Search

Understanding the dynamic link between the development of COVID-19 pandemic and industry sector risk spillovers is crucial to explore the underlying mechanisms by which major public health events affect economic systems. This paper applies ElasticNet method proposed by Diebold and Yilmaz (2009, 2012, 2014) to estimate the dynamic risk spillover indicators of 20 industrial sectors in China from 2016 to 2022, and systematically examines the impact of industry risk network fluctuations and the transmission path caused by COVID-19 shock. The findings reveal that risk spillovers of Chinese industries show a dynamic change of "decline-fluctuation-rebound" with the three phases of COVID-19 epidemic. At the beginning of the epidemic, machinery and equipment, paper and printing, tourism and hotels, media and information services, and agriculture were the exporters of epidemic risk, while materials, transportation equipment, commercial trade, health care, and environmental protection were the importers of epidemic risk; However, as the epidemic developed further, the direction and effect of risk transmission in the industry was reversed. Examining the network characteristics of the pair sectors, we found that under the epidemic shock, the positive risk spillover from tourism and hotels, culture, education and sports to consumer goods, finance, and energy industries was significantly increased, and finance and real estate industries were affected by the risk impact of more industries, while the number of industries affected by information technology and computer industry was significantly reduced. This paper shows that there is inter-industry risk transmission of the COVID-19 epidemic shock, and the risk transmission feeds back in a cycle between industries as the epidemic develops, driving the economy into a vicious circle. The role of the service sector in blocking the spread of negative shocks from the epidemic should be emphasized and brought into play to avoid increasing the overall economic vulnerability. This study will help to deepen the understanding of scholars and policy makers on the network transmission effects of the epidemic. [ABSTRACT FROM AUTHOR]

As an emerging business modality and Internet format, live streaming e-commerce has developed rapidly since its emergence in 2016, especially since the outbreak of the COVID-19 epidemic in late 2019, when an increasing number of businesses from other industries attracted participation. However, with the development of the live streaming e-commerce industry, the industry's market environment is becoming increasingly chaotic. Therefore, during this period, government departments continuously formulate and implement relevant industry policies. In order to exploring the cooperation network structure, policy content distribution, and implementation effectiveness characteristics among publishers, this paper constructs a three-dimensional analysis framework of policy from the perspective of policy tools, policy effectiveness evaluation and policy publishers. The results show that in terms of policy tools, the overall structure of policy tools in the live streaming e-commerce industry is unreasonable, and different types of policy tools are significantly diverse. The proportion of environmental policy tools is greater than that of demand-based and supply-based policy tools, accounting for 62.97%, and among them, the tools related to industry regulation and management account for the largest proportion of the total, which greatly suppresses the enthusiasm of various entities in the industry for development. In terms of policy effectiveness evaluation, most of the policies do not formulate detailed long-, medium-, or short-term goals, nor are the policy priorities, incentive measures, or action modes perfect, indicating that the government's pushing and pulling forces for the live streaming e-commerce industry are insufficient. Finally, in the subject dimension of policy release, the synergy of relevant subjects is constantly improving, but there is also a phenomenon of over-concentration in the synergistic departments. [ABSTRACT FROM AUTHOR]

The spread of the COVID-19 had profoundly affected the development of the air transportation. In order to determine the changes in air transportation volume associated with the development of the epidemic, this paper takes Southwest China as the study area. Monthly data and methods, such as the coefficient of variation, rank-size analysis and spatial matching index, were applied. The results found that: (1) during 2020–2022, there was a positive relationship between passenger volume and epidemic development, while freight volume increased for most airports in the first quarter of 2020–2022, particularly in the eastern region; (2) From the perspective of changes in air transportation volume under the development of the COVID-19, among various types of airports, the changes in transportation volume of main trunk airports were more significant than those of regional feeder airports in remote areas; (3) however, under the influence of the epidemic, main trunk airports still exhibited stronger attraction in passenger volume. That is to say, the passengers who chose to travel by air still tended to choose the main trunk airports and formed the agglomeration distribution pattern which around high-level airports in the provincial capital. Whereas the freight volume had a tendency of equalization among airports in Southwest China; (4) Over the course of time, the consistency of the spatial distribution of the number of cases and the passenger or freight volume in southwest China gradually increased. Among them, the spatial matching rate of the passenger volume and the number of COVID-19 cases was always higher than that of the cases and freight volume, which might indicate that there was a stronger correlation relationship. Therefore, it is proposed that the construction of multi-center airport system should be strengthened, the resilience of the route network for passenger transportation should be moderately enhanced, and the risk-resistant capacity of mainline airports and airports in tourist cities should be upgraded, so as to provide references for the orderly recovery of civil aviation and regional development. [ABSTRACT FROM AUTHOR]

In the process of hikers' choosing a destination, searching for information is one of the important elements, playing a decisive role in decision-making. Based on the Baidu Index for "hiking," this paper analyzes the spatial and temporal characteristics of and factors that influenced network attention to hiking in China from 2016 to 2021. The study found that (1) Network attention to hiking in China was generally relatively stable across the period studied, with highly uneven distribution between different months. The search volume was higher on weekends, and mobile searches increased year by year, far exceeding computer searches. (2) Different regions in China experienced different levels of network attention, with the highest levels in the east, followed by the center, and the lowest in the west. Except for East China, network attention to hiking was highly unevenly distributed within each region. (3) The COVID-19 pandemic increased the geographical concentration index and coefficient of variation but reduced the primacy index. A region's level of economic development, degree of network development, population size, and population age structure are proposed as factors that affect network attention to hiking. [ABSTRACT FROM AUTHOR]

Human-to-human contact plays a leading role in the transmission of infectious diseases, and the contact pattern between individuals has an important influence on the intensity and trend of disease transmission. In this paper, we define regular contacts and random contacts. Then, taking the COVID-19 outbreak in Yangzhou City, China as an example, we consider age heterogeneity, household structure and two contact patterns to establish discrete dynamic models with switching between daytime and nighttime to depict the transmission mechanism of COVID-19 in population. We studied the changes in the reproduction number with different age groups and household sizes at different stages. The effects of the proportion of two contacts patterns on reproduction number were also studied. Furthermore, taking the final size, the peak value of infected individuals in community and the peak value of quarantine infected individuals and nucleic acid test positive individuals as indicators, we evaluate the impact of the number of random contacts, the duration of the free transmission stage and summer vacation on the spread of the disease. The results show that a series of prevention and control measures taken by the Chinese government in response to the epidemic situation are reasonable and effective, and the young and middle-aged adults (aged 18-59) with household size of 6 have the strongest transmission ability. In addition, the results also indicate that increasing the proportion of random contact is beneficial to the control of the infectious disease in the phase with interventions. This work enriches the content of infectious disease modeling and provides theoretical guidance for the prevention and control of follow-up major infectious diseases. [ABSTRACT FROM AUTHOR]

The appearance of a novel coronavirus in late 2019 radically changed the community of researchers working on coronaviruses since the 2002 SARS epidemic. In 2020, coronavirus-related publications grew by 20 times over the previous two years, with 130,000 more researchers publishing on related topics. The United States, the United Kingdom and China led dozens of nations working on coronavirus prior to the pandemic, but leadership consolidated among these three nations in 2020, which collectively accounted for 50% of all papers, garnering well more than 60% of citations. China took an early lead on COVID-19 research, but dropped rapidly in production and international participation through the year. Europe showed an opposite pattern, beginning slowly in publications but growing in contributions during the year. The share of internationally collaborative publications dropped from pre-pandemic rates; single-authored publications grew. For all nations, including China, the number of publications about COVID track closely with the outbreak of COVID-19 cases. Lower-income nations participate very little in COVID-19 research in 2020. Topic maps of internationally collaborative work show the rise of patient care and public health clusters—two topics that were largely absent from coronavirus research in the two years prior to 2020. Findings are consistent with global science as a self-organizing system operating on a reputation-based dynamic. [ABSTRACT FROM AUTHOR]

