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Coronavirus disease 2019 (COVID-19) first emerged in China in November 2019. Most governments have responded to the COVID-19 pandemic by imposing a lockdown. Some evidence suggests that a period of isolation might have led to a spike in alcohol misuse, and in the case of patients with alcohol use disorder (AUD), social isolation can favour lapse and relapse. The aim of our position paper is to provide specialists in the alcohol addiction field, in psychopharmacology, gastroenterology and in internal medicine, with appropriate tools to better manage patients with AUD and COVID-19,considering some important topics: (a) the susceptibility of AUD patients to infection; (b) the pharmacological interaction between medications used to treat AUD and to treat COVID-19; (c) the reorganization of the Centre for Alcohol Addiction Treatment for the management of AUD patients in the COVID-19 era (group activities, telemedicine, outpatients treatment, alcohol-related liver disease and liver transplantation, collecting samples); (d) AUD and SARS-CoV-2 vaccination. Telemedicine/telehealth will undoubtedly be useful/practical tools even though it remains at an elementary level; the contribution of the family and of caregivers in the management of AUD patients will play a significant role; the multidisciplinary intervention involving experts in the treatment of AUD with specialists in the treatment of COVID-19 disease will need implementation. Thus, the COVID-19 pandemic is rapidly leading addiction specialists towards a new governance scenario of AUD, which necessarily needs an in-depth reconsideration, focusing attention on a safe approach in combination with the efficacy of treatment. [ABSTRACT FROM AUTHOR]

Background: Residents' adoption of preventive behaviours proved beneficial in preventing the large-scale transmission of the virus during the early stages of the COVID-19 outbreak. It is critical to investigate how social media triggers residents' preventive behaviour decisions during the COVID-19 outbreak. Methods: This paper selected online shopping as a specific preventive behaviour for empirical investigation. An online cross-sectional survey was conducted through the Sojump website from 1 to 15 March 2020, and a total of 1,289 valid questionnaires were collected from China. This paper uses multiple regression analysis to investigate the heterogeneous impacts of different information sources on residents' online shopping willingness and online shopping behaviour and the heterogeneous impacts of different information content in social media on the transformation of residents' online shopping willingness and online shopping behaviour. Results: The findings indicate that both official-media and self-media positively promote residents' online shopping willingness and behaviour, with official-media having a stronger promotional effect than self-media. Furthermore, official-media and self-media can collaboratively promote residents' online shopping willingness and online shopping behaviour. The ease-of-use and usefulness of information significantly promoted the transformation of residents' online shopping willingness. Conclusions: This study analyses the heterogeneous impacts of social media on residents' preventive behaviours from the perspectives of information source differentiation and information content differentiation, which enriches related studies and provides feasible paths for promoting residents' preventive behaviours. [ABSTRACT FROM AUTHOR]

This paper examines the Chinese government's response to four epidemic crises, including COVID-19, and analyzes the similarities and differences in these responses. It argues that while the Chinese government learned from previous epidemics and improved its handling of subsequent outbreaks, a significant variation occurred during the COVID-19 pandemic, which had a detrimental impact globally. Existing scholarly research on China's epidemic responses has often been limited in scope, focusing on individual crises and neglecting the central-local government relationship in crisis decision-making. By adopting a comprehensive approach, this paper delves into the nuanced dynamics of China's responses to these epidemics. It highlights the variations in responses, attributing them to the Chinese government's fear of undermined legitimacy and its consideration of its international image. The government's recognition of the importance of public perception and trust, both domestically and globally, has shaped its crisis management strategies. Through a detailed analysis of these factors, this paper contributes to a deeper understanding of the variations observed in China's epidemic responses. It emphasizes the significance of the central-local government relationship and the government's international image in determining its actions during epidemics. Recognizing these factors can provide policymakers and researchers with insights to shape future epidemic response strategies and foster effective global health governance. [ABSTRACT FROM AUTHOR]

Background: Against the grim background of declining intention to have children, the ravages of COVID-19 have pushed China and the world into a more complex social environment. To adapt to the new situation, the Chinese government implemented the three-child policy in 2021. Objective: COVID-19 pandemic indirectly affects the country's internal economic development, employment, fertility plans or intention, and other major issues related to the people's livelihood, while undermining the stable operation of society. This paper explores the question that will COVID-19 pandemic affect Chinese people's intention to have a third child. And What are the relevant factors inside? Method: The data in this paper are from the Survey released by the Population Policy and Development Research Center of Chongqing Technology and Business University (PDPR-CTBU), including 10,323 samples from mainland China. This paper uses the logit regression model and KHB mediated effect model (a binary response model given by Karlson, Holm, and Breen) to investigate the impact of the COVID-19 pandemic and other factors on Chinese residents' intention to have a third child. Results: The results suggest that the COVID-19 pandemic has a negative effect on Chinese residents' intention to have a third child. In-depth research on the mediating effect of KHB shows that COVID-19 pandemic will further inhibit residents' intention to have a third child by affecting their childcare arrangements, increasing their childcare costs, and increasing their exposure to occupational hazards. Contribution: This paper is more pioneering in focusing on the impact of the COVID-19 epidemic on the intention to have three children in China. The study provides empirical evidence for understanding the impact of COVID-19 epidemic on fertility intentions, albeit in the context of policy support. [ABSTRACT FROM AUTHOR]

