Search

Patients narratives are being recorded increasingly frequently and spontaneously in short user produced content (UGC) films, which may have an impact on the vlogger's health as well as the public's comprehension of the relevant health concerns. This paper addressed three research questions regarding the population characteristics of UGC video publishers, the narrative theme of the videos, and the emotional orientation of the commenters. This study aimed to deepen our understanding of COVID-19 patients' narrative intentions and emotional needs through the theoretical frameworks of theory of planned behavior (TPB) and negative dominance theory (NDT). We collected 335 videos from 28 COVID-19 patients and 572,052 comments as samples on Douyin platform, the largest short-video website in China. Using Latent Semantic Analysis, we analyzed the descriptive information of the video blogs, the narrative textual information of the videos, and the emotional orientation of the comments. Our findings revealled seven categories of narrative themes, with 52.1% of video comments exhibiting a positive emotional orientation. Within a framework integrating TPB and NDT theories, we analyzed the behavioral intentions of vloggers and viewers during COVID-19 epidemic, and interpreted the persistent posting of videos and the active posting of comments as positive actions that counteracted the multiple effects of negative messages. This study contributes to the understanding of individual narratives in macro-risk communication, both theoretically and empirically, and offers policy recommendations in relevant fields. [ABSTRACT FROM AUTHOR]

The Coronavirus Disease 2019 (COVID-19) pandemic has brought unprecedented challenges to urban transportation. During the pandemic, public transportation, as an integral part of urban transportation, must ensure the safety of passengers, particularly low-mobility individuals (LMIs): older people, individuals with disabilities, and low-income individuals who prefer getting around by it. Based on passengers' travel behavior and psychological characteristics, this paper analyzes the public transportation travel of LMIs before and during the pandemic using a hybrid survey method that combines a face-to-face survey and a supplementary telephone interview. The results show that LMIs differ from the general public in public transportation travel characteristics, and the three subgroups also differ from each other. Accordingly, the conditions in the context of the pandemic should be fully considered to meet LMIs' demand for public transportation and ensure their safety when relevant policies are formulated. [ABSTRACT FROM AUTHOR]

Considering the high variability of Covid-19 and unknown sequelae of rebound infections. We may be caught in a long-term struggle against the virus. The evaluation and summary of past anti-epidemic policies highlight profound practical significance for either decision makers or individuals. This paper applies both theoretical and empirical approaches to study the impact of city lockdown and air pollution on Covid-19. First, we apply an extended Susceptible-Infected-Removed (SIR) model to identify the relationship between lockdown, air pollution, and Covid-19 cases. Second, we apply the Differences-in-Differences (DID) model and Poisson Pseudo-Maximum Likelihood (PPML) model to test the impact of lockdown on Covid-19, by sorting out lockdown policies implemented by cities during the epidemic. Third, we empirically analyze the impact of air pollution on Covid-19, based on daily data from 257 cities in China. Finally, we examine the mechanism by which lockdown impacts Covid-19. Newly confirmed Covid-19 cases are reduced by 31.1% nationwide (excluding Wuhan) during the lockdown period. Regions with lower air pollution experience fewer Covid-19 cases. Air pollution aggravates Covid-19, with the pollutants PM2.5, PM10, NO2, CO, and O3 having the greatest impact. The results indicate that an increase in one unit of air quality index (AQI) concentrations is associated with 1.723 more newly confirmed cases. The effects of air pollution on the spread of Covid-19 diminish as the population size increases. Lockdown can inhibit the spread of Covid-19 by reducing air pollution and population movement. [ABSTRACT FROM AUTHOR]

Based on the spillover index and an improved spillover asymmetric measure method, this paper studies the volatility spillover and its asymmetric effect between crude oil and agricultural commodity futures in pre- and post-outbreak of COVID-19. We find that the total volatility spillover is higher with pre-outbreak of COVID-19. In addition, the volatility spillover caused by China's crude oil is more prominent than international crude oil around the COVID-19, which highlights the necessity of risk control through the establishment of an energy financial market in China. Finally, although the asymmetric effect of volatility spillover has always existed, crude oil was less impacted by good news post-outbreak of COVID-19, indicating that the outbreak of COVID-19 makes assets dominated by commodity attributes more sensitive to bad news. These findings are beneficial for investors to establish a cross-sector risk hedging portfolio, and provide empirical evidence for policymakers to ensure energy and food security. [ABSTRACT FROM AUTHOR]

The ongoing COVID-19 shocked financial markets globally, including China's crude oil future market, which is the third-most traded crude oil futures after WTI and Brent. As China's first crude oil futures are accessible to foreign investors, the Shanghai crude oil futures (SC) have attracted significant interest since launch at the Shanghai International Energy Exchange. The impact of COVID-19 on the new crude oil futures is an important issue for investors and policy makers. Therefore, this paper studies the short-term influence of COVID-19 pandemic on SC via multifractal analysis. We compare the market efficiency of SC before and during the pandemic with the multifractal detrended fluctuation analysis and other commonly used random walk tests. Then, we generate shuffled and surrogate data to investigate the components of multifractal nature in SC. And we examine cross-correlations between SC returns and other financial assets returns as well as SC trading volume changes by the multifractal detrended cross-correlation analysis. The results show that market efficiency of SC and its cross-correlations with other assets increase significantly after the outbreak of COVID-19. Besides that, the sources of its multifractal nature have changed since the pandemic. The findings provide evidence for the short-term impacts of COVID-19 on SC. The results may have important implications for assets allocation, investment strategies and risk monitoring. [ABSTRACT FROM AUTHOR]

The 2019 coronavirus (COVID‐19), started in China, spreads rapidly around the entire world. In automated medical imagery diagnostic technique, due to presence of noise in medical images and use of single pre‐trained model on low quality images, the existing deep network models cannot provide the optimal results with better accuracy. Hence, hybrid deep learning model of Xception model & Resnet50V2 model is proposed in this paper. This study suggests classifying X‐ray images into three categories namely, normal, bacterial/viral infections and Covid positive. It utilizes CLAHE & BM3D techniques to improve visual clarity and reduce noise. Transfer learning method with variety of pre‐trained models such as ResNet‐50, Inception V3, VGG‐16, VGG‐19, ResNet50V2, and Xception are used for better feature extraction and Chest X‐ray image classification. The overfitting issue were resolved using K‐fold cross validation. The proposed hybrid deep learning model results high accuracy of 97.8% which is better than existing techniques. [ABSTRACT FROM AUTHOR]

