Panel data analysis assesses surveillance effectiveness in Rwanda, suggesting targeted interventions for improvements.
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 logit(pᵢ)=β₀+β^ Xᵢ, and uncertainty reported using confidence-interval based inference.
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Hakizumirakazi et al. (2005) studied this question.
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