Machine learning approaches in GIS-based ecological modeling of the sand fly Phlebotomus papatasi, a vector of zoonotic cutaneous leishmaniasis in Golestan province, Iran

Acta Tropica ◽  
2018 ◽  
Vol 188 ◽  
pp. 187-194 ◽  
Author(s):  
Abolfazl Mollalo ◽  
Ali Sadeghian ◽  
Glenn D. Israel ◽  
Parisa Rashidi ◽  
Aioub Sofizadeh ◽  
...  
2020 ◽  
Vol 57 (6) ◽  
pp. 1768-1774
Author(s):  
Aioub Sofizadeh ◽  
Kamran Akbarzadeh ◽  
Ehsan Allah Kalteh ◽  
Fatemeh Karimi

Abstract Zoonotic cutaneous leishmaniasis (ZCL) is prevalent in Golestan Province, Iran. The current study determined the relationship between the distribution and biodiversity of sand flies with cutaneous leishmaniasis at 14 villages in plain and hillsides areas. In each village from July to September 2017, 60 sticky traps and 2 CDC light traps were laid. Spearman and Mann–Whitney tests were used to determine the relationship between the incidence of ZCL and the abundance of different species of sand flies. Simpson, Shannon-Wiener, Evenness, and Margalef indices were calculated to estimate the diversity of species. A total of 5,295 phlebotomine sand flies were collected, comprising 10 species of the genus Phlebotomus (3,947 flies) and 7 species of genus Sergentomyia (1,248 flies). The abundance of sand flies and incidence of ZCL in plain areas were greater than that of hillsides areas (P = 0.013, P = 0.002). There was a significant correlation between the incidence of ZCL and the abundance of Phlebotomus papatasi (r = 0.72, P = 0.004) and P. caucasicus groups (P = 0.006; 0.022). In the Shannon-Wiener index, the rest of the biodiversity indices were reduced in higher-altitude areas. Increasing Shannon-Wiener index showed higher diversity of sand flies in higher-altitude areas. Data of the reported cases of leishmaniasis in plain areas can reveal the relationship between less diversity index (Shannon-Wiener), higher dominant diversity index (Simpson), and incidence of leishmaniasis in these areas.


2012 ◽  
Vol 68 (5) ◽  
pp. 669-675 ◽  
Author(s):  
Zahra Saeidi ◽  
Hassan Vatandoost ◽  
Amir Ahmad Akhavan ◽  
Mohamad Reza Yaghoobi-Ershadi ◽  
Yavar Rassi ◽  
...  

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