Targeting leishmaniasis in the Mediterranean: climate clusters and SDGs-based interventions

Area of Science:

• Environmental science
• Epidemiology
• Public health

Background:

• Leishmaniasis, a parasitic disease, poses a significant public health challenge in the Mediterranean.
• Understanding the spatial and environmental drivers of leishmaniasis is crucial for effective control strategies.

Purpose of the Study:

• To investigate the spatial distribution and environmental patterns of cutaneous and visceral leishmaniasis in the Mediterranean region.
• To identify key ecological, climatic, and land use predictors associated with leishmaniasis occurrence.
• To provide a data-driven framework for targeted leishmaniasis interventions.

Main Methods:

• Kernel density estimation for hotspot identification.
• Land cover classification, Köppen climate mapping, and soil type analysis.
• Ensemble machine learning (Random Forest, XGBoost) and ecological niche clustering (K-means).

Main Results:

• Hotspots for cutaneous leishmaniasis identified in Morocco, Tunisia, the Levant, Turkey, and Crete.
• Visceral leishmaniasis hotspots detected in Tunisia, Israel, France, and Albania.
• Both diseases exhibited a U-shaped urbanization pattern and were associated with specific Mediterranean/semi-arid climates and soil types.
• Precipitation and soil variables were identified as major predictors by machine learning models.

Conclusions:

• Leishmaniasis distribution is strongly influenced by environmental factors in the Mediterranean.
• Overlapping ecological niches suggest shared transmission dynamics.
• Findings support integrated control measures, including land management, climate-adaptive surveillance, and urban vector control planning.