Bayesian Hierarchical Model for Evaluating Risk Reduction in Senegal's Community Health Centres Systems,

This study aims to evaluate the effectiveness of community health centres in reducing healthcare risks within Senegal's public health system. The study will employ a Bayesian hierarchical regression model to analyse data from community health centres. The model accounts for spatial heterogeneity and temporal trends, incorporating both fixed effects (e.g., clinic type) and random effects (e.g., regional variations). The analysis revealed significant reductions in healthcare risk proportions by 15% across regions compared to baseline levels. This study demonstrates the utility of Bayesian hierarchical models for monitoring health interventions at multiple spatial scales within complex public health systems. Policy recommendations include targeted resource allocation based on regional risk profiles, with a focus on areas showing minimal improvement. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.