Public health surveillance systems are crucial for monitoring diseases in Kenya. However, their efficiency can vary significantly across different regions and levels of government. A multilevel regression model was employed to analyse data collected from various regions. The model accounts for hierarchical structures, such as regional differences within the national context. The multilevel regression analysis revealed a significant improvement (p < 0.05) in surveillance efficiency when considering both regional and national factors. This study provides empirical evidence on how to enhance public health surveillance systems, particularly in terms of their effectiveness across different levels of governance. Public health managers should prioritise cross-regional collaboration and resource allocation based on the findings from this analysis. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.