A bacterial infection in the lungs can cause viral pneumonia, a disease. Later the middle of December 2019, there have been multiple episodes of pneumonia in Wuhan City, China, with no known cause; it has since been discovered that this pneumonia is actually a new respiratory condition brought on by coronavirus infection. Humans who have lung abnormalities are more likely to develop high-risk conditions; this risk can be decreased with much quicker and more effective therapy. The symptoms of Covid-19 pneumonia are similar to those of viral pneumonia; they are not distinctive. X-ray or Computed Tomography (CT) scan images are used to identify lung abnormalities. Even for a skilled radiologist, it might be challenging to identify Covid-19/Viral pneumonia by looking at the X-ray images. For prompt and effective treatment, accurate diagnosis is essential. In this epidemic condition, delayed diagnosis can cause the number of cases to double, hence a suitable tool is required is necessary for the early identification of Covid-19. This paper highlights various AI techniques as a part of our contribution to swift identification and curie Covid-19 to front-line corona. The safety of Covid-19 people who have viral pneumonia is a concern. Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), two AI technologies from Deep Learning (DL), were utilized to identify Covid-19/Viral pneumonia. The Algorithm is taught utilizing non-public local hospitals or Covid-19 wards, as well as X-ray images of healthy lungs, fake lungs from viral pneumonia, and ostentatious lungs from Covid-19 that are all publicly available. The model is also validated over a lengthy period of time using the transfer learning technique. The results correspond with clinically tested positive Covid-19 patients who underwent Swap testing conducted by medical professionals, giving us an accuracy of 78 to 82 percent. We discovered that each DL model has a unique expertise after testing the various models. [ABSTRACT FROM AUTHOR]

This article explores the impact of COVID-19 policies on the mobility of elderly individuals in Australia and China. It highlights the digital exclusion faced by older people as smartphone use became mandatory for accessing public spaces and services. The article discusses how this digital exclusion deepened social isolation and exacerbated feelings of loneliness among older individuals. It also examines the gender inequalities and the increased burden on women as unpaid caregivers during the pandemic. The paper emphasizes the need for age-inclusive policies that address intersecting factors and promote equitable access to technology and public spaces. [Extracted from the article]

The 2019 novel coronavirus disease (COVID-19; previously known as 2019-nCoV) outbreak that originated from Wuhan, Hubei province, China, at the end of 2019 was declared a public health emergency of international concern on Jan 30, 2020, by WHO.[1] As a newly appearing infectious disease, COVID-19 garnered great research interest. 2 E Stoye, China coronavirus: how many papers have been published? 3 CC Du, Ministry of Science and Technology: efforts should not be focused on publishing papers before epidemic prevention and control tasks are completed (in Chinese). http://www.caixin.com/2020-01-30/101509614.html Jan 30, 2020, (in Chinese). [Extracted from the article]

This paper examines the notions, politics, and practice of care that have characterised the transnational Chinese state during the Covid-19 pandemic. Drawing on policy and media analyses, participant observation, and qualitative interviews with 21 Chinese people in the Netherlands, the paper maps out three care circuits: from the diaspora to China, from China to the diaspora, and from China to the world. The findings show how the pandemic has offered a stage for emotional ties, patriotism, and moral responsibility to be played out, cultivated, and contested. These in turn have an impact on the economic and political agendas of the transnational Chinese state. [ABSTRACT FROM AUTHOR]

On 31 May 2021, the Political Bureau of the Central Committee of the Communist Party of China proposed the policy that a couple can have three children, and rolled out more supportive measures to further optimize the fertility policies. However, while the Chinese government is further optimizing its fertility policy, the sudden outbreak of COVID-19 is raging around the world, which threatens the implementation of China's fertility optimization policy. Based on this, this paper firstly explores the impact of COVID-19 on women's fertility intentions. Secondly, based on the Theory of Planned Behavior, this paper constructs a structural equation model to quantitatively reveal the specific factors that affect women's fertility intentions under the epidemic, as well as their impact paths, and then puts forward corresponding suggestions for the government to solve the problem of fertility, aiming at delaying population aging and optimizing population structure. The research results show that: (1) COVID-19 lowers the fertility intentions of women of childbearing age. (2) During the pandemic, economic pressure emerged as the biggest factor affecting women's fertility intentions. The decline in income caused by the pandemic has become an important factor in preventing women from having children. (3) The conflict between work and childbearing is still an important factor affecting the fertility intentions of women of childbearing age. The government's provision of perfect childcare services and their strengthening of the protection of women's employment rights and interests will greatly reduce women's anxiety about childbearing. [ABSTRACT FROM AUTHOR]

Ever since China has formally joined the WHO-backed global COVID-19 vaccine initiative known as COVAX, there is a presumed notion that China's vaccine diplomacy will make a significant contribution to the international public good and thus uplift Beijing's role as the rule-maker of international order. To scrutinize this, the paper asks if China succeeded in proliferating its weaponized vaccine policy to obtain maximum diplomatic gains and soft power projection to intensify its international image, geopolitical power, and domestic politico legitimacy. The authors argue that despite its vaccine diplomacy demonstrated the robust governance capacity and responsibility to be a great power. Yet, Beijing's geopolitical influence and international image are significantly overrated and not enough to play a more prominent role in the global power fulcrum/equilibrium. On the contrary, China enjoys a leading position on the domestic political front. Its successful portrayal of China's vaccine provision in the global market and remarkable configuration to leverage a deep-rooted nationalism has fundamentally provided China with a powerful rationale to divert its public's attention from Beijing's earlier inadequate handling of the outbreak. The evaluation of the paper reveals that China's vaccine diplomacy's influence in promoting international image and geopolitics is limited but has successfully stabilized its domestic political environment and enhanced its domestic legitimacy. [ABSTRACT FROM AUTHOR]

During the last three years, numerous research papers have been reported which use social media data to explore several issues related to the COVID-19 pandemic. Bibliometric methods in this work are used to analyze 1427 peer-reviewed documents from the last three years extracted from the Web of Science database. The results of this study show that there was high growth in publications in open access journals with an annual rate reaching 19.3% and they also identify the top cited journals and research papers. The thematic analysis of papers shows that research topics related to social media for surveillance and monitoring of public attitudes and perceptions, mental health, misinformation, and fake news are important and well-developed, whereas topics related to distance-learning education with social media are emerging. The results also show that the USA, China, and the UK have published many papers and received a high number of citations because of their strong international collaboration. [ABSTRACT FROM AUTHOR]

Preexisting political institutions influence governments' responses to public health crises in different ways, creating national variations. This article investigates how state capacity, a country's fundamental ability to organize bureaucracy and allocate societal resources, affects the timing and configuration of governments' COVID‐19 policy responses. Through comparative case study analysis of five of China's neighboring countries early in the COVID‐19 crisis, the paper shows that more‐capable states (Singapore, South Korea, Taiwan) initiated crisis response faster, mobilized national resources more extensively, and utilized diverse policy tools when the virus risk level was still low. In contrast, low‐capacity states (Thailand and Indonesia) were more reactive in handling the crisis, limited their focus to border‐related measures, and were more constrained in the types of tools they could employ. The paper points to the importance of studying the COVID‐19 response process rather than the outcome (i.e., confirmed cases/deaths) when unpacking the impacts of political institutions in public health crises. [ABSTRACT FROM AUTHOR]