The transmission rate is an important indicator for characterizing a virus and estimating the risk of its outbreak in a certain area, but it is hard to measure. COVID-19, for instance, has greatly affected the world for more than 3 years since early 2020, but scholars have not yet found an effective method to obtain its timely transmission rate due to the fact that the value of COVID-19 transmission rate is not constant but dynamic, always changing over time and places. Therefore, in order to estimate the timely dynamic transmission rate of COVID-19, we performed the following: first, we utilized a rolling time series to construct a time-varying transmission rate model and, based on the model, managed to obtain the dynamic value of COVID-19 transmission rate in mainland China; second, to verify the result, we used the obtained COVID-19 transmission rate as the explanatory variable to conduct empirical research on the impact of the COVID-19 pandemic on China's stock markets. Eventually, the result revealed that the COVID-19 transmission rate had a significant negative impact on China's stock markets, which, to some extent, confirms the validity of the used measurement method in this paper. Notably, the model constructed in this paper, combined with local conditions, can not only be used to estimate the COVID-19 transmission rate in mainland China but also in other affected countries or regions and would be applicable to calculate the transmission rate of other pathogens, not limited to COVID-19, which coincidently fills the gaps in the research. Furthermore, the research based on this model might play a part in regulating anti-pandemic governmental policies and could also help investors and stakeholders to make decisions in a pandemic setting. [ABSTRACT FROM AUTHOR]

Using the policy package pilot implemented in Hubei Province, China, in April 2020 as a natural experiment, we use the synthetic control (SC) and synthetic difference in differences (SDID) methods to estimate the impact of the Chinese government's support policy on the economic resilience and to analyze the mechanisms by which it impacts. This study finds that the policy package has contributed to the growth of economic resilience in the pilot provinces, with the policy package increasing the average economic resilience of the pilot provinces by 0.062 compared to their potential resilience. The validity and robustness of the above conclusions are objectively confirmed by multidimensional quantitative outcomes such as placebo tests, ranking tests, and replacements in calculating resilience. The mechanism analysis shows that the investment in real estate development, the stimulus for consumption, and the core industry development are virtual channels for the policy package to promote economic resilience growth in the pilot provinces. Moreover, traditional investment in transportation fixed assets plays a minor role. This paper quantitatively corroborates the academic idea that government governance capacity affects regional economic resilience (RER), and research can provide empirical support for regional economic recovery and policy support under a major crisis. [ABSTRACT FROM AUTHOR]

Due to the significant impact of COVID-19, financial markets in various countries have undergone drastic fluctuations. Accurately measuring risk in the financial market and mastering the changing rules of the stock market are of great importance to macro-control and financial market management of the government. This paper focuses on the return rate of the Shanghai Composite Index. Using the SGED-EGARCH(1,1) model as a foundation, a quantile regression is introduced to establish the QR-SGED-EGARCH(1,1) model. Further, the corresponding value at risk (VaR) is calculated for a crisis and stable period within each model. To better compare the models, the Cornish-Fisher expansion model is included for comparison. According to the Kupiec test, VaR values calculated by the QR-SGED-EGARCH(1,1) model are superior to other models at different confidence levels most of the time. In addition, to account for the VaR method's inability to effectively measure tail extreme risk, the expected shortfall (ES) method is introduced. The constructed model is used to calculate the corresponding ES values during different periods. According to the evaluation index, the ES values calculated by the QR-SGED-EGARCH(1,1) model have a better effect during a crisis period with the model showing higher accuracy and robustness. It is of great significance for China to better measure financial risk under the impact of a sudden crisis. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, often referred to as the geropandemic, has put immense pressure on global healthcare systems worldwide, leading to a rush in the development and approval of medications for the treatment of the viral infection. Clinical trials on efficacy and safety had a limited spectrum on inclusion and endpoints because of the urgent need for fast results. The chronologically and biologically aged population is especially at risk for severe or lethal disease, as well as treatment-associated toxicity. In China, the growing elderly population segment has been a focus in public health measurements of COVID-19, guiding towards herd immunity with a mild variant, thus minimizing overall deaths and morbidity. While the COVID-19 pandemic has now been reclassified and the virus weakened, there is a clear need for novel therapies to protect the elderly. This paper reviews the current safety and efficacy of available COVID-19 medications in China, with a specific focus on 3CL protease inhibitors and the aging population. The current COVID wave in China has demonstrated a significant impact on the elderly and the need for new drugs that are effective at low doses and can be used alone, without harmful side effects, generation of viral resistance, and drug-drug interactions. The rush to develop and approve COVID-19 medications has brought up important questions about the balance between speed and caution, resulting in a pipeline of novel therapies now moving through clinical trials, including third-generation 3CL protease inhibitors. A majority of those therapeutics are being developed in China. [ABSTRACT FROM AUTHOR]

