Pricing the Pandemic: Evidence from the Bond Market in China

This study investigates whether and how the pandemic is priced in the bond market in China. Using the city-level COVID-19 cases on a daily basis, we find a significant positive relationship between the pandemic outbreak and corporate credit spreads, implying that investor risk perception on pandemic exposure attracts a premium. Consistent with the default risk channel, corporate financial resilience alleviates pandemic pricing. Information asymmetry and tail risk can amplify the pricing effect because of reduced investor risk-bearing capacity. These findings are robust in addressing endogeneity concerns. We contribute to the emerging literature on the pandemic effect on credit markets. © 2023 Taylor & Francis Group, LLC.

Exploration on the construction of the regional center of continuing medical education under the background of normalization of epidemic prevention and control

The COVID-19 epidemic is running at a high level globally, affecting all aspects of society, and medical education is no exception. With the rapid development of medical science, continuing medical education is an important way for medical workers to receive lifelong education. Meanwhile, attending continuing medical education is an inevitable requirement to ensure clinical ability. Under the background of normalization of epidemic prevention and control and the new situation of medical development, the management of continuing medical education in hospitals must follow the current situation and keep pace with the times. Therefore, the Internet support system to continuing education has emerged. This study used PDSA method to explore the construction of the regional center of continuing medical education through Internet under the background of normalization of epidemic prevention and control, aiming to promote the integration of medical education resources under the new situation, expand the learning channels of medical staff, and improve the level of medical education and teaching. © 2022 IEEE.

High-Performance Flexible Humidity Sensor Based on MoOX Nanoparticle Films for Monitoring Human Respiration and Non-Contact Sensing

Flexible humidity sensors with high sensitivity, fast response time, and outstanding reliability have the potential to revolutionize electronic skin, healthcare, and non-contact sensing. In this study, we employed a straightforward nanocluster deposition technique to fabricate a resistive humidity sensor on a flexible substrate, using molybdenum oxide nanoparticles (MoOx NPs). We systematically evaluated the humidity-sensing behaviors of the MoOx NP film-based sensor and found that it exhibited exceptional sensing capabilities. Specifically, the sensor demonstrated high sensitivity (18.2 near zero humidity), a fast response/recovery time (1.7/2.2 s), and a wide relative humidity (RH) detection range (0-95%). The MoOx NP film, with its closely spaced granular nanostructure and high NP packing density, exhibited insensitivity to mechanical deformation, small hysteresis, good repeatability, and excellent stability. We also observed that the device exhibited distinct sensing kinetics in the range of high and low RH. Specifically, for RH > 43%, the response time showed a linear prolongation with increased RH. This behavior was attributed to two factors: the higher physical adsorption energy of H2O molecules and a multilayer physical adsorption process. In terms of applications, our sensor can be easily attached to a mask and has the potential to monitor human respiration owing to its high sensing performance. Additionally, the sensor was capable of dynamically tracking RH changes surrounding human skin, enabling a non-contact sensing capability. More significantly, we tested an integrated sensor array for its ability to detect moisture distribution in the external environment, demonstrating the potential of our sensor for contactless human-machine interaction. We believe that this innovation is particularly valuable during the COVID-19 epidemic, where cross-infection may be averted by the extensive use of contactless sensing. Overall, our findings demonstrate the tremendous potential of MoOx NP-based humidity sensors for a variety of applications, including healthcare, electronic skin, and non-contact sensing.

Bank funding costs during the COVID-19 pandemic: Evidence from China

This paper investigates whether and how the COVID-19 pandemic affects bank funding costs in China. We find a significantly positive relationship between the offering yield spreads of negotiable certificates of deposit and banks' pandemic exposure. The surge in bank funding costs is alleviated by banks' asset quality, financial flexibility, operational resilience, and government support, indicating that pandemic-induced risks are priced in the interbank market. The alternative explanations of monetary policy interventions, investors' flight-to-liquidity effect, bank liquidity hoarding, and banks' mispricing are further excluded. We contribute to the literature on the pandemic effects on financial markets, and bank funding during crises. © 2023 Elsevier B.V.

