Spatio-temporal patterns and determinants of measles incidence in Ethiopia between 2018 and 2024

Despite the availability of an effective vaccine, measles remains a major public health concern in Ethiopia, with recurrent outbreaks and substantial spatial heterogeneity. Understanding its spatio-temporal patterns and determinants is critical for optimizing control strategies and achieving elimination goals.

A retrospective spatio-temporal analysis was conducted using national measles surveillance data from 2018-2024, aggregated at the zonal level. Geographic clustering was assessed using Moran's I, Getis-Ord Gi^*, and Local Indicators of Spatial Association (LISA) statistics. A negative binomial regression model incorporating spatial and temporal effects was fitted to identify determinants of measles distribution, integrating epidemiological, environmental, nutritional, and socioeconomic variables.

Between 2018 and 2024, 71,635 measles cases were reported, with the highest burdens observed in Oromia, Somali, Southern Ethiopia, and parts of Amhara. Significant spatial clustering was detected (Moran's I = 0.154, p = 0.003), with persistent hotspots in southern and southwestern zones. The model showed that higher night-light intensity (IRR = 2.21, p < 0.001) and temporal (IRR = 1.24, p = 0.028) and spatial lag effects (IRR = 1.73, p < 0.001) were strongly associated with increased measles incidence. Higher temperature (IRR = 0.78, p = 0.005) and relative wealth index (IRR = 0.40, p < 0.001) were inversely associated, while underweight prevalence and distance to health facilities were not significant predictors of measles distribution.

Measles transmission in Ethiopia exhibits clear spatial clustering and temporal persistence, strongly influenced by socioeconomic inequities, human concentration, and climatic conditions. Incorporating spatio-temporal modeling into routine surveillance can enhance early detection and guide geographically targeted immunization, nutrition, and equity-focused interventions toward measles elimination.