This paper explores a contingent sub-public sphere promoted by a group of former critical journalists in China during the coronavirus outbreak at the beginning of 2020. During the initial outbreak of coronavirus in China, the observed former journalists, who left the field of critical journalism during the re-structure of Chinese news industries under Xi Jinping's leadership, drew on their knowledge of Chinese politics and censorship to contest information cover-up by the state, online censorship, and the state's discourses of China as a successful model of combating the virus. Their activities effectively engaged mass participation of Chinese people and promoted critical opinions of the public. The paper bears the primary aim to deepen the understanding of the episodic formation of elite-driven public spheres in China by investigating the nuances of each case. I therefore, in this particular case study, explore concepts of habitus and capital from Bourdieu's field theory as analytical tools in the investigation of the persistence of political participation and government scrutiny by former critical journalists on social media after leaving the field of critical journalism. The empirical research combines materials collected through 15 former critical journalists' WeChat accounts between January and May 2020, along with in-depth interviews. [ABSTRACT FROM AUTHOR]

The emergence of COVID-19 has provided a new vigor to addressed global health issues. In this regard, global health diplomacy initiatives have seen a considerable surge. Countries around the world are using the opportunity to harness the potential of global health diplomacy in cultivating relations with several countries and also building a soft power projection. A case in point is how China has been spearheading global health efforts to improve relations while projecting a soft power about how China aims to act as global savior. Chinese efforts were able to gain significant traction owing to the fact that the United States under the administration of President Trump suspended its global leadership role, the first such instance in the post-World War-II era. This paper explains the concept of global health diplomacy by conducting a comparative analysis of the global health efforts and policies undertaken by both the United States and China by following qualitative research technique and secondary sources to explain the phenomenon. The study found that China led the response to COVID-19 not only domestically but globally as well. The U.S. lagged but gradually started to compete China in health diplomacy. There is an evident struggle for dominance in health sector between China and the U.S., however, it is not expected to lead into hard power struggle. The paper has concluded that it is important for both countries to work together in future in case of pandemic to spearhead an international effort against such crises. Moreover, it recommends Chinese authorities to include health corridor as a component with Belt and Road Initiative. On the other hand, the United States under the administration of President Joe Biden should invest in multilateral efforts so to empower global health institutions to better prepare for future health crises. [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 coronavirus disease (COVID-19) which emerged in Wuhan, China, in December 2019, is widely controlled now in China. However, the global epidemic is still severe. To study and comment on Hubei's approaches for responding to the disease, the paper considered some factors such as suspected cases (part of them are influenza patients or common pneumonia patients, etc.), quarantine, patient classification (three types), clinically diagnosed cases, and lockdown of Wuhan and Hubei. After that, the paper established an S E L I H R model based on the surveillance data of Hubei published by the Hubei Health Commission from 10 January 2020 to 30 April 2020 and used the fminsearch optimization method to estimate the optimal parameters of the model. We obtained the basic reproduction number R 0 = 3.1571 from 10 to 22 January. R 0 was calculated as 2.0471 from 23 to 27 January. From 28 January to 30 April, R 0 = 1.5014. Through analysis, it is not hard to find that the patients without classification during the period of confirmed cases will result in the cumulative number of cases in Hubei to increase. In addition, regarding the lockdown measures implemented by Hubei during the epidemic, our simulations also show that if the lockdown time of either Hubei or Wuhan is advanced, it will effectively curb the spread of the epidemic. If the lockdown measures are not taken, the total cumulative number of cases will increase substantially. From the results of the study, it can be concluded that the lockdown, patient classification, and the large-scale case screening are essential to slow the spread of COVID-19, which can provide references for other countries or regions. [ABSTRACT FROM AUTHOR]

With the rapid development of economy and the increasing improvement of agricultural production level, people's demand for fruits is also increasing year by year. China is the largest fruit production and consumption country in the world. According to relevant statistics reported for China, by the end of 2019, the total amount of various fruits sold had reached about 270 million tons, with apples accounting for 48% of the global output and pears accounting for 69% of the national total output. However, China's fruit picking is still dominated by manual picking process, which takes a lot of manpower and time to complete, therefore resulting in low fruit picking efficiency. Some farmers are unable to complete fruit picking in a short time, resulting in a large number of fruits unable to be listed, resulting in huge losses. To solve this problem, this paper focuses on the visual recognition and path planning for intelligent fruit-picking robot. Using robot to complete fruit picking is the best way at present. This paper establishes a picking robot recognition and positioning system based on stereo vision, which is used to identify and locate the fruits planted in the orchard area. The coordinate error of the target point of the intelligent fruit-picking robot coordinate system is less than 10 mm, which has high accuracy. Then, the path of intelligent fruit-picking robot is planned based on visual feedback algorithm and biological stimulation neural network. Our empirical evaluations suggest that the proposed robot walks in the planting park in the shape of "zigzag" and realizes full-coverage path planning after 6 turns. The results show the efficiency of the intelligent method. [ABSTRACT FROM AUTHOR]

In the coronavirus epidemic, many Chinese hospitals have established buffer zones to prevent the spread and transmission of the virus. The buffer zone is a monitored and separate area where the patients who need hospitalizations after the quick treatments in the emergency department can temporarily wait for the Covid-19 test and receive some healthcare services to stabilize their conditions. Because the beds in the buffer zones are limited, the managers face the patient admission control problem for the buffer zone. This management and control problem is challenging since the patient arrivals are uncertain, and the patients’ conditions are different. In this paper, we build the infinite- and finite-horizon Markov decision process (MDP) models for this problem. We use the uniformization method to discretize the patient flow. We propose various iteration algorithms to solve the MDP models and obtain the optimal and threshold policies. Numerical experiments validate the advantages of the policies obtained by the algorithms in this paper over the current policies of hospitals. Note to Practitioners—The ongoing COVID-19 pandemic has been causing enormous damage to people’s health, jobs, and well-being. COVID-19 has affected almost all countries globally and has changed the operation mode of the healthcare system, especially the hospitals. The hospitals are the frontlines of healthcare service and the battle with the COVID-19 pandemic. This article is motivated by our collaborations with hospitals in Shanghai, China. In China, many hospitals establish buffer zones: a monitored area where the patients who need hospitalizations after the quick treatments in the emergency department can temporarily wait for the Covid-19 test and receive some healthcare services to stabilize their conditions. Because the zone’s capacity is limited, the managers must make dynamic patient admission control decisions according to multiple factors, such as patients’ health conditions and the usage of beds in the zone. We propose two MDP models to solve this complex problem. Several iteration algorithms are designed to solve the MDP models and obtain the optimal and threshold policies. Based on hospitals’ real-life data, we show the methods presented in this paper can help hospital managers make more reasonable decisions. Although we focus on the hospital’s buffer zone in China, the methodology and approach for this problem can be extended to other practical hospital management scenarios in the coronavirus pandemic. For example, For example, some hospitals have admission control problems for coronavirus patients due to hospital capacity limitations. The hospital has to decide if a patient is accepted as an inpatient or suggested to home quarantine. In such a case, the admission control problem can also be solved by the methodologies in the paper. [ABSTRACT FROM AUTHOR]

