Public health surveillance systems are crucial for monitoring infectious diseases in developing countries like Kenya. A mixed-methods approach combining quantitative data analysis with qualitative interviews to assess system performance and identify areas for improvement. The median time from symptom onset to reporting was reduced by 24% in the intervention group compared to baseline, indicating improved efficiency. The trial validated the effectiveness of targeted interventions on reducing detection delays in public health surveillance systems. Implementing data-driven strategies and regular system audits are recommended for enhancing surveillance capabilities. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.