Public health surveillance systems play a crucial role in monitoring infectious diseases such as malaria, tuberculosis (TB), and HIV/AIDS. The study employed a difference-in-differences model to analyse pre- and post-intervention data from selected regions. Data on reported cases before and after implementing new surveillance protocols were collected and analysed. A significant increase of 20% in the detection rate of malaria was observed, suggesting improved efficiency in surveillance systems. The difference-in-differences model effectively highlighted improvements in public health surveillance systems in Ethiopia. Further studies should consider expanding coverage to include more regions and diseases for a comprehensive evaluation. Public Health Surveillance, Difference-in-Differences, Efficiency Analysis, Public Health Systems, Ethiopia Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.