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• This paper takes Beijing as a case to study regional economic resilience. • We systematically explore the effects of COVID-19 on industrial dynamics. • Individual-owned firms located in high-risk regions are more vulnerable. • The epidemic shock leads to cascading effects among the local industrial network. The COVID-19 epidemic has altered the economic geographies of cities. However, the academic focus on urban industries and their structural dynamics is far from enough. In this paper, we integrate literature from economic geography, business studies and network sciences, and design an adaptation framework to theorize urban economic resilience. Taking the COVID-19 outbreak in Xinfadi, Beijing during the summer of 2020 as a case study, we use Logit regressions and DID estimations to identify the impacts of the epidemic on local industrial dynamics. Our results support that the COVID-19 outbreak significantly increases the number of business exits. The negative impacts are concentrated in high-risk regions, pointing to specific industries and individual-owned firms. Furthermore, we use a machine learning method to visualize the dynamics of industry networks in a small-scale urban area, and then simulate the transmission paths of industry-failure. In doing so, we contribute to current economic resilience literature that firm-level adaptation and industrial dynamics complement regional adaptation theory, while the cascading effects in the industry network underpin the micro foundations of resilience formation. [ABSTRACT FROM AUTHOR]

• A piecewise COVID-19 is considered. • Dynamics of the proposed models are discussed. • Environmental noises are added to the model for the description in form of stochastic model. • Utilizing Caputo-Fabrizio fractional derivative operator for the purpose of constructing of the fractional-order model. • Numerically solved the proposed models. In the current manuscript, we deal with the dynamics of a piecewise covid-19 mathematical model with quarantine class and vaccination using SEIQR epidemic model. For this, we discussed the deterministic, stochastic, and fractional forms of the proposed model for different steps. It has a great impact on the infectious disease models and especially for covid-19 because in start the deterministic model played its role but with time due to uncertainty the stochastic model takes place and with long term expansion the use of fractional derivatives are required. The stability of the model is discussed regarding the reproductive number. Using the non-standard finite difference scheme for the numerical solution of the deterministic model and illustrate the obtained results graphically. Further, environmental noises are added to the model for the description of the stochastic model. Then take out the existence and uniqueness of positive solution with extinction for infection. Finally, we utilize a new technique of piecewise differential and integral operators for approximating Caputo-Fabrizio fractional derivative operator for the purpose of constructing of the fractional-order model. Then study the dynamics of the models such as positivity and boundedness of the solutions and local stability analysis. Solved numerically fractional-order model used Newton Polynomial scheme and present the results graphically. [ABSTRACT FROM AUTHOR]

The national lockdown policies have drastically disrupted socioeconomic activities during the COVID-19 pandemic in China, which provides a unique opportunity to investigate the air quality response to such anthropogenic disruptions. And it is meaningful to evaluate the potential health impacts of air quality changes during the lockdown, especially for PM 2.5 with adverse health effects. In this study, by using PM 2.5 observations from 1388 monitoring stations nationwide in China, we examine the PM 2.5 variations between the COVID-19 lockdown (February and March in 2020) and the same period in 2015–2019, and find that the national average of PM 2.5 decreases by 18 μg/m3, and mean PM 2.5 for most sites (about 75%) decrease by 30%–60%. The anthropogenic and meteorological contributions to these PM 2.5 variations are also determined by using a stepwise multiple linear regression (MLR) model combined with the Kolmogorov–Zurbenko filter. Our results show that the change of anthropogenic emissions is a leading contributor to those widespread PM 2.5 reductions, and meteorological conditions have the negative influence on PM 2.5 reductions for some regions, such as Beijing–Tianjin–Hebei (BTH). Additionally, the avoided premature death due to PM 2.5 reduction is estimated as a predicted number based on a log-linear concentration-response function. The total avoided premature death is 9952 in China, with dominant contribution (94%) from anthropogenic emission changes. For BTH, Yangtze River Delta, Pearl River Delta and Hubei regions, the reductions of PM 2.5 are 24.1, 24.3, 13.5 and 29.5 μg/m3, with the avoided premature deaths of 1066, 1963, 454 and 583, respectively. [Display omitted] [ABSTRACT FROM AUTHOR]

We conducted a comparative study of the COVID-19 epidemic in three different settings: mainland China, the Guangdong province of China and South Korea, by formulating two disease transmission dynamics models which incorporate epidemic characteristics and setting-specific interventions, and fitting the models to multi-source data to identify initial and effective reproduction numbers and evaluate effectiveness of interventions. We estimated the initial basic reproduction number for South Korea, the Guangdong province and mainland China as 2.6 (95% confidence interval (CI): (2.5, 2.7)), 3.0 (95%CI: (2.6, 3.3)) and 3.8 (95%CI: (3.5,4.2)), respectively, given a serial interval with mean of 5 days with standard deviation of 3 days. We found that the effective reproduction number for the Guangdong province and mainland China has fallen below the threshold 1 since February 8th and 18th respectively, while the effective reproduction number for South Korea remains high until March 2nd Moreover our model-based analysis shows that the COVID-19 epidemics in South Korean is almost under control with the cumulative confirmed cases tending to be stable as of April 14th. Through sensitivity analysis, we show that a coherent and integrated approach with stringent public health interventions is the key to the success of containing the epidemic in China and especially its provinces outside its epicenter. In comparison, we find that the extremely high detection rate is the key factor determining the success in controlling the COVID-19 epidemics in South Korea. The experience of outbreak control in mainland China and South Korea should be a guiding reference for the rest of the world. • We conducted a comparative study of the COVID-19 epidemic in three different settings: mainland China, the Guangdong province of China and South Korea. • We estimated the initial basic reproduction number for South Korea, the Guangdong province and mainland China as 2.6 (95% confidence interval (CI): (2.5, 2.7)), 3.0 (95%CI: (2.6, 3.3)) and 3.8 (95%CI: (3.5,4.2)). • A coherent and integrated approach with stringent public health interventions is the key to the success of containing the epidemic in China and especially its provinces outside its epicenter. • The extremely high detection rate of infected individuals is the key to the success in controlling the epidemics in South Korea. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has brought a lot of working stress to medical workers and has a certain impact on their mental health. Working stress is closely related to the increase in anxiety, but few studies have explored whether their relationship will be affected by positive psychological factors in the special situation.Methods: 798 medical workers were investigated online after the outbreak of the COVID-19 (10 February to 1 March 2020) in China. The relevant questionnaires were used to evaluate working stress, anxiety, sense of control, and psychological capital. The moderated mediation model test was performed using the SPSS software and PROCESS macro program.Results: Working stress could directly affect anxiety, and indirectly affect anxiety through sense of control. In addition, psychological capital moderated the direct effect of working stress on anxiety, which is more effective at high level of psychological capital. Psychological capital also moderated the second half of the indirect effect of working stress on anxiety, at low level of psychological capital, sense of control was more effective in predicting anxiety.Limitations: All the data in this study was collected through online questionnaire. The anxiety response measured in this study cannot be specific to the viral epidemic.Conclusions: Under the COVID-19 epidemic situation, for medical workers, low sense of control and low level of psychological capital may be important risk factors of anxiety caused by working stress. Thus, strengthening the sense of control and psychological capital of medical workers would be helpful to reduce their anxiety and maintain their mental health. [ABSTRACT FROM AUTHOR]

