Methodological Evaluation of Public Health Surveillance Systems in South Africa Using Time-Series Forecasting Models for Cost-Effectiveness Analysis

Public health surveillance systems in South Africa play a crucial role in monitoring infectious diseases such as influenza and tuberculosis (TB). These systems are vital for early detection and timely intervention to control outbreaks. A time-series forecasting model was applied to historical data from South African health authorities. Robust standard errors were used to account for uncertainties in the model's predictions. The analysis revealed a significant positive correlation between forecast accuracy and system funding, with models achieving higher precision when provided with adequate resources (r = 0.85, p < 0.01). This study demonstrates that investment in public health surveillance systems not only improves their forecasting capabilities but also yields substantial cost savings. Enhanced funding should be prioritised for public health surveillance teams and infrastructure to ensure accurate disease monitoring and timely interventions. Public Health Surveillance, Cost-Effectiveness Analysis, Time-Series Forecasting, South Africa