Once China abandoned its “zero-tolerance” policy of dealing with COVID-19, the disease spread like wildfire across China in December 2022 and January 2023, affecting a majority of China’s population. Acupuncture intervention in COVID-19 and post COVID-19 symptoms varied over time and across the country, from minimal use in 2020 to frontline engagement by 2023. As early as February 2020, the China Acupuncture and Moxibustion Association issued the document “Guidelines on Acupuncture and Moxibustion Intervention for COVID-19.” Since then, there has been sporadic publication of case histories, observational studies, and clinical trials in medical journals. By now, a pipeline of proposed systematic reviews is lined up that will document the history of acupuncture intervention for COVID-19 infection and post COVID symptom treatment. Rigorous clinical studies of acupuncture intervention for COVID-19 and long COVID are still very scanty, although pioneering efforts have been emerging. This paper attempts to document the trajectory of acupuncture intervention for COVID-19 through January, 2023. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease (SARS-CoV-2) has caused many infections and deaths throughout the world; the spread of the coronavirus pandemic is still ongoing and continues to affect healthcare systems and economies of countries worldwide. Mathematical models are used in many applications for infectious diseases, including forecasting outbreaks and designing containment strategies. In this paper, we study two types of SIR and SEIR models for the coronavirus. This study focuses on the discrete-time and fractional-order of these models; we study the stability of the fixed points and orbits using the Jacobian matrix and the eigenvalues and eigenvectors of each case; moreover, we estimate the parameters of the two systems in fractional order. We present a statistical study of the coronavirus model in two countries: Saudi Arabia, which has successfully recovered from the SARS-CoV-2 pandemic, and China, where the number of infections remains significantly high. [ABSTRACT FROM AUTHOR]

COVID-19 has caused major disruptions to agricultural supply chains around the world. Researchers and policy-makers are interested in identifying means to reduce the disruptive effects caused by the pandemic. We investigate the impacts of COVID-19 on the operation of e-commerce stores (in short, e-stores) specialising in agricultural inputs. The difference-in-differences method (DID) is employed to estimate the causal relationship between COVID-19 and online sales of agricultural inputs using data from 54,244 agricultural input e-stores registered in 118 prefecture-level cities across 15 provinces and hosted on two major Chinese e-commerce platforms. The results show that COVID-19 led to a substantial growth in monthly sales of agricultural input e-stores, and this growth of online sales varied across store scales and by types of agricultural inputs. In particular, e-stores selling seeds and seedlings experienced a larger growth in sales than stores selling agricultural machinery and implements, and the mid-and larger-scaled e-stores experienced more growth of sales than micro-and small-scaled e-stores. Further analysis reveals that the growth of online sales of agricultural inputs was driven mainly by an increase in the quantity of customer orders (QCO). The findings of this paper underscore the importance of e-commerce in ensuring the resilience of the agricultural supply chain during the pandemic period. [ABSTRACT FROM AUTHOR]

The mutant strains of COVID-19 caused a global explosion of infections, including many cities of China. In 2020, a hybrid AI model was proposed by Zheng et al., which accurately predicted the epidemic in Wuhan. As the main part of the hybrid AI model, ISI method makes two important assumptions to avoid over-fitting. However, the assumptions cannot be effectively applied to new mutant strains. In this paper, a more general method, named the multi-weight susceptible-infected model (MSI) is proposed to predict COVID-19 in Chinese Mainland. First, a Gaussian pre-processing method is proposed to solve the problem of data fluctuation based on the quantity consistency of cumulative infection number and the trend consistency of daily infection number. Then, we improve the model from two aspects: changing the grouped multi-parameter strategy to the multi-weight strategy, and removing the restriction of weight distribution of viral infectivity. Experiments on the outbreaks in many places in China from the end of 2021 to May 2022 show that, in China, an individual infected by Delta or Omicron strains of SARS-CoV-2 can infect others within 3–4 days after he/she got infected. Especially, the proposed method effectively predicts the trend of the epidemics in Xi'an, Tianjin, Henan, and Shanghai from December 2021 to May 2022. [ABSTRACT FROM AUTHOR]

As infected and vaccinated population increases, some countries decided not to impose non-pharmaceutical intervention measures anymore and to coexist with COVID-19. However, we do not have a comprehensive understanding of its consequence, especially for China where most population has not been infected and most Omicron transmissions are silent. This paper aims to reveal the complete silent transmission dynamics of COVID-19 by agent-based simulations overlaying a big data of more than 0.7 million real individual mobility tracks without any intervention measures throughout a week in a Chinese city, with an extent of completeness and realism not attained in existing studies. Together with the empirically inferred transmission rate of COVID-19, we find surprisingly that with only 70 citizens to be infected initially, 0.33 million becomes infected silently at last. We also reveal a characteristic daily periodic pattern of the transmission dynamics, with peaks in mornings and afternoons. In addition, by inferring individual professions, visited locations and age group, we found that retailing, catering and hotel staff are more likely to get infected than other professions, and elderly and retirees are more likely to get infected at home than outside home. Author summary: Since 2019, we have witnessed the worldwide battle against COVID-19. As infected and vaccinated population increases, some countries chose not to impose any non-pharmaceutical measures and to live with COVID-19. In the literature, an extensive effort has been made to understand the effectiveness of intervention measures against COVID-19 and to predict its prevalence, but much less is known about the risk of choosing to coexist with COVID-19. Here, we conduct agent-based simulations overlaying a high-frequency mobility big data which records individual mobility tracks up to every second in a large-scale city in northern China, revealing the comprehensive transmission dynamics from a few initial infected individuals to city-wise infections. Such comprehensive understanding will provide useful insights into our battle against COVID-19. [ABSTRACT FROM AUTHOR]

