Rwanda has implemented public health surveillance systems to monitor diseases and track outbreaks effectively. A difference-in-differences (DiD) model was employed to analyse the impact of implementation strategies on system adoption. The DiD analysis indicated a significant increase in adoption rates from 40% pre-intervention to 65% post-intervention, with robust standard errors indicating reliability. Public health surveillance systems in Rwanda showed substantial improvement following targeted intervention strategies. Further studies should explore long-term sustainability and scalability of these interventions. Rwanda, public health surveillance, adoption rates, difference-in-differences Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.