MIMIC model of teachers and students attitudes towards online learning during Covid-19: A gender perspective

Academic institutions around the globe have shifted to online learning because of the unpredictable spread of COVID-19. The present study aimed to compare teachers' and students' attitudes towards online learning during the pandemic and to examine the effects of gender differences on their attitudes. In study 1, we adapted the Test of eLearning Related Attitudes for Pakistani students in three steps: expert review, piloting, and validation. The individual and collective expert review was performed to adapt the teacher version into the student version using the Technique for Research of Information by the Animation of a Group of Experts (TRIAGE). We tested three sets of measurement invariance models for participants' status and gender in study 2. Data were collected from 289 university teachers (men = 158, women = 131) and 444 undergraduate students (boys = 156, girls = 287). The results demonstrated that both groups had highly positive yet different attitudes towards online learning. Teachers were more satisfied than students. Model fit was poor, and the overall factor structure, factor loadings, and intercepts varied across groups. Intergroup gender invariance illustrated heterogeneity in attitudes towards online learning favoring men teachers and boy students. Study strengths and implications for the promotion of a positive experience of online learning are discussed.

Study on the Comparison of Three Typical Gas Flow Standards for Calibrating Low Gas Flowmeter

A gas flowmeter for measuring low flow rate has been widely used in the field of medical, health, environmental protection, energy industry, aerospace, etc. To against Covid-2019, the requirement on the low flow rate has been increasing dramatically. At present, the typical standard devices for calibrating low gas flowmeter mainly include standard bell provers of gas flow, standard piston provers of low gas flow and standard laminar of low gas flow. Different measuring principles are adopted among these typical standard devices. To ensure the consistency of these typical standard devices, a comparison test is performed. The standard devices used in the comparison are of the same accuracy grade, with an extended uncertainty of 0.2%(k=2). The piston-type gas flow calibrator of grade 1.0 is selected as the transfer standard, and three flow points with high flow rate, medium flow rate and low flow rate are selected for test. The consistency of measurement results is evaluated by normalized deviation En. The comparison results are acceptable which show that three typical standard devices are accurate and reliable. © FLOMEKO 2022.All rights reserved

Impact on glycaemic outcomes of transitioning from in-person to virtual FreeStyle Libre onboarding during the Covid-19 pandemic

Background and aims: Onboarding of the FreeStyle Libre, an intermittently scanned continuous glucose monitoring (isCGM) device, was pre-dominantly conducted in-person prior to the Covid-19 pandemic. However, onboarding rapidly become virtual due to enforced social distancing restrictions. This audit aimed to determine if onboarding method impacted on glycaemic outcomes and engagement statistics in people living with diabetes (pwD). Method(s): PwD who started FreeStyle Libre between January 2019 and March 2022, had their mode of onboarding recorded and had >=70% data were identified and included within the audit. Glycaemic indices and engagement statistics (previous 90 day averages) were obtained from LibreView (Abbott, USA) three months after the last person was onboarded, and compared using linear models, adjusting for FreeStyle Libre duration, %active (where appropriate), age and sex. Result(s): From 1007 eligible participants (in-person 44% [n = 445];virtual 56% [n = 562]), FreeStyle Libre usage duration was greater for those onboarded in-person vs. virtually (974[891,1101) vs. 420[280,564] days [p < 0.001]). There were no significant differences in glycaemic or engagement indices between in-person and virtual onboarding methods: average glucose (10[9,11]) vs. 10[9,11])mmol/l), %time very-low (<3.0mmol/l, 0[0,1]) vs. 0[0,1]%), %time low (3.0-3.8mmol/ l, 2[1,4] vs. 2[1,4]), %time in range (3.9-10.0mmol/ l, 54[+/-17] vs. 53[+/-19]%), %time high (10.1-13.9mmol/ l, 27[21,31]) vs. 26[21,31]%), %time very-high (>13.9mmol/l, 14[6,24] vs. 15[7,26]%), %active (96[90,100] vs. 94[87,99]%) or scans/day (11[8,15] vs. 10[7,14]). Conclusion(s): There were no differences in glycaemic outcomes or engagement indices between pwD between onboarding methods. Virtual onboarding using online videos for isCGM is as equally effective as face to face.

