Methodological Evaluation of Public Health Surveillance Systems in Rwanda Using Difference-in-Differences Models to Measure Risk Reduction Effects

Public health surveillance systems are crucial for monitoring infectious diseases in Rwanda. However, their effectiveness can be assessed through methodological evaluations. The study employed DiD models to analyse pre- and post-intervention data, focusing on the impact of enhanced surveillance protocols on disease incidence rates. Uncertainty was quantified using robust standard errors. A significant decrease in measles cases (30%) was observed after implementation of new surveillance measures, supported by a Y = β₀ + β₁Treated + β₂PreTreatment + β₃(Treated * PreTreatment) + ε model where β₃= -0.45 with 95% confidence interval (-0.68 to -0.22). The DiD models effectively demonstrated the impact of surveillance system improvements on disease reduction, providing a robust method for future public health interventions. Further research should explore scalability and cost-effectiveness of these methods in other Rwandan regions and diseases. Public Health Surveillance, Difference-in-Differences, Risk Reduction, DiD Models, Rwanda