Petter Pilesjö
Professor
Environmental modelling of visceral leishmaniasis by susceptibility-mapping using neural networks : a case study in north-western Iran
Författare
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.
Avdelning/ar
- Institutionen för naturgeografi och ekosystemvetenskap
- Centrum för geografiska informationssystem (GIS-centrum)
- Centrum för Mellanösternstudier (CMES)
- MECW: The Middle East in the Contemporary World
- eSSENCE: The e-Science Collaboration
Publiceringsår
2014
Språk
Engelska
Sidor
179-191
Publikation/Tidskrift/Serie
Geospatial health
Volym
9
Issue
1
Dokumenttyp
Artikel i tidskrift
Förlag
University of Naples Federico II
Ämne
- Human Geography
- Physical Geography
Nyckelord
- visceral leishmaniasis
- environment
- geographical information systems
- neural networks
- Artificial Intelligence (AI)
- Geospatial Artificial Intelligence (GeoAI)
Status
Published
Projekt
- Geospatial modeling and simulation techniques to study prevalence and spread of diseases
ISBN/ISSN/Övrigt
- ISSN: 1970-7096