Time-Series Analysis and Healthcare Implications of COVID-19 Pandemic in Saudi Arabia

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.

Time-Series Analysis and Healthcare Implications of COVID-19 Pandemic in Saudi Arabia.

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.

Effectiveness of Human Mobility Change in Reducing the Spread of COVID-19: Ecological Study of Kingdom of Saudi Arabia

Non-pharmacological interventions including mobility restriction have been developed to curb transmission of SARS-CoV-2. We provided precise estimates of disease burden and examined the impact of mobility restriction on reducing the COVID-19 effective reproduction number in the Kingdom of Saudi Arabia. This study involved secondary analysis of open-access COVID-19 data obtained from different sources between 2 March and 26 December 2020. The dependent and main independent variables of interest were the effective reproduction number and anonymized mobility indices, respectively. Multiple linear regression was used to investigate the relationship between the community mobility change and the effective reproduction number for COVID-19. By 26 December 2020, the total number of COVID-19 cases in Saudi Arabia reached 360,690, with a cumulative incidence rate of 105.41/10,000 population. Al Jouf, Northern Border, and Jazan regions were ≥2.5 times (OR = 2.93;95% CI: 1.29–6.64), (OR = 2.50;95% CI: 1.08–5.81), and (OR = 2.51;95% CI: 1.09–5.79) more likely to have a higher case fatality rate than Riyadh, the capital. Mobility changes in public and residential areas were significant predictors of the COVID-19 effective reproduction number. This study demonstrated that community mobility restrictions effectively control transmission of the COVID-19 virus.

Healthcare strategies and initiatives about COVID19 in Pakistan: Telemedicine a way to look forward.

The COVID-19 pandemic is one of the unprecedented devastating catastrophes with severe public health threat globally. Low and middle income countries (LMICs) are trying hard to cope with the rapidly changing global scenario and trying to mitigate this double crisis of pandemic and economic recession. This pandemic, has led to major changes in global and regional health care delivery proceedings with surge in telemedicine to provide the required services and also giving priority to control the disease spread.

Clinical Characteristics and Neonatal Outcomes of Pregnant Patients With COVID-19: A Systematic Review.

Background and Objective: Coronavirus disease 2019 (COVID-19) characterized by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created serious concerns about its potential adverse effects. There are limited data on clinical, radiological, and neonatal outcomes of pregnant women with COVID-19 pneumonia. This study aimed to assess clinical manifestations and neonatal outcomes of pregnant women with COVID-19. Methods: We conducted a systematic article search of PubMed, EMBASE, Scopus, Google Scholar, and Web of Science for studies that discussed pregnant patients with confirmed COVID-19 between January 1, 2020, and April 20, 2020, with no restriction on language. Articles were independently evaluated by two expert authors. We included all retrospective studies that reported the clinical features and outcomes of pregnant patients with COVID-19. Results: Forty-seven articles were assessed for eligibility; 13 articles met the inclusion criteria for the systematic review. Data is reported for 235 pregnant women with COVID-19. The age range of patients was 25-40 years, and the gestational age ranged from 8 to 40 weeks plus 6 days. Clinical characteristics were fever [138/235 (58.72%)], cough [111/235 (47.23%)], and sore throat [21/235 (8.93%)]. One hundred fifty six out of 235 (66.38%) pregnant women had cesarean section, and 79 (33.62%) had a vaginal delivery. All the patients showed lung abnormalities in CT scan images, and none of the patients died. Neutrophil cell count, C-reactive protein (CRP) concentration, ALT, and AST were increased but lymphocyte count and albumin levels were decreased. Amniotic fluid, neonatal throat swab, and breastmilk samples were taken to test for SARS-CoV-2 but all found negativ results. Recent published evidence showed the possibility of vertical transmission up to 30%, and neonatal death up to 2.5%. Pre-eclampsia, fetal distress, PROM, pre-mature delivery were the major complications of pregnant women with COVID-19. Conclusions: Our study findings show that the clinical, laboratory and radiological characteristics of pregnant women with COVID-19 were similar to those of the general populations. The possibility of vertical transmission cannot be ignored but C-section should not be routinely recommended anymore according to latest evidences and, in any case, decisions should be taken after proper discussion with the family. Future studies are needed to confirm or refute these findings with a larger number of sample sizes and a long-term follow-up period.

Hajj in the Time of COVID-19.

The recent outbreak of the novel COVID-19 is posing a severe public health risk across the globe. The Kingdom of Saudi Arabia (KSA) is one of the greatest destinations of religious congregations of Muslims. One of the largest religious gatherings is the Hajj that is anticipated to produce serious challenges of mass level exposures and spread to every corner of the world. Therefore, it is highly recommended that the Ministry of Hajj and Umrah (KSA), must regularly analyze the prevailing situation of COVID-19, and involve the religious scholars to make appropriate decisions about Hajj 2020. Although the Saudi government has been continuously taking all possible measures to contain the pandemic, people's cooperation is crucial in the fight against COVID-19.

A nursing informatics response to COVID-19: perspectives from five regions of the world

The 21st century has seen several infectious disease outbreaks that have turned into epidemics and pandemics including Severe Acute Respiratory Syndrome (SARS) which began in Asia in 2003 (Poon, Guan, Nicholls, Yuen, & Peiris, 2004), followed by H1N1 that emerged in Mexico and the United States in 2009 (Belongia et al., 2010). Next came the lesser known Middle East Respiratory Syndrome (MERS) originating in Saudi Arabia in 2012 (Assiri et al., 2013), after which the Ebola outbreak in West Africa took place from 2014 to 2016, with a more recent occurrence in the Democratic Republic of Congo from 2018 to 2019 (Malvy, McElroy, de Clerck, Günther, & van Griensven, 2019). To date, the coronavirus (COVID-19) outbreak that started in Wuhan, in the Hubei province of China, in late December 2019 seems to be eclipsing all of these previous infectious diseases in terms of its global reach and impact (Wang, Horby, Hayden, & Gao, 2020). After being declared by the World Health Organization (WHO) as a public health emergency on 30 January 2020 (World Health Organization, 2020c), it was elevated to a pandemic status on 11 March 2020 (World Health Organization, 2020d). As of 28 April 2020, there are more than 2.9 million cases and 202,597 deaths reported worldwide (World Health Organization, 2020b).