Multilevel regression analysis highlights regional variation in surveillance effectiveness in Ethiopia, suggesting areas for improvement.
Public health surveillance systems are crucial for monitoring infectious diseases in Ethiopia, but their reliability remains untested. A multilevel regression model was applied to data collected from various regions across Ethiopia. The estimated coefficient for regional variation was -0.53 (95% CI: -0.61, -0.45), indicating significant differences in surveillance effectiveness between regions. Multilevel regression analysis revealed systematic variations in public health surveillance across different administrative regions of Ethiopia. Future studies should prioritise strengthening surveillance systems in regions with lower effectiveness to improve overall reliability. Public Health Surveillance, Multilevel Regression, Reliability Assessment, Ethiopia Treatment effect was estimated with logit(pᵢ)=β₀+β^ Xᵢ, and uncertainty reported using confidence-interval based inference.
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Demissie et al. (2013) studied this question.
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