Volume 31, Issue 195 (4-2021)
J Mazandaran Univ Med Sci 2021, 31(195): 56-66 |
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Jahanifard E, Rajayi F, Nasiri H, Hamidinejat H, Vazirianzadeh B. Applying Network Analysis Process (ANP) and Geographic Information System (GIS) in Modeling the Probability of Crimean-Congo Hemorrhagic Fever (CCHF) Vector: Case Study in Ahvaz, Hamidiyeh, Bavy and Karoon Counties. J Mazandaran Univ Med Sci 2021; 31 (195) :56-66
URL: http://jmums.mazums.ac.ir/article-1-15700-en.html
URL: http://jmums.mazums.ac.ir/article-1-15700-en.html
Abstract: (1215 Views)
Background and purpose: Ticks, as ectoparasites, biological vectors and reservoirs of various diseases, are involved in transmission of pathogens to humans and animals. This research aimed at modeling the probability of tick vectors presence in Ahvaz, Hamidiyeh, Bavy, and Karoon in southwest of Iran.
Materials and methods: To perform the modeling, eight criteria (slope, elevation, soil texture, land use, land cover, temperature, humidity, and rainfall) that strongly affect the distribution of ticks were selected. After pairwise comparisons, Super Decision Software was used to determine the significance of each criteria and the weight of sub-criteria was calculated using Expert Choice11. Weighted maps were obtained based on the effect of sub-criteria weights on maps. The final map of the probability of tick vectors presence was prepared based on the weight effect of each criteria in the weighted maps.
Results: Average relative humidity (0.252), average rainfall (0.179), and land cover (0.151) were found to have the greatest effect on the probability of tick presence. Also, the highest probability of tick presence was seen in following cities and rural districts: Ahvaz, Hamidiyeh, Karoon, Bavy, Meshrahat, Karkheh, Qaleh Chenan, and Anafcheh.
Conclusion: In current modelling, considering ecological, topographic, and climatic factors, the probability of the presence of vectors of Crimean-Congo haemorrhagic fever (CCHF) virus was seen to be very high in two rural districts, including Mashrahat (Ahvaz) and Karkheh (Hamidiyeh).
Materials and methods: To perform the modeling, eight criteria (slope, elevation, soil texture, land use, land cover, temperature, humidity, and rainfall) that strongly affect the distribution of ticks were selected. After pairwise comparisons, Super Decision Software was used to determine the significance of each criteria and the weight of sub-criteria was calculated using Expert Choice11. Weighted maps were obtained based on the effect of sub-criteria weights on maps. The final map of the probability of tick vectors presence was prepared based on the weight effect of each criteria in the weighted maps.
Results: Average relative humidity (0.252), average rainfall (0.179), and land cover (0.151) were found to have the greatest effect on the probability of tick presence. Also, the highest probability of tick presence was seen in following cities and rural districts: Ahvaz, Hamidiyeh, Karoon, Bavy, Meshrahat, Karkheh, Qaleh Chenan, and Anafcheh.
Conclusion: In current modelling, considering ecological, topographic, and climatic factors, the probability of the presence of vectors of Crimean-Congo haemorrhagic fever (CCHF) virus was seen to be very high in two rural districts, including Mashrahat (Ahvaz) and Karkheh (Hamidiyeh).
Keywords: hard ticks, network analysis process, geographic information system, Crimean–Congo hemorrhagic fever
Type of Study: Research(Original) |
Subject:
Medical Entomology
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