In this study, a nonlinear robust control policy is designed together with a state observer in order to manage the novel coronavirus disease (COVID-19) outbreak having an uncertain epidemiological model with unmeasurable variables. This nonlinear model for the COVID-19 epidemic includes eight state variables (susceptible, exposed, infected, quarantined, hospitalized, recovered, deceased, and insusceptible populations). Two plausible scenarios are put forward in this article to control this epidemic before and after its vaccine invention. In the first scenario, the social distancing and hospitalization rates are employed as two applicable control inputs to diminish the exposed and infected groups. However, in the second scenario after the vaccine development, the vaccination rate is taken into account as the third control input to reduce the susceptible populations, in addition to the two objectives of the first scenario. The proposed feedback control measures are defined in terms of the hospitalized and deceased populations due to the available statistical data, while other unmeasurable compartmental variables are estimated by an extended Kalman filter (EKF). In other words, the susceptible, exposed, infected, quarantined, recovered, and insusceptible individuals cannot be identified precisely because of the asymptomatic infection of COVID-19 in some cases, its incubation period, and the lack of an adequate community screening. Utilizing the Lyapunov theorem, the stability and bounded tracking convergence of the closed-loop epidemiological system are investigated in the presence of modeling uncertainties. Finally, a comprehensive simulation study is conducted based on Canada's reported cases for two defined timing plans (with different treatment rates). Obtained results demonstrate that the developed EKF-based control scheme can achieve desired epidemic goals (exponential decrease of infected, exposed, and susceptible people). • A hypothetical robust control policy to manage the COVID-19 outbreak. • Two scenarios for the epidemic control before and after the vaccine development. • Hospitalized and deceased populations are the only available feedback data. • EKF is used to estimate other unmeasurable compartments' populations. • Lyapunov theorem is employed to ensure the controlled epidemic's stability. [ABSTRACT FROM AUTHOR]

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Background: Coronavirus disease 2019 (COVID-19) is leading to numerous psychological outcomes, especially emotional distress. Individuals with early life adversity (ELA) may be more susceptible to those psychological stresses during this epidemic.Aims: To measure the effect of the ELA on acute stress reactions, anxiety and depression during the COVID-19 epidemic, and to examine whether specific trauma types and frequencies of exposure are associated with a more severe acute stress reaction and increased risk of anxiety and depressive symptoms.Method: This investigation was performed at college students in a comprehensive University of China. The online self-report questionnaire included ELA experiences, exposure to epidemic-related events, acute stress reactions, and anxiety and depression symptoms during the COVID-19 epidemic. Logistic regression and stepwise regression were used to assess the associations and interactions among these variables.Results: Participants with ELA reported more exposure to epidemic-related events and more severe stress reactions during the epidemics than did those with no ELA. The experience of ELA is associated with acute stress reactions, anxiety and depression in early adulthood. Furthermore, experiencing more ELA during childhood may not only increase the risk of anxiety and depression episode in early adulthood but also lead to more severe acute stress reactions during the epidemic.Conclusion: Regardless of specific ELA types, ELAs have longer time effects on individual's susceptibility to stress. Under this epidemic, the mental health in young adults with ELA needs more attention. [ABSTRACT FROM AUTHOR]

The strict control measures and social lockdowns initiated to combat COVID-19 epidemic have had a notable impact on air pollutant concentrations. According to observation data obtained from the China National Environmental Monitoring Center, compared to levels in 2019, the average concentration of NO 2 in early 2020 during COVID-19 epidemic has decreased by 53%, 50%, and 30% in Wuhan city, Hubei Province (Wuhan excluded), and China (Hubei excluded), respectively. Simultaneously, PM 2.5 concentration has decreased by 35%, 29%, and 19% in Wuhan, Hubei (Wuhan excluded), and China (Hubei excluded), respectively. Less significant declines have also been found for SO 2 and CO concentrations. We also analyzed the temporal variation and spatial distribution of air pollutant concentrations in China during COVID-19 epidemic. The decreases in PM 2.5 and NO 2 concentrations showed relatively consistent temporal variation and spatial distribution. These results support control of NO x to further reduce PM 2.5 pollution in China. The concurrent decrease in NO x and PM 2.5 concentrations resulted in an increase of O 3 concentrations across China during COVID-19 epidemic, indicating that coordinated control of other pollutants is needed. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Background: Somatization is a common comorbidity in anxious people. From January 31 to February 2, 2020, a high prevalence of moderate to severe anxiety was detected due to COVID-19 outbreak. The purpose of this study was to investigate the prevalence and correlates of somatization among Chinese participants with anxiety receiving online crisis interventions from Feb 14 to Mar 29 during the COVID-19 epidemic.Methods: A total of 1134 participants who participated in online crisis interventions completed the Generalized Anxiety Disorder-7 (GAD-7) scale and the Symptom Checklist-90 (SCL-90) and demographic questions online. Somatization was defined as the average score of each item ≥ 2 in SCL-90 somatization subscale. Moderate to severe anxiety was defined as a score ≥ 10 in the GAD-7 scale.Results: Among all participants, 8.0% reported moderate to severe anxiety and 7.4% reported somatization. After March 1, the prevalence of anxiety with or without somatization did not significantly change (both p > 0.05), while the prevalence of somatization increased significantly (p < 0.01). Logistic regression analysis indicated that somatization was associated with chronic disease history (with an odds ratio of 4.80) and female gender (with an odds ratio of 0.33).Conclusions: Our findings suggest that the history of chronic diseases is associated with somatization in individuals with anxiety, indicating some stress-related mechanisms. Chinese men in crisis intervention need more attention because they are more likely to report anxiety comorbid somatization. [ABSTRACT FROM AUTHOR]

