title: Environmental modelling of visceral leishmaniasis by susceptibility-mapping using neural networks: a case study in north-western Iran.
abstract: Visceral leishmaniasis (VL) is a potentially fatal vector-borne zoonotic disease, which has become an increasing public health problem in the north-western part of Iran. This work presents an environmental health modelling approach to map the potential of VL outbreaks in this part of the country. Radial basis functional link networks is used as a data-driven method for predictive mapping of VL in the study area. The high susceptibility areas for VL outbreaks account for 36.3% of the study area and occur mainly in the north (which may affect the neighbouring countries) and South (which is a warning for other provinces in Iran). These parts of the study area have many nomadic, riverside villages. The overall accuracy of the resultant map was 92% in endemic villages. Such susceptibility maps can be used as reconnaissance guides for planning of effective control strategies and identification of possible new VL endemic areas.
authors.affiliation: Lund University GIS Centre, Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden.
authors.forename: Mohammadreza
authors.initials: M
authors.lastname: Rajabi
authors.affiliation: Lund University GIS Centre, Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden.
authors.forename: Ali
authors.initials: A
authors.lastname: Mansourian
authors.affiliation: Lund University GIS Centre, Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden.
authors.forename: Petter
authors.initials: P
authors.lastname: Pilesjö
authors.affiliation: Infectious and Tropical Diseases Research Centre, Tabriz University of Medical Sciences, Tabriz, Iran.
authors.forename: Ahad
authors.initials: A
authors.lastname: Bazmani
mesh_terms: D004196:Disease Outbreaks / Q000706:statistics & numerical data; D004777:Environment; D040362:Geographic Information Systems; D062305:Geographic Mapping; D006801:Humans; D007492:Iran / Q000453:epidemiology; D007898:Leishmaniasis, Visceral / Q000453:epidemiology* / Q000209:etiology; D015233:Models, Statistical; D016571:Neural Networks, Computer; D012307:Risk Factors