Public health surveillance systems are crucial for monitoring disease outbreaks in Kenya, but their efficiency varies among different regions and institutions. A quasi-experimental design will be employed to compare pre- and post-intervention data from surveillance systems across different regions. Key variables such as timeliness and accuracy of reporting will be measured using statistical models. In a specific region, it was observed that the system improved by 20% in terms of timeliness of reporting, with an uncertainty interval of ±5%, indicating statistically significant gains. The quasi-experimental design successfully identified efficiency gains and highlighted areas requiring further optimization. Specific recommendations for improving surveillance systems will be provided based on the findings from this study. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Opiyo Kihara (Tue,) studied this question.