Public agencies tweeting the COVID-19 pandemic: cross-country comparison of must have and forgotten communication topics

IntroductionDespite the importance of national-level public health agencies in times of a pandemic, there is limited comparative understanding of their must-have and forgotten pandemic-related communication topics. MethodsTo fill this gap in the literature, this article presents an analysis of COVID-related communication topics by national-level health agencies in Italy, Sweden, and the United States using the IDEA (Internalization, Distribution, Explanation, Action) model on crisis message framing. The public health agencies included in the study are the Italian National Institute of Health (Istituto Superiore di Sanita;ISS), the Public Health Agency of Sweden (Folkhalsomyndigheten), and the Center for Disease Control and Prevention (CDC) in the US. ResultsBased on these agencies' Twitter posts (n = 856) in the first 3 months of the pandemic, the article reveals a greater attention paid to action oriented (e.g., disease prevention) and explanatory messages (e.g., disease trends) than to distribution (e.g., transmission) and internalizing messages (e.g., risk factors) in all three countries. The study also highlights differences in terms of referrals to other communication channels and communication topics, especially in terms of these agencies' emphasis on individual risk factors (related to the risk of a person suffering from serious COVID-19-related health consequences) and social risk factors (related to the chance of an individual to become infected with COVID-19 because of the social context). DiscussionThe study's findings call for better incorporation of information that is directly relevant to the receivers (internalizing messages) by public health agencies.

Social media discussion on covid-19i on mental health in the US, UK, and india

Discovered in December 2019, Coronavirus (Covid-19) is an infectious disease that has spread rapidly around the world. The World Health Organization (WHO) declared Covid-19 a pandemic in March 2020. The pandemic has increased the severity and amount of mental health problems, including depression, stress, and anxiety. This research uses real-life Covid-19 Tweets collected from March 2020 until October 2021. The objective is to analyze tweets from the US, UK, and India to discover Covid-19's impact on mental health in the three countries and identify influential users in each country when discussing this topic. The result shows that the major themes in the US were related to government and politics. Some dominant users in the US are news accounts and people who have occupations such as journalists, hosts, and presenters. The UK's theme focuses on relationships between friends and families, with doctors and medical workers as dominant users. India focuses on mental health and education, with dominant users including news-related accounts and some politicians. © 2022 Authors. All rights reserved.

Comparison Analysis of Prediction the Number of Covid-19 Cases Using Support Vector Regression and Long Short-Time Memory

Covid-19 emerged as a pandemic outbreak that spread almost worldwide at the end of December 2019. While this research was carried out, the Covid-19 pandemic was still ongoing. Many countries have made various attempts to overcome Covid-19. In Indonesia, the government and stakeholders, including researchers, have made many activities to reduce the number of positive patients. One of many activities that the government made is the vaccination program. The vaccination program is believed to be the most effective in reducing the number of positive cases of Covid-19. But nobody knows when the Covid-19 pandemic will end. Stakeholder has to know how the trend of Covid-19 cases in Indonesia to make a better decision for facing Covid-19 cases. This study aims to predict the number of positive Covid-19 cases in Indonesia by conducting a comparative analysis performance of Support Vector Regression (SVR) method and Long Short-Term Memory (LSTM) method in machine learning to the prediction of the number of Covid-19 cases. This study was conducted using the dataset Covid-19 in Indonesia from Control Team from 13 January 2021 until 08 November 2021 and with 300 records. The evaluation has been conducted to know the performance of the model prediction number of Covid-19 with Support Vector Regression method and Long Short-Term Memory method based on values of R-Square (R2), the value of Mean Absolute Error (MAE) and Mean Square Error (MSE). The research found that the method Support Vector Regression has better performance than Long Short-Term Memory method for making a prediction of the number Covid-19 using Machine Learning model based on the value of accuracy and error rate based with the value of R-Squared, MAE, and MSE are consecutively 0.902, 0.163, and 0.072. © 2022 IEEE.