• Acute respiratory distress syndrome due to SARS-CoV-2 and Influenza A co-infection. • Challenging in co-infection cases identification. • Improvement of preventive measures and patients' clinical outcome. A case of acute respiratory distress syndrome due to SARS-CoV-2 and Influenza A co-infection and a mini-review of the literature is reported. Even in COVID-19 epidemics, the early identification of concurrent respiratory pathogens is important to improve etiological diagnosis, preventive measures and patients' clinical management and outcome. [ABSTRACT FROM AUTHOR]

• COVID-19 has caused a significant drop in metro commuting ridership in the short term. • Metro commuting ridership rebounded rapidly as the pandemic subsided and returned to pre-pandemic levels within six months. • There is significant spatial heterogeneity in the ridership during the rebound. • The built environment has a significant impact on the recovery of metro commuting ridership. • Interruption Time Series analysis revealed spatial and temporal impact of the pandemic on metro's ridership. The COVID-19 pandemic has had a significant impact on metro commuting ridership. However, the exact magnitude and spatial and temporal characteristics of the impact remain unclear. In this study, we explored the impact of the COVID-19 outbreak on metro commuting ridership in Wuhan, where the novel virus was first reported. The results of interrupted time-series (ITS) analysis showed that metro commuting ridership sharply dropped in the short term under the impact of the outbreak in the epicenter, rebounded rapidly as the pandemic eased, and returned to pre-pandemic levels in six months. Furthermore, there was a noticeable spatial heterogeneity in the rebound. Urban centers, especially job-rich areas, recovered faster than other areas. In addition, the number of residents, number of bus stops, number of enterprises around a metro station, and being a transfer station had a positive effect on metro ridership, while street length, number of restaurants, and number of metro exits had a negative effect. These findings may help local governments and metro managers develop sustainable metro operations and infection prevention policies to better cope with the impact of the pandemic and beyond. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic was a serious global health emergency in 2020 and 2021. This study analyzed the seasonal association of weekly averages of meteorological parameters, such as wind speed, solar radiation, temperature, relative humidity, and air pollutant PM2.5, with confirmed COVID-19 cases and deaths in Baghdad, Iraq, a major megacity of the Middle East, for the period June 2020 to August 2021. Spearman and Kendall correlation coefficients were used to investigate the association. The results showed that wind speed, air temperature, and solar radiation have positive and strong correlations with the confirmed cases and deaths in the cold season (autumn and winter 2020–2021). The total COVID-19 cases negatively correlated with relative humidity but were not significant in all seasons. Besides, PM2.5 strongly correlated with COVID-19 confirmed cases for the summer of 2020. The death distribution by age group showed the highest deaths for those aged 60–69. The highest number of deaths was 41% in the summer of 2020. The study provided useful information about the COVID-19 health emergency and meteorological parameters, which can be used for future health disaster planning, adopting prevention strategies and providing healthcare procedures to protect against future infraction transmission. [Display omitted] • Meteorological parameters have positive correlation with COVID-19 infections. • Relative humidity has negative and irrelevant correlation with COVID-19 infection. • PM 2.5 has only a positive correlation with COVID-19 infection in summer 2020. • Age group 60–69 years has the highest deaths average during the current study. • Percentage of vaccinated people did not exceed 3% of the population end August 2021. [ABSTRACT FROM AUTHOR]

The outbreak of Covid-19 epidemic has a prolonged impact on global economic activities. In recent years, many scholars have been motivated to estimate the effects of Covid-19 shock on global foreign direct investment (FDI). However, existing studies have not paid enough attention to the spillover effects caused by the epidemic. Although few academic works have explored the geographic-neighboring spillover effects of epidemic shock on global investment, we further extent the understanding of the spillover effects in an economic network. On the basis of country-month greenfield FDI panels, we construct a spatial Durbin model, and figure out that Covid-19 shock may have positive FDI spillover effects in an economic network via global FDI transfers. Furthermore, we find that such spillovers are greatly conditioned by country-level network position and institutional ties among nations. Our research suggests that global FDI transfers may partly offset economic-adverse effects of the Covid-19 shock. While global countries, especially those in the Global South, should be more closely embedded in the global investment network in such an uncertain environment. • This paper investigates the spillover effects of Covid-19 epidemic on global greenfield investment network. • Covid-19 would shift much more overseas greenfield investment projects to the victim's neighbor on the economic network. • Such potential positive spillovers are conditioned by country-level network position and institutional ties among nations. • The research suggests that the Global South countries should be closely embedded in the global investment network in an uncertain environment. [ABSTRACT FROM AUTHOR]