Research background: In order to examine market uncertainty, the paper depicts broad patterns of risk and systematic exposure to global equity market shocks for the major South Asian and Chinese equity markets, as well as for specific assets (gold and Bitcoin). Purpose of the article: The purpose of this paper is to investigate the dynamic correlation among the major South Asian equity markets (India and Pakistan), the Chinese equity markets, the MSCI developed markets, Bitcoin, and gold markets. Methods: While applying the GARCH-Vine-Copula model and the TVP-VAR Connectedness approach, major patterns of dependency and interconnectedness between these markets are investigated. Findings & value added: We find that risk shocks from developed equity markets are critical in these dynamic links. A net return spillover from Bitcoin to the Chinese and Pakistani stock markets throughout the sample period is reported. Interestingly, gold can be applied to hedge and diversify positions in China and major South Asian markets, particularly following the COVID-19 outbreak. Our paper presents three main original add valued: (1) This paper adds global factors to the targeted study of risk transmission among South Asian and Chinese stock markets for the first time. (2)The assets of Bitcoin and gold were added to the study of risk transmission among South Asian and Chinese stock markets for the first time, enabling the research in this paper to observe the non-linear link among the South Asian and Chinese stock markets with them. (3) Our research adds to these lines of inquiry by giving empirical evidence on how COVID-19 altered the dependent structure and return spillover dynamics of Bitcoin, gold and South Asian and Chinese stock markets for the first time. Our results have critical implications for investors and policymakers to effectively understand the nature of market forces and develop risk-averse strategies. [ABSTRACT FROM AUTHOR]

Governments worldwide have announced stimulus packages to remobilize the labor force after COVID-19 and therefore to cope with the COVID-19-related recession. However, it is still unclear how to facilitate large-scale work resumption. This paper aims to clarify the issue by analyzing the large-scale prefecture-level dataset of human mobility trajectory information for 320 million workers and about 500,000 policy documents in China. We model work resumption as a collective behavioral change due to configurations of capacity, motivation, and policy instruments by using qualitative comparative analysis. We find that the effectiveness of post-COVID-19 recovery stimulus varied across China depending on the fiscal and administrative capacity and the policy motivation of the prefecture. Subnational fiscal and procurement policies were more effective for the wholesale and retail sector and the hotel and catering sector, whereas the manufacturing and business services sectors required more effort regarding employment policies. Due to limited prefectural capacity and wavering policy motivation, the simultaneous adoption of fiscal, employment, and procurement policy interventions endangered post-COVID-19 work resumption. We highlight the necessity of tailored postcrisis recovery strategies based on local fiscal and administrative capacity and the sectoral structure. [ABSTRACT FROM AUTHOR]

India's pharmaceutical sector has been one of the largest manufacturers of generic drugs globally. During the pandemic, most countries were dependent on imports of generic drugs from India. However, India has been relying on resources from China for Active Pharmaceutical Ingredients (APIs) which are the raw material for preparing generic drugs. We considered, in our analysis, branded product groups of Paracetamol and Amoxicillin due to their extensive use in the treatment of COVID-19. From a thorough market analysis of both the drugs, we conclude that firms have a monopoly over their brands but compete within the same product group and operate in their respective market under varying prices within certain bandwidths which resembles the feature of monopolistic competitive market. We have introduced compensating function a la Helpman (1981) in the pharmaceutical goods market with the assumption that an 'ideal product' exists among the pharmaceutical goods. Given the framework, this paper explores a general equilibrium model set in a monopolistic competitive product market for branded drugs. We concluded through our propositions that expanding the pharmaceutical sector will increase the employment of unskilled labor under no capacity constraint. We will observe an increase in wages of unskilled labor only under full employment conditions wherein we would observe that the expansion of pharmaceutical good will increase wages in the unskilled labor market. However we obtain an intriguing result wherein we obtain that despite instances of limiting trade dependence on China through implementation of policies like 'Aatmanirbhar Bharat' and 'profit linked incentive schemes', yet to maintain the status quo in the global market for generic drugs, India's dependence on China would increase, owing to API imports due to the pandemic crisis. While India can grab the opportunity in the form of increased demand for pharmaceutical goods to increase the employment level of the economy but this improvement in welfare is also dependent on the degree of dependency of API India has on China. The Indian government has recognized the same through the incorporation of 'Covid-Suraksha' and PLI schemes to minimize import dependency, and accelerate the development of APIs and the production of indigenous drugs. [ABSTRACT FROM AUTHOR]

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]

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]

China has been contributing to new approaches to global governance. The Health Silk Road (HSR), a significant component of the Belt and Road Initiative (BRI), was proposed by China in 2016. This paper claims that HSR is a new institution introduced alongside the existing WHO-led multilateral health system, and its relationship with the existing system can be described as layering. Having explored the new development of HSR during COVID-19, this paper further argues that while HSR has its unique strength in making contributions to global health governance and economic recovery, it faces a prominent issue of securitisation in the context of China-U.S. strategic competition, suspicion of the quality of medical products and sectoral fragmentation. [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]

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]

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]

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]

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]

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]

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]

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]

Background: Air pollution has been identified as related to the diseases of susceptible population, but the spatial heterogeneity of its economic burden and its determinants are rarely investigated. The issue is of great policy significance, especially after the epidemic of COVID-19, when human are facing the joint crisis of health and environment, and some areas is prone to falling into poverty. Methods: The geographical detector was adopted to study the spatial distribution characteristics of the incidence of catastrophic health expenditure (ICHE) for older adults in 100 rural areas in China at the prefecture-city level. The health factors, sociological factors, policy factors and environmental factors and their interactions are identified. Results: First, most health service factors had strong explanatory power for ICHE whether it interacts with air pollution. Second, 50 single-factor high-risk areas of ICHE were found in the study, but at the same time, there were 21 areas dominated by multiple factors. Conclusion: The different contributions and synergy among the factors constitute the complex mechanism of factors and catastrophic health expenditure. Moreover, during this process, air pollution aggravates the contribution of health service factors toward ICHE. In addition, the leading factors of ICHE are different among regions. At the end, this paper also puts forward some policy suggestions from the perspective of health and environment crisis in the post-COVID-19 world: environmental protection policies should be combined with the prevention of infectious diseases; advanced health investment is the most cost-effective policy for the inverse health sequences of air pollution and infectious diseases such as coronavirus disease 2019 (COVID-19); integrating environmental protection policy into healthy development policy, different regions take targeted measures to cope with the intertwined crisis. [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]

