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COVID-19 lockdown has caused disruption to education of all levels with far-reaching implications and unveiled the shortfalls of the current education model. Cycles of tightening and relaxation of COVID-19 lockdown confer uncertainty to the continuity of education. This article aims to comprehensively present the impacts of COVID-19 on primary, secondary and tertiary education and propose sound educational practices in the COVID-19 era. Papers related to educational impacts and implications of COVID-19 were selected for this review through a PRISMA model. The review shows that a shift of learning remotely or online has affected educators and learners, especially in relation to learning loss among learners, limitations in instructions, assessment and experiential learning in virtual environment, technology-related constraints, connectivity, learning resources and materials, besides psychosocial well-being. These impacts are exacerbated by inequalities in the distribution of resources as well as inequities attributed to socioeconomic status, gender, ethnicity, learning ability and physical conditions. The recommendations for future educational practices comprise adaptability of curricula to embed independent and online learning options, concurrence of diverse learning modalities for seamless learning transitions and flexibility, flexible staffing and learning model, enhanced support, technological and curricular innovation with simplification and standardization, as well as interactive, responsive and authentic virtual environment. This review contributes significantly to enhance preparedness of education to crisis while ensuring continuity and quality of education in the era of COVID-19 uncertainty. © 2022, This is a U.S. Government work and not under copyright protection in the US;foreign copyright protection may apply.
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Faced with COVID-19 and the trend of aging, it is demanding to develop an online health metrics sensing solution for sustainable healthcare. An edge radio platform owning the function of integrated sensing and communications is promising to address the challenge. Radar demonstrates the capability for noncontact healthcare with high sensitivity and excellent privacy protection. Beyond conventional radar, this article presents a unique silicon-based radio platform for health status monitoring supported by coherent frequency-modulated continuous-wave (FMCW) radar at Ku-band and communication chip. The radar chip is fabricated by a 65-nm complementary metal–oxide–semiconductor (CMOS) process and demonstrates a 1.5-GHz chirp bandwidth with a 15-GHz center frequency in 220-mW power consumption. A specific small-volume antenna with modified Vivaldi architecture is utilized for emitting and receiving radar beams. Biomedical experiments were implemented based on the radio platform cooperating with the antenna and system-on-chip (SoC) field-programmable gate array (FPGA) edge unit. An industrial, scientific, and medical (ISM)-band frequency-shift keying (FSK) communication chip in 915-MHz center frequency with microwatt-level power consumption is used to attain communications on radar-detected health information. Through unified integration of radar chip, management software, and communication unit, the integrated radio platform featuring <inline-formula> <tex-math notation="LaTeX">$-$</tex-math> </inline-formula>72-dBm sensitivity with a 500-kb/s FSK data rate is exploited to drastically empower sustainable healthcare applications. IEEE
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Background: The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected socially disadvantaged groups;however, the association between socioeconomic status and healthcare utilization among COVID-19 patients remains unclear. Therefore, a systematic review and meta-analysis was conducted to assess the association between socioeconomic status and hospitalization and intensive care unit admission among COVID-19 patients.Methods: PubMed, Embase, and the Cochrane Register of Controlled Trials were searched for relevant litera-ture (updated to Jun 2022). Studies that investigated the association of social deprivation with hospitalization and intensive care unit admission in COVID-19 patients were included. The primary outcomes included risk of hospitalization and intensive care unit admission, measured by odds ratio.Results: Eleven studies covering 2,423,095 patients were included in the meta-analysis. Socially disadvantaged patients had higher odds of hospitalization in comparison to socially advantaged patients (odds ratio 1.25, 95% confidence interval: 1.14 to 1.38;P<0.01). The odds of intensive care unit admission among more deprived patients was not significantly different from that of less deprived patients (odds ratio 1.03, 95% confidence interval: 0.78 to 1.35;P=0.85). These findings were proven robust through subgroup and sensitivity analyses.Conclusion: Socially disadvantaged populations have higher odds of hospitalization if they become infected with COVID-19. More effective medical support and interventions for these vulnerable populations are re-quired to reduce inequity in healthcare utilization and alleviate the burden on healthcare systems.
