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A better understanding of various patterns in the coronavirus disease 2019 (COVID-19) spread in different parts of the world is crucial to its prevention and control. Motivated by the previously developed Global Epidemic and Mobility (GLEaM) model, this paper proposes a new stochastic dynamic model to depict the evolution of COVID-19. The model allows spatial and temporal heterogeneity of transmission parameters and involves transportation between regions. Based on the proposed model, this paper also designs a two-step procedure for parameter inference, which utilizes the correlation between regions through a prior distribution that imposes graph Laplacian regularization on transmission parameters. Experiments on simulated data and real-world data in China and Europe indicate that the proposed model achieves higher accuracy in predicting the newly confirmed cases than baseline models. [ABSTRACT FROM AUTHOR]

Aim: We aim to investigate the prevalence and associated factors for compassion fatigue among nurses in Fangcang Shelter Hospitals in Wuhan. Studies have shown that compassion fatigue was more common among nurses than other health‐care providers, and its predictors were also different. In recent years, most studies have investigated compassion fatigue in emergency and oncology nurses, whereas there is little information on compassion fatigue among nurses from the frontline of Fangcang Shelter Hospitals during the COVID‐19 pandemic. Methods: A descriptive, cross‐sectional design was used in this study. An online survey was conducted among nurses (n = 972) of five Fangcang Shelter Hospitals in Wuhan, Hubei province, China, from 6 March to 10 March 2020. A self‐administered questionnaire including demographic information, work‐related information, General Health Questionnaire, Perceived Stress Scale and Compassion Fatigue Scale was used. Results: The prevalence of compassion fatigue among nurses in Fangcang Shelter Hospitals was moderate, and most cases were mild. There was a significant relationship between compassion fatigue and work‐related factors, mental health and perceived stress among nurses working in Fangcang Shelter Hospitals. Conclusions: Various factors contribute to compassion fatigue, including lower job satisfaction and job adaptability, less praise from patients, more fear of infection and more perceived stress. A good working atmosphere, organizational support and psychological consultation are essential to alleviate nurses' compassion fatigue during the anti‐epidemic period. Summary statement: What is already known about this topic? Nurses are particularly vulnerable to compassion fatigue among health‐care providers, and it causes billions of dollars in productivity losses to economies in different countries every year.Personal factors (professional cognition, health condition, gender etc.), working environment (working hours, working load, working system problems, professional roles etc.), mental health and stress may affect nurses' compassion fatigue. What this paper adds? Both extrinsic and intrinsic factors played a crucial role in nurses in Fangcang Shelter Hospitals who are exposed to adverse events, leading to compassion fatigue. The implications of this paper: This paper reveals a new perspective on the factors influencing compassion fatigue of nurses working in Fangcang Shelter Hospitals.We suggest that compassion fatigue among nurses in Fangcang Shelter Hospitals could be reduced by maintaining a good working atmosphere, providing organizational support, helping nurses keep a healthy mental state and reducing stress levels. [ABSTRACT FROM AUTHOR]

Aim: To investigate the current condition and degree of fear of disease progression and associated factors in patients with mild or common type COVID‐19. Background: At the end of 2019, COVID‐19 spread from Wuhan in Hubei Province throughout China. Confirmed cases and deaths have since been reported in many countries around the world. However, fear of progression in these patients has been poorly explored. Methods: During February 2020, we recruited 114 patients with mild or common type COVID‐19 admitted to a Fangcang shelter hospital. We assessed patients' degree of fear using the simplified Fear of Progression Questionnaire (Chinese version). Multiple regression analysis was applied to explore potential factors. Results: The fear of disease progression scores of patients with mild or common COVID‐19 was at the low‐to‐moderate level. Current unemployment, disease duration of 28 days or more and not having a spouse diagnosed with COVID‐19 were factors potentially associated with fear of progression. Conclusion: With a high prevalence of fear of disease progression in patients with COVID‐19, the risk of psychological effects from the pandemic is significant and fear of progression is one of the manifestations. The need for psychological support services for patients should be included in all pandemic and disaster planning. Summary statement: What is already known about this topic? Fear of progression is a common bio‐socio‐psychological consequence that widespread in cancer patients as well as chronic diseases.Very few studies focus on fear of progression in patients with major infectious disease, not to mention coronavirus disease (COVID‐19). What this paper adds? The present study surveys fear of progression in patients with mild or common type COVID‐19 and revealed a low‐to‐moderate level overall.Being unemployed, having no spouse diagnosed with COVID‐19, and a disease duration of 28 days or more are potential factors associated to patients' fear of the disease progression. The implications of this paper: The COVID‐19 outbreak has been declared as a public health emergency of international concern. Mental health problems such as fear of disease progression might need more attention beyond medical treatment.Future mental health nursing practice and research need to focus on those potential factors or patients with specific characteristics. [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]

