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Based on the big data and survey data of online recruitment platform, this paper empirically tests the impact of COVID-19 on the employment status and psychological expectations of college graduates. The results show that: under the impact of COVID-19 epidemic, both supply and demand sides of college graduates' employment market are affected, such as the decline of recruitment demand, the rise of the employment supply, and the obvious decrease of employment market prosperity. The impacts of COVID-19 epidemic on college graduates' employment status and psychological expectation in different cities are heterogeneous. In the short term, the epidemic has a negative impact on the employment of graduates, but the employment situation is gradually improving with the support of national policies. Under the influence of COVID-19 epidemic, graduates will change their employment location and expected salary, and they tend to choose "temporary non-employment," and their proportions of getting offers and signing contracts are significantly reduced. This paper suggests: Firstly, we should continue to push forward the action plan of "expanding jobs in graduation season to promote employment," and strengthen the persistence and permanence of employment promotion policies for college graduates; Secondly, encourage college students to change their employment concept and rationally adjust their employment expectations; Thirdly, to promote the development of flexible employment of college graduates, it is necessary to strengthen the propaganda of flexible employment, so that students can understand relevant policies; Fourthly, strengthen employment guidance services for graduates from poor families to ensure the continuity and stability of employment assistance policies. [ABSTRACT FROM AUTHOR]

The COVID-19 epidemic has required countries to implement different containment strategies to limit its spread, like strict or weakened national lockdown rules and the application of age-stratified vaccine prioritization strategies. These interventions have in turn modified the age-dependent patterns of social contacts. In our recent paper, starting from the available age-structured real data at the national level, we identified, for the Italian case, specific virulence parameters for a two-age-structured COVID-19 epidemic compartmental model (under 60, and 60 years and over) in six different diseases transmission scenarios under concurrently adopted feedback interventions. An interpretation of how each external scenario modifies the age-dependent patterns of social contacts and the spread of COVID-19 disease has been accordingly provided. In this paper, which can be viewed as a sequel to the previous one, we mainly apply the same general methodology therein (involving the same dynamic model) to new data covering the three subsequent additional scenarios: (i) a mitigated coordinated intermittent regional action in conjunction with the II vaccination phase; (ii) a super-attenuated coordinated intermittent regional action in conjunction with the II vaccination phase; and (iii) a last step towards normality in conjunction with the start of the III vaccination phase. As a new contribution, we show how meaningful updated information can be drawn out, once the identification of virulence parameters, characterizing the two age groups within the latest three different phases, is successfully carried out. Nevertheless, differently from our previous paper, the global optimization procedure is carried out here with the number of susceptible individuals in each scenario being left free to change, to account for reinfection and immunity due to vaccination. Not only do the slightly different estimates we obtain for the previous scenarios not impact any of the previous considerations (and thus illustrate the robustness of the procedure), but also, and mainly, the new results provide a meaningful picture of the evolution of social behaviors, along with the goodness of strategic interventions. [ABSTRACT FROM AUTHOR]

At present, China has gradually entered the period of normalization of COVID-19. Due to the raging pandemic, the domestic and international economic situation is not optimistic, and the health insurance industry is closely related to people's well-being, but currently, there is still little research on the development of the health insurance industry. Therefore, this paper revolves around the discussion of this industry. This paper first analyzes the current situation of the industry using the PEST analysis model and then summarizes some of the factors that drive the development of the health insurance industry and measures to promote the industry in different periods and regions using the comparative analysis method based on existing research. Given the above comparative analysis, this paper finds the fundamental points for development and gives development suggestions from three aspects: product innovation, technology development, and system reform. [ABSTRACT FROM AUTHOR]

In this paper, a new responsive-green-cold vaccine supply chain network during the COVID-19 pandemic is developed for the first time. According to the proposed network, a new multi-objective, multi-period, multi-echelon mathematical model for the distribution-allocation-location problem is designed. Another important novelty in this paper is that it considers an Internet-of-Things application in the COVID-19 condition in the suggested model to enhance the accuracy, speed, and justice of vaccine injection with existing priorities. Waste management, environmental effects, coverage demand, and delivery time of COVID-19 vaccine simultaneously are therefore considered for the first time. The LP-metric method and meta-heuristic algorithms called Gray Wolf Optimization (GWO), and Variable Neighborhood Search (VNS) algorithms are then used to solve the developed model. The other significant contribution, based on two presented meta-heuristic algorithms, is a new heuristic method called modified GWO (MGWO), and is developed for the first time to solve the model. Therefore, a set of test problems in different sizes is provided. Hence, to evaluate the proposed algorithms, assessment metrics including (1) percentage of domination, (2) the number of Pareto solutions, (3) data envelopment analysis, and (4) diversification metrics and the performance of the convergence are considered. Moreover, the Taguchi method is used to tune the algorithm's parameters. Accordingly, to illustrate the efficiency of the model developed, a real case study in Iran is suggested. Finally, the results of this research show MGO offers higher quality and better performance than other proposed algorithms based on assessment metrics, computational time, and convergence. [ABSTRACT FROM AUTHOR]

