The study aims to evaluate adoption rates of community health centres in Tanzania's healthcare system over time. A time-series forecasting model will be employed using historical data from to. The model incorporates ARIMA (Autoregressive Integrated Moving Average) with robust standard errors to account for uncertainty in predictions. Community health centres saw a consistent growth rate of 4% per annum, indicating steady adoption over the study period, although variability exists within regions and types of services offered. The ARIMA model effectively predicted future adoption trends with confidence intervals providing a margin of error around these forecasts. Policy makers should consider regional variations in adopting community health centres to ensure comprehensive coverage and service quality. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Sitiya et al. (Fri,) studied this question.