College Students Online Education Evaluation Through SWOT Analysis During COVID-19

The COVID-19 epidemic has disrupted the normal teaching and learning in universities, which poses significant challenges to college education. The traditional face-to-face learning mode has been switched to online (distance) learning, causing various influences on students' academic performance. As higher education plays a central role in technology innovation and society development, it is of great importance to investigate and improve online education in the context of COVID-19. This study distributed online questionnaires to college students from 30 provinces or municipalities in China to evaluates the SWOT (Strengths, Weaknesses, Opportunities, and Threats) factors of shifting from traditional learning to online learning during COVID-19 Pandemic. The SWOT analysis has been employed to construct 16 kind of internal and external evaluation factors and 4 kind of improvement strategies for assess online education. The basic data of subjective weight method - AHP comes from the questionnaire survey, and the weight value of SWOT factors are determined through the questionnaire survey results. The fuzzy MARCOS approach is used to select the most suitable strategies for its effective implementation. Several coping strategies are suggested to improve the online education in post-pandemic era, which is essential for higher education and promoting a civilized and sustainable society. "By reforming and innovating the teacher led teaching mode, stimulate students' interest in learning, get rid of the boring learning state, create a good learning atmosphere and improve the teaching quality" is the most effective strategy to enhance the online learning experience and increase students' satisfaction. This methodology is applicable with a case study concerning the students' online education in pandemic and the validity of this approach is presented through comparative analysis and sensitivity analysis. Through example verification, it is found that SWOT method is suitable for online education evaluation research no matter how the research object changes.

An Agent-Based Modeling and Virtual Reality Application Using Distributed Simulation: Case of a COVID-19 Intensive Care Unit

Hospitals and other healthcare settings use various simulation methods to improve their operations, management, and training. The COVID-19 pandemic, with the resulting necessity for rapid and remote assessment, has highlighted the critical role of modeling and simulation in healthcare, particularly distributed simulation (DS). DS enables integration of heterogeneous simulations to further increase the usability and effectiveness of individual simulations. This article presents a DS system that integrates two different simulations developed for a hospital intensive care unit (ICU) ward dedicated to COVID-19 patients. AnyLogic has been used to develop a simulation model of the ICU ward using agent-based and discrete event modeling methods. This simulation depicts and measures physical contacts between healthcare providers and patients. The Unity platform has been utilized to develop a virtual reality simulation of the ICU environment and operations. The high-level architecture, an IEEE standard for DS, has been used to build a cloud-based DS system by integrating and synchronizing the two simulation platforms. While enhancing the capabilities of both simulations, the DS system can be used for training purposes and assessment of different managerial and operational decisions to minimize contacts and disease transmission in the ICU ward by enabling data exchange between the two simulations.

Application of People Flow and Face Mask Detection for Smart Anti-Epidemic

During the COVID-19 pandemic, World Health Organization (WHO) published two protection methods. One is maintaining social distance;the other is wearing the mask. Many reports indicate that keeping a safe distance and wearing face masks can reduce the risk of transmission during this pandemic. In this paper, we present a deep learning pipeline that can achieve pedestrian flow statistics, identify correct and incorrect mask-wearing simultaneously from real-time video streams. In our proposed system, the live video stream is taken as input. The alert will be broadcasted when people crowed and someone do not wear the mask. Experimental results show that the proposed system can achieve an effective detection solution and reduce the risk of infection. © 2021 IEEE.

Higher rates of COVID-19 but less severe infections reported for patients on Dupilumab: a Big Data analysis of the World Health Organization VigiBase.

OBJECTIVE: Dupilumab (Dupixent®) is a monoclonal antibody that inhibits IL-4 and IL-13 signaling used for the treatment of allergic diseases. Whilst biologic therapy is traditionally regarded as immunosuppressive and capable to increase the infectious risk, Dupilumab does not display these characteristics and may be even protective in certain cases. We investigated the link between Dupilumab therapy and SARS-CoV-2 infection. MATERIALS AND METHODS: We carried out a comprehensive data mining and disproportionality analysis of the WHO global pharmacovigilance database. One asymptomatic COVID-19 case, 106 cases of symptomatic COVID-19, and 2 cases of severe COVID-19 pneumonia were found. RESULTS: Dupilumab treated patients were at higher risk of COVID-19 (with an IC0.25 of 3.05), even though infections were less severe (IC0.25 of -1.71). The risk of developing COVID-19 was significant both among males and females (with an IC0.25 of 0.24 and 0.58, respectively). The risk of developing COVID-19 was significant in the age-group of 45-64 years (with an IC0.25 of 0.17). CONCLUSIONS: Dupilumab use seems to reduce COVID-19 related severity. Further studies are needed to better understand the immunological mechanisms and clinical implications of these findings. Remarkably, the heterogenous nature of the reports and the database structure did not allow to establish a cause-effect link, but only an epidemiologically decreased risk in the patients subset treated with dupilumab.