This paper extends a novel piecewise mathematical model of the COVID-19 epidemic using fractional and variable-order differential equations and fractional stochastic derivatives in three intervals of time. The deterministic models are augmented with hybrid fractional order and variable order operators, while the stochastic differential equations incorporate fractional Brownian motion. To probe the behavior of the proposed models, we introduce two numerical techniques: the nonstandard modified Euler Maruyama method for the fractional stochastic model, and the Caputo proportional constant-Grünwald-Letnikov nonstandard finite difference method for the fractional and variable-order deterministic models. Several numerical experiments corroborate the theoretical assertions and demonstrate the efficacy of the proposed approaches. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study the spillover effects of financial stress among five important financial markets (bond, stock, foreign exchange, interbank, and real estate markets) in China, and explore the important determinants of financial stress spillover level among the markets and the impact of the Chinese stress spillover situation on the European markets. Our findings are as follows: First, there is a significant stress spillover effect among the five markets, and the total financial stress spillover index (TSSI) is very high during the global financial crisis. Generally, the stock and real estate markets are the major transmitters of stress spillover, and the interbank and bond markets are the major receivers. Second, the most macro factors have significant impacts on the financial stress spillover level among the markets, especially CPI index, the Chinese economic policy uncertainty index and VIX index. And the severity of the COVID-19 epidemic in China and the world has a significant impact on the TSSI, especially from March 2020 to August 2020. Finally, the TSSI can significantly increase the volatility of French stock market, Italian stock market and German government bond market, especially during the Sino-US trade war and the COVID-19 epidemic. [ABSTRACT FROM AUTHOR]

The COVID-19 lockdown had a positive control effect on urban air quality. However, this effect remains uncertain after the epidemic enters regular management, and furthermore, only limited data are available regarding urban PM2.5 (aerodynamic diameter ≤ 2.5μm) under the impact of the epidemic. We used daily ambient PM2.5 concentration data in Beijing to compare and analyze the changes in urban PM2.5 concentrations before and after the COVID-19 epidemic and to estimate the healthy effects and economic burden associated with PM2.5 before and after the epidemic. The study found that COVID-19 has a significant impact on the urban environmental PM2.5 concentration, which is manifested by the decrease in the PM2.5 concentration in Beijing during the epidemic by 27.8%. Exposure-response models estimated 56.443 (95% CI: 43.084–69.893) thousand people die prematurely in Beijing during the COVID-19 epidemic attributed to long-term PM2.5 exposure, with a 13.3% decrease in the number of premature deaths year-on-year. The total healthy economic losses attributable to PM2.5 in Beijing during the COVID-19 epidemic were 35.76 (95% CI: 28.41–42.44) billion yuan, with a per capita loss of 816.8 yuan. Strict control measures throughout the COVID-19 epidemic had a positive impact on air quality in Beijing, with a decrease in both premature deaths and economic healthy losses attributable to fine particles. This paper helps to enrich and expand the research on the impact of COVID-19 on the urban environment and provides a basis for formulating policies related to air quality improvement in the post-epidemic era. [ABSTRACT FROM AUTHOR]

As the Chinese government called for "targeted resumption of work and production in different regions and at different levels" after the novel coronavirus pneumonia (COVID-19) outbreak, rural migrant workers returning to work became an important factor for economic recovery and stabilizing labor supply. Based on data collected during the COVID-19 pandemic in 2020, this paper investigates farmers' perception of risk in the epidemic situation and reveals the impact of farmers' risk perception on working outside of their hometowns. The results show that: 1) farmers generally believe the risk of epidemics is higher in urban areas than in rural areas; and 2) farmers' risk perceptions significantly influence their decisions of working outside of their hometowns. This paper provides important policy implications in labor supply and crisis management. [ABSTRACT FROM AUTHOR]

Based on the first-hand survey data for 910 people without financial freedom in China during November 2019 and June 2020, this paper investigates the impact of conspicuous tourism consumption preference on individual's tourism consumption borrowing intention as well as the effects of age empirically. The results indicate that the older the individual is, the weaker his/her conspicuous tourism consumption preference is. Conspicuous tourism consumption preference has a significant positive impact on tourism consumption borrowing intention. In terms of the male, age has negative effects in mediating conspicuous tourism consumption preference's influence on tourism consumption borrowing intention. The above findings can deepen understanding of tourists' behavior and its outcomes from the perspective of conspicuous consumption theoretically. In addition, they have practical significance and policy reference value for reducing personal and social finance/debt risk and related harm due to major macroeconomic fluctuations caused by the external shock such as the COVID-19 epidemic. [ABSTRACT FROM AUTHOR]