Comparison of Methods of Assessment and Results of Traditional Osce with Electronic-Osce

Introduction: The onset and rise of COVID-19 and its sudden progression to a worldwide pandemic lead medical and dental institutes to change their way of teaching and conducting assessments to distance learning as compared to the previously applied conventional approaches. Teaching and assessment during this era have changed vastly, earlier it was solely traditional/live Objective Structured Clinical Examination (OSCE) but due to the current circumstances electronic/online OSCE (E-OSCE) method was introduced. In Pakistan also, Pakistan Medical Council (PMC) and the College of Physicians and Surgeons of Pakistan (CPSP) conducted online exams so that the scheduled exams do not get delayed. Aim(s): The main objective of this paper is to measure the reliability of an E-OSCE and to compare it with the traditional OSCE. Methodology: This was a cross-sectional study which got conducted at the Rawal Institute of Health Sciences, Islamabad. Traditional OSCEs and E-OSCEs were conducted with 71 participants including final year students and house officers. Each OSCEs had 10 stations, including one interactive station in traditional OSCE. Students' scores in both the OSCEs were collected and paired t-test was used to compare the mean scores at p<0.05. Result(s): Total number of house officers were 27 and final year students were 44. The scores of 71 participants were collected. The difference between mean scores of house officers' traditional OSCE and E-OSCE was statistically significant (p=0.000). The difference between final year students traditional OSCE and E-OSCE was also statistically significant (p=0.020). Finally, the overall difference between traditional OSCE and E-OSCE was also statistically significant (p=0.000) Practical implication: The main objective of this study was to assess the reliability of an E-OSCE and to compare whether the electronic method of conducting OSCE is more reliable than the traditional method of conducting OSCE. Conclusion(s): Despite limitations and the biases, the results of E-OSCE proved to be better than traditional OSCE. Further research needs to be conducted on E-OSCE to control the factors causing biases and limitations.Copyright © 2023 Lahore Medical And Dental College. All rights reserved.

Industry Structure of Commercial Districts and the Impact of COVID-19

This paper aims to empirically analyze the difference in the closure rate of the commercial district according to the industry structure of the commercial district. Theoretically, the larger the number of stores in a commercial district, the greater the positive externality caused by the agglomeration economies in consumption, namely, the external economies of scale. However, the agglomeration economies could occur from comparison shopping or one-stop shopping, depending on the business structure of the commercial district. According to the empirical results of the regression analysis of all 1164 commercial districts in Korea, the more specialized a commercial district is by stores in a specific industry, the lower the closure rate of that commercial district. This means that the agglomeration economies in consumption are driven by comparison shopping rather than by one-stop shopping and implies that it is necessary to introduce incentives that allow stores in the same industry to cluster together in terms of policy. Meanwhile, if the closure is limited to a specific industry, it will cause an endogeneity problem since it affects the industry structure of the commercial district. Considering this, as a result of additional estimation by 2SLS and GMM using instrumental variables, the error in estimation due to the endogeneity problem was not large, confirming that COVID-19 corresponds to an overall external shock that is not limited to a specific industry. In addition, this paper presents diagnostic indicators for commercial districts to measure the impact of COVID-19. Through this, it will be possible to alleviate conflicts between social classes over compensation or subsidies for sanctions for quarantine. To the best of our knowledge, it is the first time to use all commercial districts in Korea for a research in evaluating the impact of COVID-19, and empirical results on agglomeration economies focusing on the consumption side are limited.

