Modeling of at Risk Areas of Zoonotic Cutaneous Leishmaniasis (ZCL

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Modeling of at Risk Areas of Zoonotic Cutaneous Leishmaniasis (ZCL DOI : 10.5958/0974-4576.2020.00054.7 © J. ent. Res., 44 (2) : 315-322 (2020) Modeling of at risk areas of Zoonotic Cutaneous Leishmaniasis (ZCL) using Hierarchical Analysis Process (AHP) and Geographic Information System (GIS) in Southwest of Iran Elham Jahanifard*, Ahmad Ali Hanafi-Bojd**, Amir Ahmad Akhavan**, Mona Sharififard*, Atefeh Khazeni**** and Babak Vazirianzadeh*** *Social Determinants of Health Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran ABSTRACT Present study is concentrated on modeling of ZCL using eco-environmental and climatic elements in some counties situated in the center of the province and preparing their risk maps. Pairwise comparative matrices were designed based on 7 criteria, including mean temperature, mean humidity, mean rainfall, elevation, distance from river, land use and soil texture that were completed by leishmaniasis experts. The weight of criteria was obtained by Expert choice 11. The risk map was drawn using overlaying seven criteria and multiplying their weight derived from AHP method in ArcGIS10.5 software. The highest weight belongs to the climatic elements and the lowest weights were related to distance from the river. Also, very high- and high-risk areas were regarded as hot spots. The incidence rate of disease was calculated in Hamidyeh (6.5), Karoun (1.5), Ahvaz (1.03) and Bavy (0.726) per 10000 in 2017. The incidence rate of ZCL decreased in Bavy County to 0.4 per 10000 persons while the ZCL incidence rates were increased to 1.04, 6.7 and 1.7 per 10000 persons in Ahvaz, Hamidyeh and Karoun Counties in 2018, respectively. In two rural districts, Tarah and Jahad, of Hamidyeh County and the majority parts of Ahvaz County the risk of disease was predicted moderate. The risk map based on AHP and GIS is able to visualize the problems and help to Health policy makers to use the available evidence and make the best decision. Key words : AHP, Cutaneous leishmaniasis, Khuzestan, risk map, Iran. INTRODUCTION due to agricultural, urbanization, industrial activities, Leishmaniasis as neglected infectious and weak immune system and lack of financial resources vector- borne disease is caused by a variety species (WHO, 2019). Zoonotic cutaneous leishmaniasis of Leishmania parasite that transmit by sand flies is a common disease between human and animal species (Yaghoobi-Ershadi, 2012). Leishmaniasis is that environmental, ecological and geological an endemic disease in Iran and have three clinical factors can influence the distribution of the forms including zoonotic cutaneous leishmaniasis vector and the reservoir and consequently the (ZCL), anthroponetic cutaneous leishmaniasis (ACL) emergence of the disease (Salomón et al., 2012). and zoonotic visceral leishmaniasis (ZVL) due The most cases of CL occur in the Americas, the to Leishmania major, L. tropica and L. infantum, Mediterranean basin, the Middle East and Central respectively (Yaghoobi-Ershadi, 2012; Mohebali, Asia. More than 95% of new CL cases occurred 2013). The different forms of the disease are in 6 countries as follows: Afghanistan, Algeria, correlated to numerous factors including poverty, Brazil, Colombia, Iran, Iraq and the Syrian Arab malnutrition, population emigration, inappropriate Republic during 2017. New cases of cutaneous and poor housing, making environmental changes leishmaniasis are estimated to be 7,00,000 to 1 million and also some 26,000 to 65,000 deaths *Corresponding author's E-mail : [email protected], elham.jahani56@ gmail.com occur annually (WHO, 2019). Moreover, the new **Department of Medical Entomology & Vector Control, School of Public cases of zoonotic visceral leishmaniasis (ZVL) are Health, Tehran University of Medical Sciences, Tehran, Iran ***Department of Medical Entomology & Vector Control, School of Public about 100-300 in the country, annually (Mohebali, Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran 2013). Iran is one of counties in view of cases ****Isfahan Province Health Center, Isfahan University of Medical Sciences, Isfahan, Iran number of CL in the world in 2015 (Piroozi, Journal of Entomological Research, June 2020 2019). Zoonotic cutaneous leishmaniasis (ZCL) based MCDA used to spatio-temporal distribution is endemic in 18 of 31 provinces. About 80% of ZCL in Golestan Province, northeast of Iran (Mollalo cases reported in the country are in the form of and Khodabandehloo, 2016). Analytic Hierarchy ZCL (Yaghoobi-Ershadi, 2012). About 4700 cases of Process and AHP fuzzy were used to determine ZCL were reported from Khuzestan Province during the susceptibility map of visceral leishmaniasis in 2010-2014 (Ostad et al., 2016). More than 400 northwest of Iran (Rajabi et al., 2012). cases have been reported in the Dasht Azadegan, The Analytic Hierarchy Process (AHP) is an Ahvaz and Andimeshk Counties during 2009-2014 effective tool for dealing with complex decision (Khademvatan et al., 2017). The geographical making that introduced by Thomas Saaty (1970s). distribution in