual Mean Temperature (oC)  2.2  0  BIO2  Mean Diurnal Range (Mean of monthly (max temp - min temp)) (oC)  2.6  0  BIO3  Isothermality (BIO2/BIO7) (×100)  9.3  9.5  BIO4  Temperature Seasonality (standard deviation ×100)  0.6  7.2  BIO5  Max Temperature of Warmest Month (°C)  0.8  12.6  BIO6  Min Temperature of Coldest Month (°C)  0.5  3.9  BIO7  Temperature Annual Range (BIO5-BIO6) (°C)  0.3  0  BIO8  Mean Temperature of Wettest Quarter (°C)  0  0  BIO9  Mean Temperature of Driest Quarter (°C)  8.1  4  BIO10  Mean Temperature of Warmest Quarter (°C)  0  4.2  BIO11  Mean Temperature of Coldest Quarter (°C)  0.2  0  BIO12  Annual Precipitation (mm)  0  1.2  BIO13  Precipitation of Wettest Month (mm)  5.1  29  BIO14  Precipitation of Driest Month (mm)  0.6  0.2  BIO15  Precipitation Seasonality (Coefficient of Variation)  1.8  0  BIO16  Precipitation of Wettest Quarter (mm)  0  0.1  BIO17  Precipitation of Driest Quarter (mm)  0  2  BIO18  Precipitation of Warmest Quarter (mm)  0.6  0  BIO19  Precipitation of Coldest Quarter (mm)  0  24.9  View Large Modeling Potential Occurrence of Sand Flies MaxEnt software Ver. 3.3.3 was used to predict the most appropriate ecological niches for targeted species (Phillips et al. 2006).The contribution of the environmental variables was calculated by Jackknife analysis. Table 1 shows estimates of relative contributions of the environmental variables to the MaxEnt model for CL vectors. Variables with no contribution were omitted from the final analysis. Eighty percent of sand fly collection points were used for model training and 20% kept for testing the results. Point selection process was done by MaxEnt in random. Results In our present entomological studies in Qeshm Island, just two species, i.e., 809 P. papatasi (96.2%) and 32 Sergentomyia baghdadis Adler (3.8%) were collected and identified. Out of these species, 75% were collected from indoors and 25% from outdoors. There were two peaks of activity observed in this island during the collection, the first and biggest was between March and April whereas the second and smallest was between September and October (Fig. 2). Efforts made for sand fly collection in Abu Musa, Greater Tunb, and Lesser Tunb islands yielded no results, despite installing 1440 sticky paper traps during the study period. Fig. 2. View largeDownload slide Monthly activity of sand flies in Qeshm Island, Hormozgan Province, 2014. Fig. 2. View largeDownload slide Monthly activity of sand flies in Qeshm Island, Hormozgan Province, 2014. In Bashagard County 427 specimens were collected in three occasions and 15 species were identified: P. papatasi (4), Phlebotomus bergeroti Parrot (9), P. sergenti s.l. (6), Phlebotomus alexandri (20), Sergentomyia mervynae Pringle (28), Sergentomyia tiberiadis Adler (250), Sergentomyia baghdadis (43), Sergentomyia hodgsoni Sinton (2), Sergentomyia africana Newstead (2), Sergentomyia squamipleuris Newstead (36), Sergentomyia dentata Sinton (3), Sergentomyia clydei Sinton (11), Sergentomyia sintoni Pringle (7), Sergentomyia iranica Lewis and Mesghali (4), and Sergentomyia pawlowskyi Perfiliev (2). This is the first study on the sand fly fauna of Bashagard. Overall, based on the results of our field study and other earlier works (Mesghali 1965; Oshaghi 1989; Soleimani Ahmadi et al. 1998; Hanafi-Bojd et al. 2006; Azizi and Fekri 2011; Azizi et al. 2011a, 2011b, 2012), 27 sand fly species have been reported from the Hormozgan Province including 12 Phlebotomus and 15 Sergentomyia. Phlebotomus alexandri, P. bergeroti, Phlebotomus eleanorae Sinton, Phlebotomus kazeruni Theodor and Mesghali, Phlebotomus keshishiani Shchurenkova, Phlebotomus longiductus Parrot, Phlebotomus jacusieli Theodor, Phlebotomus major (P. neglectus Tonnoir), Phlebotomus mongolensis Sinton, P. papatasi, P. salehi, P. sergenti s.l., S. africana, Sergentomyia antennata Newstead, S. baghdadis, Sergentomyia christophersi Sinton, S. clydei, S. dentata, S. hodgsoni Sinton, S. iranica, S. mervynae, Sergentomyia palestinensis Adler and Theodor, S. pawlowskyi, S. sintoni, S. squamipleuris, Sergentomyia theodori Parrot and S. tiberiadis Adler were reported in the study area. The spatial distributions of different species are mapped in Figs. 3 and 4. Red circles show the collection record(s) for each species, whereas green ones are collection sites with no record for that sand fly. Fig. 3. View largeDownload slide Spatial distribution of genus Phlebotomus in Hormozgan Province, South of Iran. Fig. 3. View largeDownload slide Spatial distribution of genus Phlebotomus in Hormozgan Province, South of Iran. Fig. 4. View largeDownload slide Spatial distribution of genus Sergentomyia in Hormozgan Province, South of Iran. Fig. 4. View largeDownload slide Spatial distribution of genus Sergentomyia in Hormozgan Province, South of Iran. Results of MaxEnt model showed the probability