RESUMEN
The first case of coronavirus disease 2019 (COVID-19) in Saudi Arabia was reported on 2 March 2020. Since then, it has progressed rapidly and the number of cases has grown exponentially, reaching 788,294 cases on 22 June 2022. Accurately analyzing and predicting the spread of new COVID-19 cases is critical to develop a framework for universal pandemic preparedness as well as mitigating the disease's spread. To this end, the main aim of this paper is first to analyze the historical data of the disease gathered from 2 March 2020 to 20 June 2022 and second to use the collected data for forecasting the trajectory of COVID-19 in order to construct robust and accurate models. To the best of our knowledge, this study is the first that analyzes the outbreak of COVID-19 in Saudi Arabia for a long period (more than two years). To achieve this study aim, two techniques from the data analytics field, namely the auto-regressive integrated moving average (ARIMA) statistical technique and Prophet Facebook machine learning technique were investigated for predicting daily new infections, recoveries and deaths. Based on forecasting performance metrics, both models were found to be accurate and robust in forecasting the time series of COVID-19 in Saudi Arabia for the considered period (the coefficient of determination for example was in all cases more than 0.96) with a small superiority of the ARIMA model in terms of the forecasting ability and of Prophet in terms of simplicity and a few hyper-parameters. The findings of this study have yielded a realistic picture of the disease direction and provide useful insights for decision makers so as to be prepared for the future evolution of the pandemic. In addition, the results of this study have shown positive healthcare implications of the Saudi experience in fighting the disease and the relative efficiency of the taken measures.
RESUMEN
Background: The identification of current gaps in high-impact medical research in Saudi Arabia has international significance due to the trend of collaborative research in the field of health and medicine and the focus on knowledge-sharing. The purpose of this study is to assess the current focus, gaps, and priorities in health research in Saudi Arabia. Methods: We employed a mixed-method research approach to achieve research objectives. (1) a systematic review of scientific research studies that are published between January 2020 to January 2022 in the top fifty Q1 medical science journals (2) a cross-sectional survey collected data from professionals employed in various organizations including the Ministry of Health (MoH), Ministry of Education (MoE), health organizations and universities, and the health industry. The close-ended survey questions inquired about the broad and specific areas of ongoing health research projects by these researchers and organizations in Saudi Arabia. Results: The literature search on databases identified Science Direct (n = 741), Pub Med (n = 244) and Google Scholar (n = 15,600). After screening, (n = 26) original studies were selected for detailed evaluation and synthesis. Among these (n = 7) studied infectious diseases, (n = 7) cancer, and cardiac disease (n = 5). These studies focused on the etiology, treatment management and therapy outcomes of these health conditions. The survey was completed by (n = 384) respondents from these organizations. Most of the ongoing research projects focus on clinical sciences (27%) followed by basic sciences (24%) and public health research (24%) and a limited number of researchers were involved in healthcare management (2%) and informatics (2%). Most research focused on kidney and liver disorders (80%), obesity (74%), diabetes (74%), hormonal diseases (64%), and infectious disease (66%); it is equally important to design and fund research in some of the neglected areas including reproductive health (3%), physical and mental disabilities (1%). Conclusion: Findings suggest that current gaps in original research from Saudi Arabia are in healthcare service quality, reproductive health, physical and mental disabilities and health informatics. Researchers and funding agencies and international collaborative projects should prioritize these areas.