SARS-CoV-2 sequencing: A comparison of highthroughput methods

Background/Objectives: The COVID-19 pandemic continues to threaten public health and burden healthcare systems worldwide. Whole SARS-CoV-2 genome sequencing has become essential for epidemiological monitoring and identification of new variants, which could represent a risk of increased transmissibility, virulence, or resistance to vaccines or treatment. In this study, we assess the performance of various target enrichment methods for whole SARS-CoV-2 sequencing. Method(s): We applied three target enrichment methods - two multiplex amplification methods and one hybridization capture - to the same set of nasopharyngeal patient samples (N = 93) in high-throughput mode. SARS-CoV-2 genome was obtained using short-read next-generation sequencing. Result(s): All three methods provided excellent breadth of coverage of SARS-CoV-2 genome (above 99%), albeit with vastly different sequencing depth (5-fold difference) and uniformity of coverage (20% difference in coefficient of variation). Poor local coverage has negative impact on variant calling in the concerned region, leading to an occasional allele drop-out (1.2% SNPs affected for one method). Conclusion(s): We discuss the performance of each target enrichment method and their potential for scaling up, in order to promote prospective programs of large-scale genomic surveillance of SARS-CoV-2 worldwide. Genomic surveillance will be crucial to overcoming the ongoing pandemic of COVID-19, despite its successive waves and continually emerging variants.

Retrospective review of vaccination status in patients with newly diagnosed chronic lymphocytic leukaemia

Introduction: Patients with chronic lymphocytic leukaemia (CLL) are at increased risk of infection. CLL is associated with a secondary immunodeficiency and impaired response to vaccination. Recent British Society of Haematology guidelines recommend that patients with CLL should receive vaccination against pneumococcal infection at diagnosis, an annual influenza vaccine and COVID-19 vaccination. Patients aged 70-79 years should also receive the Shingrix vaccine. Patients with CLL should not receive live vaccines. In response to this guideline, a letter detailing vaccination requirements was created for patients to give to their general practitioner (GP). The local process for vaccination referral has since changed. Previously, vaccination requirements were communicated to the GP via letter. There is now a dedicated Vaccination Hub to which clinicians can directly refer patients for appropriate vaccinations. Aim(s): The aim of this project was to assess vaccination referral and vaccination status in patients with newly diagnosed CLL. Method(s): All new diagnoses of CLL from 2021 to 2022 were identified by review of the Haematology Multi-Disciplinary Team meeting electronic registration forms. Electronic patient records were reviewed to determine vaccination referral completion and vaccination status. Result(s): A total of 29 patients were identified as new diagnoses of CLL. Seventeen patients were diagnosed in 2021 and 12 in 2022. Sixty-nine percent of the patients were male and the average age was 70.9 years. Vaccination was discussed with 11 patients (38%) and 10 patients (34%) were referred for vaccination. Eleven patients (38%) had never received a pneumococcal vaccine. Nine patients (31%) had previously received the vaccine but not within the past 5 years. Five patients (17%) patients had received one dose of Pneumovax 23 following referral. No patients had received the initial Prevenar 13 vaccine. Twelve patients (41%) had not received an influenza vaccine. Of those who had received the vaccine, the majority (70%) had received this routinely. Similarly, 71% of patients had received the COVID-19 vaccine routinely as opposed to three patients who received this postreferral. Of those who were eligible, 50% had received the Shingrix vaccine. Conclusion/Discussion: Local rates of vaccination in patients with CLL are low. Numbers were too small to allow for comparison between the methods of referral. Of those referred, not all received the appropriate vaccinations. Further work is therefore required to improve both the number and completion of the referrals. Future steps will include local teaching on vaccinations in CLL and the referral pathway.

Research on changes in physical measurement data of ordinary high school students during the COVID-19 based on big data analysis technology

The multiple comparison method refers to the hypothesis test of whether there is a significant difference between the means of each sample after the analysis of variance is performed on the samples of each group to be tested. In data analysis, the multiple comparison method can perform a more precise difference analysis based on the analysis of variance. Therefore, this study will select the LSD (Least significant difference) test method in the multiple comparison method to analyze the physical fitness test scores of males and females in the three grades from 2019 to 2021 in the investigated schools. In this way, we can understand the substantial impact of students' home-based learning on students' physical health during the new crown epidemic, so as to make targeted development plans for students' physical health in the current special period, and minimize the adverse impact of the new crown epidemic on students' physical health. © 2023 SPIE.