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]

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]

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]

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]

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 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 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]

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]

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]

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]

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]

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]

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]

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 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]

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]

The impact investing literature largely focuses on private equity investing and overlooks the investments made through debt financing that actually dominate the market. To address this research gap, this paper investigates whether impact financing is associated with financial benefits. By using COVID-19 as an exogenous shock to China's stock market, this paper applies fixed effects panel data analysis with a difference-in-differences research design to provide robust empirical outcomes. The results reveal those financial institutions that better integrated environmental impacts into their financing process experienced positive stock return changes in response to the shock. This study answers the question of how well an impact scales. The findings suggest that impact financing is an effective model, as the impacts incorporated in the debt can be scaled up compared to impact investing funds with low volumes. Impact financing has enormous potential for financial institutions to engage in the green transition since they can derive pecuniary utility while delivering environmental impacts. The revelation of financial benefits also contributes to overcoming the lack of knowledge about impact financing and helps to remove the barriers that advance industry growth. • This paper studies whether impact financing is associated with financial benefits. • Financial firms that better integrate environmental impact in financing have positive stock return changes during COVID-19. • Financial firms can derive pecuniary utility from pursuing impact financing. • The findings suggest that impact financing can be an effective model to bring impact to a substantial scale. [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]

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]

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]

Background: COVID-19 has raised many concerns about the possible side effects of pregnancy. There is currently no conclusive evidence of the vertical transmission of COVID-19. Accordingly, this paper is a Systematic Review and Meta-Analysis investigated neonatal outcomes among pregnant women with COVID-19. Methods: PubMed, Web of Science (WoS), EMBASE, ProQuest, Scopus, and Google Scholar were searched up to November 2020. The Cochran’s Q-test and I 2 statistic were applied to assess heterogeneity, a random-effects model was used to estimate the pooled estimate of the mean, and a meta-regression method was utilized to investigate the factors affecting heterogeneity between studies. Results: Of 1132 studies, 23 were included in the analysis (sample size: 749 for neonates and 820 for mothers). Most of these studies (n = 13) were conducted in China. The pooled estimate for the mean of birth weight, APGAR score in min 1 and 5 was 3084.97 g (95% CI: 2993.66–3176.29), 8.76 (95% CI: 8.27–9.25), and 9.44 (95% CI: 9.18–9.70), respectively. Also, the pooled prevalence of premature birth, shortness of breath, and neonatal death was 17.80% (95% CI: 12.47–23.13), 8.43% (95% CI: 4.50–12.37), and 7.73% (95% CI: 2.00–13.47), respectively. The meta-regression results indicated that the mother’s age, disease duration, and sample size had no significant effect on heterogeneity between studies (p-value all of them was >.05). Finally, 15 studies (65.22%) reported that vertical transmission did not occur. Conclusion: The COVID-19 infection can have adverse outcomes for the newborn. Despite the positive test of neonates, the vertical transmission of COVID-19 from the infected mother to the fetus has not yet been conclusively proven; thus, further research is needed. [ABSTRACT FROM AUTHOR]

Background: The purpose of this paper is to study how the Delta variant spread in a China city, and to what extent the non-pharmaceutical prevention measures of local government be effective by reviewing the contact network of COVID-19 cases in Xi'an, China. Methods: We organize the case reports of the Shaanxi Health Commission into a database by text coding and convert them into a network matrix. Then we construct a dynamic contact network for the corresponding analysis and calculate network indicators. we analyze the cases' dynamic contact network structure and intervals between diagnosis time and isolation time by using data visualization, network analysis method, and Ordinary Least Square (OLS) regression. Results: The contact network for this outbreak in Xi'an is very sparse, with a density of less than 0.0001. The contact network is a scale-free network. The average degree centrality is 0.741 and the average PageRank score is 0.0005. The network generated from a single source of infection contains 1371 components. We construct three variables of intervals and analyze the trend of intervals during the outbreak. The mean interval (interval 1) between case diagnosis time and isolation time is − 3.9 days. The mean of the interval (interval 2) between the infector's diagnosis time and the infectee's diagnosis time is 4.2 days. The mean of the interval (interval 3) between infector isolation time and infectee isolation time is 2.9 days. Among the three intervals, only interval 1 has a significant positive correlation with degree centrality. Conclusions: By integrating COVID-19 case reports of a Chinese city, we construct a contact network to analyze the dispersion of the outbreak. The network is a scale-free network with multiple hidden pathways that are not detected. The intervals of patients in this outbreak decreased compared to the beginning of the outbreak in 2020. City lockdown has a significant effect on the intervals that can affect patients' network centrality. Our study highlights the value of case report text. By linking different reports, we can quickly analyze the spread of the epidemic in an urban area. [ABSTRACT FROM AUTHOR]