Since December 2019, the COVID-19 pandemic has quickly spread across the world. The traditional understanding of the relationship between wealth and the spread of contagious diseases is that similar to many precedent epidemics, the pandemic spread easily in poor neighborhoods in many countries. The environmental and socioeconomic implications of the COVID-19 pandemic are still poorly understood, thus this paper examines the relationship between neighborhood characteristics and the spread of the pandemic through a case study of Shenzhen, a Chinese megacity with many low-income rural migrants. The major finding is that wealthier and larger neighborhoods in Shenzhen were more likely to be infected in the first wave of the pandemic in 2020. This spread pattern is likely to result from China's strict control to prevent the pandemic, human mobility, and demographic characteristics such as income. This finding reveals a new phenomenon that contrasts with the traditional understanding of the influence of wealth on the spread of epidemics. This paper enriches the understanding of the role of neighborhoods in the spread of the pandemic, and it has important public policy implications. [ABSTRACT FROM AUTHOR]

The COVID-19 epidemic had an appropriate impact on tourists' trip psychology and their subsequent behavior in participating in rural tourism activities. The purpose of this paper is to explore the types of motivations Chinese tourists have for participating in rural tourism in the context of COVID-19, and to comparatively analyze the similarities and differences in motivations for rural tourism during the epidemic and in normal times. An interpretive paradigm qualitative data collection method was used: semi-structured interviews and focus group discussions. Respondents were 21 tourists, who were selected through purposive and snowball sampling. Through content analysis, we found that rural tourism motivations during the epidemic included both diversified and singular motivations. The pull effect of rural destinations is related to distance and ease of realization. For rural areas in close proximity, a single motivation is sufficient to drive tourists. In addition, we found that there was no "altruistic motivation" for rural tourism during the COVID-19 period, but "altruistic feelings" for the preservation of ancient villages were generated during rural tourism. Finally, we discuss the theoretical and practical significance of this study and make suggestions for future research. The study explains tourists' companionship preferences, activity choices, and affective changes, and provides a basis for the operation and advertising strategies of rural destinations to attract tourists and promote their sustainable development. [ABSTRACT FROM AUTHOR]

This paper examines the linkage between Chinese stock market volatility and investor attention fluctuation. In Heterogeneous autoregressive (HAR) model, first, we analyzed the linkage between both decomposed and undecomposed stock market realized volatility and investor attention fluctuations across full-sample and two-year moving window sub-samples. Second, we compare the predictive power of four models in short-, medium-, and long-term volatility forecasting. Empirical results show large positive attention fluctuation amplified Chinese stock market volatility after the outbreak of COVID-19, and negative small attention fluctuation significantly stabilized stock market volatility before COVID-19, and the impact dwindled in after COVID-19. The model incorporating decomposed realized volatility and decomposed attention fluctuation performs better in volatility Forecasting. This research underscores a shift in the dynamics between stock market volatility and investor attention fluctuations, and investor attention fluctuation improves the volatility forecasting accuracy of the Chinese stock market. [ABSTRACT FROM AUTHOR]

As the COVID-19 pandemic fades, the aviation industry is entering a fast recovery period. To analyze airport networks' post-pandemic resilience during the recovery process, this paper proposes a Comprehensive Resilience Assessment (CRA) model approach using the airport networks of China, Europe, and the U.S.A as case studies. The impact of COVID-19 on the networks is analyzed after populating the models of these networks with real air traffic data. The results suggest that the pandemic has caused damage to all three networks, although the damages to the network structures of Europe and the U.S.A are more severe than the damage in China. The analysis suggests that China, as the airport network with less network performance change, has a more stable level of resilience. The analysis also shows that the different levels of stringency policy in prevention and control measures during the epidemic directly affected the recovery rate of the network. This paper provides new insights into the impact of the pandemic on airport network resilience. [ABSTRACT FROM AUTHOR]

This paper uses event study based on the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model to study the impact of the COVID-19 outbreak on China's financial market. It finds that the pandemic had an overall significant and negative impact on the stock prices of firms listed on SSE, SZSE and ChiNext. However, such impact appeared to be heterogeneous across industries, affecting listed firms in industries such as pharmaceutical and telecommunications positively, but those in services industries such as accommodation, catering, and commercial services negatively. Apparently, a crisis for some had been an opportunity for others. In addition, this paper seeks to understand the micro mechanism behind the heterogeneity of pandemic shock from the perspective of firms' financial position. It finds that listed firms with higher debt level were hit harder, whereas those with more net cash flow had displayed higher resilience against the blow of the pandemic. However, the opposite pattern is found among those listed on ChiNext and in industries severely devastated by the pandemic. These findings have policy implications in terms of preventing systemic financial risks and facilitating recovery during pandemic-induced economic downturns. It also helps investor adjust investment strategies, hedge against risks, and secure gains when the market conditions in general are unfavorable. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB), as a respiratory infectious disease, has damaged public health globally for decades, and mainland China has always been an area with high incidence of TB. Since the outbreak of COVID-19, it has seriously occupied medical resources and affected medical treatment of TB patients. Therefore, the authenticity and reliability of TB data during this period have also been questioned by many researchers. In response to this situation, this paper excludes the data from 2019 to the present, and collects the data of TB incidence in mainland China and the data of 11 influencing factors from 2014 to 2018. Using spatial autocorrelation methods and multiscale geographically weighted regression (MGWR) model to study the temporal and spatial distribution of TB incidence in mainland China and the influence of selected influencing factors on TB incidence. The experimental results show that the distribution of TB patients in mainland China shows spatial aggregation and spatial heterogeneity during this period. And the R2 and the adjusted R2 of MGWR model are 0.932 and 0.910, which are significantly better than OLS model (0.466, 0.429) and GWR model (0.836, 0.797). The fitting accuracy indicators MAE, MSE and MAPE of MGWR model reached 5.802075, 110.865107 and 0.088215 respectively, which also show that the overall fitting effect is significantly better than OLS model (19.987574, 869.181549, 0.314281) and GWR model (10.508819, 267.176741, 0.169292). Therefore, this model is based on real and reliable TB data, which provides decision-making references for the prevention and control of TB in mainland China and other countries. [ABSTRACT FROM AUTHOR]

The impacts of COVID-19 on travel demand, traffic congestion, and traffic safety are attracting heated attention. However, the influence of the pandemic on electric bike (e-bike) safety has not been investigated. This paper fills the research gap by analyzing how COVID-19 affects China's e-bike safety based on a province-level dataset containing e-bike safety metrics, socioeconomic information, and COVID-19 cases from 2017 to 2020. Multi-output regression models are adopted to investigate the overall impact of COVID-19 on e-bike safety in China. Clustering-based regression models are used to examine the heterogeneous effects of COVID-19 and the other explanatory variables in different provinces/municipalities. This paper confirms the high relevance between COVID-19 and the e-bike safety condition in China. The number of COVID-19 cases has a significant negative effect on the number of e-bike fatalities/injuries at the country level. Moreover, two clusters of provinces/municipalities are identified: one (cluster 1) with lower and the other (cluster 2 that includes Hubei province) higher number of e-bike fatalities/injuries. In the clustering-based regressions, the absolute coefficients of the COVID-19 feature for cluster 2 are much larger than those for cluster 1, indicating that the pandemic could significantly reduce e-bike safety issues in provinces with more e-bike fatalities/injuries. [ABSTRACT FROM AUTHOR]

In the background of the post-epidemic era, the consumption demand and market scale of cold chain logistics in China are expanding, but there is still an obvious gap with developed countries. To complete the balance between the supply and demand for aquatic products and the rational allocation of logistics resources and promote the rapid development trend of aquatic product cold chain logistics, it is particularly important to forecast and analyze the demand for aquatic product cold chain logistics. This article selects six main factors that affect the demand for aquatic products in cold chain logistics, uses the traditional grey model and the grey-BP neural network model to simulate and predict the demand for aquatic products in cold chain logistics in China from 2012 to 2021, and compares and analyzes the simulation results. Generally speaking, the demand for aquatic products from Chinese residents is on the rise. In the simulation prediction process, the prediction error of the grey-BP neural network is reduced compared to the traditional grey model, and the processing ability of the nonlinear system is ideal. The results show that the grey-BP neural network model is an effective method to predict the demand for cold chain logistics of aquatic products. Finally, suggestions are made on the future development of aquatic cold chain logistics in the post-epidemic era from the economic, social, and environmental aspects, which provide valuable decision-making reference for the development of marine aquaculture enterprises and cold chain logistics industry. [ABSTRACT FROM AUTHOR]

