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Cutaneous leishmaniasis in a hyperendemic metropolitan area in Iran: spatial probability modeling by machine-learning
Alireza Mohammadi1, Elahe Pishgar2, Robert Bergquist3
1Department of Geography and Urban Planning, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran.
Journal of Medical Entomology
|June 27, 2025
Summary
Cutaneous leishmaniasis (CL) risk in Mashhad, Iran, is influenced by socio-demographics, urban development, and geology. High-risk areas require targeted interventions for this parasitic infection.
Area of Science:
- Epidemiology
- Environmental Health
- Medical Geography
Background:
- Cutaneous leishmaniasis (CL) is a widespread parasitic infection.
- Mashhad, Iran, is a hyperendemic area for both anthroponotic and zoonotic CL.
- Understanding CL spatial distribution is crucial for control.
Purpose of the Study:
- To evaluate the spatial distribution probability of CL prevalence in Mashhad.
- To identify key socio-demographic, built environment, geological, and climatic factors influencing CL distribution.
- To inform targeted control strategies for CL.
Main Methods:
- Analysis of 3,033 CL patient cases diagnosed between 2013 and 2020.
- Application of generalized linear regression (GLM) and maximum entropy (MaxEnt) models.
- Assessment of sociological, environmental, and climatic variables.
Main Results:
- Socio-demographics, built environment, and geology significantly influence CL distribution.
- The MaxEnt model identified 42.6% of the study area as high-risk for CL.
- High-risk areas are linked to specific geology, urbanization, and environmental quality.
Conclusions:
- CL prevalence is associated with young individuals, low literacy, and densely populated areas.
- Risk areas are influenced by temperature (20-40°C), humidity, built environment, and specific rock types.
- Findings support targeted interventions for urban planners and health managers to control CL.