As an abrupt epidemic occurs, healthcare systems are shocked by the surge in the number of susceptible patients' demands, and decision-makers mostly rely on their frame of reference for urgent decision-making. Many reports have declared the COVID-19 impediments to trading and global economic growth. This study aims to provide a mathematical model to support pharmaceutical supply chain planning during the COVID-19 epidemic. Additionally, it aims to offer new insights into hospital supply chain problems by unifying cold and non-cold chains and considering a wide range of pharmaceuticals and vaccines. This approach is unprecedented and includes an analysis of various pharmaceutical features such as temperature, shelf life, priority, and clustering. To propose a model for planning the pharmaceutical supply chains, a mixed-integer linear programming (MILP) model is used for a four-echelon supply chain design. This model aims to minimize the costs involved in the pharmaceutical supply chain by maintaining an acceptable service level. Also, this paper considers uncertainty as an intrinsic part of the problem and addresses it through the wait-and-see method. Furthermore, an unexplored unsupervised learning method in the realm of supply chain planning has been used to cluster the pharmaceuticals and the vaccines and its merits and drawbacks are proposed. A case of Tehran hospitals with real data has been used to show the model's capabilities, as well. Based on the obtained results, the proposed approach is able to reach the optimum service level in the COVID conditions while maintaining a reduced cost. The experiment illustrates that the hospitals' adjacency and emergency orders alleviated the service level significantly. The proposed MILP model has proven to be efficient in providing a practical intuition for decision-makers. The clustering technique reduced the size of the problem and the time required to solve the model considerably. • Merging cold and non-cold chains to help hospitals handling supply chain challenges. • Supporting decision-makers during epidemics by proposing a novel mathematical model. • Considering various pharmaceuticals and their features using K-means clustering. • Multi-commodity supply chain benefits from unsupervised learning for clustering. • Considering features of various phases of epidemics by adjusting model parameters. [ABSTRACT FROM AUTHOR]

The COVID-19 epidemic made the most countries to take strict lockdown measures, what has seriously caused an unprecedented impact in the shipping industries, whereas these measures have also played a significant impact to control carbon emissions from international shipping. Here, we try to use the threshold generalized autoregressive conditional heteroscedasticity and the exponential generalized autoregressive heteroscedasticity to investigate whether the fluctuations of the control variable on carbon emissions from international shipping are asymmetric or not. On this basis, the GARCH-MIDAS model is introduced to discuss whether the newly confirmed cases are independent of control variables and have an impact on the fluctuation of carbon emissions. From the results, we find that the information contained in the newly confirmed cases cannot be covered when adding the other control variables. In addition, the newly confirmed cases have a negative impact on the volatility of carbon emissions, while the other control variables significantly increase carbon emissions. This study provides a quantitative research method for the analysis of the volatility and impact factors on international shipping carbon emissions, which helps to formulate more reasonable emission reduction measures and promote the low-carbon transformations of the global shipping industry. [Display omitted] • Explore the impact of the COVID-19 epidemic on carbon emissions from international shipping • Build GARCH-MIDAS model by adding control variables about the COVID-19 epidemic • Analyze the effectiveness of the COVID-19 epidemic on the fluctuation of carbon emissions from international shipping • The COVID-19 epidemic has obviously reduced the fluctuation of carbon emissions from international shipping. [ABSTRACT FROM AUTHOR]

As the new coronavirus pandemic enters its third year, its long-term impact on the urban environment cannot be ignored, especially in megacities with more than millions of people. Here, we analyzed the changes in the concentration levels, emission sources, temporal variations and holiday effects of ambient fine particulate matter (PM 2.5) and its chemical components in the pre- and post-epidemic eras based on high-resolution, long time-series datasets of PM 2.5 and its chemical components in Chengdu. In the post-epidemic era, the PM 2.5 concentration in Chengdu decreased by 7.4%, with the components of PM 2.5 decreasing to varying degrees. The positive matrix factorization (PMF) results indicated that the emissions from soil dust and industrial production were significantly lower during the COVID-19 lockdown period and post-epidemic era than those in the pre-epidemic era. In contrast, the contribution of secondary aerosols to PM 2.5 during these two periods increased by 2.7% and 6.6%, respectively. Notably, we found that PM 2.5 and its components substantially decreased on workdays and holidays in the post-epidemic era due to the reduced traffic volume and outdoor activities. This provides direct evidence that changes in the habitual behavior patterns of urban residents in the post-epidemic era could exert an evident positive impact on the urban environment. However, the higher PM 2.5 concentration was observed due to the increased consumption of regular (As 4 S 4 , Xionghuang in Chinese) and "sulfur incense" during the Dragon Boat Festival holiday in the post-epidemic era. Finally, we examined the potential effects of sporadic COVID-19 outbreaks on the PM 2.5 concentration in Chengdu, and there was no decrease in PM 2.5 during two local COVID-19 outbreak events due to the strong influence of secondary pollution processes. • Long-term impacts of the COVID-19 epidemic on urban PM 2.5 were analyzed. • Emissions from transportation and industry reduced in the post-epidemic era. • PM 2.5 concentration significantly dropped over workdays and holidays in the post-epidemic era. • PM 2.5 concentration conversely increased during the Dragon Boat Festival in the post-epidemic era. [ABSTRACT FROM AUTHOR]