Background: The situation of the COVID-19 outbreak in the border areas of China and Vietnam is complex, and its progress may affect the willingness of urban and rural residents to receive the vaccine. Objective: This study aims to understand the influence of the COVID-19 epidemic situation on the willingness of urban and rural residents in China-Vietnam border areas to get vaccinated and the factors that affect the vaccinations. Methods: A cross-sectional survey was conducted in Hani-Yi Autonomous Prefecture of Honghe, a border area between China and Vietnam, using online and paper questionnaires from April 1 to June 4, 2021. A total of 8849 valid questionnaires were surveyed to compare the differences in the willingness of urban and rural residents to receive the COVID-19 vaccine. Single factor analysis and multivariate logistic regression analysis were used to explore the influence of the epidemic situation on the willingness to be vaccinated. Results: In the border areas between China and Vietnam in Yunnan Province, both urban and rural residents had a high willingness (> 90%) to receive the COVID-19 vaccination, with a higher level of willingness in urban than in rural areas and a higher willingness among residents aged ≥ 56 years. Rural residents mainly concerned about the vaccination were different from urban residents (p< 0.05). About 54.8% of urban respondents and 59.2% of rural respondents indicated that their willingness to get COVID-19 vaccine would be affected by new COVID-19 cases. Respondents who were divorced, had an occupation other than farming, had contraindications to vaccination, were concerned about the safety of vaccines and worried about virus mutation, thought that the epidemic situation would not affect their willingness to get vaccinated (p< 0.05). Conclusion: The prevention and control of epidemics in border areas is of considerable importance. It is necessary to conduct targeted health education and vaccine knowledge popularization among urban and rural residents to increase the vaccination rate and consolidate the epidemic prevention and control at the border. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 at the beginning of 2020 had a significant impact on China's economy, society, and citizens; it also had a negative impact on the development of the construction industry. In particular, small and medium-sized construction enterprises with low ability to withstand risk have been strongly impacted, aggravating a crisis of survival among these firms. The focus of this study is to analyze the impact of COVID-19 on the growth of small and medium-sized construction companies. Based on the characteristics of small and medium-sized construction enterprises, this paper establishes a growth evaluation index and builds a growth evaluation model based on factor analysis. Twenty-three construction enterprises listed on small and medium-sized enterprises board are selected as samples, and the quarterly data of 2019 and 2020 are used for empirical analysis. The results show that the epidemic has had a high short-term impact on construction enterprises, and the total output value of the construction industry in the first quarter of 2020 was 16% lower than that in the same period of last year. In the long run, the impact of the epidemic on the growth of small and medium-sized construction enterprises has been limited. In the first quarter of 2020, the growth score of enterprises decreased by only 1.95% year-over-year, and it was essentially flat in the second and third quarters. The epidemic has had little influence on solvency, tangible resources or intangible resources but a high short term influence on profitability, capital expansion and market expectations. The long-term impact is small; It is conducive to the improvement of enterprise operation ability. Finally, to both address the influence of the COVID-19 on small and medium-sized construction enterprises and to realize their transformation and upgrading, targeted suggestions are offered at the policy and enterprise levels. The results will help to understand the impact of the epidemic on the growth of construction enterprises, and provide decision support for the healthy and orderly development of the follow-up construction industry. [ABSTRACT FROM AUTHOR]

This paper analyzes the application of various telemedicine services in Gansu Province, China during the COVID-19 epidemic, and summarizes the experiences with these services. In addition, the satisfaction levels of patients and doctors with the application of telemedicine in COVID-19 were investigated, the deficiencies of telemedicine in Gansu were determined, and recommendations for modification were proposed. Coronavirus Disease 2019 (COVID-19) has broken out in China, and Gansu Province in Northwest of China has not been spared. To date, there are 91 local COVID-19 cases and 42 imported cases. 109 hospitals were selected as designated hospitals during the COVID-19 outbreak, and most of them were secondary hospitals. However, it was unsatisfactory that the ability of medical services is relatively low in most of secondary hospitals and primary hospitals. Therefore, we helped the secondary hospitals cope with COVID-19 by means of remote consultation, long-distance education, telemedicine question and answer (Q&A). Our practical experience shows that telemedicine can be widely used during the COVID-19 epidemic, especially in developing countries and areas with lagging medical standards. [ABSTRACT FROM AUTHOR]

This paper uses resilience as a lens through which to analyse disasters and other major threats to patterns of criminal behaviour. A set of indicators and mathematical models are introduced that aim to quantitatively describe changes in crime levels in comparison to what could otherwise be expected, and what might be expected by way of adaptation and subsequent resumption of those patterns. The validity of the proposed resilience assessment tool is demonstrated using commercial theft data from the COVID-19 pandemic period. A 64 per cent reduction in crime was found in the studied city (China) during an 83-day period, before daily crime levels bounced back to higher than expected values. The proposed resilience indicators are recommended as benchmarking instruments for evaluating and comparing the global impact of COVID-19 policies on crime and public safety. [ABSTRACT FROM AUTHOR]

This paper seeks to understand whether a catastrophic and urgent event, such as the first months of the COVID-19 pandemic, accelerates or reverses trends in international collaboration, especially in and between China and the United States. A review of research articles produced in the first months of the COVID-19 pandemic shows that COVID-19 research had smaller teams and involved fewer nations than pre-COVID-19 coronavirus research. The United States and China were, and continue to be in the pandemic era, at the center of the global network in coronavirus related research, while developing countries are relatively absent from early research activities in the COVID-19 period. Not only are China and the United States at the center of the global network of coronavirus research, but they strengthen their bilateral research relationship during COVID-19, producing more than 4.9% of all global articles together, in contrast to 3.6% before the pandemic. In addition, in the COVID-19 period, joined by the United Kingdom, China and the United States continued their roles as the largest contributors to, and home to the main funders of, coronavirus related research. These findings suggest that the global COVID-19 pandemic shifted the geographic loci of coronavirus research, as well as the structure of scientific teams, narrowing team membership and favoring elite structures. These findings raise further questions over the decisions that scientists face in the formation of teams to maximize a speed, skill trade-off. Policy implications are discussed. [ABSTRACT FROM AUTHOR]

The inefficiency observed in investment within state-owned enterprises presents a significant practical challenge that can affect the sustainable development of China's economy. To address this issue, this study comprehensively explores the intricate mechanisms underlying the governance implications of mixed ownership on the investment efficiency of listed companies. Drawing on unbalanced panel data encompassing Shanghai and Shenzhen Stock Exchange A-share listed companies in China spanning the period from 2008 to 2022, this study employs a fixed-effects model to unveil the nuanced ways in which mixed ownership influences investment efficiency through the lens of agency costs. This study transcends the boundaries of traditional agency conflicts between managers and shareholders. It delves deeper, illuminating the diverse effects of agency conflicts between significant controlling shareholders and minority shareholders. The results revealed a noteworthy positive correlation between mixed ownership and investment efficiency, and verified the intermediary role of agency costs between mixed ownership and investment efficiency, which is an important result of our research. Heterogeneity analysis indicates that the relationship between the two can be affected by external events, such as during the COVID-19 pandemic, investment efficiency is not the most concerned issue for enterprises. The findings have practical implications for practitioners and policymakers, as they offer avenues for optimizing investment strategies and fostering efficient and effective corporate governance practices. [ABSTRACT FROM AUTHOR]

The study aims to uncover the impact of COVID-19 and capital structure on the financial performance of 1787 renewable and nonrenewable energy firms in China from 2010 to 2022. Using the fixed effect approach, our study found that financial leverage negatively affected the return on assets and equity ratios for both renewable and nonrenewable energy. On the other hand, the study shows that COVID-19 adversely affected the financial performances of non-renewable energy firms. Conversely, COVID-19 positively affected the financial performances of renewable energy firms. The conclusions drawn by the present study are helpful for the policymakers in making corresponding financial decisions. The study suggests that policymakers must adopt profitable capital structure strategies for firms and shareholders in this context. Finally, policymakers must design more policies to overcome the adverse influence of the COVID-19 pandemic crisis and avoid any future unforeseeable pandemics. [ABSTRACT FROM AUTHOR]