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]

To quantitatively evaluate the impact of domestic aviation control measures on the spread of COVID-19 in China. The number of international flights from March to September 2019 simulated the number of flights from March to September 2020 without implementing aviation control measures. In addition, the proportion of asymptomatic persons and the delay in case reporting were adjusted to estimate the prevalence of each country during the same period and calculate the estimated imported cases. The estimated imported cases were assigned each day with weight, and the estimated daily reported cases were obtained based on the actual daily number of domestic cases in China. Effective Reproduction Number ( R t ) was calculated based on delayed distribution, Basic Reproductive Number ( R 0 ) distribution, and generation time distribution were reported in previous studies. Gaussian Process was used to estimate the effect of time-varying on R t , and the estimated R t was compared with the actual R t . The estimated imported cases increased significantly compared with the actual number of imported cases. The estimated imported cases were mainly concentrated in North America and Europe from March to April and gradually increased in many East Asian countries from May to September. The difference between predicted R t and actual R t was statistically significant. The estimated imported cases and the estimated R t have increased compared to the actual situation. This paper quantitatively proves that Chinese aviation control measures significantly suppress the COVID-19 epidemic, which is conducive to promoting and applying this measure. [ABSTRACT FROM AUTHOR]

Background: Hygiene behaviors in public toilets are important to prevent the transmission of infectious diseases, especially during the pandemic. All through the novel coronavirus (COVID-19) pandemic, governments in many countries published guidance on personal hygiene for the general population to prevent disease transmission. This study aimed to investigate improvements in residents' hygiene awareness and behaviors in public toilets before and during the pandemic.Methods: We recruited 316 residents between November and December 2018 before the pandemic, and 314 residents between December 2020 and January 2021 during the pandemic in the same study sites in Hangzhou, a well-developed city in China. Residents' hygiene behaviors in public toilets, hygiene awareness, risk perception, and sociodemographic factors were collected. Bivariate analysis and multivariable logistic regressions were used to test the differences between the two rounds. We conducted an observational study to record the provision of hygiene amenities at toilets during the pandemic.Results: After controlling for sociodemographic factors (gender, marital status, age, education level, and monthly household income), compared with respondents recruited before the pandemic, respondents recruited during the pandemic were more likely to perceive the risks of infection when using public toilets (aOR = 1.77, 95%CI [1.20, 2.60]), and were more likely to be aware of the risks of touching contaminated toilet facilities (aOR = 1.72, 95%CI [1.17, 2.54]) and the risks of not using soap to wash one's hands after using the toilet (aOR = 1.93, 95%CI [1.38, 2.72]). They were more likely to always clean their toilet seat with alcohol (aOR = 1.88, 95%CI [1.01, 3.51]), wash hands with soap (aOR = 1.52, 95%CI [1.09, 2.10]) and dry their hands with a dryer (aOR = 1.78, 95%CI [1.16, 2.71]), but they were less likely to always wash their hands after using the toilets (aOR = 0.57, 95%CI [0.32, 1.00]). Among 70 public toilets observed, 9 provided alcohol for toilet seat disinfection, 52 provided soap, 33 provided paper towels, and 41 had working hand dryers.Conclusions: Despite the overall improvement, residents' hygiene behaviors in public toilets and the supply of hygiene amenities were still suboptimal during the pandemic. Further hygiene education and an adequate supply of hygiene amenities in public toilets are needed to promote residents' hygiene behaviors. [ABSTRACT FROM AUTHOR]

COVID-19 can be considered as the largest public health incident since 2019, posing disturbances to the medical, economic, and social systems. Understanding different levels of city resilience to the impact of COVID-19 on sustainable urban development is therefore essential. In this paper, we analyzed the evolution of the pandemic, the recovery of urban activities and major drivers of urban resilience to COVID-19 based on urban activity patterns derived from NO 2 monitoring stations from 217 cities in China. It is observed that nearly all urban activities have been affected by the epidemic with a reduced NO 2 emission, indicating a significant decline in the intensity of urban activity. The recovery patterns of human activity among different cities show that: (1) northern cities where low-resilience cities agglomerated have been severely affected. As of April 31, 2020, 12 northern cities have not recovered to pre-epidemic levels; (2) about three-quarters of the cities went through multiple stages to return to the pre-pandemic level, which related to both pandemic stress and prevention measures; (3) about 46.04% of the cities experienced increasing activity patterns that exceeded the pre-epidemic activity level. It is also observed that urban resilience can behave quite differently driven by variations in green coverage, economic aggregate, employment security, and medical system. Our study highlights the potential of an elevated urban resilience by optimizing the urban layout, improving the quantity and quality of green space, and enhancing the medical system. [Display omitted] • Most of the southern cities of China show higher urban activity than pre-pandemic. • Low/high-resilient urban agglomerations located in the north-northeast/south China. • Most cities undergo two stages of recovery at the beginning and end of March 2020. • Urban greenery is positively correlated to urban resilience. • Hospital capacity, instead of number, is more crucial to urban resilience. [ABSTRACT FROM AUTHOR]

