Predicting the Probability of Phlebotomus Papatasi Presence in Khuzestan Province: Combining Hierarchical Analysis Process and Geographic Information System



Bigdeli S¹ ; Hanafibojd AA^{2, 3} ; Sharififard M⁴ ; Maraghi E⁵ ; Jahanifard E^{4, 6} Show Affiliations
Source: Journal of Mazandaran University of Medical Sciences Published:2022

Abstract

Background and purpose: Khuzestan Province in Iran is one of the endemic foci of zoonotic cutaneous leishmaniasis (ZCL) caused by Leishmania major and Phlebotomus papatasi as the main vector. The aim of this study was to predict the probability of presence of Ph. papatasi in this province using Hierarchical Analysis Process (AHP) and Geographic Information System (GIS). Materials and methods: In order to determine the distribution of Ph. papatasi, sand flies were collected in five counties, including Izeh, Mahshahr, Ahvaz, Dasht-e-Azadegan, and Andimeshk by sticky paper traps in spring and summer, 2018. Six criteria, including average annual temperature, average annual rainfall, average annual relative humidity, land use, soil texture, and elevation were selected. Maps of criteria were prepared in ArcGIS 10.5 software. The weights of the criteria and sub-criteria were determined using Expert Choice 11. Then, the final map of the probability of vector presence was prepared by combination of weighted maps and including the weight of the criteria. Results: In this study, 13 species of sand flies of two genera, Phlebotomus and Sergentomyia, were collected. The abundance of Ph. papatasi from samples collected in Izeh, Dasht-e-Azadegan, Mahshahr, Andimeshk, and Ahvaz was 55%, 72%, 69.4%, 3%, and 66.5%, respectively. Based on the analysis of matrix tables, average annual temperature (0.406), average annual relative humidity (0.233), and average annual rainfall (0.156) had the highest weight in probability of the vector presence, respectively. Conclusion: This study provides useful information for health authorities in determining the distribution of Ph. papatasi to act properly based on facilities and budget in case of outbreak. © 2022, Mazandaran University of Medical Sciences. All rights reserved.