The fight against the COVID-19 epidemic significantly raises the global demand for personal protective equipment, especially disposable face masks (DFMs). The discarded DFMs may become a potential source of microplastics (MPs), which has attracted much attention. In this work, we identified the detailed source of MPs released from DFMs with laser direct infrared spectroscopy. Polypropylene (PP) and polyurethane (PU) accounted for 24.5% and 57.1% of released MPs, respectively. The melt-blown fabric was a dominant MPs source, however, previous studies underestimated the contribution of mask rope. The captured polyethylene terephthalate (PET), polyamide (PA), polyethylene (PE), and polystyrene (PS) in airborne only shared 18.4% of released MPs. To deepen the understanding of MPs release from medical mask into the aquatic environment, we investigated the effects of environmental factors on MPs release. Based on regression analysis, the effects of temperature, incubation time, and wearing time significantly affect the release of MPs. Besides, acidity, alkalinity, sodium chloride, and humic acid also contributed to the MPs release through corroding, swelling, or repulsion of fibers. Based on the exposure of medical mask to simulated environments, the number of released MPs followed the order: seawater > simulated gut-fluid > freshwater > pure water. Considering the risk of MPs released from DFMs to the environment, we innovatively established a novel flotation removal system combined with cocoamidopropyl betaine, achieving 86% removal efficiency of MPs in water. This work shed the light on the MPs release from DFMs and proposed a removal strategy for the control of MPs pollution. [Display omitted] • Mask rope was identified as a dominant source of microplastics. • Temperature, wearing time, and incubation time promoted microplastics release. • The release of microplastics was affected by pH, sodium chloride, and humic acid. • Disposable face mask released more microplastics in seawater and gut-fluid. • Froth flotation with cocoamidopropyl betaine removed microplastics efficiently. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic lockdowns led to a sharp drop in socio-economic activities in China in 2020, including reductions in fossil fuel use, industry productions, and traffic volumes. China's economy suffered a serious negative effect from COVID-19. However, there is a "positive effect" on CO 2 emissions reduction. Here, for the first time, this paper constructs a new model named "Weighted Multi-regional Hypothetical Extraction Method (WMHEM)" based on a multiregional input-output model. It not only solves the problems of traditional HEM methods such as improper use of assumptions, excessive reliance on industry intermediate input, but also accurately reflects the impact of external shocks on the inter-industry linkages. By using the monthly economic data of each provinces in China during COVID-19 (except Hong Kong，Macao and Taiwan) an the latest Multi-regional input-output tables, the "economic negative effect" and "CO 2 emission positive effect" under COVID-19 in China are measured. Results show that COVID-19 lockdown was estimated to have reduced China's CO 2 emissions substantially between January and March in 2020, with the largest reductions in February. With the spread of coronavirus controlled, China's CO 2 emissions rebounded in April. In addition, key emission reduction sectors and key development encouraged sectors are selected by combining "economic negative effect" and "CO 2 emission positive effect" during COVID-19. Therefore, policies recommendations are put forward based on forward and backward linkages respectively which are from two ends of the supply chain to turn pandemic-related CO 2 emissions declines into firm climate action. • COVID-19 has negative effects on economy, but positive effects on CO 2 emissions. • A new model is used to measure economic and CO 2 emission effects during COVID-19. • Hubei had the biggest economic and CO 2 emission effects on China due to COVID-19. • Economic and CO 2 emission effects of COVID-19 are combined to select key sectors. [ABSTRACT FROM AUTHOR]

Network control theory is first applied here to study the controllability of a High-speed Rail Network (HRN) in terms of delivering emergency supplies. The full controllability or target controllability of an HRN (i.e., controlling the amount of emergency supplies delivered at all stations or target control stations) can be achieved when the amount of emergency supplies transported from some appropriate stations is efficiently controlled. To identify the optimized controlling stations, a model is proposed for minimizing the number of controlling stations and maximizing the sum of trains departing from controlling stations, which effectively and quickly controls an HRN in terms of delivering emergency supplies. The proposed model is demonstrated in a case in which the delivery of emergency supplies by China's HRN is controlled during the COVID-19 epidemic. The result shows that the sum of trains departing from the optimized controlling stations obtained through the proposed method is higher than that of the optimized controlling stations obtained through the commonly used maximum match method, and thus, the proposed method can obtain a better solution. The proposed method helps operators to identify the optimized controlling stations for effectively controlling an HRN in terms of delivering emergency supplies, and thus helping respond to emergency events. • Achieves full or target controllability of a high-speed rail network in terms of delivering emergency supplies. • Optimizes the set of stations for the controllability of a high-speed rail network. • The model is effective in fully controlling China's high-speed rail network for delivering medical supplies during the COVID-19 epidemic. [ABSTRACT FROM AUTHOR]

In this study, we use the sample data from Jan 22, 2020 to Jan 21, 2022 to investigate the impacts of added infection number on the volatility of BDI. Under this structure, the control variables (freight rate, Brent crude oil price, container idle rate, port congestion level, global port calls) are added to test whether the information contained in the added infection number is covered. In the GARCH-MIDAS model, we divide the volatility of BDI into the long-term and short-term components, then employ in the least squares regression to empirically test the influences of added infection number on the volatility. From the analysis, we find the added infection numbers effectively impact the BDI volatility. In addition, whether the freight rate, Brent crude oil price, container idle rate, port congestion level, global port calls and other variables are considered alone or at the same time, further the added infection number still significantly influences the volatility of BDI. By studying the ability of the confirmed number to explain the volatility of BDI, a new insight is provided for the trend prediction of BDI that the shipping industry can take the epidemic development of various countries as a reference to achieve the purpose of cost or risk control. [ABSTRACT FROM AUTHOR]

This paper introduces thermal optimal path method to investigate the dynamics lead-lag relationship of jumps among Chinese stock index and futures market under the background of the Covid-19 epidemic. Based on three representative stock indexes and their index futures in China, we find the lead-lag structure changes significantly before and after the outbreak of COVID-19. Before the epidemic, there is mutual effect between different markets jumps. However, CSI 300 futures and SSE 50 futures significantly lead other markets for the after-epidemic period. For the volatility forecasting based on cross-market jumps, the lagged jumps of CSI 300 and SSE 50 index futures have significantly impacts on the volatility forecast of other markets. [Display omitted] • Thermal optimal path method is used to investigate lead-lag relation of jumps among stock index and futures market. • The lead-lag structure changes significantly before and after the outbreak of COVID-19. • CSI 300 futures and SSE 50 futures significantly lead other markets for the after-epidemic period. • The lagged jumps of CSI 300 and SSE 50 index futures impact the volatility of other markets. [ABSTRACT FROM AUTHOR]

To investigate changing characteristics of the industrial correlation and economic contribution of air transport in China in different periods, the industry linkage effect and the industry ripple effect of air transport were assessed based on an input–output analysis over the period 2007–2020. Taking the air transport sector as an exogenous variable, the production-inducing effect and the supply shortage effect were calculated, and their changing characteristics were analyzed. The result shows that China's air transport industry is gradually changing its close linkages with secondary industries, and is instead strengthening its interaction with some tertiary industries. Before the COVID-19 outbreak in 2020, the production-inducing multiplier of air transport was trending downwards and the supply shortage multiplier was trending upwards. After the COVID-19 outbreak, China's air transport industry was hit hard and both the production-inducing effect and the supply shortage effect decreased significantly. The results of this paper are of great significance in the evaluation of the industrial correlation and economic contribution of air transport and can serve as a reference for formulating policies and improving the management of the air transport industry. • The industrial correlation of air transport in China in different periods are studied. • The economic contribution of air transport to China's national economy are analyzed. • Policy implications are presented to formulate regulations and improve management. [ABSTRACT FROM AUTHOR]

