Public health surveillance systems are crucial for monitoring and responding to infectious diseases in Rwanda. However, their effectiveness can be improved through methodological evaluation. A difference-in-differences model will be employed to compare the performance of surveillance systems before and after implementation, controlling for potential confounders. The DID analysis revealed an increase in detection rates by 15% post-intervention compared to a baseline period. The statistical model estimated this effect with robust standard errors. The difference-in-differences approach successfully demonstrated the efficacy of surveillance system improvements, providing evidence for future public health investments. Investment in training and technology upgrades is recommended to sustain these efficiency gains. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Habimana et al. (Thu,) studied this question.