Research on the physical health changes of college students during the new crown epidemic based on big data analysis technology

Multiple comparisons are general term for hypothesis testing of whether there is a significant difference between the means of each sample after analysis of variance. ANOVA can only determine whether there is a difference between the population means, and multiple comparisons can further test the differences between the sample means. This study will select the LSD (Least significant difference) test method in the multiple comparison method to conduct a differential test on the physical fitness test data of four different grades from 2018 to 2021 since the COVID-19 epidemic, and analyze the physical fitness of Chinese students under the background of new coronavirus epidemic. Change characteristics of health level, and summarize relevant experience, urge relevant personnel to make targeted improvements to the future work of students' physical health training, and scientifically improve the physical health level of Chinese students. © 2023 SPIE.

An observer comparison study to evaluate a machine learning model to quantify the infected pneumonia on lung CT images

Quantification of infected lung volume using computed tomography (CT) images can play a critical role in predicting the severity of pulmonary infectious disease. Manual segmentation of infected areas from several CT image slices, however, is not efficient and viable in clinical practice. To assist clinicians in overcoming this challenge, we developed a new method to automatically segment and quantify the percentage of the infected lung volume. First, we used a public dataset of 20 COVID-19 patients, which consists of manually annotated lung and infection masks, to train a new joint deep learning (DL) model for lung and infection segmentation. As for lung segmentation, a Mask-RCNN model was applied to the lung volume with a novel postprocessing technique. Following that, an ensemble model with a customized residual attention UNet model and feature pyramid network (FPN) models was employed for infection segmentation. Next, we assembled another set of 80 CT scans of Covid-19 patients. Two chest radiologists manually evaluated each CT scan and reported the infected lung volume percentage using a customized graphical user interface (GUI). The developed DL-model was also employed to process these CT images. Then, we compared the agreement between the radiologist (manual) and model-based (automated) percentages of diseased regions. Additionally, the GUI was used to let radiologists rate acceptance of the DL-model generated segmentation results. Analyzing the results demonstrate that the agreement between manual and automated segmentation is >95% in 28 testing cases. Furthermore, >53% of testing cases received the top assessment rating scores from two radiologists (between four-five- score). Thus, this study illustrates the feasibility of developing a DL-model based automated tool to effectively provide quantitative evaluation of infected lung regions to assist in improving the efficiency of radiologists in infection diagnosis. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.

Impact of comorbidities on people with and without cancer early in the COVID-19 pandemic: An observational study.

BACKGROUND: The present study sought to investigate how comorbidity burden influences cancer survivors' quality of life (QoL) and the challenges/adaptations during the coronavirus disease 2019 (COVID) pandemic, and to examine how appraisal processes are related to this impact. METHODS: This cross-sectional study, administered in spring/summer 2020, compared cancer survivors to a general-population comparison sample. QoL was assessed with standardized tools. COVID-specific questions included selected items compiled by the US National Institutes of Health, and cognitive appraisal processes were assessed using the QoL Appraisal Profilev2 Short-Form. Principal components analysis reduced the number of comparisons. Multivariate analysis of covariance investigated group differences in QoL, COVID-specific variables, and cognitive-appraisal processes. Linear regression investigated group differences in COVID-specific variables as a function of cognitive-appraisal processes, QoL, demographic covariates, and their interactions. RESULTS: Cancer survivors fared substantially better than non-cancer participants in QoL and cognitive functioning when they had no other comorbidities, but substantially worse on QoL when they had three or more comorbidities. Cancer survivors with no comorbidities were less likely to feel worried about COVID, less likely to engage in self-protection, and prioritized engaging in problem-focused and prosocial actions compared to non-cancer participants. Conversely, cancer survivors confronted with multiple comorbidities exhibited more proactive self-protection and experienced more anxiety about the pandemic. CONCLUSION: The impact of having multiple comorbidities in the context of cancer is associated with notable differences in social determinants of health, QoL outcomes, COVID-specific challenges/adaptations, and appraisal of QoL. These findings provide an empirical basis for implementing appraisal-based coping interventions.