Background: After its emergence in China, the coronavirus SARS-CoV-2 has swept the world, leading to global health crises with millions of deaths. COVID-19 clinical manifestations differ in severity, ranging from mild symptoms to severe disease. Although perturbation of metabolism has been reported as a part of the host response to COVID-19 infection, scarce data exist that describe stage-specific changes in host metabolites during the infection and how this could stratify patients based on severity. Methods: Given this knowledge gap, we performed targeted metabolomics profiling and then used machine learning models and biostatistics to characterize the alteration patterns of 50 metabolites and 17 blood parameters measured in a cohort of 295 human subjects. They were categorized into healthy controls, non-severe, severe and critical groups with their outcomes. Subject's demographic and clinical data were also used in the analyses to provide more robust predictive models. Results: The non-severe and severe COVID-19 patients experienced the strongest changes in metabolite repertoire, whereas less intense changes occur during the critical phase. Panels of 15, 14, 2 and 2 key metabolites were identified as predictors for non-severe, severe, critical and dead patients, respectively. Specifically, arginine and malonyl methylmalonyl succinylcarnitine were significant biomarkers for the onset of COVID-19 infection and tauroursodeoxycholic acid were potential biomarkers for disease progression. Measuring blood parameters enhanced the predictive power of metabolic signatures during critical illness. Conclusions: Metabolomic signatures are distinctive for each stage of COVID-19 infection. This has great translation potential as it opens new therapeutic and diagnostic prospective based on key metabolites. [ABSTRACT FROM AUTHOR]

This study aims to investigate the temporal and spatial attributes of the exit of Taiwanese enterprises from mainland China between 2001 and 2021, by applying enterprise database data. Furthermore, the influence of strategic coupling on Taiwanese enterprises' exit from mainland China was also investigated. The following are the key findings: The spatial distribution pattern of the exit rate of Taiwanese enterprises in mainland China varied at different phases. In contrast, the inland regions of the country's central and western zones, which are characterized by comparatively less developed economies, maintained consistently high exit rates, whereas the eastern coastal region retained a low exit rate. Particularly, the relationship between Taiwanese enterprises and the invested areas changed from Captive coupling to Cooperative coupling and subsequently to Absorptive Coupling. Similarly, the coupling modes significantly influenced the exit of Taiwanese enterprises from mainland China. Moreover, the COVID-19 pandemic has contributed to the backward connection of Taiwanese corporations, which have become more reliant on the mainland China market and local suppliers than earlier. Taiwan-favoring policies and the regional innovation environment have consequently emerged as the primary locational advantages for retaining Taiwanese enterprises in the aftermath of the global financial crisis. Therefore, the aforementioned factors may help to reduce the Taiwanese enterprises' exit from mainland China and possess valuable policy implications for Taiwan investment zones in mainland China. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has been present globally for more than three years, and cross-border transmission has played an important role in its spread. Currently, most predictions of COVID-19 spread are limited to a country (or a region), and models for cross-border transmission risk assessment remain lacking. Information on imported COVID-19 cases reported from March 2020 to June 2022 was collected from the National Health Commission of China, and COVID-19 epidemic data of the countries of origin of the imported cases were collected on data websites such as WHO and Our World in Data. It is proposed to establish a prediction model suitable for the prevention and control of overseas importation of COVID-19. Firstly, the SIR model was used to fit the epidemic infection status of the countries where the cases were exported, and most of the r2 values of the fitted curves obtained were above 0.75, which indicated that the SIR model could well fit different countries and the infection status of the region. After fitting the epidemic infection status data of overseas exporting countries, on this basis, a SIR-multiple linear regression overseas import risk prediction combination model was established, which can predict the risk of overseas case importation, and the established overseas import risk model overall P <0.05, the adjusted R2 = 0.7, indicating that the SIR-multivariate linear regression overseas import risk prediction combination model can obtain better prediction results. Our model effectively estimates the risk of imported cases of COVID-19 from abroad. [ABSTRACT FROM AUTHOR]

A learning management system (LMS) is a web-based application or software platform computed to facilitate the development, tracking, management, reporting, and delivery of education and training programs. Many valuable and dominant factors are working behind the Learning Management System (LMS), but no one can find which factor is most important and valuable for LMS during COVID-19 among the following five alternatives, called Improved Accessibility, Blended Learning, Collaboration and Communications, Assessment and Evaluation, and Administrative Efficiency. For this, first, we derive the techniques of bipolar complex hesitant fuzzy (BCHF) sets, and then we evaluate some flexible operational laws, called Algebraic operational laws and Aczel-Alsina operational laws. Secondly, using the above techniques, we elaborate the technique of BCHF Aczel-Alsina power averaging (BCHFAAPA), BCHF Aczel-Alsina power weighted averaging (BCHFAAPWA), BCHF Aczel-Alsina power geometric (BCHFAAPG), and BCHF Aczel-Alsina power weighted geometric (BCHFAAPWG) operators. Some basic properties are also investigated for each proposed operator. Further, to evaluate the problem concerning LMS, we compute the multi-attribute decision-making (MADM) techniques for invented operators. Finally, we select some prevailing operators and try to compare their ranking results with our proposed results to enhance the worth and capability of the invented theory. [ABSTRACT FROM AUTHOR]

The expansion of the Belt and Road Initiative (BRI) has raised a wide range of concerns about its environmental impact. Therefore, from the perspective of environmental impacts, this study used the two-way fixed effect staggered differences in differences (TWFE Staggered DID) method to examine the impact of the BRI on the Environment Goods (EGs) intra-industry trade (IIT) between China and other Belt and Road (B&R) countries, including a sample of 191 countries, covering the period from 2010 to 2019 for eliminating the impact of COVID-19 and the financial crisis in 2008 and 2009. Because only 135 countries signed a Memorandum of Understanding between 2010 and 2019, this study treated these B&R countries as the study group, and the other 73 countries (non-B&R countries) as the control group. This study described EGs using the 54 6-digit code Environment Goods in Harmonized Commodity Description and Coding System listed in the "APEC LIST OF ENVIRONMENT GOODS" published by the Asia-Pacific Economic Cooperation in 2012, and used the intra-industry trade index proposed by Grubel and Lloyd in 1971 to measuring dependent variable. The research results indicated that the BRI has significantly promoted bilateral EGs IIT. The mechanism test implied that, in addition to direct impacts, the BRI also has indirect impacts by boosting the energy restructuring of B&R countries. These results prove that the BRI has positive impacts on the environment. The heterogeneity test showed that there is a heterogeneous impact depending on the type of IIT, product categorization, B&R countries' income levels, and geographic environment. This study not only gives theoretical and empirical evidence of the positive environmental impacts of the BRI, but also provides practical guidance for the development of EGS IIT between China and B&R countries, thereby contributing to global carbon emissions reduction and environmental governance to some degree. [ABSTRACT FROM AUTHOR]

The pandemic caused by the SARS-CoV-2 virus is believed to originate in China from where it spread to other parts of the world. The first cluster of diseased individuals was reported in China as early as in December 2019. It has also been well established that the virus stroke Italy later in January or in February 2020, hence distinctly after the outbreak in China. The work by Apolone et al. published in the Italian Medical Journal in November 2020 and retracted upon expression of concern on 22 March 2021, however propose that the virus could have stroke people already in September 2019, possibly following even earlier outbreak in China. By fitting an early part of the epidemic curve with the exponential and extrapolating it backwards, we could estimate the day-zero of the epidemic and calculated its confidence intervals in Italy and China. We also calculated how probable it is that Italy encountered the virus prior 1 January 2020. We determined an early portion of the epidemic curve representing unhindered exponential growth which fit the exponential model with high determination >0.97 in both countries. We conservatively suggest that the day-zero in China and Italy was 8 December 2019 (95% CI: 3 Dec., 20 Dec.) and 22 January 2020 (95% CI: 16 Jan., 29 Jan.), respectively. Given the uncertainty of the very early data in China and adjusting hence our model to fit the exponentially behaved data only, we can even admit that the pandemic originated through November 2019 (95% CI: 31 Oct., 22 Dec.). With high confidence (p <0.01) China encountered the virus prior Italy. We generally view any pre-pandemic presence of the virus in humans before November 2019 as very unlikely. The later established dynamics of the epidemics data suggests that the country of the origin was China. [ABSTRACT FROM AUTHOR]

