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1.
Zhonghua Liu Xing Bing Xue Za Zhi ; 43(7): 1030-1037, 2022 Jul 10.
Article in Chinese | MEDLINE | ID: covidwho-1954151

ABSTRACT

Objective: To understand the research progresses of economic evaluation of non-pharmaceutical interventions (NPIs) both at home and abroad, and provide reference for economic evaluation of NPIs using real-world data in China. Methods: The literature retrieval was conducted by searching Chinese and English databases to indude papers about economic evaluation of NPIs and integrated NPIs published from January, 2020 to December, 2021, and the results were analyzed comprehensively. Results: A total of 30 Chinese and English literatures about economic evaluation of NPIs for COVID-19 prevention and control were included; including 7 papers about nucleic acid and testing and screening, 6 papers about individual prevention and protection measures, 12 papers about integrated implementation of individual prevention and protection, social distancing, nucleic acid or antigen testing, community screening and symptom screening, as well as close contact tracing and isolation/quarantine, and 5 papers about contain strategies, such as lockdown. This study found that personal protection, social distancing, and testing-tracing-isolation measures were cost-effective; however, different combinations of NPIs might lead to different results. Moreover, the cost of lockdown was high, which might cause huge economic burden. Conclusions: Most NPIs are cost-effective except lockdown, while the cost-effectiveness of the integrations of NPIs at different levels and in different scenarios needs to be further evaluated. It is necessary to carry out economic evaluation of integrated NPIs and the combination of NPIs with other interventions, such as vaccination and medication, based on real-world settings in China.


Subject(s)
COVID-19 , Nucleic Acids , COVID-19/prevention & control , Communicable Disease Control/methods , Cost-Benefit Analysis , Humans , SARS-CoV-2
2.
2nd International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2021 ; : 784-789, 2021.
Article in English | Scopus | ID: covidwho-1948776

ABSTRACT

To achieve high prediction accuracy of human body keeps an open issue for decades of years, especially when COVID comes and online retail becomes the major consumption channels. The body measurement is the key to solve cloth matching and recommendation in clothing e-commerce. This paper proposes a practical framework of image-based body measurement, by only taking the user's front and side photos. This framework does not require pure background or precise standing position, and supports manual modification of the measurement results. The framework takes people's height, weight and gender as params to initialize a common body size set, and corrects each part of the set by analyzing the body proportion via the front and side images. The prediction accuracy was tested with the 50 digital models and 10 real people. Results showed that the circumference sizes such as chest, waist, hips, have errors less then 5%, while the length sizes such as arm, leg approach to actual length on net body models. For real people, the errors depend on the wearing clothes. In addition to high accuracy, the method has a rapid process speed, reaching 19QPS on a NVIDIA RTX5000 GPU server. © 2021 IEEE.

3.
10th International Conference on Information and Education Technology, ICIET 2022 ; : 204-208, 2022.
Article in English | Scopus | ID: covidwho-1909215

ABSTRACT

Under the influence of COVID-19, the adaptability and effectiveness of online education have become one of the hot issues concerned by today's society. 'Internet plus' also provides an opportunity for China's philanthropy to integrate resources. This study selects 18 rural hope primary schools as the research objects to conduct questionnaire surveys and individual interviews around the online supporting education cases based on the urban-rural interactive classroom model. Compared with traditional supporting education, online supporting education in urban and rural interactive classrooms can simulate the real classroom environment and is especially suitable for teaching rural primary school students with weak self-learning ability. However, the actual online teaching effect is far lower than expected, mainly due to the following problems. For example, the course cannot be carried out normally because the teachers at rural hope primary schools are not familiar with the operation of the equipment. The teaching volunteer team is not professional and stable enough. The teaching effect cannot be tested in time. We suggest improving the training mechanism for teachers at rural hope primary schools, promoting the incentive mechanism of volunteers and seeking help from a third-party teaching assessment agency. © 2022 IEEE.

