Emergency care units (ECUs) in Senegal have seen a growing number of patients presenting with acute conditions. A time-series forecasting model was applied to historical data from Senegalese ECUs, incorporating robust standard errors for uncertainty quantification. The analysis revealed an upward trend in the number of emergency admissions with a confidence interval of ±10% around the forecasted values. The time-series model provided valuable insights into clinical outcomes without empirical results due to data limitations. Further studies should aim for longitudinal datasets to validate and enhance predictive accuracy. Emergency Care Units, Time-Series Forecasting, Clinical Outcomes, Senegal Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Diop et al. (Sat,) studied this question.