Petter Pilesjö
Professor
Environmental modelling of visceral leishmaniasis by susceptibility-mapping using neural networks : a case study in north-western Iran
Author
Summary, in English
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.
Department/s
- Dept of Physical Geography and Ecosystem Science
- Centre for Geographical Information Systems (GIS Centre)
- Centre for Advanced Middle Eastern Studies (CMES)
- MECW: The Middle East in the Contemporary World
- eSSENCE: The e-Science Collaboration
Publishing year
2014
Language
English
Pages
179-191
Publication/Series
Geospatial health
Volume
9
Issue
1
Document type
Journal article
Publisher
University of Naples Federico II
Topic
- Human Geography
- Physical Geography
Keywords
- visceral leishmaniasis
- environment
- geographical information systems
- neural networks
- Artificial Intelligence (AI)
- Geospatial Artificial Intelligence (GeoAI)
Status
Published
Project
- Geospatial modeling and simulation techniques to study prevalence and spread of diseases
ISBN/ISSN/Other
- ISSN: 1970-7096