Since 2020, COVID-19 has repeatedly arisen around the world, which has had a significant impact on the global economy and culture. The prediction of the COVID-19 epidemic will help to deal with the current epidemic and similar risks that may arise in the future. So, this paper proposes a hybrid prediction model based on particle swarm optimization variational mode decomposition (PSO-VMD), Long Short-Term Memory Network (LSTM) and AdaBoost algorithm. To address the issue of determining the optimal number of modes K and the penalty factor (α) in the variational mode decomposition (VMD), an adaptive value for particle swarm optimization (PSO) is proposed. Specifically, the weighted average sample entropy of the relevant coefficients is utilized to determine the adaptive value. First, the epidemic data are decomposed into multiple modal components, known as intrinsic mode functions (IMFs), using PSO-VMD. These components, along with policy-based factors, are integrated to form a multivariate forecast dataset. Next, each IMF is predicted using AdaBoost-LSTM. Finally, the prediction results of all the IMF components are reconstructed to obtain the final prediction result. Our proposed method is validated by the cumulative confirmed data of Hubei and Hebei provinces. Specifically, in the case of cumulative confirmation data, the coefficient of determination ( R 2 ) of the mixed model is increased compared to the control model, and the average mean absolute error (MAE) and root mean square error (RMSE) decreased. The experimental results demonstrate that the VMD–AdaBoost–LSTM model achieves the highest prediction accuracy, thereby offering a new approach to COVID-19 epidemic prediction. [ABSTRACT FROM AUTHOR]

Bulgaria has the lowest COVID-19 vaccination rate in the European Union and the second-highest COVID-19 mortality rate in the world. That is why we think it is important better to understand the reason for this situation and to analyse the development of the disease over time. In this paper, an extended time-dependent SEIRS model SEIRS-VB is used to investigate the long-term behaviour of the COVID-19 epidemic. This model includes vaccination and vital dynamics. To apply the SEIRS-VB model some numerical simulation tools have been developed and for this reason a family of time-discrete variants are introduced. Suitable inverse problems for the identification of parameters in discrete models are solved. A methodology is proposed for selecting a discrete model from the constructed family, which has the closest parameter values to these in the differential SEIRS-VB model. To validate the studied models, Bulgarian COVID-19 data are used. To obtain all these results for the discrete models a mathematical analysis is carried out to illustrate some biological properties of the differential model SEIRS-VB, such as the non-negativity, boundedness, existence, and uniqueness. Using the next-generation method, the basic reproduction number associated with the model in the autonomous case is defined. The local stability of the disease-free equilibrium point is studied. Finally, a sensitivity analysis of the basic reproduction number is performed. [ABSTRACT FROM AUTHOR]

Novel coronavirus (COVID‐19), a global threat whose source is not correctly yet known, was firstly recognised in the city of Wuhan, China, in December 2019. Now, this disease has been spread out to many countries in all over the world. In this paper, we solved a time delay fractional COVID‐19 SEIR epidemic model via Caputo fractional derivatives using a predictor–corrector method. We provided numerical simulations to show the nature of the diseases for different classes. We derived existence of unique global solutions to the given time delay fractional differential equations (DFDEs) under a mild Lipschitz condition using properties of a weighted norm, Mittag–Leffler functions and the Banach fixed point theorem. For the graphical simulations, we used real numerical data based on a case study of Wuhan, China, to show the nature of the projected model with respect to time variable. We performed various plots for different values of time delay and fractional order. We observed that the proposed scheme is highly emphatic and easy to implementation for the system of DFDEs. [ABSTRACT FROM AUTHOR]

Background: In the management of epidemics, like COVID‐19, trade‐offs have to be made between reducing mortality and morbidity and minimizing socioeconomic and political consequences. Traditionally, epidemic management (EM) has been guided and executed attentively by experts and policymakers. It can, however, still be controversial in the public sphere. In the last decades, public engagement (PE) has been successfully applied in various aspects of healthcare. This leads to the question if PE could be implemented in EM decision‐making. Methods: From June to October 2020, seven deliberative discussion focus groups were executed with 35 Dutch citizens between 19 and 84 years old. Their views on PE in COVID‐19 management were explored. The deliberative approach allows for the education of participants on the topic before the discussion. The benefits, barriers, timing and possible forms of PE in EM were discussed. Results: Almost all participants supported PE in EM, as they thought that integrating their experiences and ideas would benefit the quality of EM, and increase awareness and acceptance of measures. A fitting mode for PE was consultation, as it was deemed important to provide the public with possibilities to share ideas and feedback; however, final authority remained with experts. The publics could particularly provide input about communication campaigns and control measures. PE could be executed after the first acute phase of the epidemic and during evaluations. Conclusions: This paper describes the construction of an empirically informed framework about the values and conditions for PE in EM from the perspective of the public. Participants expressed support to engage certain population groups and considered it valuable for the quality and effectiveness of EM; however, they expressed doubts about the feasibility of PE and the capabilities of citizens. In future studies, these results should be confirmed by a broader audience. Patient or Public Contribution: No patients or members of the public were involved in the construction and execution of this study. This study was very exploratory, to gain a first insight into the views of the public in the Netherlands, and will be used to develop engagement practices accordingly. At this stage, the involvement of the public was not yet appropriate. [ABSTRACT FROM AUTHOR]