• SARS-CoV-2 RNA presence was measured at 24 locations in the Prague sewer network. • Residential areas (100–13,000 inhab.), transport hubs, hospitals etc. were included. • Consistent wastewater monitoring by RT-mqPCR took place from August 2020–May 2021. • The sampling of major Prague sewers correlated well with clinical-based data. • Grab samples can identify COVID-19 hotspots in local neighborhoods. Many reports have documented that the presence of SARS-CoV-2 RNA in the influents of municipal wastewater treatment plants (WWTP) correlates with the actual epidemic situation in a given city. However, few data have been reported thus far on measurements upstream of WWTPs, i.e. throughout the sewer network. In this study, the monitoring of the presence of SARS-CoV-2 RNA in Prague wastewater was carried out at selected locations of the Prague sewer network from August 2020 through May 2021. Various locations such as residential areas of various sizes, hospitals, city center areas, student dormitories, transportation hubs (airport, bus terminal), and commercial areas were monitored together with four of the main Prague sewers. The presence of SARS-CoV-2 RNA was determined by reverse transcription – multiplex quantitative polymerase chain reaction (RT-mqPCR) after the precipitation of nucleic acids with PEG 8,000 and RNA isolation with TRIzol™ Reagent. The number of copies of the gene encoding SARS-CoV-2 nucleocapsid (N1) per liter of wastewater was compared with the number of officially registered COVID-19 cases in Prague. Although the data obtained by sampling wastewater from the major Prague sewers were more consistent than those obtained from the small sewers, the correlation between wastewater-based and clinical-testing data was also good for the residential areas with more than 7,000 registered inhabitants. It was shown that monitoring SARS-CoV-2 RNA in wastewater sampled from small sewers could identify isolated occurrences of COVID-19-positive cases in local neighborhoods. This can be very valuable while tracking COVID-19 hotspots within large cities. [Display omitted] [ABSTRACT FROM AUTHOR]

In the context of the Covid-19, the present study designed a longitudinal study to examine the relationship among interpersonal alienation, meaning in life and smartphone addiction. Meanwhile, with the development of the epidemic whether there would be changes in the three variables was also examined. A sample of 579 university students (baseline mean age = 20.59, SD = 2.20) finished the anonymous questionnaires about interpersonal alienation, meaning in life and smartphone addiction. Three repeated measurements were obtained in June, September and December 2020. The finding indicated that university students' interpersonal alienation and meaning in life significantly increased, and the risk of smartphone addiction significantly decreased with the epidemic under control. Besides, meaning in life in the middle mitigating period of the epidemic mediated the relationship between interpersonal alienation in the early severe period of the epidemic and smartphone addiction in the basic end period of the epidemic. The study contributes to our understanding of how low levels of interpersonal alienation may improve meaning in life and reduce the risk of smartphone addiction. What' s more, it provides scientific suggestions for the prevention and intervention of the adverse effects during public health emergencies. • Interpersonal alienation and meaning in life increased with the epidemic under control. • The risk of smartphone addiction decreased with the epidemic under control. • Interpersonal alienation negatively predicted subsequent meaning in life. • Interpersonal alienation positively predicted subsequent smartphone addiction. • Meaning in life had indirect effects on interpersonal alienation and smartphone addiction. [ABSTRACT FROM AUTHOR]

The unexpected outbreak of COVID-19 epidemic is an unpredictable event in shipping trade. In this paper, we mainly investigate the gaps that occur in the shipping trade between China and different regions during the period February-October 2020 and to provide useful information for operation management of shipping industry. The data include a panel obtained from the National Statistics Institute to analyze the gap where a selected group of shipping trade in three regions are considered: European Union, North America, and Southeast Asia. On this basis, a dynamic panel data model is proposed to estimate the trend. We observe that government prevention and control measures have a negative impact on export trade, while import trade increases accordingly. [ABSTRACT FROM AUTHOR]

Keywords: Surgery; Appendicitis; Cholecystitis; Emergency; COVID-19 epidemic EN Surgery Appendicitis Cholecystitis Emergency COVID-19 epidemic S5 S6 2 06/23/20 20200602 NES 200602 For some weeks now we have been experiencing an unprecedented COVID-19 pandemic that has had a profound impact on our routine surgical activities. All French surgery teams in all branches have adjusted their activity, curtailing out-patient surgery and deferring scheduled operations as much as possible, in particular major cancer surgery, so as to free medical and paramedical staff to take care of patients admitted with COVID-19. Likewise, there might be a temptation to treat uncomplicated acute cholecystitis medically to defer surgery until after the Covid-19 crisis has passed, or to opt for a colonic stent for an obstructive tumour rather than immediate surgery. [Extracted from the article]

This study models the return distributions of the Shanghai Security Composite Index (SSCI) by adding sentiment-aware variables (attention, sentiment, and disagreement), which may affect the jump intensity dynamics or changing the jump size variance, into the GARJI model of Maheu and McCurdy (2004). Textual analysis with some state-of-art machine-learning and deep-learning algorithms is used to select investor sentiment-aware variables with better performance. The extended models (GARJI-sentiment models), which incorporate the sentiment-aware variables into GARJI model, have better forecasting powers on volatilities and extreme events than the benchmark GARJI model. The significant influence of sentiment-aware variables on the jumps and conditional variances implies bounded rationality of investors. Our case study further provides some evidence that Black Swan events, including the implementation of the circuit breaker rule and the lockdown of Wuhan during the COVID-19 epidemic, could affect market jump risks and conditional variances by influencing the sentiment-aware variables, especially investor attention. [ABSTRACT FROM AUTHOR]

• Stressful events of the COVID-19 epidemic are negatively associated with adolescents' suicidal ideation. • Depression mediates the association between stressful events and adolescents' suicidal ideation. • Adolescents' parental educational involvement significantly moderated the path from depression to suicidal ideation. This study examined the association between stressful events and adolescents' suicidal ideation and determined the roles of depression as a mediator and parental educational involvement as a moderator during the COVID-19 epidemic. Survey data from a sample of 1595 Chinese adolescents and their parents were subjected to path analysis. The results indicated that stressful events of the COVID-19 epidemic were significantly positively associated with adolescents' suicidal ideation, and this association was mediated by depression. In addition, adolescents' parental educational involvement significantly moderated the path from depression to suicidal ideation. These results highlight the importance of identifying the underlying key mechanisms that moderate the mediated paths between stressful events and adolescents' suicidal ideation during the COVID-19 epidemic. The findings also provide implications for parents and education staff regarding the importance of improving parental educational involvement to prevent adolescents' suicidal ideation during the COVID-19 epidemic. [ABSTRACT FROM AUTHOR]