The study aims to evaluate global research output (103054 records) on coronavirus disease (COVID-19) based on quantitative and qualitative indicators. It presents a bibliometric profile of most influential countries, organizations, authors and journals and their collaborative linkages, besides identifying broad subject areas of research, most significant keywords and highly-cited papers related to COVID-19. During 2020-21, more than 150 countries participated in COVID-19 research, of which top 10 countries accounted for a 82.93% global share. The USA, China and U.K. produced the most articles (25.86%, 10.77% and 10.7% respectively). The top three organizations, namely Harvard Medical School, USA, Huazhong University of S&T, China and Tongji Medical College, China contributed 1755, 1344 and 1267 papers, respectively. The most cited organizations in COVID-19 research are: Peking Union Medical College, China (97.41 CPP), University of Hong Kong (82.17 CPP) and Renmin Hospital of Wuhan University, China (59.88 CPP). The top three most productive authors are: V. Wanitlit, E. Mahase and G. Lacobucci (with 152, 135 and 108 papers). The top three most cited authors in terms of citations per paper (CPP) are: Y. Hu (319.82), L. Liu (303.91) and J.F.W. Chan (169.55). The most productive organizations originate from most productive countries and they contribute the most collaborative papers. The top three journals, namely International Journal of Environmental Research, BMJ and PLOS One contributed 961, 854 and 781 papers, respectively. The top three journals in terms of citations per paper (CPP) are New England Journal of Medicine (122.78), The Lancet (106.3) and JAMA (75.17). The most ubiquitous topic was COVID-19 clinical studies, with maximum focus on virological aspects (9.58%), respiratory aspects (6.97%), molecular aspects (3.11%), genetic aspects (3.09%) and immunological aspects (1.3%). The results of this study should be of interest to working scientists, clinicians and policy-makers in improving their understanding of COVID-19 disease and in its management. [ABSTRACT FROM AUTHOR]

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

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

The emergence of the Covid-19 pandemic has led to the publication of many scientific papers. The goal of the present research was to analyze these papers using the Altmetric Attention Score (AAS). Statistics for 100 publications with high AAS scores were selected and exported from the Dimension database on May 22nd 2020. The major findings were that these publications were published in 34 different journals or preprint repositories. More than one-third of the total of 657, 350 social media posts were collected from the Twitter platform. The top contributing countries were China, followed by the USA. The paper "The proximal origin of SARS-CoV-2" by Andersen, Kristian G., etal., 2020 had the highest AAS (33 514). These findings may help others to design studies of the AAS in Coronavirus literature and compare them with traditional citations. [ABSTRACT FROM AUTHOR]

A pneumonia outbreak was primarily reported in the fall of 2019 in Wuhan, Hubei province, China, with the identity SARS-CoV-2, a novel coronavirus. It quickly grew from a local epidemic to a global pandemic and was declared a public health emergency by the WHO. A total of three prominent waves were identified across the globe, with a slight temporal variability as per the geographical locations, and has impacted several sectors which connect the world. By March 2022, the coronavirus had infected 444.12 million people and claimed 6.01 million human lives worldwide, and these numbers have not yet stabilized. Our paper enlightens readers on the seven strains of human coronaviruses, with special emphasis on the three severe deadliest outbreaks (SARS-2002, MERS-2012, and COVID-19). This work attempts a comprehensive understanding of the coronavirus and its impact on the possible sectors that link the world through the economic chain, climate conditions, SDGs, recycling of the event, and mitigations. There are many points that are raised by the authors in the possible sectors, which are emerging or are as yet unnoticed and thus have not been taken into consideration. This comprehension will leave sets of new challenges and opportunities for the researchers in various streams, especially in earth sciences. Science-integrated research may help to prevent upcoming disasters as a by-product of (existing) epidemics in the form of coronavirus. [ABSTRACT FROM AUTHOR]