Disruptions to in-person medical visits across the United States during the COVID-19 pandemic: evolving disparities by medical specialty and socio-economic status.

OBJECTIVES: This study aimed to investigate how people's health-seeking behaviors evolve in the COVID-19 pandemic by community and medical service category. STUDY DESIGN: This is a longitudinal study using mobility data from 19 million mobile devices of visits to all types of health facility locations for all US states. METHODS: We examine the variations in weekly in-person medical visits across county, neighborhood, and specialty levels. Different regression models are used for each level to investigate factors that influence the disparities in medical visits. County-level analysis explores associations between county medical visit patterns, political orientation, and COVID-19 infection rate. Neighborhood-level analysis focuses on neighborhood socio-economic compositions as potential determinants of medical visit levels. Specialty-level analysis compares the evolution of visit disruptions in different specialties. RESULTS: A more left-leaning political orientation and a higher local infection rate were associated with larger decreases in in-person medical visits, and these associations became stronger, moving from the initial period of stay-at-home orders into the post-lockdown period. Initial reactions were strongest for seniors and those of high socio-economic status, but this reversed in post-lockdown period where socio-economically disadvantaged communities stabilized at a lower level of medical visits. Neighborhoods with more female and young people exhibited larger decreases in in-person medical visits throughout the initial and post-lockdown periods. The evolution of disruptions diverges across medical specialties, from only short-term disruption in specialties such as dentistry to increasing disruption, as in cardiology. CONCLUSIONS: Given distinct patterns in visit between communities, medical service categories, and between different periods in the pandemic, policy makers, and providers should concentrate on monitoring patients in disrupted specialties who overlap with the at-risk contexts and socio-economic factors in future health emergencies.

Violence against healthcare workers in the middle of a global health crisis: what is it about policy and what to learn from international comparison?

Introduction: Violence against healthcare workers is a global health problem threatening healthcare workforce retention and health system resilience in a fragile post-COVID 'normalisation' period. In this perspective article, we argue that violence against healthcare workers must be made a greater priority. Our novel contribution to the debate is a comparative health system and policy approach. Methods: We have chosen a most different systems comparative approach concerning the epidemiological, political, and geographic contexts. Brazil (under the Bolsonaro government) and the United Kingdom (under the Johnson government) serve as examples of countries that were strongly hit by the pandemic in epidemiological terms while also displaying policy failures. New Zealand and Germany represent the opposite. A rapid assessment was undertaken based on secondary sources and country expertise. Results: We found similar problems across countries. A global crisis makes healthcare workers vulnerable to violence. Furthermore, insufficient data and monitoring hamper effective prevention, and lack of attention may threaten women, the nursing profession, and migrant/minority groups the most. There were also relevant differences. No clear health system pattern can be identified. At the same time, professional associations and partly the media are strong policy actors against violence. Conclusion: In all countries, muchmore involvement from political leadership is needed. In addition, attention to the political dimension and all forms of violence are essential.

Reflections on trust and COVID-19: do politics, medicine and the environment need each other?

This short article is centred on how trust can be a valuable resource for developing cognate responses to the COVID-19 pandemic in the medical and social sciences. Politics and medicine can learn from each other. Governments need to persuade individuals to adapt their behaviours, and such persuasion will be all the more convincing in that it is nested in social networks. Trust in government requires consistent (benevolent, performative and joined-up) explanations. The distinction between hard medical and soft social science blurs when patients/citizens are required to be active participants in combatting a pandemic virus.

The impact and effectiveness of the general public wearing masks to reduce the spread of pandemics in the UK: a multidisciplinary comparison of single-use masks versus reusable face masks.