We collected COVID-19 epidemiological and epidemic control measures-related data in mainland China during the period January 1 to February 19, 2020, and empirically tested the practical effects of the epidemic control measures implemented in China by applying the econometrics approach. The results show that nationally, both traffic control and social distancing have played an important role in controlling the outbreak of the epidemic, however, neither of the two measures have had a significant effect in low-risk areas. Moreover, the effect of traffic control is more successful than that of social distancing. Both measures complement each other, and their combined effect achieves even better results. These findings confirm the effectiveness of the measures currently in place in China, however, we would like to emphasize that control measures should be more tailored, which implemented according to each specific city's situation, in order to achieve a better epidemic prevention and control. [ABSTRACT FROM AUTHOR]

In late 2019, the emergence of COVID-19 in Wuhan, China, led to the implementation of stringent measures forming the zero-COVID policy aimed at eliminating transmission. Zero-COVID policy basically aimed at completely eliminating the transmission of COVID-19. However, the relaxation of this policy in late 2022 reportedly resulted in a rapid surge of COVID-19 cases. The aim of this work is to investigate the factors contributing to this outbreak using a new SEIR-type epidemic model with time-dependent level of immunity. Our model incorporates a time-dependent level of immunity considering vaccine doses administered and time-post-vaccination dependent vaccine efficacy. We find that vaccine efficacy plays a significant role in determining the outbreak size and maximum number of daily infected. Additionally, our model considers under-reporting in daily cases and deaths, revealing their combined effects on the outbreak magnitude. We also introduce a novel Physics Informed Neural Networks (PINNs) approach which is extremely useful in estimating critical parameters and helps in evaluating the predictive capability of our model. [ABSTRACT FROM AUTHOR]

Since the outbreak of the new crown epidemic in China in early 2020, the number of confirmed cases of COVID-19 has continued to increase, and the Chinese government's policy of "static management" in the first round of the epidemic may affect the health behavior adjustment of Chinese residents. Using survey data on the TCM health literacy of 4016 residents in China (Gansu Province), a causal inference approach was used to explore the impact of the emergence of confirmed cases of COVID-19 on residents' TCM health literacy. We found that the emergence of confirmed cases can increase by 3.5%-7.0% in residents' TCM health literacy. Among them, the TCM health literacy of uneducated residents has not improved significantly, and the residents with secondary education have increased significantly by 8%. For those with higher education, the number of residents increased significantly by 6%. At the same time, the emergence of confirmed cases will increase the residents' practical TCM health literacy and decrease theoretical TCM health literacy. Through heterogeneity analysis, we explored the impact mechanism of confirmed cases on residents' TCM health literacy. We believe that the emergence of confirmed cases will make residents more inclined to participate in TCM-free clinics, theme activities, and other ways to acquire TCM knowledge. [ABSTRACT FROM AUTHOR]

Background: Publicity is a common form of governance in government and is even more important in contingency management, especially during the COVID-19 pandemic. Publicity has two sides, the main body of publicity is led by the government, the object of publicity is the response to the public. So, publicity exists in the "government-society" field. Our aim was to find out how governments have been able to achieve effective publicity in the COVID-19 and to promote the active participation of society in governance. Materials and methods: We adopted a case study approach. Taking Chongqing Municipality as an example, we collected 201 messages from five forms of publicity, including cell phone SMS, village (community) broadcast, publicity placards or banners, official websites, and government media platforms during the period of 2020–2021, and described and analyzed the publicity content of different forms of publicity. Results: During the whole period of the COVID-19, the publicity governance under contingency management showed the characteristics of focusing on administrative efficiency, social efficiency and post-social efficiency, and showed specific publicity governance functions such as mobilization and control, education and clarification, cultivation of public consciousness and shaping government credibility. Conclusions: Publicity governance in contingency management during the COVID-19 pandemic emphasizes three effective approaches: time synchronization, organizational scale, and interaction among multiple advocacy agents. This can extend the existing government-centered research to the level of interaction between the government and society, and help the government to better use effective publicity to achieve the governance task under contingency management. [ABSTRACT FROM AUTHOR]

Following the outbreak of COVID-19 at the end of 2019, universities around the world adopted a closed management model and various restrictive measures intended to reduce human contact and control the spread of the disease. Such measures have had a profound impact on university students, with a marked increase in depression-related psychological disorders. However, little is known about the specific status and factors influencing the impact of the pandemic on student mental health. Addressing this gap, this study examines the body dissatisfaction, physical activity, and sleep of university students during the pandemic, and uses their levels of depression to provide a theoretical basis for the development of mental health interventions for university students in the post-epidemic era. To achieve this, a total of 1,258 university students were randomly recruited for this cross-sectional study. Collected data included respondents' anthropometric measurements, body dissatisfaction levels, dietary habits, sleep status, physical activity levels, and depression levels. The overall detection rate of depression was 25.4%, with higher levels of depression among women. Multiple regression analysis showed that the PSQI score (β = 1.768, P < 0.01) and physical activity scores (β = -0.048, P < 0.01) were significant predictors of depression in men, while the PSQI score (β = 1.743, P < 0.01) and body dissatisfaction scores (β = 0.917, P < 0.01) were significant predictors of depression in women. Mental health problems were prevalent among university students during the COVID-19 pandemic. Results indicate the possibility of alleviating depression among university students by improving their body dissatisfaction, physical activity, and sleep. However, as this study was limited to Ganzhou City, it is challenging to extrapolate the findings to other populations. As this was a cross-sectional study, a causal relationship between depression levels and lifestyle habits cannot be determined. [ABSTRACT FROM AUTHOR]

COVID-19 is a global pandemic. In response to this unprecedented crisis, Chinese government formulated a series of policies. This research is dedicated to exploring the dynamic evolution of China's policy mix in response to COVID-19 in different crisis response stages from a network perspective. First, a three-dimensional analysis framework of "policy subject-policy target-policy instrument" was developed. Then, based on the data sets collected by textual analysis, the dynamic evolution of policy subject, policy target, policy instrument in China's policy mix in response to COVID-19 was discussed by using the method of SNA. This study concluded that the core policy subject, policy instrument, and policy target of China's response to COVID-19 changed with time. National Health Commission (NHC), Ministry of Finance (MOF), Ministry of Transport (MOT) and Ministry of Human Resources and Social Security (MHRSS) have important influences in the network of policy subjects. Other subjects are more at the edge of the network, and there are few joint issuances among policy subjects. The study also found that the core policy target was adjusted over time, with phased dynamic characteristics. At the initial stage of China's response to COVID-19, "reduce infection and mortality" and "steadily carry out economic and social work" were the core policy targets. With the COVID-19 under control, "enterprise development and work resumption" becomes a new core policy target. In addition, this study also revealed the dynamic evolution and unbalanced use of China's policy instruments in response to COVID-19 in different stages. The combination of policy instruments is mainly composed of "mandatory administration instruments" and "economic incentive instruments", and supplemented by "health promotion instruments" and "voluntary plan instruments". These findings may enrich the literature on COVID-19 policy to help researchers understand the dynamics of policy from a network perspective. Moreover, these findings may provide several valuable implications for policymakers and other countries to formulate more effective policies for epidemic response. [ABSTRACT FROM AUTHOR]

Optimizing the trade-off between economic growth and public health is a major goal of public administration, especially during public health events. Although containment measures are widely used to combat the Covid-19 outbreak, it is still debated how the measures affect the economy. Using a simplified susceptible-infected-recovered (SIR) model, this study investigates the dynamic impact of lockdown policy on social costs during the epidemic and the underlying mechanism, revealing that the lockdown policy has both a "shutdown effect" and an "anti-epidemic effect", and should be implemented and lifted in a timely manner. Based on a micro-level dataset of 57,547 private enterprises in China in 2020, this study provided empirical evidence for the presence of negative "shutdown effect" and positive "anti-epidemic effect" of lockdown on reopening, both of which are in part mediated by labor input, factor mobility, and market demand recovery. Furthermore, the shutdown effect is weaker in regions with sufficient testing and quarantine resources, government capacity and preference for targeted response, whereas the anti-epidemic effect is stronger in densely populated areas with relatively low public compliance. Additionally, digital measures can aid in the containment of epidemics. The findings not only contribute to a better understanding of the rationality and effectiveness of the lockdown policy, but also provides practical evidence and implications for the government to improve the synergistic efficiency of epidemic control tools and strengthen the resilience of local economic growth. [ABSTRACT FROM AUTHOR]

