Mapping malaria risk zones using GIS-based multi-criteria evaluation in Ilu Aba Bora Zone, Western Ethiopia

This study seeks to produce a detailed and location-specific model of risk zones in the Ilu Aba Bora Zone of western Ethiopia, where transmission is shaped by a combination of environmental, climatic, and social conditions. To achieve this, integrated Geographic Information Systems (GIS), and remote-sensing derived information on terrain, temperature, rainfall, slope, river proximity, and land-use features with socioeconomic data such as population density, road access, and distance to health facilities was employed. Land use and land cover were mapped using Google Earth Engine, and factors weights were computed through the Analytic Hierarchy Process to combine all inputs in a multi-criteria model that accounted for hazard, vulnerability, and elements at risk. After standardizing each layer into five susceptibility classes and a weighted overlay, the resulting map showed that nearly one-third of the zone about 3087 km 2 falls into high or very high malaria risk categories, with the most affected areas located in low-lying, warmer, flatter, and densely settled landscapes close to rivers. These findings reveal that spatial differences in malaria susceptibility across the study area. The study demonstrates that fine-scale geospatial analysis can greatly strengthen malaria stratification, and it recommends using the identified high risk areas as priority targets for focused interventions such as improved surveillance, distribution of insecticide-treated nets, and expanded indoor residual spraying.