The healthcare sector in off-grid communities of Kenya faces challenges due to unreliable power supply from grid-based systems. A time-series forecasting model was applied using historical data on electricity usage, patient health records, and economic indicators. Robust standard errors were computed to account for uncertainty. The model demonstrated a moderate correlation (R² = 0. 56) in predicting clinical outcomes over the study period, indicating room for improvement in forecasting accuracy. While the model showed promise, further refinement is needed to enhance its predictive power and applicability. Future studies should consider incorporating additional variables such as socioeconomic status and environmental factors into the model. Off-grid communities, healthcare systems, time-series forecasting, clinical outcomes, robust standard errors The empirical specification follows Y=₀+^ X+, and inference is reported with uncertainty-aware statistical criteria.
Mwai Kibaki Kalwa (Mon,) studied this question.