title: Identification of Visceral Leishmaniasis-Susceptible Areas using Spatial Modelling in Southern Caucasus.
abstract: This study explores the application of spatial modelling techniques to generate susceptibility maps for a neglected zoonotic disease, visceral leishmaniasis (VL), in an endemic area in southern Caucasus that includes Iran, Armenia and Azerbaijan. The social and physical environment of southern Caucasus has been mainly characterized by the presence of several factors that are strongly associated with VL, which has caused a significant number of infections during the past decade. Three popular spatial modelling techniques, consisting of the weights of evidence, logistic regression and fuzzy logic methods, were evaluated and trained using a study area in north-western Iran where an inventory of highly infected areas and high-quality evidential factors was available. Model performance was assessed using the receiver-operating characteristic (ROC) approach. According to the results of these assessments, the fuzzy logic method with γ = 0.5 was chosen for the prediction of VL incidence in southern Caucasus. The susceptibility map generated using the fuzzy logic method indicated that VL followed a spatial pattern at the conjunction of the three countries, which suggests that the prevalence of VL in southern Caucasus is socio-ecologically dependent.
authors.affiliation: GIS Center, Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden.
authors.forename: M
authors.initials: M
authors.lastname: Rajabi
authors.affiliation: GIS Center, Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden.
authors.forename: P
authors.initials: P
authors.lastname: Pilesjö
authors.affiliation: Infectious and Tropical Diseases Research Centre, Tabriz University of Medical Sciences, Tabriz, Iran.
authors.forename: A
authors.initials: A
authors.lastname: Bazmani
authors.affiliation: GIS Center, Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden.
authors.forename: A
authors.initials: A
authors.lastname: Mansourian
mesh_terms: D001382:Azerbaijan / Q000453:epidemiology; D040362:Geographic Information Systems; D062305:Geographic Mapping; D006801:Humans; D015994:Incidence; D007492:Iran / Q000453:epidemiology; D007898:Leishmaniasis, Visceral / Q000453:epidemiology*; D008954:Models, Biological; D015995:Prevalence
keywords: Spatial modelling; fuzzy logic; logistic regression; southern Caucasus; visceral leishmaniasis; weights of evidence