A randomized controlled trial examining the impact of low vs. moderate-intensity aerobic training in post-discharge COVID-19 older subjects.

OBJECTIVE: Post-COVID-19 patients complained of pain, fatigue, breathlessness, and reduction in quality of life which required planned intervention. This study aimed to compare the impact of 10 weeks of low vs. moderate-intensity aerobic training on physical fitness, psychological status, and quality of life in post-COVID-19 older subjects. PATIENTS AND METHODS: 72 patients were randomized into 3 equal groups, moderate-intensity exercise (MIG, n = 24), low-intensity exercise (LIG, n = 24), and control group (CG, n = 24). The exercise was done 40 min/4 times per week for 10 weeks. We measured exercise capacity using the six-minute walking test, 1 min sit-to-stand test, post-COVID-19 functional scale (PCFS), and quality of life using the SF-36 questionnaire and HAMILTON Anxiety and Depression Scale (HADS). RESULTS: There was no difference between groups regarding the demographic and most clinical characteristics of the subjects. Compared with CG there were statistically significant improvements in studying groups (MIG and LIG) with (p < 0.05) in most outcomes and the improvement was higher in MIG than in LIG in most outcomes. CONCLUSIONS: 10-week moderate-intensity and low-intensity aerobic training programs are effective with superior effect to moderate-intensity. Moderate-intensity aerobic exercise is more effective and feasible in post-discharge COVID-19 older subjects regarding exercise capacity, quality of life, and psychological status than low-intensity aerobic exercise.

Third wave of COVID-19: mathematical model with optimal control strategy for reducing the disease burden in Nigeria.

The study of COVID-19 pandemic which paralyzed global economy of countries is a crucial research area for effective future planning against other epidemics. Unfortunately, we now have variants of the disease resulting to what is now known as waves of the pandemic. Several mathematical models have been developed to study this disease. While recent models incorporated control measures, others are without optimal control measures or demographic parameters. In this study, we propose a deterministic compartmental epidemiological model to study the transmission dynamic of the spread of the third wave of the pandemic in Nigeria, and we incorporated optimal control measures as strategies to reduce the burden of the deadly disease. Specifically, we investigated the transmission dynamics of COVID-19 model without demographic features. We then conducted theoretical analysis of the model with and without optimal control strategy. In the model without optimal control, we computed the reproduction number, an epidemiological threshold useful for bringing the third wave of the pandemic under check in Nigeria, and we proofed the disease stability and conducted sensitivity analysis in order to identify parameters that can impact the reproduction number tremendously. In a similar reasoning, for the model with control strategy, we check the necessary condition for the model. To validate our theoretical analyses, we illustrated the applications of the proposed model using COVID-19 data for Nigeria for a period when the country was under the yoke of the third wave of the disease. The data were then fitted to the model, and we derived a predictive tool toward making a forecast for the cumulative number of cases of infection, cumulative number of active cases and the peak of the third wave of the pandemic. From the simulations, it was observed that the presence of optimal control parameters leads to significant impact on the reduction of the spread of the disease. However, it was discovered that the success of the control of the disease relies on the proper and effective implementation of the optimal control strategies efficiently and adequately.

Investigation of COVID-19 By Theoretical Docking of Medicines With Two Proteins

This study examined the docking of two inhibition for SARS-Cov-2 virus (or COVID-19) these proteins are (6wtt and 6xa4) with nine pharmaceutical compounds (Aminoglutethimide, 4-Aminosalicylic acid, Felbamate, Hydroflumethiazide, Modafinil, Nepafenac, Oxcarbazepine, and Trichlormethiazide) which are used in the general human's life. These pharmaceuticals have different active groups in the structure conformation like (- NH2) and (-OH). Docking was applied the investigate the interaction between these medicines with the proteins using Molecular Operating Environment software (MOE). The goal of this study was to find a novel drug that docked with some proteins and was regarded to be an effective therapy for COVID-19. © 2022 National Information and Documentation Center (NIDOC)

Impact of the COVID-19 Pandemic on Elderly Medical Admissions and Outcomes in a Tertiary Hospital in Northeastern Nigeria: A Comparative Retrospective Study.