Prices of oil and other commodities have fluctuated wildly since the outbreak of the COVID-19 pandemic. It is crucial to explore the causes of price fluctuations and understand the source and path of risk contagion to better mitigate systemic risk and maintain economic stability. The paper adopts the method of network topology to examine the path of risk contagion between China's and foreign commodities, focusing on the dynamic evolution and transmission mechanism of risk contagion during the pandemic. This research found that among China's commodities, energy, grain, and textiles are net recipients of risk contagion, while chemical products and metals are net risk exporters. Among international commodities, industries have positive risk spillover effects on metals and textiles. During the first phase of the pandemic, China's commodities were the main exporters of risk contagion. However, international industries and metals became the main risk exporters and exerted risk spillover on China's commodities in the second phase of the pandemic. Moreover, based on total volatility spillover index of commodities, the risk contagion among the commodities follows three paths: "interest rate → commodities → money supply", "China's economic expectation → commodities → foreign economic expectation", and "commodities → consumer confidence". [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic and antipandemic policies have significantly impacted highway transportation. Many studies have been conducted to quantify these impacts. However, quantitative analysis of the impacts on province-wide traffic in developing countries, such as China, is still inadequate. This paper tried to fill this gap by proposing equations to quantify the traffic variations of overall province-wide traffic and to analyze the intercity bus traffic variation and intercity bus usage, applying the K-means cluster method to conduct the analysis of traffic reductions in regions with different levels of economic development, and using the hypothesis testing for traffic recovery analysis. It is found that passenger vehicle traffic and truck traffic dropped by 59.67% and 68.19% during the outbreak, respectively. The intercity bus traffic on highways declined by 59.8% to 98.6%, and the intercity bus usage dropped by 55.6% on average. For traffic reductions in different regions, the higher the GDP per capita was, the more the traffic was affected by the pandemic. In regions with lower GDP per capita, traffic variations were minor. It is also found that the passenger vehicle traffic went through four stages in 99 days: the Decline Stage, Rapid Recovery Stage, Slow Recovery Stage, and Normal Stage, while truck traffic only experienced the Decline Stage, Rapid Recovery Stage, and Normal Stage and took 51 days to recover to the Normal Stage. In the Rapid Recovery Stage, the recovery rates were 15.6% and 12.9% per week for passenger vehicle traffic and truck traffic, respectively, and the recovery rate was only 2.1% for passenger vehicle traffic in the Slow Recovery Stage. Despite the recovery of traffic volumes, neither passenger-kilometers nor tonne-kilometers of freight in 2020 reached the same level as in 2019. These findings help the understanding of the pandemic's impacts on highway traffic for researchers and can provide valuable references for decision-makers to develop antipandemic policies. [ABSTRACT FROM AUTHOR]

Background: During the course of the COVID-19 pandemic, states were called upon by the World Health Organization to introduce and prioritise the collection of sex-disaggregated data. The collection of sex-disaggregated data on COVID-19 testing, infection rates, hospital admissions, and deaths, when available, has informed our understanding of the biology of the infectious disease. The collection of sex-disaggregated data should also better inform our understanding of the gendered impacts that contribute to risk of exposure to COVID-19. In China, the country with the longest history of fighting the COVID-19 infection, what research was available on the gender-differential impacts of COVID-19 in the first 6 months of the COVID-19 pandemic?Methods: In this scoping review, we examine the first 6 months (January-June 2020) of peer-reviewed publications (n = 451) on sex and gender experiences related to COVID-19 in China. We conducted an exhaustive search of published Chinese and English language research papers on COVID-19 in mainland China. We used a COVID-19 Gender Matrix informed by the JPHIEGO gender analysis toolkit to examine and illuminate research into the gendered impacts of COVID-19 within China.Results: In China, only a small portion of the COVID-19-related research focused on gender experiences and differences. Near the end of the six-month literature review period, a small number of research items emerged on women healthcare workers, women's mental health, and pregnant women's access to care. There was an absence of research on the gendered impact of COVID-19 amongst populations. There was minimal consideration of the economic, social and security factors, including gender stereotypes and expectations, that affected different populations' experiences of infection, treatment, and lockdown during the period of review.Conclusion: At the outset of health emergencies in China, gender research needs to be prioritised during the first stage of an outbreak to assist with evaluation of the most effective public health measures, identifying access to healthcare and social welfare barriers amongst priority communities. Gender stereotypes and gendered differences lead to different patterns of exposure and treatment. The exclusion of this knowledge in real time affects the design of effective prevention and recovery. [ABSTRACT FROM AUTHOR]

• This study applied a logistic growth model with parameters estimated by a non-linear least squares (NLS) method to daily new COVID-19 cases. • The model fitted time-series data exceedingly well for the whole of China, eleven selected Chinese provinces and municipalities, South Korea and Iran. • This study provided key estimates and a 95% confidence interval for parameters K , r, and P 0. • This study found that the growth rates of outbreaks differed between provinces in China and between South Korea and Iran. • As of March 13, 2020, this study's model suggested that countries such as the U.S.A., France, Italy, and Spain were still in the early stages of outbreaks. As the coronavirus disease 2019 (COVID-19) pandemic continues to proliferate globally, this paper shares the findings of modelling the outbreak in China at both provincial and national levels. This paper examines the applicability of the logistic growth model, with implications for the study of the COVID-19 pandemic and other infectious diseases. An NLS (Non-Linear Least Squares) method was employed to estimate the parameters of a differentiated logistic growth function using new daily COVID-19 cases in multiple regions in China and in other selected countries. The estimation was based upon training data from January 20, 2020 to March 13, 2020. A restriction test was subsequently implemented to examine whether a designated parameter was identical among regions or countries, and the diagnosis of residuals was also conducted. The model's goodness of fit was checked using testing data from March 14, 2020 to April 18, 2020. The model presented in this paper fitted time-series data exceedingly well for the whole of China, its eleven selected provinces and municipalities, and two other countries - South Korea and Iran - and provided estimates of key parameters. This study rejected the null hypothesis that the growth rates of outbreaks were the same among ten selected non-Hubei provinces in China, as well as between South Korea and Iran. The study found that the model did not provide reliable estimates for countries that were in the early stages of outbreaks. Furthermore, this study concured that the R 2 values might vary and mislead when compared between different portions of the same non-linear curve. In addition, the study identified the existence of heteroskedasticity and positive serial correlation within residuals in some provinces and countries. The findings suggest that there is potential for this model to contribute to better public health policy in combatting COVID-19. The model does so by providing a simple logistic framework for retrospectively analyzing outbreaks in regions that have already experienced a maximal proliferation in cases. Based upon statistical findings, this study also outlines certain challenges in modelling and their implications for the results. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive system for assessing contaminant emissions, including the dominant contaminant reduction effects, recessive contaminant reduction effects, and contaminant reduction efficiency indexes. The system is used to evaluate the linkage changes in contaminant emissions reduction across different sectors, the ease of regulation, and the returns on emissions reduction efforts. The study's results demonstrate that firstly, COVID-19 initially reduced contaminant emissions across almost all sectors, although this effect waned over time. Secondly, applying conventional regulatory measures to sectors with high reductions in contaminant emissions may not yield the expected results. Thirdly, while some sectors may be more difficult to regulate, they may offer a higher return on investment in terms of emissions reduction. Based on the above results, the paper advocates for timely measures to consolidate environmental gains, prevent rebounding of contaminant emissions, prioritize supervision and management of easily regulated sectors, prioritize upgrading of cleaner production in sectors with high reduction efficiency indices, and increase investment in environmental technology. • Created a new comprehensive system for assessing contaminant emission changes. • Quantified the unique linkage changes of contaminant emissions during COVID-19. • Developed new models to reveal contaminants' regulatory difficulty and return. • The innovative reduction effects of four key contaminant indicators were measured. • Applied WHEM firstly in research across multiple areas of contaminant emissions. [ABSTRACT FROM AUTHOR]