A reflection on the Great Resignation in the hospitality and tourism industry

Purpose: This paper aims to provide a critical reflection on the Great Resignation in the hospitality and tourism industry in the wake of the COVID-19 pandemic. Specifically, this paper reviews the causes and effects of the Great Resignation, addresses the labor shortage in this industry and proposes strategies that can help manage the challenges. Design/methodology/approach: This paper is based on a critical analysis of emerging phenomena, related literature and researchers' experiences and insights. Findings: The Great Resignation has presented unprecedented challenges for the hospitality and tourism industry. A closer examination reveals that the pandemic has served as a catalyst rather than a leading cause of this trend. Workforce issues are becoming increasingly complex under contemporary influences, including internal elements such as new explications at work and external factors like the gig economy and technology implementation. Practical implications: This study provides practical implications on how Hospitality and Tourism practitioners can respond to the Great Resignation on micro, meso and macro levels. The practical implications revolve around employees' changing needs and preferences in the wave of Great Resignation, as well as the necessity for employers' reflection and improvement. Originality/value: This study marks an initial attempt to provide a critical assessment of a contemporary issue involving the Great Resignation. This paper extends its discussion through an advanced analysis of the issue, offers suggestions to manage current obstacles related to labor issues in hospitality and tourism, and illuminates future research directions. © 2022, Emerald Publishing Limited.

Effective multipurpose sewage sludge and food waste reduction strategies: A focus on recent advances and future perspectives

Energy crisis and increasing rigorous management standards pose significant challenges for solid waste management worldwide. Several emerging diseases such as COVID-19 aggravated the already complex solid waste management crisis, especially sewage sludge and food waste streams, because of the increasingly large production year by year. As mature waste disposal technologies, landfills, incineration, composting, and some other methods are widespread for solid wastes management. This paper reviews recent advances in key sewage sludge disposal technologies. These include incineration, anaerobic digestion, and valuable products oriented-conversion. Food waste disposal technologies comprised of thermal treatment, fermentation, value-added product conversion, and composting have also been described. The hot topic and dominant research foci of each area are summarized, simultaneously compared with conventional technologies in terms of organic matter degradation or conversion performance, energy generation, and renewable resources production. Future perspectives of each technology that include issues not well understood and predicted challenges are discussed with a positive effect on the full-scale implementation of the discussed disposal methods. © 2022 Elsevier Ltd

Study on Measuring Method of Vehicle Carbon Emission in Expressway Network

Under the background of dual-carbon policy, it is imperative to maintain ecological balance and reduce carbon emissions. Nowadays, it is very important to accurately measure the carbon emission index of vehicles on a wide range of road networks. Therefore, this study proposed a measuring method of vehicle carbon emission in expressway network based on multi-source data fusion. Firstly, a basic data cleaning method for carbon emission statistics was proposed to clean the basic data required for subsequent carbon emission calculation. Secondly, the highway carbon emission calculation model was established, and then the related calculation process was designed. Finally, taking the whole highway network of Guangdong province as an example, this paper calculated the vehicle carbon emission from September 2020 to June 2021, and compared the calculation results with China's carbon accounting database. Through this method, the proposed method was proved to be scientific and reliable. The research shows that the average carbon emission of mini buses in Guangdong province is small, but the total carbon emission accounts for the largest proportion of all types of vehicles, up to 52.1%;the total carbon emission of gasoline vehicles accounts for 49.8%, which is higher than that of diesel vehicles (45.4%) and of other energy vehicles (4.8%). Vigorously promoting new energy vehicles can effectively reduce the carbon emission of expressways. In addition, the study finds that there are significant differences in the travel patterns of different vehicles under COVID-19, but the overall impact on the transportation economy is limited. © 2022, Editorial Department, Journal of South China University of Technology. All right reserved.