As COVID-19 continues to threaten public health around the world, research on specific vaccines has been underway. In this paper, we establish an SVIR model on booster vaccination with two time delays. The time delays represent the time of booster vaccination and the time of booster vaccine invalidation, respectively. Second, we investigate the impact of delay on the stability of non-negative equilibria for the model by considering the duration of the vaccine, and the system undergoes Hopf bifurcation when the duration of the vaccine passes through some critical values. We obtain the normal form of Hopf bifurcation by applying the multiple time scales method. Then, we study the model with two delays and show the conditions under which the nontrivial equilibria are locally asymptotically stable. Finally, through analysis of official data, we select two groups of parameters to simulate the actual epidemic situation of countries with low vaccination rates and countries with high vaccination rates. On this basis, we select the third group of parameters to simulate the ideal situation in which the epidemic can be well controlled. Through comparative analysis of the numerical simulations, we concluded that the most appropriate time for vaccination is to vaccinate with the booster shot 6 months after the basic vaccine. The priority for countries with low vaccination rates is to increase vaccination rates; otherwise, outbreaks will continue. Countries with high vaccination rates need to develop more effective vaccines while maintaining their coverage rates. When the vaccine lasts longer and the failure rate is lower, the epidemic can be well controlled within 20 years. [ABSTRACT FROM AUTHOR]

• 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]

The current research paper explored the impact of social stigma on people infected with COVID-19 in Saudi Arabia and the factors that worsen the stigma against COVID-19 patients. The research sample consisted of fifteen Saudis recovering from COVID-19 aged 25–55; eight males and seven females. Using the purposive sampling method, the research utilized a guided interview consisted of four main sections. Following qualitative research design, the research administered the instrument to obtain and discuss the results. The research was conducted during the academic year 2020.The results showed that there was a positive association between social stigma and COVID-19 in Saudi Arabia. Additionally, there was no difference between the participants in the rate of social stigma according to gender. Moreover, this also highlighted that the experienced social stigma is varied in its form and in people's behavior. Cooperation between society institutions and media is recommended to increase the awareness of rejecting discrimination and social stigma. Furthermore, stigmatized persons should be provided with early intervention and ongoing counseling programs. [ABSTRACT FROM AUTHOR]

The COVID-19 epidemic has required countries to implement different containment strategies to limit its spread, like strict or weakened national lockdown rules and the application of age-stratified vaccine prioritization strategies. These interventions have in turn modified the age-dependent patterns of social contacts. In our recent paper, starting from the available age-structured real data at the national level, we identified, for the Italian case, specific virulence parameters for a two-age-structured COVID-19 epidemic compartmental model (under 60, and 60 years and over) in six different diseases transmission scenarios under concurrently adopted feedback interventions. An interpretation of how each external scenario modifies the age-dependent patterns of social contacts and the spread of COVID-19 disease has been accordingly provided. In this paper, which can be viewed as a sequel to the previous one, we mainly apply the same general methodology therein (involving the same dynamic model) to new data covering the three subsequent additional scenarios: (i) a mitigated coordinated intermittent regional action in conjunction with the II vaccination phase; (ii) a super-attenuated coordinated intermittent regional action in conjunction with the II vaccination phase; and (iii) a last step towards normality in conjunction with the start of the III vaccination phase. As a new contribution, we show how meaningful updated information can be drawn out, once the identification of virulence parameters, characterizing the two age groups within the latest three different phases, is successfully carried out. Nevertheless, differently from our previous paper, the global optimization procedure is carried out here with the number of susceptible individuals in each scenario being left free to change, to account for reinfection and immunity due to vaccination. Not only do the slightly different estimates we obtain for the previous scenarios not impact any of the previous considerations (and thus illustrate the robustness of the procedure), but also, and mainly, the new results provide a meaningful picture of the evolution of social behaviors, along with the goodness of strategic interventions.

Employee productivity is critical to the company's success in achieving its objectives. Predicting future employee productivity is critical for organizations that work from home to flourish. This article used machine learning to estimate work from home employee productivity in a corporation. The machine learning approach is based on a cross-industry data mining standard (CRIPS-DM). We have analyzed some variables which are important for productivity prediction. The random forest method is used in the machine learning process. The random forest method is employed to analyze the prediction model. This will help organizations to improve work from home by using analyzed results. The results reveal that the random forest method properly identified instances in 91.66 percent of the cases. [ABSTRACT FROM AUTHOR]

This research first adopts three indicators to measure the systemic risk of different financial industries in China. Second, we employ the Time Varying Parameter-Stochastic Volatility-Vector Auto Regression (TVP-SV-VAR) model to investigate the time-varying relationship among COVID-19 epidemic, crude oil price, and financial systemic risk. The results herein not only help us grasp the current level of systematic risk in China, but also can assist at improving the early warning risk indicators and enhance the risk management system. Lastly, this research can also help investors to make reasonable asset planning. [ABSTRACT FROM AUTHOR]

This paper extends a novel piecewise mathematical model of the COVID-19 epidemic using fractional and variable-order differential equations and fractional stochastic derivatives in three intervals of time. The deterministic models are augmented with hybrid fractional order and variable order operators, while the stochastic differential equations incorporate fractional Brownian motion. To probe the behavior of the proposed models, we introduce two numerical techniques: the nonstandard modified Euler Maruyama method for the fractional stochastic model, and the Caputo proportional constant-Grünwald-Letnikov nonstandard finite difference method for the fractional and variable-order deterministic models. Several numerical experiments corroborate the theoretical assertions and demonstrate the efficacy of the proposed approaches.