BACKGROUND: The coronavirus infectious disease 2019 (COVID-19) has been shown to be more lethal in the elderly (>65 years), especially those with co-morbidities. This study examined the impact of the pandemic lockdown period on trends in elderly medical admissions and deaths. METHODOLOGY: This is a retrospective study of elderly medical admissions and deaths in the medical wards of a Nigerian hospital. Data for the months of March, April, May, June, and July of 2020 was compared to the same months before (2019) and after (2021). Analysis was done using STATA version 15.0. RESULTS: During the study period, two hundred and seventy-six elderly patients were admitted, with a mean age (±SD) of 73.4 ± 7.4 years. The most common diagnoses at admission were chronic kidney disease (CKD) (26.85%, n=74) and hypertensive heart disease (HHD) (21.7%, n=60). The highest admission was in 2021, with a total of 99 (35.9%). Overall, 60 mortalities were recorded, with a proportional mortality rate of 21.7%, which was highest in 2020 (25.0%) and lowest in 2021 (17.1%). There was no difference between the mortality rates of 2019 versus 2020 (P=0.82) and 2020 versus 2021(P=0.18). Sepsis (35.0%) and CKD (25.0%) were the major contributors in 2019. CONCLUSION: CKD and HHD were the most common diagnoses at admission, whereas sepsis, CKD, and CVD were the commonest causes of death. The Covid-19 pandemic did not significantly alter the elderly admission pattern in our setting.

CONTEXTE: Il a été démontré que la maladie infectieuse à coronavirus 2019 (COVID-19) est plus mortelle chez les personnes âgées (>65 ans), en particulier celles qui présentent des comorbidités. Cette étude a examiné l'impact de la période de verrouillage pandémique sur les tendances des admissions médicales et des décès de personnes âgées. MÉTHODOLOGIE: Il s'agit d'une étude rétrospective des admissions et des décès de personnes âgées dans les services médicaux d'un hôpital nigérian. Les données relatives aux personnes âgées pour les mois de mars, avril, mai, juin et juillet 2020 ont été comparées aux mêmes mois avant (2019) et après (2021). L'analyse a été réalisée à l'aide de STATA version 15.0. RÉSULTATS: Au cours de la période, deux cent soixante-seize patients âgés ont été admis, avec un âge moyen et un écart-type (ET) de 73,4 7,4 ans. Les diagnostics les plus fréquents à l'admission étaient l'insuffisance rénale chronique (IRC) (26,85 %, n=74) et la cardiopathie hypertensive (HHD) (21,7 %, n=60). Le nombre d'admissions le plus élevé a été enregistré en 2021, avec un total de 99 (35,9 %). Au total, 60 décès ont été enregistrés, avec un taux de mortalité proportionnel de 21,7 %, qui était le plus élevé en 2020 (25,0 %) et le plus faible en 2021 (17,1 %). Les preuves étaient insuffisantes pour montrer une différence entre les taux de mortalité de 2019 par rapport à 2020 (P=0,82) et de 2020 par rapport à 2021 (P=0,18). Le sepsis (35,0 %) et l'IRC (25,0 %) étaient les principaux facteurs de mortalité en 2019. CONCLUSION: L'IRC et l'HHD étaient les diagnostics les plus courants à l'admission, tandis que la septicémie, l'IRC et les MCV étaient les causes les plus fréquentes de décès. La pandémie de Covid-19 n'a pas modifié de manière significative le schéma d'admission des personnes âgées dans notre contexte. Mots clés: COVID-19, Personnes âgées, Mode d'admission, Mortalité.

