Evaluation reveals urban areas have higher public health surveillance adoption rates in Ethiopia, suggesting targeted strategies for underserved regions.
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
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Weyniak et al. (2004) studied this question.
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