Arguably the first thing that a reader notices of a news item, the headline serves the semantic function of providing pertinent information and the pragmatic function of appealing to target addressees. Moreover, it often embodies the stance of the news writer or the news agency on a particular issue and could program the reader's perception and interpretation of the ensuing news story in a pre-determined direction. In view of the distinctive significance of headlines in news discourse, in this paper, we analyze how the headlines of The Economist, an elite newsmagazine, frame China in relation to the COVID-19 pandemic. The sample of headlines was examined for their structural components, syntactic features, as well as linguistic characteristics, and compared with a selection of the outlet's headlines on COVID responses of certain other countries. Through identifying the framing patterns adopted in the headlines and unpacking the ideological overtones encoded therein, this systematic analysis has illuminated the role and effects of the tactful employment of language in constructing country image and striking a balance between purported impartiality and ideological dispositions. Its findings and implications are expected to contribute to scholarship on media framing and inform the practice of journalistic writing. [ABSTRACT FROM AUTHOR]

The Chinese government refuted rumors on social media for infodemic management when COVID-19 outbroke. This study selected 80 government accounts on Sina Weibo and collected 501 valid anti-rumor posts with comments from 18 January to 29 February 2020. This paper evaluated the effectiveness of rumor debunking from the public emotions reflected in the comments. This study also examined the influence of different anti-rumor strategies, such as fact-checking, rumor response modes, and presentation forms, on the effectiveness of rumor debunking. The findings revealed that fact-checking, combined response mode and text presentation could improve the effectiveness of rumor debunking to some extent. Further analysis of the public emotions indicated a correlation between the trust in government and the effectiveness of rumor debunking. These findings suggested building a multiparticipant response mechanism with medical institutions and media to mitigate the COVID-19 infodemic through targeted strategies, thus further increasing the government's credibility via information governance. [ABSTRACT FROM AUTHOR]

Since China's reform and opening up, the domestic economic structure has undergone significant changes, and the industrial system has gradually developed to the tertiary industry. As the core of the tertiary sector and service industry, tourism has, therefore, entered a stage of vigorous development. At the same time, in the context of promoting new-type urbanization, industrial parks created by the theory of industry-urban integration have entered a new stage of development. Due to the respective characteristics of industrial parks and tourism, tourism industrial parks with comprehensive coverage and a strong driving ability have gradually formed under the promotion of industry-urban integration. As a new carrier of the tourism industry, tourism industrial parks are being built all over China. However, due to the differences in the development level of each region, how to improve the competitiveness in the construction of tourism industrial parks has become a problem worth studying. Based on the diamond model in the competitiveness theory, this paper first improves the model according to the actual situation and constructs the competitiveness evaluation index system of tourism industrial parks from the perspective of new-type urbanization. Second, the weight of each index is calculated using the Analytic Network Process (ANP), and then the competitiveness evaluation model is constructed by the matter-element method. Finally, the evaluation model is verified by taking the Suining city Tourism Industrial Park as an example, and corresponding improvement suggestions are put forward for this case. At the same time, the feedback from this evaluation process also provides a scientific method and theoretical basis for enhancing the competitiveness of tourism industrial parks and provides a new idea for the future development of such parks. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 has resulted in an unprecedented attention and response to health surveillance in China, in which the Health Code has made outstanding contributions to digital social governance as well as epidemic control work. As China steps into the post-COVID-19 era, the Health Code will keep upgrading, optimizing and continue to play a role in regular epidemic prevention and control. This paper reviews the background, promoting reasons, significance and controversies of Health Code, so as to provide reference for the relative research and practical applications in the future. [ABSTRACT FROM AUTHOR]