north parts of Khuzestan for L. major Furthermore, it is a method of measurement and L. tropica with the high amount were calculated with ratio scales that help the decision makers 91.84 and 8.16%, respectively (Maraghi et al., 2013). in complicated circumstances to judge and make the best decision (Saaty, 1987). This method is Geographic Information System (GIS) is used to one of the multi-criteria decision making analysis assess the impact of various factors on health, public (MCDA) which is applicable to solving complicated health, disease distribution, health care, and to help problems due to simplicity and making multilevel make a decision (Keola et al., 2002). Moreover, this hierarchies (Danesh et al., 2015). GIS-based MCDA software was used for ecological niche modeling was used for spatio-temporal distribution of ZCL of various vectors and distribution of vector-borne in Golestan Province, northeast of Iran (Mollalo disease (Zou et al., 2006). Environmental variables and Khodabandehloo, 2016). Analytic Hierarchy are considered as a risk factor of leishmaniasis Process and AHP fuzzy were used to determine the distribution (Sharifi et al., 2015). Furthermore, susceptibility map of VL in northwest of the country ecological factors (vegetation cover, elevation) in (Rajabi et al., 2012). Modeling based on MCDA in combination with environmental variables can be combination with GIS is a useful and affordable used for predicting and GIS modeling of vectors method to prevent, control and monitor the disease. of diseases and also it can be used for better The objective of this research is modeling and understanding the way in vector control program prediction of zoonotic cutaneous leishmaniasis risk (Bhunia et al., 2012; Tsegaw et al., 2013). In the map using GIS and AHP methods in some counties survey of eco-environmental risk factors of CL, the in the center of Khuzestan Province. The result result showed that rainy days, minimum temperature, can reduce field operations costs and increase the wind velocity, maximum relative humidity and ability of decision makers. population density were the most effective factors in distributing the disease (Ali-Akbarpour et al., 2012). MATERIALS AND METHODS Slope, precipitation of the wettest quarter and Study area : Khuzestan Province (29° 58’ N, 47° the mean temperature of coldest as topographical 41’ E and 33° 4’ N, 50° 39’ E) is situated in the and environmental variables are involved in the southwest of Iran in bordering Iraq and the Persian prediction of distribution of Rhombomys opimus, Meriones libycus and Tatera indica, respectively Gulf. This province has two regions: mountainous (Gholamrezaei et al., 2016). Another study in regions north of the Ahvaz ridge, and the plains and southwest of Iran showed soil texture, land cover and marshlands to its south. The area is irrigated by four land use are the most elements in the distribution rivers (Karoun, Karkheh, Jarahi and Maroun). The of Nesokia indica and T. indica (Jahanifard et al., climate of Khuzestan is generally very hot and humid, 2019). The Analytic Hierarchy Process (AHP) is an especially in the south, while winters are cold and effective tool that introduced by Thomas Saaty at dry. Furthermore, desert conditions and sandstorms 1970s. Furthermore, it is a method of measurement are also observed. Ahvaz County (30.883333 N, with ratio scales that help to the decision maker 48.016667 E and 31.766667 N, 49.3 E) is the capital in complicated circumstance to do judge and make of Khuzestan Province. The county distance to the the best decision (Saaty, 1987). This method is farthest city of Khuzestan in the northeast is 276 one of the multi-criteria decision making analysis km (Izeh) and the nearest is 30 km (Hamidiyeh in (MCDA) that is applicable to solving complicated the west of Ahvaz). The county is 18 m above sea decision problems due to simplicity and making level. The larger part of Khuzestan Province is in multilevel hierarchies (Danesh et al., 2015). GIS- the lowlands and Ahvaz is also in this area that it 316 Modeling of at risk areas of Zoonotic Cutaneous Leishmaniasis can be called the hottest areas of the country due AHP and predicting map of ZCL : Analytical Hierarchy to the lack of vegetation. Process is one of the main mathematical models and Karoun County (31.35 N, 48.683333 E and 31.7 multi-criteria techniques to support the decision theory N, 49.25 E) is situated in southwest of Khuzestan (Marinoni, 2004). This method developed in 1980 and in an area of over 5,000 Km2 and it is the fourth has experienced in various fields such as assessing, largest city in Khuzestan Province. The city has a designing, performance and decision making (Saaty warm and humid climate that reaches over 50°C and Vargas, 1991). The method summarized in nine in the hot summer. Hamidyeh County (30.883333 steps. Step 1: define alternatives, Step 2: organize N, 48.35 E and 31.266667 N, 48.9 E) is located at criteria, Step 3: make pairwise comparison, Step 25 Km from west of Ahvaz City in the Ahvaz road 4: collect input, Step 5: check consistency, Step 6: to Susanger City.
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