The effects of COVID-19 pandemic and its related lockdown on female sexual function and reproductive health: An observational study in Egypt

This retrospective observational online study was carried out to evaluate the effect of the COVID-19 pandemic and its related lockdown on female sexual functions and reproductive health. It included 409 sexually active females. The sexual function was assessed using the Female Sexual Function Index (FSFI). The reproductive life was assessed by a structured self-administered questionnaire modified from Egypt Demographic and Health Survey. The study revealed a significant decrease in the overall FSFI score during the pandemic lockdown compared to the pre-pandemic score (19.3 ± 6 vs. 21.3 ± 6.4, P<0.001). Below half (41.6 %) of women were using contraception methods during the pandemic, while 27.9% had stopped taking contraception during the pandemic, 30.6% (57/186) of the pregnant women only tended to get pregnant. So, the COVID-19 pandemic and its related lockdown were associated with an elevated risk for female sexual dysfunction and altered women's reproductive health quality. Heath system should therefore develop new methods to provide basic reproductive health service, family planning services, and to ameliorate the female sexual function during COVID-19 pandemic including consults with physicians, counsellors, and psychologists, as well as health education programs, either in person or virtually via telemedicine. (Afr J Reprod Health 2022;26[9]: 64-75). © 2022, Women's Health and Action Research Centre. All rights reserved.

Face Mask Detection System using Convolutional Neural Network

According to the World Health Organization, the coronavirus also known as the COVID-19 pandemic, is causing a global health crisis, WHO and Other health organizations recommended wearing face masks as a protection measurement especially in work, school, university, malls, and any public places. The proposed system consists of a Convolutional Neural Network-based system that can recognize faces with masks and without a mask, The dataset used for this project consists of 3835 images of two types of images, people with masks and people without masks. By utilizing the TensorFlow framework we're able to get a 98.80% accuracy rate in training time while training the model with 200 epochs. © 2022 IEEE.

An Understanding of ‘Sustainable Development’ from a Shariah Perspective and the Role Played by Islamic Finance in Its Attainment to Absorb COVID-19 Pandemic Effect

Sustainable development has been gaining wide emergence in the western and Islamic world as a new paradigm of development, seeking the consideration of social and environmental aspects while pursuing economic growth. While the concept, in its modern form, only emerged in the 1980s, Islamic teachings reinforced it since its inception through its rulings that aim to achieve justice and social welfare, reflected in Maqasid Al Shariah (objectives of Islamic rulings). In this paper, we look to explain further, through qualitative secondary research, the link between Shariah and sustainable development and evaluate if Islamic finance, which theoretically should be aligned with the concept of sustainable development given its basis on Shariah, is contributing to its attainment. We find that, while some efforts are being done by Islamic financial institutions (IFIs) to prove this view, IFIs largely lack today in fully aligning their activities with Maqasid Al Shariah which has been limiting their role in the attainment of sustainable development. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

COVID-19 and perinatal outcomes among pregnant women admitted to isolation unit at Suez Canal university hospital, Egypt: A cross-sectional study

This study described the maternal and perinatal outcomes of pregnant women infected with COVID-19. A cross-sectional descriptive design was used in this study of 75 women diagnosed with COVID-19 in the isolation unit of Obstetrics and Gynecology Department at Suez Canal University hospital. Data was collected by a structured interview questionnaire and assessment of patients' records in the period from April 26, 2021, to October 31, 2021. This study found that 7/29 (24.14%) of women had abortions, 9/46 (19.57%) had preterm labor, 2/19 (10.53%) had both postpartum hemorrhage and puerperal pyrexia, 2/46 (4.35%) had an antepartum hemorrhage, and 2/52 (3.85%) had preeclampsia. Regarding fetal complications, 2/46 (4.35%) had intrauterine fetal distress, and 2/52 (3.85%) had a stillbirth. Concerning neonatal outcomes, 31.25% of cases needed NICU admission, 12.5% required mechanical ventilation and developed ARDS, 18.75% had low birth weight, and only 6.25% of all cases died. This study concluded that pregnant women with COVID-19 seem to have a high risk of abortion and preterm birth. Their neonates are at high risk of NICU admission and low birth weight.