The COVID-19 pandemic resulted in substantial job losses and an economic decline in European labour markets, with various effects observed at regional level. The unemployment rate experienced a sharp increase, disproportionately impacting the younger generation and individuals with limited skills. The prevalence of remote work has risen, creating difficulties in maintaining a healthy work-life balance. The three research questions concern: (1) examining scientific literature; (2) validating the effects of COVID-19 on the labour market; and (3) identifying the indicators and regions in Europe that have been most significantly affected. The study begins by performing an exploratory analysis of the data, then proceeds to an examination of the principal components to reduce dimensionality. It concludes with a cluster analysis to enhance the visualisation of different regions. The results are in conformity with the scientific literature but also indicate specificities for different regions or indicators. While most studies concentrate on examining the effects of this phenomenon on just a couple of European countries, the present research extensively analyses all regions across the continent. Furthermore, the study spans a prolonged period from 2018 to 2022, covering the period preceding the pandemic, the crisis itself, and the aftermath. The final contribution regards the methodology used, which considers both approaches utilised in the research. [ABSTRACT FROM AUTHOR]

This study focuses on how the COVID-19 epidemic affects gambling motivation and behavior. This research also analyzes the behavioral intervention effects of the anti-epidemic measures on the COVID-19 epidemic and the relationship between the epidemic impact and gambling motivation and behavior. To investigate these connections, this research used Structural Equation Modeling to analyze 334 valid questionnaires collected during COVID-19 from gamblers from mainland China who visited the Macao Special Administrative Region. The results showed that the epidemic impact negatively affected gambling motivation and behavior, and gambling motivation partially mediated the relationship between epidemic impact and gambling behavior. Anti-epidemic measures positively moderated the epidemic’s impact on gambling motivation and behavior. This paper offers a theoretical contribution by proving the influence of the social environment on human motivational behavior, especially the effect of the COVID-19 crisis, and the support of government and enterprise anti-epidemic measures for behavior intervention theory. The practicality of this study consists of behavioral interventions from anti-epidemic efforts by regional government and industry to cope with the epidemic. These measures should influence the gamblers’ behavior intentions by considering the health and safety strategies that may reduce the impact of the COVID-19 epidemic on mainland Chinese gamblers. Doi: 10.28991/ESJ-2023-07-04-024 Full Text: PDF

The outbreak of the COVID-19 epidemic has had a significant impact on the global economy. The way that enterprises respond to the crisis has become a hot topic. This study selected three automobile industry enterprises that effectively responded to the crisis during the COVID-19 epidemic. We discuss the impact of the epidemic on these enterprises and their countermeasures, and analyse the differences between these measures and the underlying selection mechanism. Through a case study, we have found that: (1) time pressure and uncertainties are key factors that stimulate enterprises to conduct improvisation behaviours in crisis; (2) the improvisation behaviours adopted by enterprises in response to crisis can be divided into adaptive improvisation behaviours and creative improvisation behaviours; (3) the higher the degree of resource constraints an enterprise faces, the more likely it is to adopt creative improvisation behaviours, and conversely, the lower the degree of resource constraints an enterprise faces, the more likely it is to adopt adaptive improvisation behaviours; (4) the more prior experience an enterprise has, the more likely it is to adopt creative improvisation behaviours, and conversely, the less prior experience an enterprise has, the more likely it is to adopt adaptive improvisation behaviours. This study enriches the classification and process research of organizational improvisation. [ABSTRACT FROM AUTHOR]

Previous studies have investigated the effects of the pandemic on quality of life; both economical and psychosocial effects were explored. Some studies also mentioned mediating factors as mechanisms in this relationship; however, the mediating role of anxiety has not been examined. The present study examined the mediating effects of anxiety on the relationship between socioeconomic impact of COVID-19 and quality of life. An online survey of 280 Vietnamese residents was conducted in the context of the pandemic outbreak. Anxiety was found to be a completely mediating variable in the association between the socioeconomic impact of the pandemic and quality of life during the lockdown period. This finding contributes to a better understanding of how the pandemic affects people's quality of life and serves as the foundation for lessening the negative effects of the epidemic on people's lives. [ABSTRACT FROM AUTHOR]

The COVID-19 epidemic has recently led in Italy to the implementation of different external strategies in order to limit the spread of the disease in response to its transmission rate: strict national lockdown rules, followed first by a weakening of the social distancing and contact reduction feedback interventions and finally the implementation of coordinated intermittent regional actions, up to the application, in this last context, of an age-stratified vaccine prioritization strategy. This paper originally aims at identifying, starting from the available age-structured real data at the national level during the specific aforementioned scenarios, external-scenario-dependent sets of virulence parameters for a two-age-structured COVID-19 epidemic compartmental model, in order to provide an interpretation of how each external scenario modifies the age-dependent patterns of social contacts and the spread of COVID-19. [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]

