Urban primary care networks in Senegal are crucial for delivering healthcare services to underserved populations. However, their effectiveness remains under scrutiny. The study will employ a DiD approach with longitudinal data from urban clinics in Senegal, comparing pre-intervention and post-intervention periods. Data will be analysed using mixed-effects regression models. A preliminary analysis suggests a significant improvement (p < 0.05) in patient recovery rates post-network implementation. The DiD model demonstrates the potential of longitudinal data to assess primary care network effectiveness, offering valuable insights for policy and resource allocation. Further research should explore long-term effects and cost-benefit analyses for sustainable interventions. Urban Primary Care Networks, Difference-in-Differences, Clinical Outcomes, Senegal, Mixed-Effects Regression Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.