Environmental modelling of visceral leishmaniasis by susceptibility-mapping using neural networks : a case study in north-western Iran

Mohammadreza Rajabi, Ali Mansourian, Petter Pilesjö, Ahad Bazmani

Research output: Contribution to journalArticlepeer-review

16 Citations (SciVal)

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.
Original languageEnglish
Pages (from-to)179-191
JournalGeospatial health
Volume9
Issue number1
DOIs
Publication statusPublished - 2014

Subject classification (UKÄ)

  • Human Geography
  • Physical Geography

Keywords

  • visceral leishmaniasis
  • environment
  • geographical information systems
  • neural networks
  • Iran

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