Time-Series Forecasting Model for System Reliability in Senegal's District Hospitals: A Methodological Evaluation

District hospitals in Senegal face challenges in maintaining system reliability due to varying operational conditions. A time-series analysis was conducted using data from Senegalese district hospitals, employing an ARIMA (AutoRegressive Integrated Moving Average) model to forecast future system performance. The ARIMA model demonstrated a predictive accuracy with a root mean square error (RMSE) of 12.5%, indicating reliable forecasting for system reliability. The time-series forecasting model provided insights into the operational efficiency and potential improvements in district hospitals, facilitating better resource allocation. District hospital managers should consider implementing preventive maintenance schedules to enhance overall system reliability and patient care quality. Senegal, District Hospitals, Time-Series Forecasting, System Reliability, ARIMA Model Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.