Reliability Measurement in Public Health Surveillance Systems in Senegal Employing Multilevel Regression Analysis

Public health surveillance systems play a crucial role in monitoring infectious diseases across Senegal. These systems are vital for early detection and effective response to disease outbreaks. This research employs a multilevel regression model to analyse data from multiple levels within the surveillance system. The specific model used is Yᵢⱼ = eta₀ + eta₁Xᵢⱼ + bⱼ + uᵢⱼ, where Y represents surveillance outcomes, X denotes predictor variables, bⱼ captures random intercepts at the level of health districts, and uᵢⱼ accounts for residuals. The multilevel regression analysis reveals a significant proportion (25%) of variability in system reliability attributed to district-level factors, indicating that targeted interventions could enhance performance. This study provides evidence on the effectiveness of multilevel regression analysis in assessing public health surveillance systems' reliability. Future work should explore implementation strategies for improved system performance. Health authorities in Senegal are advised to consider district-specific factors when designing and implementing surveillance programmes, aiming for more robust and reliable disease monitoring.