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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) o...

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Autores principales: Jahanifard, Elham, Hanafi-Bojd, Ahmad Ali, Nasiri, Hossein, Matinfar, Hamid Reza, Charrahy, Zabihollah, Abai, Mohammad Reza, Yaghoobi-Ershadi, Mohammad Reza, Akhavan, Amir Ahmad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Tehran University of Medical Sciences 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6928385/
https://www.ncbi.nlm.nih.gov/pubmed/31879670
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author Jahanifard, Elham
Hanafi-Bojd, Ahmad Ali
Nasiri, Hossein
Matinfar, Hamid Reza
Charrahy, Zabihollah
Abai, Mohammad Reza
Yaghoobi-Ershadi, Mohammad Reza
Akhavan, Amir Ahmad
author_facet Jahanifard, Elham
Hanafi-Bojd, Ahmad Ali
Nasiri, Hossein
Matinfar, Hamid Reza
Charrahy, Zabihollah
Abai, Mohammad Reza
Yaghoobi-Ershadi, Mohammad Reza
Akhavan, Amir Ahmad
author_sort Jahanifard, Elham
collection PubMed
description 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.
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spelling pubmed-69283852019-12-26 Prone Regions of Zoonotic Cutaneous Leishmaniasis in Southwest of Iran: Combination of Hierarchical Decision Model (AHP) and GIS Jahanifard, Elham Hanafi-Bojd, Ahmad Ali Nasiri, Hossein Matinfar, Hamid Reza Charrahy, Zabihollah Abai, Mohammad Reza Yaghoobi-Ershadi, Mohammad Reza Akhavan, Amir Ahmad J Arthropod Borne Dis Original Article 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. Tehran University of Medical Sciences 2019-09-30 /pmc/articles/PMC6928385/ /pubmed/31879670 Text en Copyright© Iranian Society of Medical Entomology & Tehran University of Medical Sciences http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Jahanifard, Elham
Hanafi-Bojd, Ahmad Ali
Nasiri, Hossein
Matinfar, Hamid Reza
Charrahy, Zabihollah
Abai, Mohammad Reza
Yaghoobi-Ershadi, Mohammad Reza
Akhavan, Amir Ahmad
Prone Regions of Zoonotic Cutaneous Leishmaniasis in Southwest of Iran: Combination of Hierarchical Decision Model (AHP) and GIS
title Prone Regions of Zoonotic Cutaneous Leishmaniasis in Southwest of Iran: Combination of Hierarchical Decision Model (AHP) and GIS
title_full Prone Regions of Zoonotic Cutaneous Leishmaniasis in Southwest of Iran: Combination of Hierarchical Decision Model (AHP) and GIS
title_fullStr Prone Regions of Zoonotic Cutaneous Leishmaniasis in Southwest of Iran: Combination of Hierarchical Decision Model (AHP) and GIS
title_full_unstemmed Prone Regions of Zoonotic Cutaneous Leishmaniasis in Southwest of Iran: Combination of Hierarchical Decision Model (AHP) and GIS
title_short Prone Regions of Zoonotic Cutaneous Leishmaniasis in Southwest of Iran: Combination of Hierarchical Decision Model (AHP) and GIS
title_sort prone regions of zoonotic cutaneous leishmaniasis in southwest of iran: combination of hierarchical decision model (ahp) and gis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6928385/
https://www.ncbi.nlm.nih.gov/pubmed/31879670
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