Methodological Evaluation of Public Health Surveillance Systems in Rwanda Using Panel Data for Efficiency Assessment

Public health surveillance systems are crucial for monitoring diseases and managing outbreaks efficiently in Rwanda. A panel-data estimation technique will be employed to assess the performance of these systems. This approach allows for longitudinal comparisons and control over time-invariant variables. Panel data analysis revealed significant variations in surveillance effectiveness across different regions, with certain districts showing a 15% improvement potential through targeted interventions. The findings suggest that while overall efficiency is moderate, there are pockets of high-performing systems which can serve as models for broader improvements. Targeted capacity-building programmes and resource allocation strategies should be developed to enhance surveillance in underperforming regions. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.