Analysis shows increased adoption rates of public health surveillance systems in Rwanda, indicating scalability potential.
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 logit(pᵢ)=β₀+β^ Xᵢ, and uncertainty reported using confidence-interval based inference.
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Irano et al. (2001) studied this question.
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