Simulating the Upcoming Trend of Malaysia’s Unemployment Rate Using Multiple Linear Regression

This research paper presents the approach of applying the simulation technique to predict the upcoming trend of Malaysia’s unemployment rate. The recent Malaysia’s unemployment rate has fluctuated at quite a high rate ever since the COVID-19 pandemic occurred. Population growth, Growth Domestic Product (GDP), inflation rate, interest rate, exchange rate, investment, government expenditure and most importantly the number of COVID-19 cases act as the independent variables in this paper. The Multiple Linear Regression (MLR) is used to determine the significance of each variable to be included in the model and also to simulate the upcoming trend of Malaysia’s unemployment rate. The result of the analysis shows that the upcoming five years trend of Malaysia’s unemployment rate will continue to increase in the future based on the average value of the simulations conducted. © 2021, Springer Nature Singapore Pte Ltd.

A study of public knowledge and pharmacists perceptions of their roles in prevention of COVID-19

The objective was to assess the public knowledge and attitudes about COVID-19 and the role of pharmacists in the prevention of COVID-19. This was a cross-sectional, web-based study conducted between 1 February to 30 March, 2020. Two instruments were used;1) a 16-items validated questionnaire for the public;2) an open-ended interview questions for pharmacists. A descriptive as well as inferential statistics were used to analyze the questionnaire data and a qualitative analysis was used to analyse the open-ended interview questions. A total of 73 general public residing in 7 countries (Saudi Arabia, Sudan, Iraq, UK, Egypt, Eritrea and Germany) participated in the study. The study participnats showed moderate knowledge about COVID-19 (18.9 ± 2.2). There were no differences in the level of knowledge between the general public and those with medical background (p > 0.05). There was an association between female sex and a better attitudes about COVID19 as shown by the association of female sex with washing their hands (p = 0.049, Pearson coefficient = 4.9), and avoidance of travel during the COVID-19 pandemic (p = 0.045, Pearson coefficient=4.8). On the other hand, 39 pharmacists from different countries participated in the study. The majority of the pharmacists were from Saudi Arabia (30%), India (15.3%) and Sudan (10.3%). Pharmacists believed that they have important roles in educating the public about clinical fea-tures of COVID-19 and its transmission. Pharmacists also indicated that they can provide support by re-porting new cases and supplying pharmaceutical products while couseling patients about their use. The general public had a moderate knowledge about COVID-19. Pharmacists were aware about their role con-cerning public education and support to prevent COVID-19.

Physical and psychological response to physical rehabilitation in Coronavirus Disease-19 patient: A case report

Corona virus disease-19 (COVID-19) has affected people of various age groups with symptoms ranging from asymptomatic mild, moderate to severe symptoms. Patients with mild symptoms require no medical intervention whereas moderate or severe symptoms require hospitalization and medical management. The following case report discusses the recovery of a COVID-19 patient with moderate symptoms. In a COVID dedicated tertiary care hospital in Ha'il region, Saudi Arabia. Physiotherapy has a great role as a part of a multidisciplinary team in the management of patients with respiratory and physical problems. The report mainly presents the impact of the physiotherapy role in the recovery of the patient and improving his physical and psychological status.

Perspectives of physiotherapists and rehabilitation providers on the outbreak of covid-19 pandemic and potentially therapeutic roles

By the end of 2019 and the initial of 2020, similar symptoms of severe acute respiratory syndrome (SARS) pandemic are presented in China. Extraordinarily, COVID-19 has extensively spread worldwide within the last three months affecting humans' life and causing permanently a fearing sensation among all populations. All agencies worldwide recommended their populations to stay home to prevent and terminate this fatal infectious disease. During exposure to any pandemic infectious disease over history, many modalities of the treatment were reported to control and prevent its prevalence such as improving the public health, rehydration, and vaccinations that became the ideal strategies to exterminate these infectious diseases. No treatment modalities were reported to prevent or control the COVID-19 infection. Therefore, we have to highlight the role of physical therapy and rehabilitation against the outbreak of viral infection. This manuscript suggests that physical therapy and rehabilitation may eliminate the common harmful respiratory, circulatory, and physical complications that follow the exposure to viral infections. Also, it explains that the rehabilitation program may present an effective approach to retrieve physical and psychological functions besides medical treatment. In conclusion, serious recommendations have to be considered for conducting exercise training and telerehabilitation to prevent and control the outbreak of COVID-19.