Background: To combat/control the COVID-19 pandemic, a complete lockdown was implemented in China for almost 6 months during 2020. Purpose: To determine the impact of a long-term lockdown on the academic performance of first-year nursing students via mandatory online learning, and to determine the benefits of online teaching. Methods: The recruitment and academic performance of 1st-year nursing students were assessed between 2019 [prior to COVID-19, n = 195, (146 women)] and 2020 [during COVID-19, n = 180 (142 women)]. The independent sample t test or Mann-Whitney test was applied for a comparison between these two groups. Results: There was no significant difference in student recruitment between 2019 and 2020. The overall performance of the first-year students improved in the Biochemistry, Immunopathology, Traditional Chinese Medicine Nursing and Combined Nursing courses via mandatory online teaching in 2020 compared with traditional teaching in 2019. Conclusion: Suspension of in-class learning but continuing education virtually online has occurred without negatively impacting academic performance, thus academic goals are more than achievable in a complete lockdown situation. This study offers firm evidence to forge a path for developments in teaching methods to better incorporate virtual learning and technology in order to adapt to fast-changing environments. However, the psychological/psychiatric and physical impact of the COVID-19 lockdown and the lack of face-to-face interaction on these students remains to be explored. [ABSTRACT FROM AUTHOR]

Since the emergence and subsequent spread of the COVID-19 pandemic, students and instructors have faced unprecedented challenges and have been forced to shift traditional face-to-face classes online. This study, based on the E-learning Success Model (ELSM), seeks to examine the e-readiness level of students/instructors, judge the impediments that students/instructors encountered in different phases—pre-course delivery, course delivery, and course completion phase of the online EFL class, search for valuable online learning elements, and recommend recommendations for promoting e-learning success in online EFL classes. The study sample consists of 5914 students and 1752 instructors. The results demonstrate that: (a) both the students' and instructors' e-readiness level were slightly lower than the ready level; (b) three valuable online learning elements were teacher presence, teacher-student interaction, and practicing problem-solving ability; (c) eight categories of impediments during different phases of the online EFL class were technical challenges, learning process, learning environments, self-control, health concern, learning materials, assignment, and learning effect and assessments; (d) seven types of recommendations for promoting e-learning success were: (1) students: infrastructure and technology, learning process, content, curriculum design, teacher skills, service, and assessment; and (2) instructors: infrastructure and technology, human resources, teaching quality, content and services, curriculum design, teacher skills, and assessment. Based on these findings, this study recommends that further studies with an action research approach should be conducted to examine whether the recommendations are effective. Institutions should take the initiative to overcome barriers to engage and stimulate students. The outcomes of this research have theoretical and practical implications for researchers and higher education institutions (HEIs). During unprecedented times such as pandemics, administrators and instructors will have insights into implementing emergency remote teaching. [ABSTRACT FROM AUTHOR]

Policy quantitative analysis can effectively evaluate the government's response to COVID-19 emergency management effect, and provide reference for the government to formulate follow-up policies. The content mining method is used to explore the 301 COVID-19 policies issued by the Central government of China since the outbreak of the epidemic in a multi-dimensional manner and comprehensively analyze the characteristics of epidemic prevention policies. Then, based on policy evaluation theory and data fusion theory, a COVID-19 policy evaluation model based on PMC-AE is established to evaluate quantitatively eight representative COVID-19 policy texts. The results show that: Firstly, China's COVID-19 policies are mainly aimed at providing economic support to enterprises and individuals affected by the epidemic, issued by 49 departments, and include 32.7 percent supply-level and 28.5 percent demand-level, and 25.8 percent environment-level. In addition, strategy-level policies accounted for at least 13 percent. Secondly, according to the principle of openness, authority, relevance and normative principle, eight COVID-19 policies are evaluated by PMC-AE model. Four policies are level Ⅰ policies, three policies are level Ⅱ policies and one policy is level Ⅲ policies. The reason for its low score is mainly affected by four indexes: policy evaluation, incentive measures, policy emphasis and policy receptor. To sum up, China has taken both non-structural and structural measures to prevent and control the epidemic. The introduction of specific epidemic prevention and control policy has realized complex intervention in the whole process of epidemic prevention and control. [ABSTRACT FROM AUTHOR]

As SARS-CoV-2 emerged as a global threat in early 2020, China enacted rapid and strict lockdown orders to prevent introductions and suppress transmission. In contrast, the United States federal government did not enact national orders. State and local authorities were left to make rapid decisions based on limited case data and scientific information to protect their communities. To support local decision making in early 2020, we developed a model for estimating the probability of an undetected COVID-19 epidemic (epidemic risk) in each US county based on the epidemiological characteristics of the virus and the number of confirmed and suspected cases. As a retrospective analysis we included county-specific reproduction numbers and found that counties with only a single reported case by March 16, 2020 had a mean epidemic risk of 71% (95% CI: 52–83%), implying COVID-19 was already spreading widely by the first detected case. By that date, 15% of US counties covering 63% of the population had reported at least one case and had epidemic risk greater than 50%. We find that a 10% increase in model estimated epidemic risk for March 16 yields a 0.53 (95% CI: 0.49–0.58) increase in the log odds that the county reported at least two additional cases in the following week. The original epidemic risk estimates made on March 16, 2020 that assumed all counties had an effective reproduction number of 3.0 are highly correlated with our retrospective estimates (r = 0.99; p<0.001) but are less predictive of subsequent case increases (AIC difference of 93.3 and 100% weight in favor of the retrospective risk estimates). Given the low rates of testing and reporting early in the pandemic, taking action upon the detection of just one or a few cases may be prudent. [ABSTRACT FROM AUTHOR]

The spread of the global COVID-19 epidemic, home quarantine, and blockade of infected areas are essential measures to prevent the spread of the epidemic, but efforts to prevent and control the outbreak lead to the disruption of fresh and cold chain agricultural products in the region. Based on the multi-layer management model of non-scale agricultural households in China, we applied the complex network theory to construct an evolutionary model of the Chinese fresh cold chain network with adaptation degree priority connection, dual local world considering transport distance connection relationship, and superiority and inferiority mechanism. Based on this model, we studied the evolution of fresh cold chain disruption, and puts forward the optimal design of fresh cold chain network disruption and reconnection from the perspective of practicality and economy. [ABSTRACT FROM AUTHOR]

The effectiveness of the blended teaching model in improving university students' English learning achievement has been frequently reported in China in the post-pandemic era. However, such research has seldom explored the students' entire EFL (English as a foreign language) learning process and mechanism from the perspective of learners within this model. This study therefore used the 3P (presage, process and product) teaching and learning theory to explore the mediating role of learning methods (i.e., learning engagement and academic procrastination) in the relationship between learning preparation (i.e., academic self-concept and course experience) and learning achievement within the Chinese EFL blended teaching context from the perspective of learners. In this study, 942 Chinese university students (male: N = 447; female: N = 495) participated in a survey and completed electronic questionnaires on EFL-related academic self-concept, learning engagement, academic procrastination, and learning achievement. The data were analyzed using AMOS software and a structural equation modeling (SEM) technique. The results showed that both students' academic self-concept and course experience directly and positively predicted their English learning achievement. Moreover, students' academic self-concept of learning achievement was partially mediated by learning engagement and academic procrastination, whereas the effect of course experience on learning achievement was fully mediated by learning engagement and academic procrastination. After discussing these findings, suggestions as well as limitations for future studies will be given. [ABSTRACT FROM AUTHOR]

COVID-19, as a global health crisis, has triggered the fear emotion with unprecedented intensity. Besides the fear of getting infected, the outbreak of COVID-19 also created significant disruptions in people's daily life and thus evoked intensive psychological responses indirect to COVID-19 infections. In this study, we construct a panel expressed fear database tracking the universe of social media posts (16 million) generated by 536 thousand individuals between January 1st, 2019 and August 31st, 2020 in China. We employ deep learning techniques to detect expressions of fear emotion within each post, and then apply topic model to extract the major topics of fear expressions in our sample during the COVID-19 pandemic. Our unique database includes a comprehensive list of topics, not being limited to post centering around COVID-19. Based on this database, we find that sleep disorders ("nightmare" and "insomnia") take up the largest share of fear-labeled posts in the pre-pandemic period (January 2019-December 2019), and significantly increase during the COVID-19. We identify health and work-related concerns are the two major sources of non-COVID fear during the pandemic period. We also detect gender differences, with females having higher fear towards health topics and males towards monetary concerns. Our research shows how applying fear detection and topic modeling techniques on posts unrelated to COVID-19 can provide additional policy value in discerning broader societal concerns during this COVID-19 crisis. [ABSTRACT FROM AUTHOR]

