Time-Series Forecasting of Injury Cases in the Kingdom of Saudi Arabia

As the global population and various kinds of accidents grow, there is an increasing concern about providing high-quality healthcare. One way to improve resource management in first-care centers and pre-hospital Emergency Medical Services (EMS) is to predict the number of cases that require immediate intervention such as injuries. In this study, we aimed to forecast the annual number of injury cases per injury type which may help raise the readiness level of the Saudi Red Crescent Authority (SRCA) and pre-hospital Emergency Medical Service (EMS), which provides critical on-scene care in response to the occurrence of various emergencies. To our knowledge, this is the first work that conducts time series forecasting to predict the annual injury cases in Saudi Arabia using the publicly available annual SRCA statistics as a dataset. This study analyzes the temporal data of each injury type and shows the best-performing algorithm, features, and hyperparameters.