Public health surveillance systems are crucial for monitoring and managing infectious diseases in developing countries like Ethiopia. A mixed-method approach combining quantitative and qualitative data will be employed. Panel data analysis will be conducted to estimate cost-effectiveness ratios (CERs) for different surveillance interventions. The preliminary findings suggest that the current system underinvests in early warning systems, particularly in rural areas where disease transmission is higher. This study aims to provide evidence-based recommendations for improving public health surveillance in Ethiopia by optimising resource allocation based on cost-effectiveness analysis. Policy makers should prioritise investments in digital infrastructure and training programmes to enhance the early detection of infectious diseases. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.