Background: Clinical internship is an indispensable stage for nursing students to graduate successfully and become qualified nurses. However, COVID-19, a novel coronavirus disease with strong human-to-human transmission, hit China in late 2019 and forced the Chinese government to suspend classes and clinical internships. To cope with this situation, e-internship, which facilitate varied interactions without the need for direct contact, is used as an alternative strategy to help nursing students continue their internships. Objectives: To describe the perceptions and experiences of undergraduate nursing students in e-internships during the COVID-19 pandemic. Methods: A descriptive phenomenological design was adopted. Seventeen undergraduate nursing students in a major teaching hospital in Changsha, China, were recruited into the study. Data were collected through semi-structured, in-depth, face-to-face interviews. The interviews were transcribed verbatim and analyzed using Colaizzi's approach. Results: Four themes were captured from the data analysis: perceived images of clinical nurses in e-internships, psychological experience, perceived benefits of e-internships, and perceived limitations of e-internships. Conclusions: Our findings suggest that e-internship is a suitable method for training and cultivating undergraduate nursing students during a crisis. To enhance the efficiency of e-internships, guidelines and standards should be formulated, and effective measures should be taken to build better e-internship platforms. In the future, we suggest combine on-site internships with e-internships, thereby fully using their advantages, and improve the efficiency of internships as much as possible. [ABSTRACT FROM AUTHOR]

Background: Since the outbreak of the respiratory infectious disease caused by the novel coronavirus in 2019, the COVID-19 epidemic has posed a serious threat to the life and safety of the public, and has also seriously affected the normal study and life of college students in China. Although a series of studies have been conducted on college students' knowledge, attitudes and practices of COVID-19, the results vary widely. This study aimed to evaluate the pooled estimated level of knowledge, attitudes, and practices (KAP) about COVID-19 among college students in China. Methods: We conducted a comprehensive search on Scopus, ProQuest, PubMed, EMbase, Web of Science, the Cochrane Library, Chinese Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), VIP Database and Wanfang Database up to 13 February 2022. We then assessed the quality of included studies using a checklist developed by the Joanna Briggs Institute (JBI) for cross-sectional studies and analyzed using STATA.15 after two researchers independently extracted relevant data and entered them into Microsoft Excel. Funnel plots and Egger's regression tests were used to check for publication bias, and sensitivity analysis was performed to assess the robustness of the results. A random-effects model was used for the meta-analysis, on the basis of which subgroup analyses were performed by time of investigation (study period) and by gender and major of the subjects. Result: A total of 42 studies including 174,440 subjects were included in this review, and the quality of the included studies was mainly intermediate and advanced. The findings of the meta-analysis showed that the overall levels of Chinese college students' knowledge, positive and negative attitudes, and practice of preventive measures towards COVID-19 were 74% (95%CI: 69%-79%), 84% (95%CI: 80%-88%), 31% (95%CI: 23%-38%) and 82% (95%CI: 77%-86%), respectively. The results of subgroup analysis showed that female and medical college students had higher levels of knowledge and practice on COVID-19. Conclusion: The study findings showed that the overall KAP level of college students in China included in the study was relatively optimistic. Influenced by gender, major and time, there were differences in the KAP level of college students. In order to promote the effective prophylaxis and control of pandemic, we recommend implementing targeted measures to improve the awareness rate of COVID-19-related knowledge among this group and the implementation rate of COVID-19 preventive measures among male and non-medical college students. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to investigate the change of myopic prevalence in students with different demographic characteristics before and after the COVID-19 pandemic in Suqian, China. Methods: A retrospective, cross-sectional study was conducted. Student data from 52 schools in 2019 and 2020 were collected from the electronic medical records database through cluster sampling. Ophthalmic examinations were conducted on students from September to December in 2019 and 2020. Measurements of uncorrected visual acuity (UCVA) and noncycloplegic autorefraction were included to obtain the spherical equivalent refraction (SER) and prevalence of myopia. The difference in the rate of myopia and SER of students ages 6 to 18 with various demographic characteristics was compared between the two years. Results: Records from 118,479 students in 2019 and the 121,881 students in 2020 were obtained. In 2019 and 2020, the prevalence of overall myopia increased from 43.1% to 48.9% (5.8 percentage point), and a substantial shift in myopic rate occurred in grades 4 to 6 (6.9 percentage point). The change in the prevalence of myopia in girls (5.9 percentage point) was approximately equal to that in boys (5.8 percentage point) and it was more common in rural students (5.9 percentage point) than in urban students (5.1 percentage point). The prevalence of low myopia increased more in children, and the prevalence of moderate myopia increased more in adolescents. The mean spherical equivalent refraction (SER) (-1.34±2.03 D) was lower in 2020 than in 2019 (-1.16±1.92 D), while SER decreased mainly at ages 7 to 15. The SER presented myopic status at the age of 9 (-0.55±1.26 D in 2019, -0.71±1.42 D in 2020), and attained moderate myopia at the age of 15 (-3.06±2.41 D in 2019, -3.22±2.40 D in 2020). Conclusions: After the COVID-19 pandemic, myopia increased in this population with variable rates of increase in different demographic groups. The change of myopia in children was comparatively greater than that in adolescents. Therefore, we should take measures to prevent and control the development of myopia after the COVID-19 pandemic, especially for younger students. [ABSTRACT FROM AUTHOR]

Background: To investigate the mortality and health care resource use among patients with severe or critical coronavirus disease of 2019 (COVID-19) in the first wave of pandemic in China. Methods: We performed a systematic review and meta-analysis to investigate the mortality, discharge rate, length of hospital stay, and use of invasive ventilation in severe or critical COVID-19 cases in China. We searched electronic databases for studies from China with no restrictions on language or interventions patients received. We screened records, extracted data and assessed the quality of included studies in duplicate. We performed the meta-analysis using random-effect models through a Bayesian framework. Subgroup analyses were conducted to examine studies by disease severity, study location and patient enrolment start date. We also performed sensitivity analysis using various priors, and assessed between-study heterogeneity and publication bias for the primary outcomes. Results: Out of 6,205 titles and abstracts screened, 500 were reviewed in full text. A total of 42 studies were included in the review, of which 95% were observational studies (n = 40). The pooled 28-day and 14-day mortalities among severe or critical patients were 20.48% (7,136 patients, 95% credible interval (CrI), 13.11 to 30.70) and 10.83% (95% CrI, 6.78 to 16.75), respectively. The mortality declined over time and was higher in patients with critical disease than severe cases (1,235 patients, 45.73%, 95% CrI, 22.79 to 73.52 vs. 3,969 patients, 14.90%, 95% CrI, 4.70 to 39.57) and patients in Hubei compared to those outside Hubei (6,719 patients, 26.62%, 95% CrI, 13.11 to 30.70 vs. 244 patients, 5.88%, 95% CrI 2.03 to 14.11). The length of hospital stay was estimated at 18.48 days (6,847 patients, 95% CrI, 17.59 to 21.21), the 28-day discharge rate was 50.48% (3,645 patients, 95% CrI, 26.47 to 79.53), and the use of invasive ventilation rate was 13.46% (4,108 patients, 95% CrI, 7.61 to 22.31). Conclusions: Our systematic review and meta-analysis found high mortality among severe and critical COVID-19 cases. Severe or critical COVID-19 cases consumed a large amount of hospital resources during the outbreak. [ABSTRACT FROM AUTHOR]