A reflection on the Great Resignation in the hospitality and tourism industry

Purpose: This paper aims to provide a critical reflection on the Great Resignation in the hospitality and tourism industry in the wake of the COVID-19 pandemic. Specifically, this paper reviews the causes and effects of the Great Resignation, addresses the labor shortage in this industry and proposes strategies that can help manage the challenges. Design/methodology/approach: This paper is based on a critical analysis of emerging phenomena, related literature and researchers’ experiences and insights. Findings: The Great Resignation has presented unprecedented challenges for the hospitality and tourism industry. A closer examination reveals that the pandemic has served as a catalyst rather than a leading cause of this trend. Workforce issues are becoming increasingly complex under contemporary influences, including internal elements such as new explications at work and external factors like the gig economy and technology implementation. Practical implications: This study provides practical implications on how Hospitality and Tourism practitioners can respond to the Great Resignation on micro, meso and macro levels. The practical implications revolve around employees’ changing needs and preferences in the wave of Great Resignation, as well as the necessity for employers’ reflection and improvement. Originality/value: This study marks an initial attempt to provide a critical assessment of a contemporary issue involving the Great Resignation. This paper extends its discussion through an advanced analysis of the issue, offers suggestions to manage current obstacles related to labor issues in hospitality and tourism, and illuminates future research directions. © 2022, Emerald Publishing Limited.

Using the extended parallel process model (EPPM) to explore US consumers' dining behaviors during COVID-19

Purpose The purpose of this study was to examine consumers' dining behaviors and explore their decision-making process when dining out during the COVID-19 pandemic. Design/methodology/approach Based on the extended parallel process model (EPPM) and the related literature, a conceptual model was developed and tested. This study conducted an online survey with 351 responses. In addition, a series of statistical analyses, including descriptive analyses and path analyses, were conducted to analyze the associations among key constructs in the proposed model. Findings The findings of this study confirmed the pragmatic utility of applying EPPM in a hospitality management context. The findings of this study also outline the different nature between the participants' enactment of self-protective measures and dining out activities. Lastly, while consumers are hesitant about dining out, the results showed that consumers' dining behaviors are directly related to their personality trait of sensation-seeking. Research limitations/implications This study was delimited to a cross-sectional design and self-reported data. Such information may provide insights into individuals' decision-making and behaviors related to dining in a COVID-19 context. In addition, this study only includes US samples, while future studies can extend this study by including samples from different countries and cultural backgrounds. Originality/value This study adopts an interdisciplinary approach, which derives from tourism and hospitality management and public health. As a result, the findings of this study not only identify the major influencers affecting consumers' dining behavior but also help contextualize a public health model and contribute to the tourism and hospitality management literature.

A comprehensive examination of consumers' intentions to use food delivery apps

Purpose: Guided by the theory of planned behavior and the technology acceptance model, the purpose of this study was to comprehensively examine the factors that affect consumers' intentions to continue to use food delivery apps by developing and testing a research model and examining the differences between consumers with different demographic characteristics or behavior changes during the coronavirus disease 2019 (COVID-19) pandemic. Design/methodology/approach: An online survey instrument was developed, and 316 valid responses were collected. A measurement model was developed and tested by using the structural equation modeling partial least squares (SEM-PLS) method. Findings: The four basic constructs in the theory of planned behavior model (attitude, subjective norms, perceived behavioral control and trust) positively predicted consumers' intentions to continue to use food delivery apps. Predictors (including perceived innovativeness, hedonic and utilitarian motivations, perceived usefulness, perceived ease of use, and food safety risk perception) of these four basic constructs were also identified and confirmed. Multigroup analyses were conducted, and differences were found between male and female consumers and those with different ordering frequencies during the COVID-19 pandemic. Originality/value: This study expanded the application of the theory of planned behavior by examining consumers' intentions to continue using food delivery apps and improved the authors’ understanding of this theory. Further, the successful application of the technology acceptance model improved the authors’ understanding of consumers' attitudes and behavioral intentions related to food delivery app usage. © 2021, Emerald Publishing Limited.