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In the fight against the COVID-19 pandemic, vaccines are the most critical resource but are still in short supply around the world. Therefore, efficient vaccine allocation strategies are urgently called for, especially in large-scale metropolis where uneven health risk is manifested in nearby neighborhoods. However, there exist several key challenges in solving this problem: (1) great complexity in the large scale scenario adds to the difficulty in experts' vaccine allocation decision making;(2) heterogeneous information from all aspects in the metropolis' contact network makes information utilization difficult in decision making;(3) when utilizing the strong decision-making ability of reinforcement learning (RL) to solve the problem, poor explainability limits the credibility of the RL strategies. In this paper, we propose a reinforcement learning enhanced experts method. We deal with the great complexity via a specially designed algorithm aggregating blocks in the metropolis into communities and we hierarchically integrate RL among the communities and experts solution within each community. We design a self-supervised contact network representation algorithm to fuse the heterogeneous information for efficient vaccine allocation decision making. We conduct extensive experiments in three metropolis with real-world data and prove that our method outperforms the best baseline, reducing 9.01% infections and 12.27% deaths.We further demonstrate the explainability of the RL model, adding to its credibility and also enlightening the experts in turn. © 2022 Owner/Author.
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Background: Several studies have demonstrated immunogenicity after COVID-19 vaccination in patients with autoimmune rheumatic diseases (AIRD) [1], but the differences between mRNA-based and vector vaccines and the cellular responses to COVID-19 vaccines according to distinct immunogenicity in AIRD patients are still unclear. Objectives: To investigate the differences in efficacy and safety between the vector vaccine ChAdOx1 nCoV-19/AZD1222 (Oxford-AstraZeneca) and mRNA-based vaccine mRNA-1273 (Moderna) in patients with AIRD, and to explore the cell-cell interactions between high and low anti-SARS-CoV-2 IgG levels in patients with rheumatic arthritis (RA) by single-cell RNA sequencing (scRNA-seq). Methods: From September 16 to November 15, 2021, we consecutively enrolled 243 participants aged ≥20 years with AIRD who received COVID-19 vaccination, of whom 113 were immunized with AZD1222 and 130 with mRNA-1273. The level of serum IgG antibodies to the SARS-CoV-2 receptor-binding domain on the spike protein S1 subunit was quantifed by electrochemiluminescence immuno-assay at 4-6 weeks after vaccination. Moreover, peripheral blood mononuclear cells were isolated from two RA patient with high anti-SARS-CoV-2 IgG level and four RA patients with low level for scRNA-seq and cell-cell communication signal was analyzed by CellChat. Results: The anti-SARS-CoV-2 IgG seropositivity rate was 78.8% (89/113) for AZD1222 and 83.1% (108/130) for mRNA-1273. The level of anti-SARS-CoV-2 IgG was higher in patients who received mRNA-1273 than in those who received AZD1222 (β: 30.15, 95% CI: 11.67-48.63, p=0.002) (Table 1). Prednisolone-equivalent dose >5 mg/day and methotrexate (MTX) use in AIRD patients, and non-anti-tumor necrosis factor (TNF)-α biologics and Janus kinase (JAK) inhibitor use in RA patients were associated with inferior immunogenicity. ScRNA-seq revealed CD16-monocytes were predominant in RA patients with high anti-SARS-CoV2-IgG antibody level, and enriched pathways related to antigen presentation via major histocompatibility complex class II (MHC class II) were found (Figure 1). HLA-DRA and CD4 interaction was vigorous among all identifed MHC-II pathway and was enhanced in high anti-SARS-CoV2-IgG antibody group. Conclusion: mRNA-1273 and AZD1222 vaccines exhibited differential immunogenicity in patients with AIRD. Enriched pathways related to antigen presentation via MHC class II in CD16-monocytes might be associated with higher anti-SARS-CoV2-IgG level in RA patients and further study is warranted.
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Based on the information suggested by World Health Organization (WHO) and Hong Kong Special Administrative Region (HKSAR) government, wearing a mask and sterilizing hands with alcohol-based hand disinfectants are effective ways to maintain good personal hygiene to prevent viral infections. This study focused on the real-time concentrations of alcohol vapor in the air associated with five alcohol-based hand disinfectants. The results indicated that the alcohol concentrations increased dramatically (max. ~46,000 ppb/g sample) in the hand-rubbing process. Hong Kong residents' survey on habits of using such disinfectants showed that 65% of people use them daily and 34% of people use them ≥ 5 times per day, indicating a high frequency of usage. About 79% of respondents claimed to have skin problems, and 18% got eyes discomfort when using these disinfectants. Despite the potential health risks of using alcohol disinfectants remaining unclear, such a large amount and frequent usage should be aware of potential health problems in the long term. © 2022 by the authors.