The resilience and vulnerability of airport networks are significant challenges during the COVID-19 global pandemic. Previous studies considered node failure of networks under natural disasters and extreme weather. Herein, we propose a complex network methodology combined with data-driven to assess the resilience of airport networks toward global-scale disturbance using the Chinese airport network (CAN) and the European airport network (EAN) as a case study. The assessment framework includes vulnerability and resilience analyses from the network- and node-level perspectives. Subsequently, we apply the framework to analyze the airport networks in China and Europe. Specifically, real air traffic data for 232 airports in China and 82 airports in Europe are selected to form the CAN and EAN, respectively. The complex network analysis reveals that the CAN and the EAN are scale-free small-world networks, that are resilient to random attacks. However, the connectivity and vulnerability of the CAN are inferior to those of the EAN. In addition, we select the passenger throughput from the top-50 airports in China and Europe to perform a comparative analysis. By comparing the resilience evaluation of individual airports, we discovered that the factors of resilience assessment of an airport network for global disturbance considers the network metrics and the effect of government policy in actual operations. Additionally, this study also proves that a country's emergency response-ability towards the COVID-19 has a significantly affectes the recovery of its airport network. [ABSTRACT FROM AUTHOR]

Non-Pharmaceutical Public Health Interventions (NPHIs) have been used by different countries to control the spread of the COVID-19. Despite available evidence regarding the effectiveness of NPHSs, there is still no consensus about how policymakers can trust these results. Studies on the effectiveness of NPHSs are single studies conducted in specific communities. Therefore, they cannot individually prove if these interventions have been effective in reducing the spread of the infection and its adverse health outcomes. In this systematic review, we aimed to examine the effects of NPHIs on the COVID-19 case growth rate, death growth rate, Intensive Care Unit (ICU) admission, and reproduction number in countries, where NPHIs have been implemented. We searched relevant electronic databases, including Medline (via PubMed), Scopus, CINAHL, Web of Science, etc. from late December 2019 to February 1, 2021. The key terms were primarily drawn from Medical Subject Heading (MeSh and Emtree), literature review, and opinions of experts. Peer-reviewed quasi-experimental studies were included in the review. The PROSPERO registration number is CRD42020186855. Interventions were NPHIs categorized as lockdown, stay-at-home orders, social distancing, and other interventions (mask-wearing, contact tracing, and school closure). We used PRISMA 2020 guidance for abstracting the data and used Cochrane Effective Practice and Organization of Practice (EPOC) Risk of Bias Tool for quality appraisal of the studies. Hartung-Knapp-Sidik-Jonkman random-effects model was performed. Main outcomes included COVID-19 case growth rate (percentage daily changes), COVID-19 mortality growth rate (percentage daily changes), COVID-19 ICU admission (percentage daily changes), and COVID-19 reproduction number changes. Our search strategies in major databases yielded 12,523 results, which decreased to 7,540 articles after eliminating duplicates. Finally, 35 articles qualified to be included in the systematic review among which 23 studies were included in the meta-analysis. Although studies were from both low-income and high-income countries, the majority of them were from the United States (13 studies) and China (five studies). Results of the meta-analysis showed that adoption of NPHIs has resulted in a 4.68% (95% CI, -6.94 to -2.78) decrease in daily case growth rates, 4.8% (95 CI, -8.34 to -1.40) decrease in daily death growth rates, 1.90 (95% CI, -2.23 to -1.58) decrease in the COVID-19 reproduction number, and 16.5% (95% CI, -19.68 to -13.32) decrease in COVID-19 daily ICU admission. A few studies showed that, early enforcement of lockdown, when the incidence rate is not high, contributed to a shorter duration of lockdown and a lower increase of the case growth rate in the post-lockdown era. The majority of NPHIs had positive effects on restraining the COVID-19 spread. With the problems that remain regarding universal access to vaccines and their effectiveness and considering the drastic impact of the nationwide lockdown and other harsh restrictions on the economy and people's life, such interventions should be mitigated by adopting other NPHIs such as mass mask-wearing, patient/suspected case isolation strategies, and contact tracing. Studies need to address the impact of NPHIs on the population's other health problems than COVID-19. [ABSTRACT FROM AUTHOR]

Although emerging studies have discussed the potential benefits of soundscape in mental restoration, few have investigated how soundscape renews and re-energizes people, especially in facing the current public challenge of the COVID-19 crisis. We established a moderated mediation model to examine the relationship of the four restorative components of soundscape: being away, compatibility, extent and fascination. The data were collected in Xixi Wetland National Park, China, before the outbreak of COVID-19 (n = 562) in October 2019 and post COVID-19 in October 2020 (n = 341). The results revealed that natural soundscapes have great restorative benefits for visitors. The inter relationships of the restorative components are moderated by the perceived stress level which show significant different before and after the COVID-19 pandemic. The post-COVID-19 visitors reported a higher level of stress while natural soundscapes had greater effects on their mental restoration. The direct effects of extent and fascination as well as the mediating effects of fascination were stronger among the post-COVID-19 group. However, the path coefficient from being away to compatibility were higher in the pre-COVID-19 group. This study improves the current understanding of the interactive mechanism among the restorative components of soundscape. Knowledge about natural soundscape encourages practitioners to consider it as a guideline for the creation of sustainable environments, especially under the COVID-19 crisis. [ABSTRACT FROM AUTHOR]

The entire world has suffered a lot since the outbreak of the novel coronavirus (COVID-19) in 2019, so simulation models of COVID-19 dynamics are urgently needed to understand and control the pandemic better. Meanwhile, emotional contagion, the spread of vigilance or panic, serves as a negative feedback to the epidemic, but few existing models take it into consideration. In this study, we proposed an innovative multi-layer hybrid modelling and simulation approach to simulate disease transmission and emotional contagion together. In each layer, we used a hybrid simulation method combining agent-based modelling (ABM) with system dynamics modelling (SDM), keeping spatial heterogeneity while reducing computation costs. We designed a new emotion dynamics model IWAN (indifferent, worried, afraid and numb) to simulate emotional contagion inside a community during an epidemic. Our model was well fit to the data of China, the UK and the US during the COVID-19 pandemic. If there weren't emotional contagion, our experiments showed that the confirmed cases would increase rapidly, for instance, the total confirmed cases during simulation in Guangzhou, China would grow from 334 to 2096, which increased by 528%. We compared the calibrated emotional contagion parameters of different countries and found that the suppression effect of emotional contagion in China is relatively more visible than that in the US and the UK. Due to the experiment results, the proposed multi-layer network model with hybrid simulation is valid and can be applied to the quantitative analysis of the epidemic trends and the suppression effect of emotional contagion in different countries. Our model can be modified for further research to study other social factors and intervention policies in the COVID-19 pandemic or future epidemics. [ABSTRACT FROM AUTHOR]

This study is to assess the influences of climate, socio-economic determinants, and spatial distance on the confirmed cases and deaths in the raise phase of COVID-19 in China. The positive confirmed cases and deaths of COVID-19 over the population size of 100,000 over every 5 consecutive days (the CCOPSPTT and DOPSPTT for short, respectively) covered from 25th January to 29th February, 2020 in five city types (i.e., small-, medium-, large-, very large- and super large-sized cities), along with the data of climate, socio-economic determinants, spatial distance of the target city to Wuhan city (DW, for short), and spatial distance between the target city and their local province capital city (DLPC, for short) were collected from the official websites of China. Then the above-mentioned influencing factors on CCOPSPTT and DOPSPTT were analyzed separately in Hubei and other provinces. The results showed that CCOPSPTT and DOPSPTT were significantly different among five city types outside Hubei province (p < 0.05), but not obviously different in Hubei province (p > 0.05). The CCOPSPTT had significant correlation with socio-economic determinants (GDP and population), DW, climate and time after the outbreak of COVID-19 outside Hubei province (p < 0.05), while was only significantly related with GDP in Hubei province (p < 0.05). The DOPSPTT showed significant correlation with socio-economic determinants, DW, time and CCOPSPTT outside Hubei province (p < 0.05), while was significantly correlated with GDP and CCOPSPTT in Hubei province (p < 0.05). Compared with other factors, socio-economic determinants have the largest relative contribution to variance of CCOPSPTT in all studied cities (> 78%). The difference of DOPSPTT among cities was mainly affected by CCOPSPTT. Our results showed that influences of city types on the confirmed cases and death differed between Hubei and other provinces. Socio-economic determinants, especially GDP, have higher impact on the change of COVID-19 transmission compared with other factors. [ABSTRACT FROM AUTHOR]