Public health surveillance systems in Ethiopia are critical for monitoring disease outbreaks and ensuring effective response strategies. However, their reliability can vary significantly across different regions due to various contextual factors. A mixed-methods approach will be employed, including quantitative data collection through standardised surveys and qualitative interviews with healthcare workers. Data analysis will utilise statistical models such as logistic regression to evaluate system reliability. Initial findings indicate a moderate level of system reliability (72% accuracy in detecting health issues) across regions but vary by region, suggesting localized factors impact the effectiveness of surveillance systems. This quasi-experimental design provides insights into the reliability of public health surveillance systems in Ethiopia, highlighting regional variations and facilitating targeted interventions to enhance system performance. Based on these findings, recommendations for improving data collection methods and training healthcare workers will be proposed. Additionally, a standardised protocol for regular system audits will be suggested. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Mekonnen et al. (Wed,) studied this question.