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Fully functioning hospitals are the backbone of society. The current design of hospitals in the UK and elsewhere tends to over-emphasise empirical knowledge and experimental research, but limits their ability to cope with new infectious diseases and increasing global connectedness. For example, around one-fifth of UK Covid-19 cases, including the majority of infected hospital healthcare workers, were infected in hospitals. This paper discusses a new agent-based modelling approach to developing more flexible and efficient hospital layouts that are better able to control the spread of infectious disease. © 2021 ICE Publishing. All rights reserved.
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Dino-Store is a persuasive game that was designed to use gamification way to communicate with people and raise awareness on COVID-19. The game's setting is grocery shopping and the mechanic indicates that how different protection strategies, such as wearing mask, keeping social distance can affect people's infection chances in the COVID-19 pandemic. This paper will break down how the game designed by merging concepts from persuasive game models and uncomfortable interaction theory to create an engaging, but stressful experience for the user. © 2021 Owner/Author.
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Background: Non-alcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease worldwide. The mainstay of treatment involves lifestyle modifications such as weight loss, exercise, and dietary changes to prevent the progression of liver disease. Since the emergence of the coronavirus disease 2019 (COVID-19), research efforts have focused on the influence of liver disease on COVID-19 and the impact of COVID-19 on those living with liver disease. The aim of this study was to assess the metabolic impact of COVID-19 on lifestyle behaviors of patients with NAFLD. Methods: We investigated the impact of the COVID-19 pandemic on dietary and lifestyle habits in patients with NAFLD using an online questionnaire. The questionnaire was distributed to patients identified to have a diagnosis of NAFLD or non-alcoholic steatohepatitis (NASH) through a search of the hospital electronic medical records system. Demographic information, anthropometric data, and dietary and lifestyle habits before and during the pandemic were inquired. The survey was conducted from December 2020 to March 2021. Results: A total of 360 out of 2,800 individuals responded to the survey. Incomplete surveys were excluded. Among the 312 respondents included, 84.6% identified ethnically as Caucasian, 60.6% were female, and 77.4% described themselves as overweight or obese. The mean age was 60.7 years. Of the respondents, 39.6% (p=0.002) and 51.4% (p<0.001) felt that their dietary habits and lifestyle habits significantly worsened, respectively. Consumption of fruits, vegetables, and water increased while the consumption of salty snacks, frozen desserts, and sugary beverages decreased during COVID-19 (Table 1). Moreover, there was a marked decrease in fast food consumption and increase in homecooked meals (Table 1). There was a decrease in physical activity and an increase in screen time on working and non-working days primarily due to entertainment and boredom. Conclusion: Patients with NAFLD felt that their dietary and lifestyle habits were negatively impacted by the COVID-19 pandemic. Healthy dietary modifications were made in food and beverage consumption patterns before and during the pandemic. However, there was an increase in sedentary behaviors reflected by decreased physical activity and increased screen time. Our findings signify the importance of recognizing the impact of a global pandemic on healthy lifestyle and its downstream effects on patients with NAFLD.
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COVID-19 is a new type of infectious disease that has been massively outbroken in December 2019. So far, with the development and promotion of the vaccines against COVID-19, the epidemic throughout the world appears to be contained. In this paper, we propose a multi-layer prediction method with a SEIRD model which is improved from a classical Susceptible-Exposed-Infected-Recovered (SEIR) model. We expand the classical model by taking the effect of vaccines into account. Furthermore, we use epidemic data accessed from the U.S. government to fit the model and visualize the results, a conclusion that the U.S. will be able to contain its epidemic effectively by practicing the development and injection of vaccines can be inferred. © 2021 IEEE.
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OBJECTIVES: The transmission of COVID-19 has sent Malaysia into cycles of tightening and relaxation of movement control, which are still continuing currently in line with local fluctuations of new COVID-19 cases. During movement control, measures comprising physical distancing, hand cleaning or sanitizing, and sanitization of premises are consistently implemented while self-isolation and travel restrictions are adaptively enforced. This study aims to examine if the control of COVID-19 transmission has an effect on the national influenza occurrences as some measures for COVID-19 control are similar to those for influenza. STUDY DESIGN: For this study, data of weekly new cases of influenza and COVID-19 were obtained from official platforms for non-parametric statistical analysis. METHODS: This study compared the influenza occurrences before and after the onset of COVID-19 using the Mann-Whitney U-test and explored Spearman's correlations between COVID-19 and influenza incidences after the onset of COVID-19. RESULTS: It shows that influenza incidences before and after the onset of COVID-19 were significantly different and that influenza cases have significantly reduced after the onset of COVID-19. The weekly cases of influenza and COVID-19 were significantly and negatively correlated. CONCLUSIONS: This study underscores the co-benefits of COVID-19 control measures and alleviates the concern for the risk of COVID-19 and influenza co-infection.