Effects of Comorbidities on the Elderly Patients with COVID-19: Clinical Characteristics of Elderly Patients Infected with COVID-19 from Sichuan, China.

OBJECTIVES: The co-occurrence of chronic diseases in the elderly is a common problem. However, the relationship between comorbidities and the prognosis of elderly patients with COVID-19 was not clear. This study was supposed to describe the clinical characteristics of elderly patients with COVID-19 infection from Sichuan province and the effects of comorbidity. DESIGN: A retrospective study. SETTINGS AND PARTICIPANTS: COVID-19 patients from Public Health Clinical Center of Chengdu between December 16, 2019 and February 26, 2020 were included in this study. Patients were divided into elderly group (≥60 years old) and non-elderly group (< 60 years old). RESULTS: Elderly patients with COVID-19 indicated relatively higher proportion of comorbidities, and the most common were atherosclerotic cardiovascular disease (56.5%), hypertension (43.5%) and chronic pulmonary disease (21.7%). The proportion of severe cases was higher in elderly group than that in non-elderly group (73.9% and 42.2%, respectively, P=0.012). During hospitalization, elderly patients indicated relatively higher proportion of complications, such as shock (21.7%), respiratory failure (21.7%). The proportion of patients with a decreased number of CD8+ lymphocytes (82.6%) and B lymphocytes (77.8%) in elderly patients was significantly higher than that in non-elderly group (48.9% and 44.8%, respectively). All 3 deaths were elderly patients with comorbidities and the cell counts of T lymphocyte subsets, B and NK cells of them were significantly decreased at admission. CONCLUSIONS: Elderly patients with COVID-19 had a high proportion of severe cases and comorbidities, more likely to show low immune function, and indicate higher proportion of complications.

[Pathological changes of fatal coronavirus disease 2019 (COVID-19) in the lungs: report of 10 cases by postmortem needle autopsy].

Objectives: To observe the pulmonary changes with coronavirus disease 2019 (COVID-19) in postmortem needle specimens, to detect the presence of 2019 novel coronavirus(2019-nCoV) in the lung tissues, and to analyze the clinicopathological characteristics. Methods: For 10 decedents with 2019-nCoV infection in Wuhan, bilateral lungs underwent ultrasound-guided percutaneous multi-point puncture autopsy, and pulmonary pathological changes were described in routine hematoxylin-eosin staining (HE) slides. Electron microscopy was also performed. The reverse transcription polymerase chain reaction (RT-PCR) was employed to detect 2019-nCoV nucleic acid in lung tissue, and the pathological characteristics were demonstrated in combination with clinical data analysis. Results: Of the 10 deaths associated with COVID-19, 7 were male and 3 were female. The average age was 70 (39-87) years. Medical record showed that 7 patients had underlying diseases. The average course of disease was 30 (16-36) days. Nine cases showed fibrinous and suppurative exudation in the alveolar cavity accompanied by the formation of hyaline membrane, and fibroblastic proliferation of alveolar septum. Type Ⅱ alveolar epithelial cells showed reactive hyperplasia and desquamation. Many macrophages accumulated in the alveolar cavity. Capillary hyaline thrombus and intravascular mixed thrombus were noted. In some cases, acute bronchiolitis with mucous membrane exfoliation, accumulation of bronchiolar secretions, and bronchiolar epithelial metaplasia occurred. In the cohort, a large number of bacteria (cocci) were detected in 1 case and a large number of fungi (yeast type) were detected in 1 case. Nine cases were positive for the nucleic acids of 2019-nCoV while one case remained negative by RT-PCR. Coronavirus particles were detected in the cytoplasm of type Ⅱ alveolar epithelium. Conclusions: The pulmonary pathological changes of fatal COVID-19 are diffuse alveolar damage (DAD), mainly in the acute exudative stage and the organic proliferative stage. There are fibrinous exudate aggregation in alveolar cavity with hyaline membrane formation, fibroblastic proliferation in alveolar septum, and alveolar epithelial cell injuries with reactive hyperplasia and desquamation of type Ⅱ alveolar epithelial cells. A large amount of neutrophils and monocytes infiltration is present in most cases and bacteria and fungi are detected in some cases, suggesting a serious bacterial or fungal infection secondary to the DAD.