Petter Pilesjö
Professor
A spatially explicit agent-based modeling approach for the spread of Cutaneous Leishmaniasis disease in central Iran, Isfahan
Author
Summary, in English
Cutaneous Leishmaniasis (CL) is an endemic vector-borne disease in the Middle East and a worldwide public health problem. The spread of CL is highly associated with the socio-ecological interactions of vectors, hosts and the environment. The heterogeneity of these interactions has hindered CL modeling for healthcare preventive measures in endemic areas. In this study, an agent-based model (ABM) is developed to simulate the dynamics of CL spread based on a Geographic Automata System (GAS). A Susceptible-Exposed-Infected-Recovered (SEIR) approach together with Bayesian modeling has been applied in the ABM to explore the spread of CL. The model is then adapted locally for Isfahan Province, an endemic area in central Iran. The results from the model indicate that desertification areas are the main origin of CL, and riverside population centers have the potential to host more sand fly exposures and should receive more preventive measures from healthcare authorities. The results also show that healthcare service accessibility prevented exposures from becoming infected and areas with new inhabitants experienced more infections from same amount of sand fly exposures.
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
Publishing year
2016-08-01
Language
English
Pages
330-346
Publication/Series
Environmental Modelling & Software
Volume
82
Document type
Journal article
Publisher
Elsevier
Topic
- Geosciences, Multidisciplinary
Keywords
- Agent-based model
- Cutaneous Leishmaniasis
- Disease modeling
- Socio-ecological interactions
- 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: 1364-8152