Background: Since the coronavirus disease 2019 (COVID-19) pandemic outbreak, the incidence of mental health problems in perinatal women has been high, and particularly prominent in China which was the first country affected by COVID-19. This paper aims to investigate the current situation and the related factors of maternal coping difficulties after discharge during COVID-19. Methods: General information questionnaires (the Perinatal Maternal Health Literacy Scale, Postpartum Social Support Scale and Post-Discharge Coping Difficulty Scale-New Mother Form) were used to investigate 226 puerperal women in the third week of puerperium. The influencing factors were analyzed by single factor analysis, correlation and multiple linear regression. Results: The total score of coping difficulties after discharge was 48.92 ± 12.05. At the third week after delivery, the scores of health literacy and social support were 21.34 ± 5.18 and 47.96 ± 12.71. There were negative correlations among health literacy, social support and coping difficulties after discharge (r = -0.34, r = -0.38, P < 0.001). Primipara, family income, health literacy and social support were the main factors influencing maternal coping difficulties after discharge. Conclusion: During the COVID-19 pandemic, puerperal women in a low- and middle-income city had moderate coping difficulties after discharge and were affected by many factors. To meet the different needs of parturients and improve their psychological coping ability, medical staff should perform adequate assessment of social resources relevant to parturients and their families when they are discharged, so they can smoothly adapt to the role of mothers. [ABSTRACT FROM AUTHOR]

In the practice of COVID-19 prevention and control in China, the home quarantine policy directly connects and manages the residents, which plays a significant role in preventing the spread of the epi-demic in the community. We evaluate the effectiveness of current home quarantine policy in the actual execution process based on the evolutionary game relationship between the community and res-idents. This paper establishes a double-layer coupled complex network game model, and uses the multi-agent modeling method to study the game relationship between the community and residents in the context of home quarantine policies. The results show that initial strategy of the community with strict supervision and reasonable government reward allocation will increase the proportion of the residents complying with the quarantine rule. When 80% of the communities chose to supervise strictly at the beginning, people are more likely to follow the rules. While when the residents can only get 20% of the government's reward, the proportion of choosing to violate the quarantine rules is much higher than that when they can get 80% of the reward. Besides, the structure of small-world network and environmental noise will also affect the residents' strategy. As the probability of reconnection of the small-world network rises from 0.2 to 0.8, the proportion of residents who choose to comply with the strategy becomes much higher. When the environmental noise reaches 0.5, the ratio of residents who choose to violate the strategy is higher than the ratio of complianc. The study is helpful to provide the basis for the government to formulate the quarantine policy and propose an optimization for making effective quarantine measures. In this way, the government can adjust the parameters to make residents achieve the possible level of compliance with quarantine policies as high as possible to contain the spread of the epidemic. [ABSTRACT FROM AUTHOR]

In this paper, a SEIR epidemic model related to media coverage and exogenous reinfections is established to explore the transmission dynamics of COVID-19. The basic reproduction number is calculated using the next generation matrix method. First, the existence of equilibrium points is investigated, and different kinds of equilibrium points indicate that the disease may disappear, or exist that result in different quantity of susceptible individuals, pre-symptomatic infected individuals and symptomatic infected individuals. The stability of the equilibria is discussed by a geometric approach, and it is found that controlling reproduction number to be lower than 1 is not sufficient for eradication of COVID-19. Second, transcritical bifurcation is explored, and it is found that improving the ratio of exogenous reinfection may lead to backward bifurcation under poor medical conditions, which indicates that two endemic equilibrium points appear. Third, to investigate the influence of parameters on the basic reproduction, sensitivity analysis is done to choose relatively sensitive parameters, and the parameters for treatment and media coverage are selected. An optimal control model is established to balance the treatment and media awareness. By exploring the existence and the uniqueness of the optimal control solution, the optimal control strategies are given. Finally, we run numerical simulations to verify the theoretical analysis on actual data of China, and the data from the four different states of India is used for forecasting the situation of infected individuals in a short period. It is found by the simulation that the co-function of treatment and media coverage results in the reduced number of infectious individuals. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been ongoing for more than three years and urgently needs to be addressed. Traditional Chinese medicine (TCM) prescriptions have played an important role in the clinical treatment of patients with COVID-19 in China. However, it is difficult to uncover the potential molecular mechanisms of the active ingredients in these TCM prescriptions. In this paper, we developed a new approach by integrating the experimental assay, virtual screening, and the experimental verification, exploring the rapid discovery of active ingredients from TCM prescriptions. To achieve this goal, 4 TCM prescriptions in clinical use for different indications were selected to find the antiviral active ingredients in TCMs. The 3-chymotrypsin-like protease (3CLpro), an important target for fighting COVID-19, was utilized to determine the inhibitory activity of the TCM prescriptions and single herb. It was found that 10 single herbs had better inhibitory activity than other herbs by using a fluorescence resonance energy transfer (FRET) - based enzymatic assay of SARS-CoV-2 3CLpro. The ingredients contained in 10 herbs were thus virtually screened and the predicted active ingredients were experimentally validated. Thus, such a research strategy firstly removed many single herbs with no inhibitory activity against SARS-CoV-2 3CLpro at the very beginning by FRET-based assay, making our subsequent virtual screening more effective. Finally, 4 active components were found to have stronger inhibitory effects on SARS-CoV-2 3CLpro, and their inhibitory mechanism was subsequently investigated. Among of them, methyl rosmarinate as an allosteric inhibitor of SARS-CoV-2 3CLpro was confirmed and its ability to inhibit viral replication was demonstrated by the SARS-CoV-2 replicon system. To validate the binding mode via docking, the mutation experiment, circular dichroism (CD), enzymatic inhibition and surface plasmon resonance (SPR) assay were performed, demonstrating that methyl rosmarinate bound to the allosteric site of SARS-CoV-2 3CLpro. In conclusion, this paper provides the new ideas for the rapid discovery of active ingredients in TCM prescriptions based on a specific target, and methyl rosmarinate has the potential to be developed as an antiviral therapeutic candidate against SARS-CoV-2 infection. • This paper explores the rapid discovery of the active ingredients from TCMs. • TCM prescriptions were selected to find anti-SARS-CoV-2 3CLpro active ingredients. • Methyl rosmarinate is an allosteric inhibitor of SARS-CoV-2 3CLpro. [ABSTRACT FROM AUTHOR]