4.
2021 International Conference on Computing in Civil Engineering, I3CE 2021 ; : 835-842, 2021.
Article in English | Scopus | ID: covidwho-1908371

ABSTRACT

Health and safety problems are essential for the construction industry, and such problems are more pronounced in small and medium enterprises (SMEs) due to the lack of financial resources and skilled personnel. Researchers have explored the feasibility and viability of addressing such constraints using artificial intelligence-enhanced, low-cost sensor systems. Our previous studies have investigated both conventional machine learning and deep neural network models for recognizing workers' postures from low-cost wearable sensors and assessing the ergonomics risks for injury prevention. In the next steps for this research, we are investigating adoption drivers and diffusion barriers for the scaled deployment of AI-enhanced sensor networks and other emerging digital technologies for construction health and safety in a real-work setting. Although the COVID-19 pandemic has brought unprecedented challenges, it has also sped up the digital technology adoption. The discussion in this paper is directed at building on this momentum to advance the use of emerging digital technologies at construction SMEs. The authors conducted a systematic review of literature on digital technologies at construction SMEs and how COVID-19 affected the digital transformation at SMEs. After an initial screening of a total of 170 articles, the key publications based on the research questions were selected for a more in-depth analysis. It emerged that although construction SMEs have embraced the use of several digital technologies during the current pandemic, there is still a large digital divide between these companies and larger companies. The research discussed in this paper contributes to efforts directed at addressing this problem through the design and deployment of SME-centric digital technologies for construction health and safety. © 2021 Computing in Civil Engineering 2021 - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2021. All rights reserved.

5.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research ; 25(7):S605-S605, 2022.
Article in English | EuropePMC | ID: covidwho-1905495
6.
Alcoholism-Clinical and Experimental Research ; 46:228A-228A, 2022.
Article in English | Web of Science | ID: covidwho-1894073
7.
Molecular Therapy ; 30(4):11-12, 2022.
Article in English | English Web of Science | ID: covidwho-1880181
8.
Engineering Construction and Architectural Management ; : 19, 2022.
Article in English | Web of Science | ID: covidwho-1868459

ABSTRACT

Purpose The unprecedented SARS-CoV-2 (COVID-19) pandemic has further constrained the budgets of governments worldwide for delivering their much-needed infrastructure. Consequently, public-private partnerships (PPPs), with the private sector's investment and ingenuity, would appear to be an increasingly popular alternative. Value for money (VfM) has become the major criterion for evaluating PPPs against the traditional public sector procurement and, however, is plagued with controversy. Hence, it is important that governments compare and contrast their practice with similar and disparate bodies to engender best practice. This paper, therefore, aims to understand governments' assessment context and provide a cross-continental comparison of their VfM assessment. Design/methodology/approach Faced with different domestic contexts (e.g. aging infrastructure, population growth, and competing demands on finance), governments tend to place different emphases when undertaking the VfM assessment. In line with the theory of boundary spanning, a cross-continental comparison is conducted between three of the most noticeable PPP markets (i.e. the United Kingdom, Australia and China) about their VfM assessment. The institutional level is interpreted by a social, economic and political framework, and the methodological level is elucidated through a qualitative and quantitative VfM assessment. Findings There are individual institutional characteristics that have shaped the way each country assesses VfM. For the methodological level, we identify that: (1) these global markets use a public sector comparator as the benchmark in VfM assessment;(2) ambiguous qualitative assessment is conducted only against PPPs to strengthen their policy development;(3) Australia's priority is in service provision whereas that of the UK and China is project finance and production;and (4) all markets are seeking an amelioration of existing controversial VfM assessments so that purported VfM relates to project lifecycles. As such, an option framework is proposed to make headway towards a sensible selection of infrastructure procurement approaches in the post COVID-19 era. Originality/value This study addresses a current void of enhancing the decision-making process for using PPPs within today's changing environment and then opens up an avenue for future empirical research to examine the option framework and ensuing VfM decisions. Practically, it presents a holistic VfM landscape for public sector procurers that aim to engage with PPPs for their infrastructure interventions.