Global impact of the COVID-19 pandemic on stroke care and intravenous thrombolysis

Objective: The objectives of this study were to measure the global impact of the pandemic on the volumes for intravenous thrombolysis (IVT), IVT transfers, and stroke hospitalizations over 4 months at the height of the pandemic (March 1 to June 30, 2020) compared with two control 4-month periods. Background: The COVID-19 pandemic led to widespread repercussions on the delivery of health care worldwide. Design/Methods: We conducted a cross-sectional, observational, retrospective study across 6 continents, 70 countries, and 457 stroke centers. Diagnoses were identified by ICD-10 codes and/or classifications in stroke center databases. Results: There were 91,373 stroke admissions in the 4 months immediately before compared to 80,894 admissions during the pandemic months, representing an 11.5% (95%CI,-11.7 to-11.3, p<0.0001) decline. There were 13,334 IVT therapies in the 4 months preceding compared to 11,570 procedures during the pandemic, representing a 13.2% (95%CI,-13.8 to-12.7, p<0.0001) drop. Interfacility IVT transfers decreased from 1,337 to 1,178, or an 11.9% decrease (95%CI,-13.7 to-10.3, p=0.001). There were greater declines in primary compared to comprehensive stroke centers (CSC) for stroke hospitalizations (-17.3% vs-10.3%, p<0.0001) and IVT (-15.5% vs-12.6%, p=0.0001). Recovery of stroke hospitalization volume (9.5%, 95%CI 9.2-9.8, p<0.0001) was noted over the two later (May, June) versus the two earlier (March, April) months of the pandemic, with greater recovery in hospitals with lower COVID-19 hospitalization volume, high volume stroke center, and CSC. There was a 1.48% stroke rate across 119,967 COVID-19 hospitalizations. SARS-CoV-2 infection was noted in 3.3% (1,722/52,026) of all stroke admissions. Conclusions: The COVID-19 pandemic was associated with a global decline in the volume of stroke hospitalizations, IVT, and interfacility IVT transfers. Primary stroke centers and centers with higher COVID19 inpatient volumes experienced steeper declines. Recovery of stroke hospitalization was noted in the later pandemic months, with greater recovery in hospitals with lower COVID-19 hospitalizations, high volume stroke centers, and CSCs.

Flexible Work Arrangements and Willingness to Stay: Mediating and Moderating Roles

During the COVID-19 period, the retention rate of new generation of employees has increased, but this is not necessarily a good thing. The purpose of this study is to analyze the impact of flexible work arrangements on new generation of employees' willingness to stay. We used randomly distributed questionnaires to collect data, and used these data to verify the connection among flexible work arrangements, well-being, emotional intelligence, willingness to stay. SPSS 26.0 was used to explore the relationships among the proposed variables based on the hypothesized model. Analysis of 445 responses obtained from the survey reveals that under the mediating role of well-being and and the moderating role of emotional intelligence, flexible work arrangements have a positive influence on willingness to stay. © 2021 IEEE.

Savable but Lost Lives when ICU Is Overloaded: a Model from 733 Patients in Epicenter Wuhan, China

Coronavirus Disease 2019 (COVID-19) causes a sudden turnover to bad at some checkpoints and thus needs the intervention of intensive care unit (ICU). This resulted in urgent and large needs of ICUs posed great risks to the medical system. Estimating the mortality of critical in-patients who were not admitted into the ICU will be valuable to optimize the management and assignment of ICU. Retrospective, 733 in-patients diagnosed with COVID-19 at a local hospital (Wuhan, China), as of March 18, 2020. Demographic, clinical and laboratory results were collected and analyzed using machine learning to build a predictive model. Considering the shortage of ICU beds at the beginning of disease emergence, we defined the mortality for those patients who were predicted to be in needing ICU care yet they did not as Missing-ICU (MI)-mortality. To estimate MI-mortality, a prognostic classification model was built to identify the in-patients who may need ICU care. Its predictive accuracy was 0.8288, with an AUC of 0.9119. On our cohort of 733 patients, 25 in-patients who have been predicted by our model that they should need ICU, yet they did not enter ICU due to lack of shorting ICU wards. Our analysis had shown that the MI-mortality is 41%, yet the mortality of ICU is 32%, implying that enough bed of ICU in treating patients in critical conditions.