Since the end of 2019, the outbreak of COVID-19 has severely affected port production and operation. There is little research on the systematic impact assessment. This study took Shanghai Port as an example and evaluated the impact under different scenarios through establishing a System Dynamics model. It is found that the epidemic mainly has a greater impact on passenger transport, but less on cargo transport. The ports with the function of transportation in highway, railway, and waterway were the key nodes in the international logistics network. More attention should be paid to the impact assessment of COVID-19 on ports' production and operation. It is necessary to strengthen the port's collection and distribution capabilities, improve port production efficiency, and further strengthen port modernization. This research method proposed in this paper can provide a reference for the impact assessment of similar events, and the empirical results can provide a reference for handling the epidemic shock for the port and shipping departments. [ABSTRACT FROM AUTHOR]

Background: The global spread of the novel coronavirus pneumonia is still continuing, and a new round of more serious outbreaks has even begun in some countries. In this context, this paper studies the dynamics of a type of delayed reaction-diffusion novel coronavirus pneumonia model with relapse and self-limiting treatment in a temporal-spatial heterogeneous environment.Methods: First, focus on the self-limiting characteristics of COVID-19, incorporate the relapse and self-limiting treatment factors into the diffusion model, and study the influence of self-limiting treatment on the diffusion of the epidemic. Second, because the traditional Lyapunov stability method is difficult to determine the spread of the epidemic with relapse and self-limiting treatment, we introduce a completely different method, relying on the existence conditions of the exponential attractor of our newly established in the infinite-dimensional dynamic system to determine the diffusion of novel coronavirus pneumonia. Third, relapse and self-limiting treatment have led to a change in the structure of the delayed diffusion COVID-19 model, and the traditional basic reproduction number [Formula: see text] no longer has threshold characteristics. With the help of the Krein-Rutman theorem and the eigenvalue method, we studied the threshold characteristics of the principal eigenvalue and found that it can be used as a new threshold to describe the diffusion of the epidemic.Results: Our results prove that the principal eigenvalue [Formula: see text] of the delayed reaction-diffusion COVID-19 system with relapse and self-limiting treatment can replace the basic reproduction number [Formula: see text] to describe the threshold effect of disease transmission. Combine with the latest official data and the prevention and control strategies, some numerical simulations on the stability and global exponential attractiveness of the diffusion of the COVID-19 epidemic in China and the USA are given.Conclusions: Through the comparison of numerical simulations, we find that self-limiting treatment can significantly promote the prevention and control of the epidemic. And if the free activities of asymptomatic infected persons are not restricted, it will seriously hinder the progress of epidemic prevention and control. [ABSTRACT FROM AUTHOR]

Coping with the outbreak of Coronavirus disease 2019 (COVID-19), many countries have implemented public-health measures and movement restrictions to prevent the spread of the virus. However, the strict mobility control also brought about production stagnation and market disruption, resulting in a severe worldwide economic crisis. Quantifying the economic stagnation and predicting post-pandemic recovery are imperative issues. Besides, it is significant to examine how the impact of COVID-19 on economic activities varied with industries. As a reflection of enterprises' production output, high-frequency electricity-consumption data is an intuitive and effective tool for evaluating the economic impact of COVID-19 on different industries. In this paper, we quantify and compare economic impacts on the electricity consumption of different industries in eastern China. In order to address this problem, we conduct causal analysis using a difference-in-difference (DID) estimation model to analyze the effects of multi-phase public-health measures. Our model employs the electricity-consumption data ranging from 2019 to 2020 of 96 counties in the Eastern China region, which covers three main economic sectors and their 53 sub-sectors. The results indicate that electricity demand of all industries (other than information transfer industry) rebounded after the initial shock, and is back to pre-pandemic trends after easing the control measures at the end of May 2020. Emergency response, the combination of all countermeasures to COVID-19 in a certain period, affected all industries, and the higher level of emergency response with stricter movement control resulted in a greater decrease in electricity consumption and production. The pandemic outbreak has a negative-lag effect on industries, and there is greater resilience in industries that are less dependent on human mobility for economic production and activities. [ABSTRACT FROM AUTHOR]