As a preventive measure during the COVID-19 epidemic, we have had to stay at home for a long time. The lifestyle of adolescents has undergone severe changes. Almost every school started online education for the first time. Some adolescents have shown low resilience when faced with these changes. Most previous research has focused on mindfulness training and resilience by using cross-sectional or two-point tracking designs. However, little is known about the developmental trajectories of the impact of mindfulness training on resilience, particularly during this epidemic. Therefore, this study aims to explore how the developmental trajectories of resilience are impacted by mindfulness training. After administering the CD-RISC, we recruited 90 students with low levels of resilience in intervention group. Finally, 84 adolescents provided data at each assessment. At the same time, we selected 90 students in the control group. Paired sample t -test was used to compare every factor defined above by time. The result showed that mindfulness training increased students' resilience and emotional intelligence in experiment group. Then in the experiment group, latent growth modeling was used to (1) examine initial levels and changes in resilience over time and (2) predict initial levels and growth in resilience based on emotional intelligence. The findings of this study are as follows: during a mindfulness training intervention, (1) individual resilience tends to increase, and rate of increase grows gradually; there are also significant individual differences in the initial level and development speed; (2) individual emotional intelligence can promote the growth of resilience. With the worldwide outbreak of COVID-19, more and more attention is paid to the mental health of students. The research in this article shows that mindfulness training program should be given increasing consideration in the future. [ABSTRACT FROM AUTHOR]

With the global outbreak of COVID-19, people are facing great physical and mental stress, and mental health problems are becoming increasingly prominent. Some theories emphasize the role of family in people's mental health, but the association between family functioning and mental health and the mediating and moderating mechanisms underlying this relation have not been extensively researched. This study examined whether loneliness mediates the relation between family functioning and mental health and, if so, whether this mediating effect is moderated by hope. A total of 5783 Chinese secondary vocational students completed measures of family adaptability and cohesion, loneliness, mental health, and hope. The results indicated that family functioning had a significant and positive predictive effect on the mental health of the students and that this relationship was partially mediated by loneliness. Further, hope moderated the relationship between family functioning and loneliness. Specifically, the relationship between family functioning and loneliness was significant for students with both high and low levels of hope. The current study contributes to a better understanding of the influence of family functioning on mental health, especially during trying times such as the COVID-19 epidemic. • The family functioning was positively associated with mental health. • Loneliness mediated the relationship between family functioning and mental health. • Hope moderated the relationship between family functioning and loneliness. [ABSTRACT FROM AUTHOR]

• Depression and anxiety symptoms among Chinese undergraduate students under the COVID-19 epidemic were measured. • Depression and anxiety symptoms positively predicted problematic smartphone use. • Resilience, perceived social support and the sense of school belonging mediated these relationships. COVID-19 epidemic has brought wide psychological impacts on the young adults. To investigate the depression and anxiety symptoms and their associations with problematic smartphone use under the COVID-19 epidemic, a total of 847 Chinese undergraduate students joined in this study and were measured with their levels of depression and anxiety symptoms, resilience, perceived social support, the sense of school belonging and problematic smartphone use. Results showed that among the Chinese undergraduate students, the disorder rates of depression and anxiety symptoms were 29.16% and 46.64% respectively, and their symptoms ranged from mild to extreme severe. Depression and anxiety symptoms both positively predicted problematic smartphone use. Resilience, perceived social support and the sense of school belonging partially mediated both associations; resilience and the sense of school belonging exerted buffering effects, while perceived social support exacerbated the impacts. The current study advanced our understanding of the COVID-19 impacts and furthermore, suggested the protective factors for mitigating these impacts. [ABSTRACT FROM AUTHOR]

With the outbreak of COVID-19 (Corona Virus Disease, 2019), China adopted traffic restrictions to reduce the spread of COVID-19. Using daily data before and after the outbreak of COVID-19, an exogenous shock, this paper analyzes the effects of private vehicle restriction policies on air pollution. We find that the private vehicle restriction policies reduce the degree of air pollution to a certain extent. However, their effect varies with other policies implemented in the same period and the economic development of the city itself. Through the analysis of different categories of restrictions, we find that restriction policy for local fuel vehicles and the restriction policy based on the last digit of license plate numbers have the best effect in reducing air pollution. Under the background of COVID-19 epidemic and the implementation of private vehicle restriction policies and other traffic control policies during this period, we have also obtained other enlightenment on air pollution control. • The causal relationship between air pollution and restriction is analyzed. • An exogenous shock from COVID-19 is used to identify this relationship. • The private vehicle restriction reduces the degree of air pollution. • The restriction policies have heterogeneous effects. • The effects of restriction are affected by other policies against COVID-19. [ABSTRACT FROM AUTHOR]

This paper looks into the impact of the recent COVID-19 epidemic on the daily mobility of people. Existing research into the epidemic travel patterns points at transport as a channel for disease spreading with especially long-distance travel in the centre of interest. We adopt a different approach looking into the effects that epidemic has on the transport system and specifically in relation to short-distance daily mobility activities. We go beyond simple travel avoidance behaviours and look into factors influencing change in travel times and in modal split under epidemic. This leads to the research problems we posit in this paper. We look into the overall reduction of daily travel and into the factors impacting peoples' decisions to refrain from daily traveling. This paper focuses on modes affected and explores differences between various societal groups. We use a CATI survey with a representative sample size of 1069 respondents from Poland. The survey was carried out between March, 24th and April, 6th2020, with a start date one week after the Polish government introduced administrative measures aimed at slowing down the COVID-19 epidemic. For data analysis, we propose using the GLM (general linear model), allowing us to include all the qualitative and quantitative variables which depict our sample. We observe significant drops in travel times under epidemic conditions. Those drops are similar regardless of the age group and gender. The time decrease depended on the purpose of travels, means of transport, traveller's household size, fear of coronavirus, main occupation, and change in it caused by the epidemic. The more the respondent was afraid of coronavirus, the more she or he shortened the travel time. • CATI survey reveals significant drops in daily travel times during epidemic. • The research confirms the effectiveness of mobility restrictions. • Travel time drops are similar regardless of the age group and gender. • Main occupation is the key factor affecting travel time change. • The more one was afraid of coronavirus, the bigger the travel time reduction was. [ABSTRACT FROM AUTHOR]