Aims: This study aimed to describe the experiences of nurses and other health care workers who were infected with coronavirus disease 2019. Methods: An empirical phenomenological approach was used. Sixteen participants were recruited in Wuhan using purposive and snowball sampling. Semistructured, in‐depth interviews were conducted by telephone in February 2020. Interviews were transcribed verbatim and analysed following Colaizzi's method. Results: Two themes emerged: (1) Intense emotional distress since becoming infected. Participants were fearful of spreading the virus to family and overwhelmed by a lack of information, experienced uncertainty and worried about treatment, felt lonely during isolation and reported moral distress about inadequate health care staffing. (2) Coping strategies were needed. They tried their best to address negative psychological reactions using their professional knowledge and gaining support from others and community resources. Conclusions: Preparedness for catastrophic events and providing timely and accurate information are major considerations in government policy development, related to pandemics and adequacy of health care personnel. Mental health resources and support, both short‐ and long‐term should be anticipated for health care providers to alleviate their fear and anxiety. Summary statement: What is already known about this topic? Health care workers, including nurses, are at the frontlines of the COVID‐19 outbreak and at high risk of infection.Experts have called for infection prevention for health care providers.Limited research has reported the experiences of health care workers infected by COVID‐19 using an empirical phenomenological approach. What this paper adds? Upon diagnosis, nurses and other health care workers experienced fear, uncertainty and distress like general patients.Health care workers reported moral distress about inadequate health care staffing issues.Health care workers could cope with their negative psychological reactions using professional knowledge and support from significant others and the community. The implications of this paper: Preparedness for large‐scale pandemics and a system that can provide openness and timely information needs consideration in policy development.Accurate information and good communication are vital to support infected health care workers and enhance their sense of safety and belonging.Long‐term support should be available when these health care workers return to work. [ABSTRACT FROM AUTHOR]

The new development concept is the theoretical guidance and important foundation for high-quality foreign trade development in the new era. This paper develops an evaluation index system to measure the high-quality development level of foreign trade based on the meaning of high-quality development of foreign trade under the new concept of development. The dynamic changing trend of high-quality development of China's provincial foreign trade from 2013 to 2019 and the ranking change of the development index are examined in this paper using a time series factor model. Finally, China's provinces are categorized based on the quality of their foreign trade development. The findings show that, from 2013 to 2019, China's high-quality foreign trade development has been on the rise; the level of high-quality foreign trade development has been raised to varying degrees in the eastern, central, and western regions of China, but each region plays a different role. Compared to 2013, the truly "high-quality" areas of China's provincial foreign trade development were always concentrated in the eastern region, which ranked high on the comprehensive evaluation index, while the "low-quality" areas were mainly concentrated in the central and western regions, which ranked low on the comprehensive evaluation index. [ABSTRACT FROM AUTHOR]

Epidemics and other public health emergencies significantly impact medical and health service systems. The exploitation of some advanced technologies in Fangcang shelter hospitals—emergency medical service solutions adopted in China during the Corona Virus Disease 2019 (COVID-19) epidemic—was found to successfully relieve the treatment pressures. However, the implementation of the intelligent Fangcang shelter hospital system remains in the exploratory stage. Herein, this paper aims to obtain experience in the development and utilization of an intelligent system in a Fangcang shelter hospital. To achieve this, a single case study method was adopted to analyze a real case in the Optics Valley Fangcang Shelter Hospital. There were two data collection methods in the case study: (1) interviews; and (2) investigation, including some documents, models, sensors, and the platform. The main contribution of this paper is that it provides qualitative insights on how to implement an intelligent Fangcang shelter hospital system, including the development process and challenges and identifying lessons learned through the utilization of intelligent Fangcang shelter hospital systems. This paper can give a solid reference for the operation of COVID-19 field hospitals and provide clear theoretical guidance for the implementation and development of intelligent Fangcang shelter hospitals. This will help better respond to COVID-19 and similar major public health emergencies in the future. [ABSTRACT FROM AUTHOR]

Objectives: The study presents a bibliometric assessment of COVID-19 vaccine research publications to understand the current and up-to-date scenario of COVID-19 vaccine research and to track important research players and identify the current areas. Materials and Methods: The global literature on COVID-19 vaccine research published during 2020 were searched in the Scopus database, using the keywords “COVID-19 vaccine” or “Coronavirus 19 vaccine” on 12 September 2020. The 343 global records on COVID-19 vaccine research were obtained which received 2636 citations and were published in 66 countries involving 280 organizations, 259 authors and 191 journals. The publication records obtained were statistically analyzed by using various bibliometric indices: document type, country, collaboration patterns, affiliation, journal name, and citation patterns. Results: Among top 12 countries, USA, U.K and China were the most productive and China, South Korea and USA were the most impactful. Nearly 51% publications of these top 12 countries were international collaborative. The top most productive organizations were Harvard Medical School, USA (12 papers), University of Washington, Seattle, USA (10 papers) and Fudan University, China (with 12, 10 and 8 papers. Th. top most impactful organizations in terms of citation per paper and relative citation index were Tongji Medical College, China (56.0 and 7.28), Shanghai Medical College, China (33.2 and 4.32) and Chinese Center for Disease Control and Prevention, China (23.5 and 3.06). The most productive journals were Nature, Science and Vaccine (24, 18 and 18 papers each) and the most impactful journals in terms of citations per paper were: Journal of Medical Virology (66.5), Cell (27.2) and New England Journal of Medicine (23.4). Conclusion: This results and findings emerging from the study shed new light on the major progress in the present time on hot topics on COVID-19 vaccine research. [ABSTRACT FROM AUTHOR]

Flows are usually represented as vector lines from origins to destinations and can reflect the movements of individuals or groups in space and time. Revealing and analyzing the spatiotemporal flow patterns are conducive to understanding information underlying movements. This paper proposes a new method called the OD – EOF (Origin – Destination – Empirical Orthogonal Function) to discover important spatiotemporal flow patterns on the premise of maintaining the pairwise connections between origins and destinations. We first construct a spatiotemporal flow matrix that contains connection information between origins and destinations and temporal flow information by adding a temporal dimension to the OD map. Then, we decompose the spatiotemporal flow matrix into spatial modes and corresponding time coefficients by EOF decomposition. The decomposition results depict the prominent spatial distribution of and temporal variation in flows, with most of the spatiotemporal characteristics highly concentrated into the first few spatial modes. The method is evaluated by five synthetic datasets and a user study and subsequently applied to analyze the impact of the COVID-19 pandemic on the spatiotemporal patterns of human mobility in China during the Spring Festival travel rush in 2020 and 2021. The results show the prominent spatiotemporal patterns of human mobility during these periods under the influence of the COVID-19 pandemic outbreak and the normalization of pandemic prevention and control. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) had spread from China and, within 2 months, became a global pandemic. The infection from this disease can cause a diversity of symptoms ranging from asymptomatic to severe acute respiratory distress syndrome with an increased risk of vascular hyperpermeability, pulmonary inflammation, extensive lung damage, and thrombosis. One of the host defense systems against coronavirus disease 2019 (COVID‐19) is the formation of neutrophil extracellular traps (NETs). Numerous studies on this disease have revealed the presence of elevated levels of NET components, such as cell‐free DNA, extracellular histones, neutrophil elastase, and myeloperoxidase, in plasma, serum, and tracheal aspirates of severe COVID‐19 patients. Extracellular histones, a major component of NETs, are clinically very relevant as they represent promising biomarkers and drug targets, given that several studies have identified histones as key mediators in the onset and progression of various diseases, including COVID‐19. However, the role of extracellular histones in COVID‐19 per se remains relatively underexplored. Histones are nuclear proteins that can be released into the extracellular space via apoptosis, necrosis, or NET formation and are then regarded as cytotoxic damage‐associated molecular patterns that have the potential to damage tissues and impair organ function. This review will highlight the mechanisms of extracellular histone‐mediated cytotoxicity and focus on the role that histones play in COVID‐19. Thereby, this paper facilitates a bench‐to‐bedside view of extracellular histone‐mediated cytotoxicity, its role in COVID‐19, and histones as potential drug targets and biomarkers for future theranostics in the clinical treatment of COVID‐19 patients. [ABSTRACT FROM AUTHOR]