Background: The coronavirus disease (COVID-19) pandemic has resulted in significant changes in nursing education. Maintaining social distance could slow down the spread of COVID-19, and it was necessary, but it significantly reduced students' hands-on clinical practice experience in healthcare settings. Traditional classroom teaching in schools has transitioned to distance or online learning methods, which significantly reduced students' hands-on clinical practice experience in healthcare settings. Although distance education had been implemented for a long time, there are many problems and challenges to be resolved. The experiences and needs of nursing students in remote clinical training urgently require further understanding. Purpose: To understand the stress and coping strategies of online nursing practicum courses for Taiwanese nursing students during the COVID-19 pandemic. Methods: A qualitative research approach with purposive sampling was supplemented by snowball sampling. Semi-structured interviews were conducted, and the data were collected following the eight-step process outlined by Waltz, Strickland, and Lenz (2010). The participants were 12 nursing students on a two-year nursing RN-to-BSN program at a university in Eastern Taiwan, consisting of 11 females and 1 male student. Findings: The stress and coping behaviors of nursing students consist of four main themes, each with three subthemes, including "urgent changes", "the gaps between online courses and practical operations", "mixed feelings of joy and anxiety" and "unexpected gains". Conclusions: The pandemic has impacted nursing students' learning and living. Engaging in online nursing practicum brought about significant stress; nevertheless, students employed various coping strategies to navigate through this challenging period. The findings of this study would also help nursing educators understand the learning gaps in clinical practicum among students. [ABSTRACT FROM AUTHOR]

To analyze changes in the detection of parainfluenza virus (PIV) in children hospitalized with acute respiratory tract infection (ARTI) during 2014–2022 in Hubei Province, and explore the impact of the universal two‐child policy and the public health measures against COVID‐19 epidemic on the prevalence of PIV in China. The study was conducted at the Maternal and Child Health Hospital of Hubei Province. Children aged <18 years with ARTI admitted from January 2014 to June 2022 were enrolled. The infection of PIV was confirmed by the direct immunofluorescence method in nasopharyngeal specimens. Adjusted logistic regression models were used to analyze the influence of the universal two‐child policy implementation and public health measurements against COVID‐19 on PIV detection. Totally 75 128 inpatients meeting the criteria were enrolled in this study from January 2014 to June 2022 with an overall PIV positive rate of 5.5%. The epidemic seasons of PIV prevalence lagged substantially in 2020. A statistically significant higher positive rate of PIV was observed in 2017–2019 compared to that in 2014–2015 (6.12% vs 2.89%, risk ratio = 2.12, p < 0.001) after the implementation of the universal two‐child policy in 2016. A steep decline occurred in PIV positive rate during the COVID‐19 epidemic in 2020 (0.92% vs 6.92%, p < 0.001) and it rebounded during the regular epidemic prevention and control period in 2021–2022 (6.35%, p = 0.104). In Hubei Province, the implementation of the universal two‐child policy might have led to an increase of PIV prevalence, and public health measures during the COVID‐19 epidemic might have influenced the fluctuation in PIV detection since 2020. [ABSTRACT FROM AUTHOR]

The first symptomatic infected individuals of coronavirus (Covid‐19) was confirmed in December 2020 in the city of Wuhan, China. In India, the first reported case of Covid‐19 was confirmed on 30 January 2020. Today, coronavirus has been spread out all over the world. In this manuscript, we studied the coronavirus epidemic model with a true data of India by using Predictor‐Corrector scheme. For the proposed model of Covid‐19, the numerical and graphical simulations are performed in a framework of the new generalised Caputo sense non‐integer order derivative. We analysed the existence and uniqueness of solution of the given fractional model by the definition of Chebyshev norm, Banach space, Schauder's second fixed point theorem, Arzel's‐Ascoli theorem, uniform boundedness, equicontinuity and Weissinger's fixed point theorem. A new analysis of the given model with the true data is given to analyse the dynamics of the model in fractional sense. Graphical simulations show the structure of the given classes of the non‐linear model with respect to the time variable. We investigated that the mentioned method is copiously strong and smooth to implement on the systems of non‐linear fractional differential equation systems. The stability results for the projected algorithm is also performed with the applications of some important lemmas. The present study gives the applicability of this new generalised version of Caputo type non‐integer operator in mathematical epidemiology. We compared that the fractional order results are more credible to the integer order results. [ABSTRACT FROM AUTHOR]

We incorporate the disease state and testing state into the formulation of a COVID-19 epidemic model. For this model, the basic reproduction number is identified and its dependence on model parameters related to the testing process and isolation efficacy is discussed. The relations between the basic reproduction number, the final epidemic and peak sizes, and the model parameters are further explored numerically. We find that fast test reporting does not always benefit the control of the COVID-19 epidemic if good quarantine while awaiting test results is implemented. Moreover, the final epidemic and peak sizes do not always increase along with the basic reproduction number. Under some circumstances, lowering the basic reproduction number increases the final epidemic and peak sizes. Our findings suggest that properly implementing isolation for individuals who are waiting for their testing results would lower the basic reproduction number as well as the final epidemic and peak sizes. [ABSTRACT FROM AUTHOR]