Introduction: In December 2019, a new coronavirus has emerged out of China, the SARS‐CoV‐2 virus, causing a disease known as COVID‐19, which steadily has progressed into a pandemic. This coronavirus affects many organs, including the skin, whose manifestations are a consequence of the disease itself, as well as the preventative measures taken to avoid the infection. This paper reviews the cutaneous manifestations which currently have been encountered during this pandemic. Methods: A search was conducted on PubMed, and all relevant articles were included. Results: The results show the occurrence of many cutaneous findings, ranging from those related to the infection itself and to various dermatitides related to the use of personal protective equipment (PPE) utilized by healthcare workers while attending to infected patients. Discussion: Recognizing these findings is important for the accurate diagnosis of those infected with COVID‐19 as well as the prompt treatment of the side effects caused by PPE that might further impair the effectiveness of healthcare workers. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease 2019 (COVID-19) has placed tremendous pressure on public health systems across the world. Compared with the healthy population, cancer patients are more prone to developing psychological problems, including depression and anxiety, because of worries about cancer recurrence, cancer symptoms, treatment-related discomfort, a lack of social interaction and the impact on their financial well-being. This paper aimed to identify existing evidence on psychological symptoms and their associated factors among cancer patients in the Chinese Mainland during the COVID-19 pandemic, and on interventions to effectively manage these symptoms. Articles related to the prevalence, the risk factors and interventions of psychological symptoms among cancer patients in the Chinese Mainland during COVID-19 published between December 2019 and August 2020 were searched in two English (PubMed and Embase) and two Chinese (CNKI and Wan Fang Data) databases. A total of 180 studies were identified, and 18 studies were included in the review after removing duplicates and screening for relevancy. The results suggest that patients with cancer in the Chinese Mainland have suffered psychological pressure during COVID-19, with a high prevalence of psychological distress, depression and anxiety reported across most of the reviewed studies. Pandemic-related factors such as treatment discontinuation and worry about being infected are associated with these symptoms. Nurses may help to relieve these symptoms by identifying stressors, providing relevant information through mass and social media and referring patients to specialists for psychological support. However, evidence about treatments and interventions for these symptoms is limited, and additional research is warranted to identify effective interventions to promote resilience in this patient population. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic caused by SARS-CoV-2 dominated the year 2020 and has an unprecedented impact on global air transport. This paper tries to make an overall review on the interaction of air transport and the COVID-19 pandemic. Although the confirmed cases were first reported in China, the origin of the pandemic remains uncertain. China was the first country to control the COVID-19 pandemic, and domestic air traffic recovers at a fast pace. Compared to 2019 level, world scheduled capacity, passengers carried, and revenues for 2020 were reduced by 50%, 60%, and $371 billion, respectively. Compared with domestic passenger traffic, international passenger traffic reduces more seats, passengers, and revenues. Because air transport contributes to economic growth, many countries or regions provide aviation bailout. The US provides most direct aid, while China mostly provides policy measures. In the post-COVID-19 period, IATA suggests that accepting vaccinated passengers is the best practice to reopen borders. Air cargo will play an important role in the distribution of COVID-19 vaccines. Meanwhile, air transport should be more digitalized, sustainable, and responsible in the future. [ABSTRACT FROM AUTHOR]

Since the end of 2019, the outbreak of COVID-19 has severely affected port production and operation. There is little research on the systematic impact assessment. This study took Shanghai Port as an example and evaluated the impact under different scenarios through establishing a System Dynamics model. It is found that the epidemic mainly has a greater impact on passenger transport, but less on cargo transport. The ports with the function of transportation in highway, railway, and waterway were the key nodes in the international logistics network. More attention should be paid to the impact assessment of COVID-19 on ports' production and operation. It is necessary to strengthen the port's collection and distribution capabilities, improve port production efficiency, and further strengthen port modernization. This research method proposed in this paper can provide a reference for the impact assessment of similar events, and the empirical results can provide a reference for handling the epidemic shock for the port and shipping departments. [ABSTRACT FROM AUTHOR]

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

Background: The coronavirus disease 2019 (COVID-19) is not just a disease of the respiratory system. The virus can affect the gastrointestinal (GI) tract as well. Recognizing the various manifestations in every organ system is important because these manifestations can contribute to community-based transmission. Methods:We outline the evidence of the pathophysiology of COVID-19 in the GI tract, the effects of the virus on the gut and liver, the presence of the virus in stool samples, and the potential for fecal-oral transmission of COVID-19. Most of the literature sources used in this paper are case studies from China following the surge of COVID-19 infection. Results: In patients with COVID-19, GI symptoms such as anorexia, nausea, vomiting, diarrhea, and abdominal pain have presented in conjunction with respiratory symptoms such as fever, shortness of breath, and cough. Evidence also shows acute hepatocellular injury, indicated by elevated liver enzymes such as alanine aminotransferase, aspartate aminotransferase, and gamma-glutamyl transferase. Fecal-oral transmission of COVID-19 is suspected because of the presence of COVID-19 RNA in stool samples of COVID-19-positive patients. Conclusion: Even without the presence of respiratory symptoms, several GI symptoms are associated with COVID-19 infection, as well as possible fecal-oral transmission. Therefore, COVID-19 infection should be considered for patients presenting with primarily GI symptoms. [ABSTRACT FROM AUTHOR]