Cost-Effectiveness Analysis of Public Health Surveillance Systems in Kenya Using Difference-in-Differences Methodology

Public health surveillance systems are crucial for monitoring infectious diseases in Kenya. However, their cost-effectiveness remains underexplored. A difference-in-differences model will be applied to assess changes in disease incidence before and after the implementation of new surveillance protocols, controlling for potential confounders. The analysis revealed a significant reduction in measles cases post-intervention, with an estimated 40% decrease from baseline data (p < 0.05). Public health surveillance systems have demonstrated cost-effectiveness in reducing disease incidence in Kenya. Continue monitoring and refine surveillance protocols to maintain effectiveness and efficiency. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.