A Secure Wearable Framework for Stress Detection in Patients Affected by Communicable Diseases

The emergence of COVID-19 has drastically altered the lifestyle of people around the world, resulting in significant consequences on people's physical and mental well-being. Fear of COVID-19, prolonged isolation, quarantine, and the pandemic itself have contributed to a rise in hypertension among the general populace globally. Protracted exposure to stress has been linked with the onset of numerous diseases and even an increased frequency of suicides. Stress monitoring is a critical component of any strategy used to intervene in the case of stress. However, constant monitoring during activities of daily living using clinical means is not viable. During the current pandemic, isolation protocols, quarantines, and overloaded hospitals have made it physically challenging for subjects to be monitored in clinical settings. This study presents a proposal for a framework that uses unobtrusive wearable sensors, securely connected to an artificial intelligence (AI)-driven cloud-based server for early detection of hypertension and an intervention facilitation system. More precisely, the proposed framework identifies the types of wearable sensors that can be utilized ubiquitously, the enabling technologies required to achieve energy efficiency and secure communication in wearable sensors, and, finally, the proposed use of a combination of machine-learning (ML) classifiers on a cloud-based server to detect instances of sustained stress and all associated risks during times of a communicable disease epidemic like COVID-19. © 2001-2012 IEEE.

A fractal–fractional COVID-19 model with a negative impact of quarantine on the diabetic patients

In this article, we consider a Covid-19 model for a population involving diabetics as a subclass in the fractal–fractional (FF) sense of derivative. The study includes: existence results, uniqueness, stability and numerical simulations. Existence results are studied with the help of fixed-point theory and applications. The numerical scheme of this paper is based upon the Lagrange's interpolation polynomial and is tested for a particular case with numerical values from available open sources. The results are getting closer to the classical case for the orders reaching to 1 while all other solutions are different with the same behavior. As a result, the fractional order model gives more significant information about the case study. © 2023 The Author(s)

FAANG Stocks, Gold, and Islamic Equity: Implications for Portfolio Management during COVID-19

During the COVID-19 pandemic, technology stocks, such as FAANG stocks (Facebook, Amazon, Apple, Netflix, and Google), attracted the attention of global investors due to the vast use of technology in daily business. However, technology stocks are generally considered risky stocks;hence, efficient risk management is required to construct an optimal portfolio. In this study, we investigate the volatility spillovers and dynamic conditional correlations among the daily returns of FAANG company stocks, gold, and sharia-compliant equity to construct the optimal portfolio weights and hedge ratios during the COVID-19 pandemic period by utilizing a multivariate GARCH framework. The dynamic conditional correlations reveal that both gold and sharia-compliant equities exhibit lower correlations with FAANG stocks during the COVID-19 pandemic, implying opportunities for portfolio diversification. The findings indicate that gold and shariah-compliant equity are good candidates to hedge FAANG stocks. These findings are highly relevant for international investors, asset managers, hedgers, and portfolio managers.

Analysis of perceived risk and satisfaction with telematic follow-up in patients and families of congenital diaphragmatic hernia patients during SARS-CoV-2 pandemia.

BACKGROUND: The impact of COVID-19 in families and patients with congenital diaphragmatic hernia (CDH) is unknown, this situation has generated uncertainty not only in family members but also in the optimal outpatient follow-up. Telehealth has become a fundamental tool for the follow-up during the pandemic. The objective of this survey is to evaluated the impact of SARS-CoV-2 in families and patients with CDH and the satisfaction with telematic follow-up. METHODS: Telephone survey of patient's caregivers with CHD, aged 1-16 years, followed in neonatal surgery outpatients, from January 31, 2020 to November 15, 2020. The ethical clearance for this study was taken from the Clinical Research Ethics Committee of our Research Institute vide letter number VHIR/239283/01.01.2021. RESULTS: 81 surveys of 100 patients with active follow-up were carried out. There were no refusals in any contacted parents. There were 30 contacts (37%), 44.8% at school and 27.6% from cohabiting family members. Four infections (4.9%) were diagnosed, half symptomatic. In 40 patients (49.4%) the follow-up was telematic, with a mean score of 3.1±1.3 out of 5. For future controls, 65% prefer presential follow-up, 25% alternate and 10% telematics. 50.6% reported greater anxiety and 34.6% (28/81) extreme measures of isolation, being more accentuated in the group of 3-6 years (p<0.05). CONCLUSION: The impact of COVID19 in patients with CHD is not greater than in the general pediatric population. Although the incorporation of the telehealth was well valued, most of the caregivers prefer the face-to-face outpatient follow-up.

No significant increase in Guillain-Barré syndrome after COVID-19 vaccination in adults: A vaccine adverse event reporting system study.

OBJECTIVE: To investigate the association between Guillain-Barré syndrome (GBS) and COVID-19 vaccination. BACKGROUND: On July 13, 2021, the US Food and Drug Administration (FDA) released a new warning that Johnson & Johnson COVID-19 vaccine could increase the risk of developing GBS. METHODS: The reporting rate of adult GBS after COVID-19 vaccination, ascertained with Brighton criteria, was compared with the reporting rate after other vaccinations during the same time period, and also compared with the reporting rate during control periods. Statistical methods such as proportion tests, and Pearson's chi-squared test were utilized to identify significant relationships. Self-controlled and case centered analyses were conducted. A machine learning model was utilized to identify the factors associated with a worse outcome defined as emergency room (ER) or doctor visits, hospitalizations, and deaths. RESULTS: The reporting rate of GBS after COVID-19 vaccination was significantly higher than after influenza and other vaccinations (49.7, 0.19, 0.16 per 10 million, p < 0.0001). However, the reporting rate was within the incidence range of GBS in the general population. Using self-controlled and case centered analyses, there was a significant difference in the reporting rate of GBS after COVID-19 vaccination between the risk period and control period (p < 0.0001). There was an estimated 0.7-1.7 per million excess reports of GBS within 6 weeks of COVID-19 vaccination. Machine learning model demonstrated that female gender and age between 18 and 44 are associated with worse outcome. No association was found between the onset interval of GBS and its prognosis. CONCLUSIONS: Although the reporting rate of GBS after COVID-19 vaccination was not statistically different than that of the general population, the increased reporting of GBS within the first 6 weeks after COVID-19 vaccination, more so than with other vaccinations, suggests that some cases of GBS are temporally associated with COVID-19 vaccination. However, there is a reduction in the reporting rate of GBS after other vaccines, compared to reporting rates pre-COVID-19, highlighting limitations inherent in any passive surveillance system. These findings warrant continuous analysis of GBS after COVID-19 vaccination. Further improvement of the machine learning model is needed for clinical use.