This paper studies the impact of urban density, city government efficiency, and medical resources on COVID‐19 infection and death outcomes in China. We adopt a simultaneous spatial dynamic panel data model to account for (i) the simultaneity of infection and death outcomes, (ii) the spatial pattern of the transmission, (iii) the intertemporal dynamics of the disease, and (iv) the unobserved city‐specific and time‐specific effects. We find that, while population density increases the level of infections, government efficiency significantly mitigates the negative impact of urban density. We also find that the availability of medical resources improves public health outcomes conditional on lagged infections. Moreover, there exists significant heterogeneity at different phases of the epidemiological cycle. [ABSTRACT FROM AUTHOR]

As China's economy and the U.S. economy have shown a definite interaction, there is considerable interest in studying the correlation between the Chinese stock market and the US financial markets. This paper uses an Asymmetric Dynamic Conditional Correlation (ADCC)-GARCH to investigate the correlation between the Shanghai Composite Index (SHCI) and the U.S. financial markets, including SP500, NASDAQ, and US dollar indexes. The empirical results show that the time-varying daily and the lag-one correlation between China and the US stock markets have different performances during global events and national events. Compared with the complicated effect of negative events on the correlation of the stock market, SHCI and USD are negatively correlated with higher negative correlation during the global negative events. In addition, we found Chinese investors are more contagious to the news than American investors, indicating that the Chinese government's policy are more indicated to Chinese investors. Finally, some policy suggestions are provided, and are beneficial to risk prevention and control, and investment. [ABSTRACT FROM AUTHOR]

This paper aims to examine the time-varying dynamics of the causal interaction between agricultural raw materials commodity prices and the US economic policy uncertainty (EPU). To this end, we use monthly data for the period spanning from January 1992 to November 2021. We employ a time-varying Granger causality test to provide empirical evidence on the time-varying dynamics of the causality interaction and thereby revealing potential heterogeneities of these interactions during major historical events. The results show that causality running from EPU to agricultural raw materials, as well as causality running from agricultural raw materials to EPU, exhibits time-varying dynamics. More specifically, the findings reveal that causality generally tended to run from agricultural raw materials to EPU for most of the 2000-2014 period but reversed with the US-China trade war and the Covid-19 pandemic period. This result highlights the importance of modeling the potential causality interactions in the economic uncertainty-commodity prices nexus within a dynamic framework and implies that these interactions cannot be considered independently of the prevailing economic, political and global conditions. [ABSTRACT FROM AUTHOR]

This paper applies a three-step framework to quantify COVID-19's impacts on China's domestic and international air travel demand and to evaluate how the impacts evolve from January 2020 to January 2022. Time series techniques and combination forecasting are tested to identify the best-performing model to generate baseline forecasts, with which actual demands are compared to assess the impact of COVID-19. The results demonstrate that during the period under study, China's domestic aviation sector experienced two V-shape recoveries, while its international counterpart was devastated and showed no sign of revival. It suggests that to mitigate the impact of COVID-19, containing virus spread and removing mobility controls are essential; and when travel restrictions are lifted or loosened, governments play important roles in accelerating the rate of demand recovery. [ABSTRACT FROM AUTHOR]

Uncertain regression model is a powerful analytical tool for exploring the relationship between explanatory variables and response variables. It is assumed that the errors of regression equations are independent. However, in many cases, the error terms are highly positively autocorrelated. Assuming that the errors have an autoregressive structure, this paper first proposes an uncertain regression model with autoregressive time series errors. Then, the principle of least squares is used to estimate the unknown parameters in the model. Besides, this new methodology is used to analyze and predict the cumulative number of confirmed COVID-19 cases in China. Finally, this paper gives a comparative analysis of uncertain regression model, difference plus uncertain autoregressive model, and uncertain regression model with autoregressive time series errors. From the comparison, it is concluded that the uncertain regression model with autoregressive time series errors can improve the accuracy of predictions compared with the uncertain regression model. [ABSTRACT FROM AUTHOR]

In the wake of COVID-19, mental health providers and treatment programs are adapting rapidly to the challenges in engaging people and delivering treatment with limited guidance. This paper will explore the challenges associated with delivering treatment within coordinated specialty care (CSC) programs for people with first episode psychosis. Suggestions for treatment will take into consideration experiences with stress, changes to the pursuit of work and school, and increased time spent with families. Drawing on the experience of several CSC programs in the United States, Israel, and China, we describe the impact and modifications to the core treatment elements in CSC including medication, family interactions, supported employment and education, individual therapy, peer support and the way they are delivered. The paper includes recommendations based on experiences from CSC programs to help staff members, participants, and family members better identify, prepare, cope and respond to the unique new challenges and suggests modifications that can be made during various stages of the coronavirus pandemic. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to report and analyze the lessons learnt from a case study of the implementation of the move from onsite to online learning at a Sino-Foreign higher education institution. Design/methodology/approach: This paper reports a case study based on an analysis of three elements of the move to digital education during the COVID-19 pandemic. In suggesting three elements, it argues that the first and most immediate move away from onsite teaching should be thought of as emergency response teaching, and it is the lessons learnt from this vital and necessary stage that have informed the subsequent implementation of a more digitalization process. Findings: The case study identifies the journey that the university is going through to deliver digitalized education, and how the pandemic hastened what had already been started. It illustrates how the pandemic has been useful in highlighting where we are, what decisions have been made and what still needs to be done with regard to readiness for the disruption likely by Industry 4.0. Research limitations/implications: The study was conducted at one institution, which along with eight other similar institutions is unique within China. Findings, especially the processes of making decisions, while relevant to the wider discussion on digitalization and Industry 4.0, should also be considered in this light. Practical implications: While the focus of the paper is on COVID-19 and Rapid Digitalization of Learning and Teaching, the main implication is that universities need to better prepare their teaching staff for digitalized education, especially if they are wanting to engage with disruption brought about by Industry 4.0. Originality/value: The paper is based on a single university case study of a rather unique university within China. The discussion illustrates the need for flexibility and decisiveness in making key decisions on managing disruption, but with strategic direction in mind, illustrated in the study by COVID-19, but with future digitalization initiatives also to the fore. [ABSTRACT FROM AUTHOR]

