Using the gravity model to estimate the spatial spread of vector-borne diseases

Area of Science:

• Epidemiology
• Spatial analysis
• Ecology

Background:

• Vector-borne diseases spread through interactions between pathogen vectors/hosts and human populations.
• Gravity models are established tools for analyzing spatial interactions across various domains.
• Understanding disease spread dynamics is crucial for public health interventions.

Purpose of the Study:

• To apply gravity model principles to predict the spatial diffusion of nephropathia epidemica and Lyme borreliosis.
• To identify significant environmental and human factors influencing disease risk.
• To evaluate different data sources for mapping relevant environmental features.

Main Methods:

• Utilized gravity model concepts to analyze spatial disease transmission.
• Incorporated land cover data (CORINE) and vegetation indices (MODIS NDVI) to characterize vegetated systems.
• Assessed the predictive power of vegetated area size and occupation-related exposure indicators.

Main Results:

• The size of vegetated areas adjacent to urban centers significantly predicted disease risk.
• Local indicators of occupation-related exposure were also significant predictors of disease risk.
• Both CORINE land cover and MODIS NDVI datasets proved suitable for identifying relevant vegetated areas, though not interchangeable.

Conclusions:

• The gravity model framework is compatible with understanding and predicting the spatial spread of vector-borne diseases.
• Environmental factors, particularly proximity and extent of vegetated areas to urban zones, are critical.
• Accurate spatial data on land cover and vegetation are essential for effective disease risk assessment.