Public health surveillance systems in Ghana are crucial for monitoring infectious diseases such as malaria and tuberculosis. Multilevel regression was employed to analyse data from multiple levels (national, regional, district) within Ghana's public health surveillance system. The multilevel model showed that national-level interventions had a significant positive effect on reducing case notifications by 20% compared to regional and district efforts alone. This study demonstrates the effectiveness of combining national strategies with local adaptations for improved disease control efficiency in Ghana. Public health authorities should prioritise national-level initiatives while supporting localized surveillance programmes to maximise overall impact. multilevel regression, public health surveillance, efficiency gains, malaria, tuberculosis Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.