Maternal care facilities in South Africa are crucial for improving maternal health outcomes. However, their effectiveness varies over time and can be influenced by a multitude of factors. The study employs time-series analysis, specifically an ARIMA (AutoRegressive Integrated Moving Average) model, to forecast future trends based on historical data from various facilities across the country. The uncertainty of these forecasts is quantified using a confidence interval around the predicted values. A significant proportion (35%) of neonatal mortality rates could be attributed to variations in maternal care quality over time, indicating that improvements are needed to align with national health goals. The ARIMA model provides valuable insights into potential future trends and areas for intervention within South African maternal care systems. Health policymakers should focus on strengthening the most vulnerable facilities identified through the analysis. Additionally, continuous monitoring and periodic reviews of maternal care quality are recommended to ensure optimal outcomes. maternal health, ARIMA model, time-series forecasting, neonatal mortality Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Khoza et al. (Wed,) studied this question.
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