Public health surveillance in Uganda is crucial for monitoring disease trends and guiding interventions. The effectiveness of these systems can be enhanced through rigorous methodological assessments. The DiD approach will compare pre- and post-intervention periods within control and treatment groups to isolate the impact of surveillance system changes. Data from multiple health facilities will be analysed for consistency in reporting practices. A significant proportion (p < 0. 05) of facility-reported hospital admissions decreased after the implementation of enhanced surveillance protocols, indicating potential improvements in clinical outcomes. The DiD model demonstrated promise in detecting changes attributable to surveillance system upgrades, although further validation is required for broader application. Future studies should consider longitudinal data collection and incorporate feedback mechanisms from healthcare providers to improve the robustness of surveillance systems. Public Health Surveillance, Difference-in-Differences, Clinical Outcomes, Uganda Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Olivier Mukasa (Mon,) studied this question.