Forecasting Adoption Rates in South African Community Health Centres Using Time-Series Models: A Methodological Evaluation

Community health centres in South Africa are pivotal for healthcare delivery in underserved areas. However, their adoption rates vary significantly and can be influenced by multiple factors. A comprehensive methodological evaluation was conducted using time-series forecasting models. The study aimed at understanding patterns and predicting future trends with a specific focus on accuracy and robustness. The analysis revealed a consistent upward trend in the adoption rates of community health centres, with an estimated forecasted increase of 15% over the next two years. Time-series models provided reliable predictions for future adoption rates, contributing to evidence-based policy-making and resource allocation strategies. Health policymakers should consider the use of time-series forecasting models in strategic planning to enhance service delivery efficiency and coverage. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.