Methodological Evaluation of Public Health Surveillance Systems in Senegal: A Time-Series Forecasting Model for Cost-Effectiveness Analysis

Public health surveillance systems are crucial for monitoring disease outbreaks in Senegal. However, their effectiveness varies widely across different regions and time periods. A systematic literature review was conducted to identify studies on public health surveillance systems, focusing on their implementation and outcomes. A time-series forecasting model was applied to assess the cost-effectiveness of these systems. The time-series forecasting model indicated that while some systems showed a positive return on investment (ROI) in terms of early detection and resource allocation, others had significant operational costs without substantial benefits. This study provides insights into optimising public health surveillance systems by highlighting the cost-effectiveness trade-offs. Public health officials should prioritise system upgrades that balance efficacy with efficiency to ensure sustainable and effective disease control measures in Senegal. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.