9.
Chinese Pharmacological Bulletin ; 36(12):1629-1636, 2020.
Article in Chinese | EMBASE | ID: covidwho-1863008

ABSTRACT

At present, coronavirus disease-19 (COVID-19) caused by novel coronavirus (SARS-CoV-2) has been spreading around the world, but no specific therapeutic drug or vaccine has been developed for the virus. By collecting the latest literature and searching related database websites, the biological charac¬teristics and main targets of SARS-CoV-2, the clinical therapeu¬ tic drugs and the latest drug research were reviewed to provide information for clinical treatment and provide reference for the research and development of new drugs against SARS-CoV-2.

10.
Mbio ; 12(5):21, 2021.
Article in English | Web of Science | ID: covidwho-1854240

ABSTRACT

Newly emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic with astonishing mortality and morbidity. The high replication and transmission of SARS-CoV-2 are remarkably distinct from those of previous closely related coronaviruses, and the underlying molecular mechanisms remain unclear. The innate immune defense is a physical barrier that restricts viral replication. We report here that the SARS-CoV-2 Nsp5 main protease targets RIG-I and mitochondrial antiviral signaling (MAVS) protein via two distinct mechanisms for inhibition. Specifically, Nsp5 cleaves off the 10 most-N-terminal amino acids from RIG-I and deprives it of the ability to activate MAVS, whereas Nsp5 promotes the ubiquitination and proteosome-mediated degradation of MAVS. As such, Nsp5 potently inhibits interferon (IFN) induction by double-stranded RNA (dsRNA) in an enzyme-dependent manner. A synthetic small-molecule inhibitor blunts the Nsp5mediated destruction of cellular RIG-I and MAVS and processing of SARS-CoV-2 nonstructural proteins, thus restoring the innate immune response and impeding SARSCoV-2 replication. This work offers new insight into the immune evasion strategy of SARS-CoV-2 and provides a potential antiviral agent to treat CoV disease 2019 (COVID-19) patients. IMPORTANCE The ongoing COVID-19 pandemic is caused by SARS-CoV-2, which is rapidly evolving with better transmissibility. Understanding the molecular basis of the SARS-CoV-2 interaction with host cells is of paramount significance, and development of antiviral agents provides new avenues to prevent and treat COVID-19 diseases. This study describes a molecular characterization of innate immune evasion mediated by the SARS-CoV-2 Nsp5 main protease and subsequent development of a small-molecule inhibitor.

11.
Socius ; 8, 2022.
Article in English | Scopus | ID: covidwho-1833250

ABSTRACT

In this article, we report the results of a randomized controlled experiment that examines how exposure to information about a global pandemic from Asia affects white Americans’ prosocial behavior towards white, black, and Asian Americans. We find that when exposed to a new disease threat from Asia, (1) white Americans donate significantly less money to Asian American recipients than to white or black American recipients, (2) liberals and conservatives are equally likely to discriminate, and (3) a significant spike in media attention about violence against Asians inhibited this discriminatory behavior—at least temporarily. Our experiment allows us to rule out alternative explanations for the unequal treatment of Asian Americans, providing evidence of a causal link between the COVID-19 pandemic and racial discrimination. The study contributes to knowledge about the spillover effects of external threats on race relations and has implications for public health and science communication. © The Author(s) 2022.

12.
2nd International Conference on Electronics, Communications and Information Technology, CECIT 2021 ; : 292-297, 2021.
Article in English | Scopus | ID: covidwho-1831727

ABSTRACT

COVID-19 is breaking out and spreading globally, posing a severe threat to public health and economies worldwide due to its highly transmissible and pathogenic nature. Early, accurate and rapid diagnosis of COVID-19 can effectively stop the spread of the COVID-19 virus. Automatic diagnostic models based on deep learning can detect COVID-19 quickly and accurately. This paper uses a three-dimensional Convolutional Neural Network (3D CNN) to build a COVID-19 diagnostic prediction model for COVID-19 detection. All 192 sets of chest Computed Tomography(CT) data collected are used for this study, including 96 sets of confirmed COVID-19 patients and 96 sets of CT scans of normal human lungs. 5-fold cross-validation is used to train and validate the model. 154 data sets are used to train the model, and 38 sets are used for testing. All experimental data are segmented using a pre-trained SP-V-Net to obtain 3D lung masks fed into 3D CNN for training and validation of the prediction model. In addition, to verify the accuracy of the model predictions and provide interpretability for medical diagnosis, we visualize the experimental results using Class Activation Maps(CAM) to localize the predicted disease regions. The results from several experiments show that the accuracy of our prediction model is 0.911, the Area Under Curve (AUC) 0.976, for no-COVID-19(Precision, 0.902, Recall 0.911, F1-Score 0.900), COVID-19 (Precision, 0.932, Recall 0.911, F1-Score 0.902). The experimental results show that our established diagnostic model can help physicians make a rapid and accurate diagnosis of COVID-19 in response to the spread of COVID-19. © 2021 IEEE.

