(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. Journal of Entomological Research. pp. 315-322. ISSN 03789519 (ISSN)
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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. © 2020.
Item Type: | Article |
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Keywords: | AHP Cutaneous leishmaniasis Iran Khuzestan Risk map |
Subjects: | QX Parasitology > QX 1-45 Parasitology |
Divisions: | Other |
Page Range: | pp. 315-322 |
Journal or Publication Title: | Journal of Entomological Research |
Journal Index: | Scopus |
Volume: | 44 |
Number: | 2 |
Identification Number: | https://doi.org/10.5958/0974-4576.2020.00054.7 |
ISSN: | 03789519 (ISSN) |
Depositing User: | Zahra Otroj |
URI: | http://eprints.mui.ac.ir/id/eprint/12818 |
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