title: Susceptibility mapping of visceral leishmaniasis based on fuzzy modelling and group decision-making methods.
abstract: Visceral leishmaniasis (VL) is a vector-borne disease, highly influenced by environmental factors, which is an increasing public health problem in Iran, especially in the north-western part of the country. A geographical information system was used to extract data and map environmental variables for all villages in the districts of Kalaybar and Ahar in the province of East Azerbaijan. An attempt to predict VL prevalence based on an analytical hierarchy process (AHP) module combined with ordered weighted averaging (OWA) with fuzzy quantifiers indicated that the south-eastern part of Ahar is particularly prone to high VL prevalence. With the main objective to locate the villages most at risk, the opinions of experts and specialists were generalised into a group decision-making process by means of fuzzy weighting methods and induced OWA. The prediction model was applied throughout the entire study area (even where the disease is prevalent and where data already exist). The predicted data were compared with registered VL incidence records in each area. The results suggest that linguistic fuzzy quantifiers, guided by an AHP-OWA model, are capable of predicting susceptive locations for VL prevalence with an accuracy exceeding 80%. The group decision-making process demonstrated that people in 15 villages live under particularly high risk for VL contagion, i.e. villages where the disease is highly prevalent. The findings of this study are relevant for the planning of effective control strategies for VL in northwest Iran.
authors.affiliation: Faculty of Geodesy and Geomatics Eng. K.N. Toosi University of Technology, No. 1346, Mirdamad cross, Valiasr st., Tehran, Iran. mreza.rajabi@gmail.com
authors.forename: Mohamadreza
authors.initials: M
authors.lastname: Rajabi
authors.forename: Ali
authors.initials: A
authors.lastname: Mansourian
authors.forename: Ahad
authors.initials: A
authors.lastname: Bazmani
mesh_terms: D000818:Animals; D002980:Climate; D003657:Decision Making; D004197:Disease Reservoirs / Q000469:parasitology*; D004285:Dogs / Q000469:parasitology; D004777:Environment; D005260:Female; D017143:Fuzzy Logic; D040362:Geographic Information Systems; D006801:Humans; D007303:Insect Vectors / Q000469:parasitology; D007492:Iran / Q000453:epidemiology; D007898:Leishmaniasis, Visceral / Q000453:epidemiology* / Q000517:prevention & control / Q000635:transmission; D008297:Male; D008954:Models, Biological; D011576:Psychodidae / Q000469:parasitology; D018570:Risk Assessment / Q000379:methods; D017678:Sex Distribution; D062206:Spatial Analysis; D014171:Transients and Migrants / Q000706:statistics & numerical data