Machine Learning to Predict ICU Admission, ICU Mortality and Survivors' Length of Stay among COVID-19 Patients: Toward Optimal Allocation of ICU Resources

COVID-19 causes burdens to the ICU. Evidence-based planning and optimal allocation of the scarce ICU resources is urgently needed but remains unaddressed. This study aims to identify variables and test the accuracy to predict the need for ICU admission, death despite ICU care, and among survivors, length of ICU stay, before patients were admitted to ICU. Retrospective data from 733 in-patients confirmed with COVD-19 in Wuhan, China, as of March 18, 2020. Demographic, clinical and laboratory were collected and analyzed using machine learning to build the predictive models. The built machine learning model can accurately assess ICU admission, length of ICU stay, and mortality in COVID-19 patients toward optimal allocation of ICU resources. The prediction can be done by using the clinical data collected within 1-15 days before the actual ICU admission. Lymphocyte absolute value involved in all prediction tasks with a higher AUC.

[Effectiveness of the "14 plus 7 day quarantine" and "nucleic acid plus total antibody testing" strategy for screening imported patients with COVID-19 in Xiamen].

Objective: To analysis effectiveness of the "14 plus 7 day quarantine" and "nucleic acid plus total antibody testing" strategy (combined screening strategy) for screenin the imported patients with COVID-19 in Xiamen. Methods: The study populations were overseas travelers arriving in Xiamen from March 17 to December 31, 2020, and overseas travelers who had quarantine outside Xiamen for less than 21 days from July 18 to December 31, 2020. Data were collected and analyzed on the timing of detection, pathways, and test results of the imported patients with COVID-19 after implementing combined screening strategy. Results: A total of 304 imported patients with COVID-19 were found from 174 628 overseas travelers and 943 overseas travelers from other cities. A total of 163 cases (53.6%) were diagnosed by multitime, multisite intensive nucleic acid testing after positive finding in total antibody testing. Among them, 27 (8.9%) were first positive for nucleic acid in 14 plus 7 day quarantine and 136 were first positive for nucleic acid in 14-day quarantine. Only 8 of these individuals were tested positive for nucleic acid after positive total antibody testing. The other 128 individuals were tested positive for nucleic acid after being negative for average 2.3 times (maximum of 6 times). Aditional 155 cases might be detected by using the combined "14 plus 7 day quarantine" and " nucleic acid plus total antibody testing" strategy compared with "14-day quarantine and nucleic acid testing" strategy, accounting for 51.0% of the total inbound infections. So the combined screening strategy doubled the detection rate for imported patients with COVID-19. No second-generation case caused by overseas travelers had been reported in Xiamen as of February 26, 2021. Conclusions: Xiamen's combined screening strategy can effectively screen the imported patients with COVID-19 who were first positive for nucleic acid after 14 day quarantine. Compared with "14 day quarantine and nucleic acid testing", the combined screening strategy improved detection rate and further reduced the risk of the secondary transmission caused by the imported patients with COVID-19.

COVID-19, IP and access: Will the current system of medical innovation and access to medicines meet global expectations?

The COVID-19 pandemic has exposed the fundamental flaws in the current system of medical innovation and access to medicines, which require urgent attention from the global community. This is prompted by the experience of the past decades, which has proven that this system was ineffective in securing adequate access to medicines for all. The understanding of the deficiencies of the existing system is crucial today, as it may help to design effective approaches for improving access. This article will also consider mechanisms that may be implemented by governments for the protection of public health. These include short-term mechanisms, such as compulsory licensing and government use, as well as the long-term design of a new innovation model, including state-coordinated research of medicines and open innovation. The current system should be reconsidered to ensure the prompt development of COVID-19 therapy accessible to everyone and full preparedness for the pandemics of the future.