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Identification of Visceral Leishmaniasis-Susceptible Areas using Spatial Modelling in Southern Caucasus

RAJABI , MOHAMMADREZA LU ; Pilesjö, Petter LU ; Bazmani, A and Mansourian, A LU (2016) In Zoonoses and Public Health
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... (More)

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.

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Contribution to journal
publication status
published
subject
in
Zoonoses and Public Health
publisher
Wiley-Blackwell
external identifiers
  • scopus:85008445054
ISSN
1863-1959
DOI
10.1111/zph.12325
language
English
LU publication?
yes
id
64a5873a-a123-486f-a8ad-42d547f5df10
date added to LUP
2017-01-09 11:34:01
date last changed
2017-08-08 09:44:35
@article{64a5873a-a123-486f-a8ad-42d547f5df10,
  abstract     = {<p>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.</p>},
  author       = {RAJABI , MOHAMMADREZA and Pilesjö, Petter and Bazmani, A and Mansourian, A},
  issn         = {1863-1959},
  language     = {eng},
  month        = {12},
  publisher    = {Wiley-Blackwell},
  series       = {Zoonoses and Public Health},
  title        = {Identification of Visceral Leishmaniasis-Susceptible Areas using Spatial Modelling in Southern Caucasus},
  url          = {http://dx.doi.org/10.1111/zph.12325},
  year         = {2016},
}