Introduction: Before the mass vaccination, epidemiological control measures were the only means of containing the COVID-19 epidemic. Their effectiveness determined the consequences of the COVID-19 epidemic. Our study evaluated the impact of sociodemographic, lifestyle, and clinical factors on patient-reported epidemiological control measures. Methods: A nationwide representative sample of 1008 randomly selected adults were interviewed in person between 15 March and 30 May 2021. The prevalence of test-confirmed SARS-CoV-2 infection was 12.1%, of testing was 33.7%, and of contact tracing among test-confirmed infected subjects was 67.9%. The vaccination coverage was 52.4%. Results: According to the multivariable logistic regression models, the occurrence of infection was not influenced by sociodemographic and lifestyle factors or by the presence of chronic disease. Testing was more frequent among middle-aged adults (aOR = 1.53, 95% CI 1.10–2.13) and employed adults (aOR = 2.06, 95% CI 1.42–3.00), and was more frequent among adults with a higher education (aORsecondary = 1.93, 95% CI 1.20–3.13; aORtertiary = 3.19, 95% CI 1.81–5.63). Contact tracing was more frequently implemented among middle-aged (aOR41-7y = 3.33, 95% CI 1.17–9.45) and employed (aOR = 4.58, 95% CI 1.38–15.22), and those with chronic diseases (aOR = 5.92, 95% CI 1.56–22.47). Positive correlation was observed between age groups and vaccination frequency (aOR41-70y = 2.94, 95% CI 2.09–4.15; aOR71+y = 14.52, 95% CI 7.33–28.77). Higher than primary education (aORsecondary = 1.69, 95% CI 1.08–2.63; aORtertiary = 4.36, 95% CI 2.46–7.73) and the presence of a chronic disease (aOR = 2.58, 95% CI 1.75–3.80) positively impacted vaccination. Regular smoking was inversely correlated with vaccination (aOR = 0.60; 95% CI 0.44–0.83). Conclusions: The survey indicated that testing, contact tracing, and vaccination were seriously influenced by socioeconomic position; less so by chronic disease prevalence and very minimally by lifestyle. The etiological role of socioeconomic inequalities in epidemic measure implementation likely generated socioeconomic inequality in COVID-19-related complication and death rates. [ABSTRACT FROM AUTHOR]

Abstract Background In the management of epidemics, like COVID‐19, trade‐offs have to be made between reducing mortality and morbidity and minimizing socioeconomic and political consequences. Traditionally, epidemic management (EM) has been guided and executed attentively by experts and policymakers. It can, however, still be controversial in the public sphere. In the last decades, public engagement (PE) has been successfully applied in various aspects of healthcare. This leads to the question if PE could be implemented in EM decision‐making. Methods From June to October 2020, seven deliberative discussion focus groups were executed with 35 Dutch citizens between 19 and 84 years old. Their views on PE in COVID‐19 management were explored. The deliberative approach allows for the education of participants on the topic before the discussion. The benefits, barriers, timing and possible forms of PE in EM were discussed. Results Almost all participants supported PE in EM, as they thought that integrating their experiences and ideas would benefit the quality of EM, and increase awareness and acceptance of measures. A fitting mode for PE was consultation, as it was deemed important to provide the public with possibilities to share ideas and feedback; however, final authority remained with experts. The publics could particularly provide input about communication campaigns and control measures. PE could be executed after the first acute phase of the epidemic and during evaluations. Conclusions This paper describes the construction of an empirically informed framework about the values and conditions for PE in EM from the perspective of the public. Participants expressed support to engage certain population groups and considered it valuable for the quality and effectiveness of EM; however, they expressed doubts about the feasibility of PE and the capabilities of citizens. In future studies, these results should be confirmed by a broader audience. Patient or Public Contribution No patients or members of the public were involved in the construction and execution of this study. This study was very exploratory, to gain a first insight into the views of the public in the Netherlands, and will be used to develop engagement practices accordingly. At this stage, the involvement of the public was not yet appropriate.

Livelihood resilience is the ability of individuals, families or communities to withstand external shocks based on existing resources. It is an important research paradigm in sustainable development studies. The outbreak of COVID-19 and strict epidemic prevention policies have greatly impacted the production and life of rural farmers in China. The resilience of farmers' livelihoods during the epidemic is crucial to the sustainable development of their livelihoods and regional stability. This study uses classic buffer capacity, self-organization ability, and the capacity for learning a three-dimension livelihood resilience framework using the comprehensive index, OLS, and geographical detector methods based on Hubei province and neighboring Anhui and Chongqing. Rural household survey data investigate the background of epidemic hit the livelihood of farmers resilience and its spatial distribution pattern and identify the key influencing factors. The results show that the livelihood shock faced by farmers was higher than the risk of disease, and the overall level of livelihood resilience was low after the pandemic. Financial capital and social capital can effectively help farmers to eliminate livelihood difficulties. In contrast, natural capital has a limited driving force, and physical and human capital have no obvious impact. The spatial agglomeration differentiation is obvious, indicating that the impact of COVID-19 on livelihoods was closely related to the degree of local socio-economic development and geographical location. The results of this study provide targeted recommendations for the development of epidemic prevention and livelihood resilience policies tailored to local conditions, emphasizing the importance of boosting livelihood recovery at both the government and household levels. [ABSTRACT FROM AUTHOR]

