Public health surveillance systems are essential for monitoring infectious diseases in developing countries such as Ethiopia. Effective implementation of these systems is crucial to timely detection and control of outbreaks. Panel data from to were analysed using a Random Effects (RE) model. The RE model is specified as: Y₈ₓ = eta₀ + eta₁X₈ₓ + uᵢ, where Y₈ₓ represents the adoption rate of surveillance systems in region i at time t, and X₈ₓ includes socio-economic variables such as education level, healthcare access, and government funding. Standard errors are adjusted for within-region correlation. The analysis revealed a significant positive relationship between educational attainment (measured by years of schooling) and surveillance system adoption rates (p < 0. 05). This study provides evidence on the factors affecting public health surveillance systems in Ethiopia, offering insights for policymakers aiming to improve disease detection. Public health authorities should prioritise community education programmes to enhance understanding of surveillance systems and their benefits. public health surveillance, adoption rates, panel data analysis, Random Effects model, Ethiopia
Mulugeta Tekle (Thu,) studied this question.
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