The novel coronavirus (COVID-19) outbreak produced devastating effects on the global economy and the health of entire communities. Although the COVID-19 survival rate is high, the number of severe cases that result in death is increasing daily. A timely prediction of at-risk patients of COVID-19 with precautionary measures is expected to increase the survival rate of patients and reduce the fatality rate. This research provides a prediction method for the early identification of COVID-19 patient’s outcome based on patients’ characteristics monitored at home, while in quarantine. The study was performed using 287 COVID-19 samples of patients from the King Fahad University Hospital, Saudi Arabia. The data were analyzed using three classification algorithms, namely, logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB). Initially, the data were preprocessed using several preprocessing techniques. Furthermore, 10-k cross-validation was applied for data partitioning and SMOTE for alleviating the data imbalance. Experiments were performed using twenty clinical features, identified as significant for predicting the survival versus the deceased COVID-19 patients. The results showed that RF outperformed the other classifiers with an accuracy of 0.95 and area under curve (AUC) of 0.99. The proposed model can assist the decision-making and health care professional by early identification of at-risk COVID-19 patients effectively.

C oronavirus disease (COVID-19) has been shown to be highly contagious and outbreaks have been reported to occur easily. Antenatal clinics and labor and delivery units are considered to be high-risk areas. The consequences of an outbreak occurring in a maternal and child health facility could be detrimental. COVID-19 is complicated to treat, unpredictable, and difficult to control. Therefore, increased health education and effective prevention and control measures must be undertaken. 1 The Saudi Society of Maternal-Fetal Medicine (SSMFM) formed a task force comprising MFM experts to review available evidence concerning pregnancy and COVID-19. Practice points and expert advice were evaluated, based on the best available evidence to date. The SSMFM aimed to provide safe care for pregnant women in the Kingdom of Saudi Arabia through exploring recent evidence that may be helpful in preventing COVID-19 transmission and provide management recommendations for those who care for suspected/confirmed patients with COVID-19. Precautionary advice for healthcare workers in contact with this specific patient population has also been included in this guidance. As of the 30th June 2020, 186,436 patients have been infected with COVID-19 in the Kingdom of Saudi Arabia, with 1599 fatalities and an average case fatality rate of 0.86%. 2 Owing to growing patient numbers, it is