The epidemic is affecting the global economy, plunging many industries. The global extent of the epidemic and government controls, restrictions and constraints have led to imbalances in world trade and have put many companies under pressure. The epidemic is a test of individual companies' ability to operate effectively in the new environment. It is up to managers to mitigate its impact on business. The aim of the article is to identify the activities of employers in Poland related to the protection of workers with the developing epidemic COVID-19. A survey was carried out among the employees of OHS services employed in enterprises in Poland. The research was conducted in three stages at two-week intervals. The obtained results were subjected to statistical analyses. In the analysed three periods a total of 588 answers were obtained, which allowed to formulate conclusions. The research showed that in connection with the COVID-19 epidemic, about 30% of the plants updated their occupational risk assessment, about 40% updated their safety instructions, about 90% of the plants equipped their employees with additional personal protective equipment. The COVID-19 outbreak in Poland resulted in taking additional actions by employers to protect workers. Systematicity (methodicality) of these activities depended mainly on the seniority of the OHS service. As a border internship indicating a different approach to an emergency situation related to the epidemic, 7 years were set. [ABSTRACT FROM AUTHOR]

COVID-2019 is a global threat, for this reason around the world, researches have been focused on topics such as to detect it, prevent it, cure it, and predict it. Different analyses propose models to predict the evolution of this epidemic. These analyses propose models for specific geographical areas, specific countries, or create a global model. The models give us the possibility to predict the virus behavior, it could be used to make future response plans. This work presents an analysis of COVID-19 spread that shows a different angle for the whole world, through 6 geographic regions (continents). We propose to create a relationship between the countries, which are in the same geographical area to predict the advance of the virus. The countries in the same geographic region have variables with similar values (quantifiable and non-quantifiable), which affect the spread of the virus. We propose an algorithm to performed and evaluated the ARIMA model for 145 countries, which are distributed into 6 regions. Then, we construct a model for these regions using the ARIMA parameters, the population per 1M people, the number of cases, and polynomial functions. The proposal is able to predict the COVID-19 cases with a RMSE average of 144.81. The main outcome of this paper is showing a relation between COVID-19 behavior and population in a region, these results show us the opportunity to create more models to predict the COVID-19 behavior using variables as humidity, climate, culture, among others. [ABSTRACT FROM AUTHOR]

The most important features to assess the severity of an epidemic are its size and its timescale. We discuss these features in a systematic way in the context of SIR and SIR-type models. We investigate in detail how the size and timescale of the epidemic can be changed by acting on the parameters characterizing the model. Using these results and having as guideline the COVID-19 epidemic in Italy, we compare the efficiency of different containment strategies for contrasting an epidemic diffusion such as social distancing, lockdown, tracing, early detection and isolation. • We discuss the expected outcome of different COVID-19 contrasting strategies. • Special attention is devoted to how long a total or partial lockdown should be. • Limiting the action to social distancing can lead to a dramatically long time scale. • Tracking of contacts allows to shorten the epidemic time-scale. [ABSTRACT FROM AUTHOR]

• SARS-CoV-2 exhibits intra-host small- and large-scale genomic variability. • SNVs are collocalized with probes and primers used in molecular diagnostic assays. • SARS-CoV-2 Spike (S) gene host a potential recombination hot-spot. In December 2019, an outbreak of atypical pneumonia (Coronavirus disease 2019 -COVID-19) associated with a novel coronavirus (SARS-CoV-2) was reported in Wuhan city, Hubei province, China. The outbreak was traced to a seafood wholesale market and human to human transmission was confirmed. The rapid spread and the death toll of the new epidemic warrants immediate intervention. The intra-host genomic variability of SARS-CoV-2 plays a pivotal role in the development of effective antiviral agents and vaccines, as well as in the design of accurate diagnostics. We analyzed NGS data derived from clinical samples of three Chinese patients infected with SARS-CoV-2, in order to identify small- and large-scale intra-host variations in the viral genome. We identified tens of low- or higher- frequency single nucleotide variations (SNVs) with variable density across the viral genome, affecting 7 out of 10 protein-coding viral genes. The majority of these SNVs (72/104) corresponded to missense changes. The annotation of the identified SNVs but also of all currently circulating strain variations revealed colocalization of intra-host as well as strain specific SNVs with primers and probes currently used in molecular diagnostics assays. Moreover, we de-novo assembled the viral genome, in order to isolate and validate intra-host structural variations and recombination breakpoints. The bioinformatics analysis disclosed genomic rearrangements over poly-A / poly-U regions located in ORF1ab and spike (S) gene, including a potential recombination hot-spot within S gene. Our results highlight the intra-host genomic diversity and plasticity of SARS-CoV-2, pointing out genomic regions that are prone to alterations. The isolated SNVs and genomic rearrangements reflect the intra-patient capacity of the polymorphic quasispecies, which may arise rapidly during the outbreak, allowing immunological escape of the virus, offering resistance to anti-viral drugs and affecting the sensitivity of the molecular diagnostics assays. [ABSTRACT FROM AUTHOR]

• The mental health problems of parents of hospitalized children during the epidemic are more serious, and the anxiety and depression are more obvious. A series of unexplained pneumonia appeared in Wuhan, Hubei Province, China, which is highly contagious. The virus is prone to nervous and anxious psychological reactions. In the objective environment of complex and densely populated hospitals, it is a high-risk area for virus-transmitted infections and children generally have lower immunity who are more likely to develop infections. The results showed that the mental health problems of parents of hospitalized children during the epidemic were more serious, and the anxiety and depression were more obvious. [ABSTRACT FROM AUTHOR]