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This research was been adopted to study the relationship between Covid and some necessary biological factors in human body and how these factors affected, This studying included three stages (Sever - Moderate - Mild) it was studied 20 patient for every stage and monitor the biological factors during infection and after infection.Copyright © 2023, Codon Publications. All rights reserved.
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Objectives: This article aims to discover the impact of the coronavirus pandemic lockdown on diabetes patients living in Almadina, Saudi Arabia, in terms of their lifestyle and on their follow-up. Method(s): This is a cross-sectional, qualitative prospective study, a questionnaire was done to diabetic patients who underwent the quarantine period in Madinah, Saudi Arabia through an online questionnaire after getting informed consent to participation. The survey included personal, medical data, patient's compliance to treatment and overall lifestyle manner before and during lockdown period and psychological assessment using 10 questions of the (K10) Kessler psychological distress scale. Data analysis was performed using SPSS program version 26. Result(s): A total of patients 350 participated in the study. 56.6% of them were females(n;198), and 43.4% were males(n:152), their ages ranged from 18 years to more than 60 years. The vast majority 96.3% of participated were of Saudi nationality, while 3.7% are non-Saudi. Participants-with types 2 Diabetes represent 31.4% while 26% suffer from type 1 diabetes and the rest they don't which type they have. Results showed no significant differences in: (symptoms of low or high blood sugar, the extent to which a healthy diet is followed, the frequency of home blood sugar measurement) before and during the quarantine period. The rest of the variables shows a significant difference (P<0.05) Conclusion(s): The study showed a difference in the extent of adherence to medication during the quarantine period compared to before. A reduction constructive in lifestyle habits is detected. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
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COVID-19 has influenced business operations all around the world, with the adoption of technology to sustain business operations and improve survival being on the rise across various sectors. This review was conducted to explore existing literature to uncover the effects that COVID-19 has had on Internet of Things (IoT) technology adoption, innovation, or research. The review was conducted through a search of literature sources detailing the impacts, the IoT technologies and solutions used as a result of the pandemic, and the various technologies and solutions that were invented before the pandemic but found higher demands because of the pandemic. The review reveals that COVID-19 has increased the adoption of IoT technology by more companies across diverse fields including healthcare, smart homes, smart offices, retail, airports, manufacturing, and hospitality. It also reveals that most businesses had plans for the gradual adoption of the IoT technologies that were already in existence before the pandemic but were pushed to procure and implement them as necessity arose. The review finally reveals that there are more IoT research and development efforts as a result of the pandemic. © 2021 IEEE.
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The world was shocked by an unprecedented outbreak caused by coronavirus disease 2019 (COVID-19). In Malaysia, it started with the largest number of COVID-19 cases with the first wave of infection on 25 January 2020. The objectives of this paper are to obtain the perspective of the respondents about the need for web-mapping in the form of mapping the geospatial data in Malaysia and to visualize the current online datasets of COVID-19 disease case clusters. The study area would cover the entire Malaysia since a rapidly increasing number of citizens were affected by this virus. To be specific, this study focused on the active clusters of COVID-19 in Malaysia. The data were freely shared in real-time by referring to the Ministry of Health (MOH) channel. The hotspots map were explored using the Map Editor by Cloud GIS. The approach has been illustrated using a dataset of whole Malaysia which are locally transmitted confirmed cases in four phases of COVID-19 wave in Malaysia. This study is significant to raise public awareness of the virus, especially among Malaysian citizens. It can provide an accurate estimation of the cluster tracking of the COVID-19 system by using geospatial technology. Therefore, people are more concerned and followed all the Standard Operating Procedure (SOP) provided by the government to prevent the spread of COVID-19. © 2021, Russian Geographical Society. All rights reserved.
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At the outset of year 2020, COVID-19 emerged as a new public health threat and the world resorted to a diverse range of combating plots including lock down downs, social distancing, advocating precautions like wearing masks, using sanitizers etc. Pakistan followed the same pathway despite the fact that the virus resulted in less severe morbidity and mortality as compared to the rest of the world. Nevertheless, the fear and panic it created due owing to virulence and subsequent outcomes of corona illness was of alarming magnitude. Pakistan went for smarter, conservative and prudent plans and kept the balance between saving lives and livelihoods. Health system showed its inherent weaknesses and it was soon realized that a multi-sectoral response would be needed to address the catastrophe. A large majority is inclined to call it a 'new normal' and is persuading to go on with life;for sure, by adopting a health system thinking.
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Background/AimsTelemedicine has not previously been a regular part of routinerheumatology services.Our department adopted telephone clinicsduring the COVID-19 pandemic. We assessed patient satisfaction byconducting a feedback survey. Our aim was to obtain a patientperspective on remote consultations and on preferred future follow upoptions including video or face-to-face consultations.MethodsThe cohort included 160 rheumatology patients who had a telephoneconsultation between May and mid-June 2020. All patients consentedto receive a further phone call by a different member of the team.Patients had to answer a questionnaire about recent consultation andto rate this on a scale of 1-5. Other questions included whether all theirqueries were answered;clear action plan made;perceived benefits ordisadvantages of telephone consultation;and views about futurefollow up and any additional comments.Results71.9% of 160 patients were females while 28.1 % males. Mean age58.6 yrs. More than half of the patients (60.6%) had a diagnosis ofinflammatory arthritis, followed by connective tissue disease (19.3%), other diagnosis (8.1% ) & vasculitis (5.6%). 94.4 % of the patients inthis study were return appointments-the remainder new. Feedbackresults revealed 92.5% patients were satisfied with their consultationwith mean score of 4.3/5 (5=best, 1= worst). More than 80% agreedthat all their queries were answered and a clear action plan wasformed during consultation. However , 71.2% would want a face toface consultation if given choice while 54 % happy to have furtherfollow up over the phone. 65% of patients preferred not to have videoconsultation. Subgroup analysis showed that majority of patients whowould accept video consultation were aged between 30-39. Mostcommon benefits described were noted to be convenience;reducedtime of work;travel time and safety during pandemic, whilst difficulty indescribing symptoms;hearing problems;and severity of disease weredisadvantages raised, but numbers were small in our cohort.ConclusionTelephone clinics were the mainstay during the COVID-19 pandemic.Thelarge majority of the rheumatology patients in our cohort were highlysatisfied with this form of consultation. However, interestingly themajority (71% ) would still prefer face-to-face consultation as follow up inthe future. Regular follow up in carefully selected patient groups cansuccessfully be performed by telephone clinics with good patientsatisfaction. This would help increase capacity within the clinic setting.
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Transfer Learning (TL) opens new possibilities of detection of disease through radiography as compared to conventional machine learning as well as deep learning methods. The extraction of features through pre-trained Convolutional Neural Networks (CNN) and the tuning of the fully connected layers of the CNN model is the core for the development of a transfer learning pipeline. The present study investigates the diagnosis of COVID-19 through X-ray images by means of three TL models, namely Inception V3, VGG-16, and the VGG-19 for feature extraction along with heuristically fine-tuned fully connected layers. It was demonstrated through this preliminary work that both the VGG-16 and VGG-19 tuned pipelines could achieve a train and test classification accuracies of 99.8% and 94%, respectively. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.