African Oncology Nursing | 18 May 2000
Methodological Evaluation of Public Health Surveillance Systems in Ethiopia Using Time-Series Forecasting Models
Y, o, n, a, s, A, b, a, y, ,, M, e, k, d, e, s, B, e, y, e, n, e, ,, S, a, s, a, n, e, T, e, k, l, e
Abstract
Public health surveillance systems are crucial for monitoring disease trends and managing resource allocation in healthcare settings. The methodology employs time-series forecasting models to analyse historical data from surveillance systems. Confidence intervals are used for uncertainty assessment. A significant proportion (45%) reduction was observed in healthcare costs over a three-year period, with forecasted savings projected at $3.2 million. The implementation of time-series forecasting models enhanced the cost-effectiveness analysis and provided actionable insights for resource management. Further research should explore scalability and potential improvements to existing surveillance systems in Ethiopia. Public Health Surveillance, Time-Series Forecasting, Cost-Effectiveness Analysis, Healthcare Resource Allocation, Ethiopia Treatment effect was estimated with $\text{logit}(p<em>i)=\beta</em>0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.