Methodological Evaluation of Public Health Surveillance Systems in Ethiopia: A Time-Series Forecasting Model for System Reliability Assessment

Public health surveillance systems in Ethiopia are crucial for monitoring infectious diseases such as tuberculosis (TB). However, their effectiveness and reliability need methodological evaluation. A time-series analysis was conducted on TB data from to . A linear regression model was applied, with uncertainty quantified by robust standard errors. The TB incidence trend showed a consistent decline over the study period (p < 0.05), indicating an effective surveillance system in place. The time-series forecasting model provided insights into the reliability of public health surveillance systems, which can inform policy improvements. Policy-makers should consider enhancing data collection and reporting mechanisms to ensure sustained monitoring effectiveness. Treatment effect was estimated with logit(pᵢ)=β₀+β^ Xᵢ, and uncertainty reported using confidence-interval based inference.