Public health surveillance systems in Nigeria are critical for monitoring infectious diseases such as cholera and malaria. However, their effectiveness varies widely across regions. A randomized controlled trial (RCT) was conducted in two selected states to measure the performance metrics of surveillance systems. The study used logistic regression models to assess the impact of various factors on system efficiency. The analysis revealed that a 15% increase in reporting delays for cholera cases led to a 20% reduction in overall case detection, highlighting the need for improved data collection and processing mechanisms. This study underscores the importance of regular system audits and technological upgrades to enhance surveillance accuracy and public health outcomes. Public health authorities should prioritise training programmes for surveillance personnel and invest in digital infrastructure improvements to reduce delays and increase detection rates. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.