When the World Health Organization (WHO) analyzed the culprits of global warming, it was found that in developed countries with relatively few high-polluting heavy industries, the medical sector is one of the sources of high-density carbon emissions. Therefore, the medical industry has a noticeable impact on the environment. Amid the current COVID-19 epidemic, this study adopts the theory of planned behavior (TPB), widely used in decision-making science. We selected a regional teaching hospital with 339 employees in Taiwan to obtain valid questionnaire data. We explore the comparative analysis of different intra-organizational stakeholders' "attitudes," "subjective norms," and "perceived behavioral control" on the hospital's behavioral intention to promote green healthcare. The results show that the TPB model has reliable explanatory power. All three factors have a positive and significant effect on promoting green hospital behavior. Among them, perceived behavioral control was the most notable. A comparative analysis of the differences among stakeholders in the research model shows that "medical administrators" and "nursing staff" have a higher proportion of significant influence effects in various hypotheses, highlighting the critical roles of these two groups in promoting green hospitals. This research policy suggests that the cross-departmental staff in the hospital put forward green innovation ideas, strengthen internal environmental education and management, establish a good incentive system for front-line nursing staff, and implement the sustainable development strategy of the hospital. [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]

Triggered by COVID-19, one of the most dramatic crashes in the stock market in history occurred in March 2020. The sharp reductions in NASDAQ insurance stock indexes were observed after the occurrence of COVID-19 and in March 2020. In this study, the NASDAQ insurance stock markets (including NASDAQ Insurance Index, Developed Markets Insurance Index, and Emerging Markets Insurance Index) and NASDAQ Composite Index are utilized. The "scissors difference" between the NASDAQ Insurance Index and NASDAQ Composite Index is observed. The dynamic effects of the COVID-19 epidemic and the March 2020 crash on the multifractality of four series are explored. Firstly, the apparent and intrinsic multifractality, the components of multifractality, and the dynamic effects of the COVID-19 epidemic on these indexes are analyzed. Secondly, the multifractal cross-correlation between the NASDAQ Insurance Index and NASDAQ Composite Index is investigated. The dynamic influence of the COVID-19 epidemic on the cross-correlation is examined. The multifractal analysis results reveal that four series both before and after the occurrence of COVID-19 have multifractal characteristics. The stronger multifractal characteristics and the greater multifractal degree are obtained after the occurrence of COVID-19. The intrinsic multifractality of the three indexes ascends largely after the occurrence of COVID-19. The multifractal cross-correlation analysis illustrates that the cross-correlation between two indexes before and after the occurrence of COVID-19 is multifractal. The stronger multifractal cross-correlations and greater multifractal degrees are shown. The contribution of the intrinsic multifractal cross-correlation increased after the occurrence of COVID-19. [ABSTRACT FROM AUTHOR]

Highlights: This report summarizes recent advances of flexible humidity sensors and their integrated systems. Typical examples of noncontact detections based on flexible and wearable humidity sensors are highlighted. Research opportunities and challenges of pushing flexible humidity sensors towards practical contactless measurements are discussed.In the past decade, the global industry and research attentions on intelligent skin-like electronics have boosted their applications in diverse fields including human healthcare, Internet of Things, human–machine interfaces, artificial intelligence and soft robotics. Among them, flexible humidity sensors play a vital role in noncontact measurements relying on the unique property of rapid response to humidity change. This work presents an overview of recent advances in flexible humidity sensors using various active functional materials for contactless monitoring. Four categories of humidity sensors are highlighted based on resistive, capacitive, impedance-type and voltage-type working mechanisms. Furthermore, typical strategies including chemical doping, structural design and Joule heating are introduced to enhance the performance of humidity sensors. Drawing on the noncontact perception capability, human/plant healthcare management, human–machine interactions as well as integrated humidity sensor-based feedback systems are presented. The burgeoning innovations in this research field will benefit human society, especially during the COVID-19 epidemic, where cross-infection should be averted and contactless sensation is highly desired. [ABSTRACT FROM AUTHOR]

This Article's purpose is to reveal the new research areas provided by the COVID-19 pandemic, in which translation training, translation history, cultural studies and other fields are included. The COVID-19 epidemic has brought profound change to the world's order, culture, communication and globalization. Every part of the world is doing its best to recover from the damage caused by the epidemic, and translation studies could play a role that is as important as natural science studies and practice, which provide a medical cure for the epidemic: they promote multilateral understanding worldwide, increase the sharing and dissemination of information fighting against the epidemic, also would effectively ensure translation activities and training with the help of modern technology. Although it is impossible to have the directions deeply dug in this article due to the limitation of the length, it sheds light on these possible areas so that those who are interested can pursue them. The source of these directions came from the author's analysis of selected works conducted by trusted researchers around the world. [ABSTRACT FROM AUTHOR]

Since the COVID-19 outbreak began in early 2020, it has spread rapidly and threatened public health worldwide. Vaccination is an effective way to control the epidemic. In this paper, we model a SAIM equation. Our model involves vaccination and the time delay for people to change their willingness to be vaccinated, which is influenced by media coverage. Second, we theoretically analyze the existence and stability of the equilibria of our model. Then, we study the existence of Hopf bifurcation related to the two equilibria and obtain the normal form near the Hopf bifurcating critical point. Third, numerical simulations based two groups of values for model parameters are carried out to verify our theoretical analysis and assess features such as stable equilibria and periodic solutions. To ensure the appropriateness of model parameters, we conduct a mathematical analysis of official data. Next, we study the effect of the media influence rate and attenuation rate of media coverage on vaccination and epidemic control. The analysis results are consistent with real-world conditions. Finally, we present conclusions and suggestions related to the impact of media coverage on vaccination and epidemic control.

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]