of presence for P. papatasi ranges from 0.0003 to 0.9410. This species was more active in Bandar-e Jask, Sirik, Bandar Abbas, Qesham, and Parsian Counties, compared to other areas (Fig. 5). For P. sergenti s.l., this range was found to be 0.0031–0.8880. This sand fly has more suitable ecological niches in Hajiabad, Bandar Abbas, Qeshm, Bashagard, Parsian, and Bastak Counties (Fig. 5). The area under curve (AUC) for P. papatasi and P. sergenti s.l. was 0.870 and 0.886, respectively. The area under the receiver operator characteristic (ROC) curve (AUC) is the statistic most frequently used to characterize model performance. This value is a number between 0 and 1, with the explanation that the closer to 1, the prediction of the model is more credible. Fig. 5. View largeDownload slide Presence probability of P. papatasi (left) and P. sergenti s.l.(right) in Hormozgan Province, Southern Iran. Fig. 5. View largeDownload slide Presence probability of P. papatasi (left) and P. sergenti s.l.(right) in Hormozgan Province, Southern Iran. Jackknife analysis for P. sergenti s.l. showed that the environmental variable with the highest gain when used in isolation was bio16, whereas bio5 decreased the gain the most when it was omitted. For P. papatasi, the environmental variable with both the highest and the lowest gain on the model was altitude (Fig. 6). Figure 7 shows the response of these two sand fly species to the variables used for modeling. Fig. 6. View largeDownload slide Jackknife of regulated training gains for P. papatasi (left) and P. sergenti s.l. (right) in Hormozgan Province, Southern Iran. Fig. 6. View largeDownload slide Jackknife of regulated training gains for P. papatasi (left) and P. sergenti s.l. (right) in Hormozgan Province, Southern Iran. Fig. 7. View largeDownload slide Most effective environmental variables in modeling niches of P. papatasi and P. sergenti s.l. in Hormozgan Province, South of Iran. Fig. 7. View largeDownload slide Most effective environmental variables in modeling niches of P. papatasi and P. sergenti s.l. in Hormozgan Province, South of Iran. During 2005–2015, a total of 2531 CL cases were reported from the study area. The disease was more prevalent in Bandar-e Jask and Bastak Counties, followed by Hajiabad and Bandar Abbas (Fig. 8). Fig. 8. View largeDownload slide Average number of Cutaneous Leishmaniasis cases during 2005–2015. Fig. 8. View largeDownload slide Average number of Cutaneous Leishmaniasis cases during 2005–2015. Discussion This study has found a new fauna of sand flies in Bashagard County located in northeastern part of Hormozgan Province. Earlier studies in Iran confirmed records of 50 species (Karimi et al. 2014), out of them 27 species are reported in Hormozgan Province. Considering report of CL cases from different Counties of this province (Soleimani Ahmadi et al. 1998, 2004, Hanafi-Bojd et al. 2006, Azizi and Fekri 2011, Azizi et al. 2011a, 2011b), it is important to predict the distribution of confirmed/potential vector species. P. papatasi is mostly distributed in semiarid and arid regions of the old world from Morocco to Indian subcontinent, whereas P. sergenti s.l. is a Mediterranean species, reported from south of Europe and north of Africa to north of the Indian subcontinent. These species are proven vectors of CL in the old world (Maroli 2013) and different foci of the disease in Iran (Karimi et al. 2014). MaxEnt is a modeling approach for predicting the ecological niches for different species of insects, animals, and plants. This model has been used for sand flies modeling in Iran as well. Modeling the distribution of sand flies has been done for both visceral and CL vectors in the country (Hanafi-Bojd et al. 2015a, 2015b), and the endemic areas for the disease as well (Abedi-Astaneh et al. 2015, Sofizadeh et al. 2017). In this investigation, bio16 (Precipitation of the Wettest Quarter) and altitude had the highest gain when used in isolation for P. sergenti and P. papatasi, respectively. On the other hand, for P. papatasi, there was a positive gain in the areas with an altitude of 0–100 m, and then it sharply dropped, whereas increasing bio16 had a negative effect on its gain in the model for P. sergenti s.l. (Fig. 7). These variables were bio8 (Mean Temperature of the Wettest Quarter) in the Country level study (Hanafi-Bojd et al. 2015a), bio16 in central Iran (Abedi-Astaneh et al. 2015) and slope in northeastern endemic area for CL (Sofizadeh et al. 2017). In other studies, there was a clear association between low elevations and CL incidence in northeastern Iran (Mollalo et al. 2015). This variable had the most effect on the distribution of sand flies in some recent investigations (Simsek et al. 2007, Ozbel et al. 2011, Kassem et al. 2012, Abdel-Dayem et al. 2012). Land cover have had a strong contribution in the distribution of sand flies and a