Methodological Evaluation of Public Health Surveillance Systems in Ethiopia Using Difference-in-Differences Models

Public health surveillance systems play a crucial role in monitoring infectious diseases such as tuberculosis (TB). In Ethiopia, these systems have been established to improve early detection and control of TB cases. A difference-in-differences (DD) model was employed to analyse changes in TB notification rates before and after implementing new surveillance tools, comparing them with a control group from previous years. The DD model indicated an increase in the proportion of notified cases by approximately 20% post-intervention, suggesting improved detection efficiency. New surveillance methods have led to a significant improvement in TB case notifications, enhancing public health outcomes. Further research should explore scalability and sustainability of these surveillance systems across different regions in Ethiopia. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.