Public health surveillance systems in Rwanda are crucial for monitoring disease outbreaks and guiding public health interventions. However, their efficiency and effectiveness need methodological evaluation to ensure optimal resource allocation. Panel data regression models will be employed to analyse trends and identify factors influencing surveillance system efficiency. Robust standard errors will account for potential heteroscedasticity and autocorrelation in the data. Analysis reveals a significant decline in reporting time from pre-pandemic levels, suggesting improvements are needed in real-time response mechanisms. The results indicate that current surveillance system efficiency can be enhanced through targeted training programmes for health workers and investment in technology infrastructure. Implementing the recommended interventions will help improve the overall efficacy of Rwanda's public health surveillance systems, thereby improving disease control outcomes. Public Health Surveillance, Efficiency Analysis, Panel Data Regression, Robust Standard Errors Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Kamugyaberwa Ernest (2009) studied this question.