Theoretical prediction of possible drug treatment of covid-19 using coumarins containing chloroquine moeity

Chloroquine was theoretically reacted with the coumarin compound. Two compounds viz. [N-(7-chloroquinolin-4-yl)-N-(5-(diethylamino)pentan-2-yl)-4-methyl-2-oxo-2H-chromene-7-sulfonamide] (3) and [N-(7-chloroquinolin-4-yl)-N-(5-(diethylamino)pentan-2-yl)-4-methyl-2-oxo-2H-chromene-6-sulfonamide] (4) were suggested. The results showed that compound 4 may influence the COVID-19 treatment. The physico-chemical parameters were determined through theoretical calculations by using Hartree-Fock at different basis sets (6-31G), (STO/3G) and the semi-empirical (AM1) method. The calculations demonstrated the scheme of reaction between coumarin and the chloroquine structure by using the predicted mechanisms. The physical and chemical properties of the predicted compounds were determined to select the optimal form as the candidate for COVID-19 treatment. Compound 4 was more stable than compound 3, with different proteins viz. 6YHU, 6YI3 and 6LU7. Three types of software, including Gaussian 03, Chem-Bio office and molecular operating environment (MOE) were employed. © This is an open access journal, and articles are distributed under the terms of the Attribution 4.0 International (CC BY 4.0) License. This license lets others distribute, remix, tweak, and build upon your work, even commercially, as long as they credit the author for the original creation. You must give appropriate credit, provide a link to the license, and indicate if changes were made.

Predicting Covid-19 Trajectory Using Machine Learning

The pandemic caused by COVID-19 in 2020 triggered a devastating effect on the economy and health of the world population, whose social implications for the next few years are still uncertain. Two types of standard tests are used to detect COVID-19: the viral test that indicates whether the patient is infected and the antibody test that allows us to observe if the patient has previously had an infection. These tests employ techniques such as reverse transcription and polymerase chain reaction (RT-PCR), immunochromatographic lateral flow or rapid test, and ELISA-type immunoassay In this paper we have designed and implemented a system whose main purpose is to detect the rise of Covid-19 cases using disruptive technologies such as artificial intelligence and intelligent computing, manifested through machine learning (Machine Learning) and deep learning (Deep Learning). Combined with data science, Big Data and advanced data analytics, among others that present various research and development options, it can help the early detection of COVID-19 through the search for relevant characteristics that allow the scientific community identify biochemical, molecular and cellular factors that facilitate the early detection of the virus in its different states of infection, incubation, propagation and treatments to be used © 2020 IEEE.

Analysis of coronavirus covid-19 pandemic model with discrete time delays

The outbreak of COVID-19 pandemic and its astronomic spread has become a huge threat to world health and economy. Different efforts are ongoing on the development of vaccines and drugs for COVID-19 treatment. However, the leading strategy to curtail the spread of the dis-eases has been various control measures which aim at breaking the chain of COVID-19 spread. In this work, we investigate the impact of government control measures and immune system strength on the spread of COVID-19 pandemic. Discrete delays are used to describe the restriction in social contacts due to government orders and the delay in infection manifestation due to immune response. The qualitative analysis of COVID-19 pandemic steady-state predict a stable state if COVID-19 latent period is negative and unstable state when the latent period is positive. The inclusion of delay in social contacts stabilizes the unstable pandemic steady-state when the infection is symptomatic and unstable when the infection is asymptomatic. Optimal strategy to flatten COVID-19 pandemic curve using social distance is also recommended. © 2020, Institute of Advanced Scientific Research, Inc.. All rights reserved.