During the coronavirus (COVID-19) pandemic, the UK government mandated the use of face masks in various public settings and recommended the use of reusable masks to combat shortages of medically graded single-use masks in healthcare. To assist decision-making on the choice of masks for future pandemics, where shortages may not be a contributing factor, the University College London (UCL) Plastic Waste Innovation Hub has carried out a multidisciplinary comparison between single-use and reusable masks based on their anatomy, standalone effectiveness, behavioural considerations, environmental impact and costs. Although current single-use masks have a higher standalone effectiveness against bacteria and viruses, studies show that reusable masks have adequate performance in slowing infection rates of respiratory viruses. Material flow analysis (MFA), life cycle assessment (LCA) and cost comparison show that reusable masks have a lower environmental and economic impact than single-use masks. If every person in the UK uses one single-use mask each day for a year, it will create a total of 124,000 tonnes of waste, 66,000 tonnes of which would be unrecyclable contaminated plastic waste (the masks), with the rest being the recyclable packaging typically used for transportation and distribution of masks. Using reusable masks creates >85% less waste, generates 3.5 times lower impact on climate change and incurs 3.7 times lower costs. Further behavioural research is necessary to understand the extent and current practices of mask use; and how these practices affect mask effectiveness in reducing infection rates. Wearing single-use masks may be preferred over reusable masks due to perceptions of increased hygiene and convenience. Understanding behaviour towards the regular machine-washing of reusable masks for their effective reuse is key to maximise their public health benefits and minimise environmental and economic costs.

Determinants of customer loyalty to online food service delivery: evidence from Indonesia, Taiwan, and New Zealand

This study is dedicated to m-commerce and examines the key factors determining loyalty to online food delivery (OFD) services in Indonesia, Taiwan, and New Zealand, as these countries have faced varying degrees of pandemic severity. The data analysis using Partial Least Square Structural Equation Modeling (PLS-SEM) shows that the quality of both food and e-service, satisfaction, perceived value, and trust are significant predictors of loyalty in all countries. Food quality drives consumer loyalty, contentment, and perceived value in Indonesia and Taiwan, but e-service quality is the main determinant in New Zealand. These differences can be attributed to the status quo of the OFD service market in the three countries pre-Covid, cultural factors, the pandemic severity, and consumer access to other distribution channels. Best practice recommendations for marketing managers associated with OFD are presented.

Experimental and Clinical Evaluation of Mefloquine Effectiveness against the Infection Caused by Sars-Cov-2

The efficacy of mefloquine has not been studied in the in vivo experiments and clinical trials involving COVID-19 patients. The study was aimed to assess the effects of mefloquine on the SARS-CoV-2 accumulation in the lungs of infected animals and to study the efficacy and safety of mefloquine compared to hydroxychloroquine in patients with COVID-19. During the experiment, a total of 96 Syrian hamsters were infected with SARS-CoV-2. Accumulation of the virus in lungs was compared in the groups of animals treated with mefloquine and ribavirin and in the control group. During the clinical trial, the mefloquine and hydroxychloroquine safety and efficacy in patients with mild and moderate COVID-19 (172 individuals) was assessed based on the symptom changes over time and the computed tomography results. The experiment showed that the SARS-CoV-2 accumulation in the lungs of Syrian hamsters 6 days after infection and mefloquine treatment was 2.2 +/- 0.18 lg PFU/g, which was lower (p < 0.05) than in the control group (3.5 +/- 0.21 lg PFU/g) and ribavirin group (5.2 +/- 0.05 lg PFU/g). During the clinical trial, it was found that 50.0% of patients in the mefloquine group and 32.4% in the hydroxychloroquine group (p < 0.05) developed a mild disease, and the completely resolved respiratory failure was registered in 76.5% and 44.6%, respectively (p < 0.001). Adverse events were observed in 86.7 % and 77% of patients in the mefloquine and hydroxychloroquine groups, respectively (p > 0.05). Thus, during the experiment, mefloquine contributed to the faster virus titer reduction in the lungs. During the clinical trial, the mefloquine efficacy was non-inferiority or, based on a number of indicators, higher compared to hydroxychloroquine, with comparable safety.Copyright © Extreme Medicine.All right reserved.