survey raised that the urban area was correlated with high probability of sand flies (Colacicco-Mayhugh et al. 2010). Mean monthly temperature range of 16–44°C was determined to be favorable for P. papatasi (Cross et al. 1996). The area under curve (AUC) for P. papatasi and P. sergenti s.l. was 0.870 and 0.886, respectively. Although this value was reported to be more than 0.9 in recent studies in Iran (Hanafi-Bojd et al. 2015a, Abedi-Astaneh et al. 2015, Sofizadeh et al. 2017), our results also showed enough validity of the model. Prediction of the model for ecological niches of CL vectors in this study showed the most favorable niche to be the same as the spatial distribution of the disease based on the data provided by health centers. Among other sand fly species recorded from Hormozgan Province, there were three vectors of Visceral Leishmaniasis (VL), i.e., P. major, P. keshishiani, and P. alexandri. The latter was confirmed to be infected with Leishmania infantum Nicolle (Trypanosomatida: Trypanosomatidae) in Fars province, northwest of the study area (Azizi et al. 2006). Although the number of collection sites was not enough to be used for modeling these species, an earlier study conducted in the Country level predicted very low probability of presence for P. major and P. alexandri in Hormozgan Province (Hanafi-Bojd et al. 2015b). So, it is unlikely to establish foci of VL in Hormozgan Province. There were no reported cases of the disease to confirm our assertion in this regard. Activity of sand flies in Qeshm Island also included two peaks, the first and biggest one took place in October, whereas the activity in the environment stopped during December–February. During these months, the average of minimum monthly temperature dropped below 16°C (12.4–15.7). This shows the same temporal trend as other studies in tropical areas of southern Iran (Azizi and Fekri 2011, Karimi et al. 2014). Other studies on sand flies in Iran showed a short active season with one peak in August in northwestern foci of Leishmaniasis (Hazratian et al. 2011), as well as seven to eight months of activity including two peaks in May and September; the latter being the biggest (Karimi et al. 2014, Abedi-Astaneh et al. 2015). Temperature can be considered as the most important environmental variable with critical effect on the length of seasonal activity. In a study conducted in central Iran (Abedi-Astaneh et al. 2015), the minimum threshold of temperature was found to have a monthly average of 16°C. In this study, we found that the sand fly population dropped during July–August, the warmest period of the time in Qeshm Island. The mean monthly average of maximum temperature in these months was recorded as 37–38°C. This value can be considered as a threshold in which the sand fly activity will be stopped. So, it was easy to model spatio-temporal distribution of P. papatasi across the areas at risk of ZCL. Earlier studies confirmed the circulation of L. major in humans, gerbils and P. papatasi in Hormozgan Province (Soleimani Ahmadi et al. 1998, Hanafi-Bojd et al. 2006, Azizi et al. 2011a, 2011b). The zoonotic form of Leishmaniasis is more prevalent in the province and should be a focus for control and prevention programs. The incidence of CL in Hormozgan Province was reported as 22/100,000 for the last 3 decades although this value has decreased significantly to 6.39/100,000 in recent years. Hot spots of the disease based on incidence are; Ilam, Fars, Khorassan-e-Razavi and Isfahan in recent years, although 17 out of 31 provinces in Iran have endemic foci (Holakouie-Naieni et al. 2016, Norouzinejad et al. 2016). Moreover, risk assessment and vulnerability analysis are necessary to make proper decision and do targeted interventions. Hormozgan Province is one of the economic poles of Iran, and so many developmental projects are running. These projects will lead to population movements from endemic areas of CL or to clear regions. Lack of attention to this issue will lead to risk of epidemics in some regions. In conclusion, proven and suspected vectors of CL and VL were recorded from Hormozgan Province. Due to existence of the endemic foci of CL, and favorite ecological niches for its vectors, there is potential risk of emerging CL in new areas. Spatio-temporal analysis of vector activity will allow authorities and stakeholders to plan and implement preventive and control programs to limit the transmission and will be a good and applicable step for towards the elimination of CL in the area. Acknowledgment The authors are grateful to the kindness and hospitability displayed by the people of Bashagard and Qeshm for their collaboration during the field study. 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Journal of Medical EntomologyOxford University Press

Published: Mar 1, 2018

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