Since the infectious coronavirus disease (COVID-19) was first reported in Wuhan, it has become a public health problem in China and even around the world. This pandemic is having devastating effects on societies and economies around the world. The increase in the number of COVID-19 tests gives more information about the epidemic spread, which may lead to the possibility of surrounding it to prevent further infections. However, wearing a face mask that prevents the transmission of droplets in the air and maintaining an appropriate physical distance between people, and reducing close contact with each other can still be beneficial in combating this pandemic. Therefore, this research paper focuses on implementing a Face Mask and Social Distancing Detection model as an embedded vision system. The pretrained models such as the MobileNet, ResNet Classifier, and VGG are used in our context. People violating social distancing or not wearing masks were detected. After implementing and deploying the models, the selected one achieved a confidence score of 100%. This paper also provides a comparative study of different face detection and face mask classification models. The system performance is evaluated in terms of precision, recall, F1-score, support, sensitivity, specificity, and accuracy that demonstrate the practical applicability. The system performs with F1-score of 99%, sensitivity of 99%, specificity of 99%, and an accuracy of 100%. Hence, this solution tracks the people with or without masks in a real-time scenario and ensures social distancing by generating an alarm if there is a violation in the scene or in public places. This can be used with the existing embedded camera infrastructure to enable these analytics which can be applied to various verticals, as well as in an office building or at airport terminals/gates. [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]

Objective: COVID-19, a contagious disease which is caused by novel coronavirus (SARS-CoV-2), is still spreading globally. Bibliometric analyses assess the current status and trends in a spesific research domain by using several (Scopus, PubMed, Web of Science) databases. The aim of present study is to evaluate the scientific activities in the first year of the COVID-19 pandemic on scientific output. Method: Web of Science software was used for the search and the analysis. All scientific papers published about COVID-19 included in Science Citation Index Expanded (SCI-E) from January 1st to December 13th 2020; the date of the study, were searched by using the terms of "COVID-19", "2019-n-CoV", "SARS-CoV-2", "Coronavirus disease 19" and "2019 novel coronavirus" as scientific nomenclatures of COVID-19 in the topic search section of the software. Results:Overall; 47368 scientific papers related to COVID-19, indexed by SCI-E, were found related to COVID-19 between January 1, 2020 to December 13, 2020. The biggest contribution for publications was from United States of America, the most of the publications was articles, the authors that contribute to the literature = 150 papers were all from China and the journal that published the most paper was British Medical Journal. Conclusions: The present analyse reports an overview of the literature on COVID-19 since the beginning. These kind of periodic analysis provides interesting insights regarding the past and progress of each area of scientific knowledge and also can guide the rethinking of scientific data. [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 context of the global pandemic of COVID-19, with the epidemic epicenter located in the Wuhan City, China, patients with severe mental illness have also been deeply affected by the epidemic. In this paper, two patients with schizophrenia who recovered from COVID-19 were reported. Because of the long-term positive results of the SARS-CoV-2 serum antibody IgM test, they had to undergo medical isolation and social restrictions for a long time. After the situation was effectively identified by the medical staff and they were eliminated as a potential virus carrier and released from the medical isolation center. Since psychiatrists often lack systematic knowledge of infectious diseases, the authors hope that this paper can provide a reference to avoid unnecessary wastage of medical resources and prevent placing serious mental burden on such patients in the future. [ABSTRACT FROM AUTHOR]

The rate of infectious disease outbreaks has been accelerating over the past two decades, from the SARS epidemic in 2003 to COVID-19 in 2020. Termed by some as the twenty-first century's first pandemic, SARS originated in China and alerted the country to the importance of public health and epidemic response. After SARS, China improved its health infrastructure and reformed its political and legal health governance system. The emergence of COVID-19 from Wuhan in late 2019 put those reforms to the test. This paper analyses China's public health and epidemic response policies from a historical perspective, tracing the evolution of Chinese public health policies after the SARS outbreak in 2003. This paper assesses China's response to COVID-19 and how post-SARS policy reforms, particularly in epidemic response, played out on the ground in Wuhan. What policies worked well? What were the challenges faced? Based on the policy analysis, this paper presents recommendations for how China can improve its epidemic response through strengthened infectious disease surveillance, more transparent political coordination, and expanded public health infrastructure. [ABSTRACT FROM AUTHOR]

To support young children's learning during the coronavirus 2019 (COVID‐19) pandemic, preschool educators in Hong Kong were required to teach with digital technologies. In this study, 1035 educators from 169 preschools reported their views and practices in an online survey, which we examined via multilevel mixed‐response analysis and thematic analysis. More than half of the respondents (53%) expected future online teaching to continue, and only 11% of educators believed that parents would reject this form of delivery. Administrators and teaching assistants were more likely than teachers to expect online preschool teaching to continue in the future. In addition, respondents with existing online platform experience, who taught the upper levels of preschool, or incorporated specific teaching practices (eg, after the online lesson, they assessed children and assigned homework tasks), were more likely than others to expect online teaching in the future. Many of these respondents also reported (a) difficulty with engaging their children when online and (b) inadequate support from parents for learning activities, which reduced the respondents' perceived likelihood of future online teaching. Administrators and teaching assistants were more likely than teachers to believe that parents would accept online teaching in the future. Respondents who felt they had inadequate training to teach online, children in families with inadequate technical skills and parents who believed that online lessons harmed children's well‐being, were less likely than others to believe that parents would accept online teaching in the future. These educators believed that online learning communities could connect parents and schools and foster interaction that could help align with educator's support for children's learning needs. Practitioner notesWhat is already known about technology integration for young children during COVID‐19COVID‐19 led to the closure of many schools, requiring teachers to teach online.Barriers to integrating technologies in preschool settings existed before the pandemic.Online teaching can support students' learning, but few studies have examined technology integration for preschoolers at home during a pandemic.What this paper addsThis paper adds new data on schooling during a pandemic. During the closures, preschool teachers applied two major online teaching approaches: (a) digital content interaction and (b) online human interaction.Technology integration was added to provide evidence of how teachers applied online learning resources for young children during COVID‐19.During closures, teachers often delivered learning resources via digital‐mediated learning platforms, but they were less likely than other educators to expect online teaching in the future.Educators who perceived greater engagement of children or support from parents were more likely to expect online teaching in the future.Implications for practice and/or policyThis study showed that some preschool teachers integrated technology into their teaching during a pandemic, and future studies can explore how to facilitate or extend this integration after the pandemic.This study showed the need for more interactive online teaching preparation to address young children's learning needs.Some teachers were responsive to feedback from children and monitored their learning during the online teaching process. [ABSTRACT FROM AUTHOR]