During the current global COVID-19 crisis Taiwan has portrayed itself as both an example for other countries to follow and as a country willing to assist others in their own efforts with the virus. Taiwan has also renewed efforts to participate in the World Health Organization (WHO), an organisation from which it is currently excluded. Although some countries have supported Taiwan's efforts to participate in the WHO or have praised its COVID-19 response, others have been silent or even critical, sometimes citing commitments to a "one China policy." In this paper, we use newly collected data to explore cross-national variation in support for Taiwan during the current pandemic. We find that a country's level of economic development and security ties with the US are strongly correlated with support for Taiwan while a country's economic ties to China is a less consistent predictor. [ABSTRACT FROM AUTHOR]

With the gradual normalization of the COVID-19, unmanned delivery has gradually become an important contactless distribution method around China. In this paper, we study the routing problem of unmanned vehicles considering path flexibility and the number of traffic lights in the road network to reduce the complexity of road conditions faced by unmanned vehicles as much as possible. We use Monte Carlo Tree Search algorithm to improve the Genetic Algorithm to solve this problem, first use Monte Carlo Tree Search Algorithm to compute the time-saving path between two nodes among multiple feasible paths and then transfer the paths results to Genetic Algorithm to obtain the final sequence of the unmanned vehicles fleet. And the hybrid algorithm was tested on the actual road network data around four hospitals in Beijing. The results showed that compared with normal vehicle routing problem, considering path flexibility can save the delivery time, the more complex the road network composition, the better results could be obtained by the algorithm. [ABSTRACT FROM AUTHOR]

Copper in the international market has been priced by copper futures contracts from the London Metal Exchange (LME) and the New York Commodity Exchange (COMEX). Copper prices initially showed a downward trend until March 2020, but after the outbreak of COVID-19, they continued to rise and reached a record high in May 2021. The rise in copper demand also stimulated the continuous growth of copper production. However, a significant amount of smelting flue gas is produced in the copper smelting process. The main component of the flue gas is SO2 and other acid gases, which pollute the environmental atmosphere. At the same time, due to the Chinese government's effective control of the pandemic, China's economy continued to grow. Therefore, as one of the world's largest copper consumers and producers, China's futures market has attracted attention for its influence on copper pricing and the pollution caused by copper smelting. In this paper, we used the grey entropy method to compare the influence of copper prices on the three futures markets and changes in China's air pollution in recent years. Our results show that before the pandemic, the influence of the LME futures copper price was the same as the COMEX but greater than the Shanghai Futures Exchange (SHFE). After the outbreak of the pandemic, the influence of the SHFE copper futures price significantly improved and slightly exceeded the LME and COMEX. This result echoes our finding that SO2 has caused serious air pollution in recent years. [ABSTRACT FROM AUTHOR]

The exploration of the dependency structure of the Chinese and EU carbon trading markets is crucial to the construction of a globally harmonized carbon market. In this paper, we studied the characteristics of structural interdependency between China's major carbon markets and the European Union (EU) carbon market before and after the launch of the national carbon emissions trading scheme (ETS) and the occurrence of the new coronavirus (COVID-19) by applying the C-vine copula method, with the carbon trading prices of the EU, Beijing, Shanghai, Guangdong, Shenzhen and Hubei as the research objects. The study shows that there exists a statistically significant dependence between the EU and the major carbon markets in China and their extremal dependences and dependence structures are different at different stages. After the launch of the national carbon ETS, China has become more independent in terms of interdependency with the EU carbon market, and is more relevant between domestic carbon markets. Most importantly, we found that the dependence between the EU and Chinese carbon markets has increased following the outbreak of COVID-19, and tail dependency structures existed before the launch of the national carbon ETS and during the outbreak of the COVID-19. The results of this study provide a basis for the understanding of the linkage characteristics of carbon trading prices between China and the EU at different stages, which in turn can help market regulators and investors to formulate investment decisions and policies. [ABSTRACT FROM AUTHOR]

China features significantly in the Covid-19 narrative for good and bad reasons. The purpose of this paper is to test, empirically, the assumption that Covid-19 would negatively influence perceptions of China in Ghana, due to its perceived relationship with the pandemic. We characterise Chinese manufactured products as soft power resources and analyse the role they play in addressing the personal needs and interests of Ghanaians and how they affect positive and negative perceptions of China amid the Covid-19 pandemic. We used a mixed research method and collected data from a sample size of 1,020 for analysis. We found that Ghanaians are rational actors who maximise the perceived gains of their actions in pursuit of their objectives. Thus, the self-interest and personal satisfaction Ghanaians gain through China's manufactured products outweigh the negative representation of China in the Covid-19 narrative, shaping a positive attitude in Ghana towards China. We situate the argument within rational choice theory. [ABSTRACT FROM AUTHOR]