Evaluation of Public Health Surveillance Systems in Ethiopia Using Multilevel Regression Analysis for Adoption Rate Measurement

Public health surveillance systems are critical for monitoring disease prevalence and guiding intervention strategies in Ethiopia. Multilevel logistic regression models were used to analyse data from various health districts. The models account for both regional and district-level variations in surveillance system implementation. The analysis revealed a significant variation in adoption rates across regions, with urban areas showing higher adoption compared to rural ones (OR = 1.8, p < 0.05). Multilevel regression analysis provided insights into the factors affecting surveillance system adoption, offering recommendations for policy makers. Policy makers should prioritise implementation in underserved regions and consider socio-economic factors when designing public health interventions. Public Health Surveillance, Multilevel Regression Analysis, Adoption Rate, Ethiopia