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COVID-19 , Influenza, Human , Humans , Influenza, Human/epidemiology , Influenza, Human/prevention & control , Malaysia/epidemiology , SARS-CoV-2 , TravelABSTRACT
Under the influence of COVID-19, more and more e-commerce companies are in urgent need to understand the causality and impact probability of B2B strategies, and formulate effective cooperative operation strategies. Although recently, few articles believe that B2B strategies are beneficial to improving enterprise profitability. In this paper, data from 362 takeout APP users were surveyed by questionnaire. Through machine learning, Bayesian Networks (BNs) algorithm was adopted to analyze the B2B strategy adopted by the takeout industry for the impact of COVID-19. Firstly, BNs analysis structure is designed according to prior knowledge and market information. Then the maximum likelihood estimation is used to calculate the conditional dependence probability. Finally, the effectiveness of BNs model is verified by training set and test set. The results show that the causal relationship between B2B strategies is highly concentrated in rider's daily health clock, and this strategy is also dependent on green passcode, highlighting the reliability of the windowing strategy. The contribution of this paper is to introduce BNs to B2B strategies and dependent probabilities, specifically providing a feasible way to find the causal relationship between strategies. © 2021 IEEE.
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The new coronavirus is a highly infectious and lethal RNA coronavirus, which may have been from a bat parasitic virus through its infection and evolution in a mammalian intermediate host. The new coronavirus has caused a pandemic of more than 24 million infections and more than 800 thousand deaths in a short period of time without strict and standard physical insulation. It has severely affected human health and economic development, and it is still threatening people's lives today. Its typical characteristics are the refractory nature and high mortality of clinically severe diseases, which lead to excessive consumption and even collapse of medical resources. Therefore, the clinical severe cases in the literature were analyzed, the risk factors of severe COVID-19 were summarized and potential severe risk markers were explored to guide the prevention and treatment of COVID-19. Nineteen risk factors were highlighted that suggested severe illness of the new coronavirus from three aspects: individual characteristics, disease factors, and biomarkers. Overall, it is recommended that people with the above risk factors should be given prior protection during the prevention process, and relevant markers should be monitored in confirmed patients to reduce severe mortality and medical resource consumption. © 2020 IEEE.
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It is a new challenge for medical students and teachers to set up basic study of Medical Immunology fully online during the outbreak of coronavirus disease 2019 (COVID-19). To achieve the same educational quality with that of offline teaching, the online education design should be reconstructed according to the online cognitive rules of the students. During teaching progress, a cutting-edge research paper on COVID-19 was utilized as the main line for education design to accomplish the immunology teaching. We also combined multiple sources in auxiliary classroom and improved the interaction between the students and teachers through internet which might be the privilege of online teaching. These attempts achieved the curriculum standard requirements and the expected effect of education, which might provide future reference regarding the online or online-offline combined teaching model of Medical Immunology.
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In order to understand a pandemic like the COVID-19 crisis of 2020, we have to keep in mind larger patterns (e.g., information visualizations such as charts), and individual perspectives (e.g., interviews). However, it is challenging to connect these larger patterns with lived experiences. In this work-in-progress paper, we argue that interactive digital experiences such as games have the potential to bridge this gap by allowing players to explore the pandemic at multiple levels of abstraction. We present Essential Workers: an online multiplayer game which situates players as one of four workers?Nurse, Grocery Worker, Office Worker, or Delivery Driver?who face difficult dilemmas as they live through three weeks of rising infection during the COVID-19 pandemic. Through a core cooperative game mechanic, Essential Workers seeks to tie the constraints and choices of the individual to the health of their communities, and to simulate some of the interdependencies that keep our communities functional during the pandemic. We aim to illustrate our approach to key challenges commonly faced by designers seeking to model the entanglements of the individual and society. © 2020 ACM.