Public health surveillance systems in Ghana are essential for monitoring infectious diseases such as malaria and tuberculosis. However, their effectiveness varies across different regions. A mixed-methods approach was employed, including quantitative data from surveillance records and qualitative interviews with stakeholders. Data were analysed using logistic regression models to estimate odds ratios for risk reduction effects. In the intervention group, there was a 20% reduction in reported cases of malaria compared to the control group (OR = 0.80, CI: 0.65-0.98). The randomized field trial demonstrated promising results for risk reduction in public health surveillance systems. Further research should focus on scaling up these interventions and exploring longer-term outcomes to validate the findings. Public Health Surveillance, Randomized Field Trial, Risk Reduction, Logistic Regression