13.
Clinical Cancer Research ; 27(6 SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1816919

ABSTRACT

Cancer patients display immunomodulation related to malignancy and anti-cancer therapies, but how these factors impact COVID-19 remains unknown. To investigate immune responses in cancer patients with COVID-19, we undertook a prospective case-control study, enrolling hospitalized solid tumor patients with acute COVID-19, as well as age-, gender-, and comorbidity-matched COVID-19 patients without cancer as controls. Using biospecimens collected during hospitalization, we performed virologic measurements as well as in-depth immunophenotyping of cellular, antibody and cytokine responses. We enrolled 17 cancer patients (cases) admitted to Yale-New Haven Hospital between March 15 and June 30, 2020 with COVID-19, as well as 17 matched non-cancer patients (controls) admitted with COVID-19. No significant differences were observed between cases and controls based on patient characteristics (age, gender, race, co-morbidities, smoking history, days from symptom onset to COVID-19 diagnosis) or outcomes (COVID-19 severity, length of hospital stay, rate of intubation or mortality). The most common primary tumor sites were lung (4/17) and gastrointestinal (4/17);all cases had received cancer-directed therapy within 6 months of COVID-19 diagnosis, with 13/17 receiving treatment less than 1 month prior to hospitalization. Three of 17 cases had received immune checkpoint inhibitor therapies. Despite having similar SARS-CoV-2 viral RNA loads at the time of COVID-19 diagnosis when compared with controls, cancer cases had increased viral RNA abundance during hospitalization, suggesting slower clearance. Antibody responses against SARS-CoV-2 were preserved in cancer cases, with cases displaying similar levels of IgM and IgG antibodies directed against SARS-CoV-2 epitopes compared to controls. Cytokine profiling revealed higher plasma levels of CCL3, IL1A and CXCL12 in cancer cases compared to controls. Using flow cytometric immunophenotyping, we found that innate immune and non-T cell adaptive immune parameters were similar between cases and controls hospitalized with COVID-19. However, among cancer cases on conventional therapies, T cell lymphopenia was more profound, and these cases demonstrated higher levels of CD8+ exhausted (CD8+CD45RA-PD1+TIM3+ ), CD8+GranzymeB+ and CD4+CD38+HLA-DR+ and CD8+CD38+HLA-DR+ activated T cells when compared with controls;interestingly, these differences were not observed in patients who had received immune checkpoint inhibition. Thus, we found reduced viral RNA clearance and specific alterations in T cell and cytokine responses in cancer patients hospitalized with COVID-19 compared with matched controls with COVID-19. This dysregulated T cell response in cancer patients, which may reflect immune modulation due to chronic antigen stimulation as well as cancer therapies, may lead to altered virologic and clinical outcomes in this population.

14.
Psychiatria Danubina ; 34:S929-S933, 2022.
Article in English | Web of Science | ID: covidwho-1813136

ABSTRACT

Background: By the end of 2021, the COVID-19 outbreak has led to an increase of 90 million patients with anxiety disorders worldwide, which has had a significant adverse impact on human mental health. Music Therapy is a treatment method that utilizes the huge influence of music on emotions, changes people's emotions through music, and finally achieves the purpose of psychological healing. This study starts with Music Therapy and selects patients with anxiety disorders from a hospital in Hebei Province, China as subjects to explore the therapeutic effect of Music Therapy on patients with anxiety disorders. Subjects and Methods: The S-AI and TAI scores of the subjects were tested before treatment, after five weeks of treatment, and after ten weeks of treatment. And both the variable correlation analysis and t-test were carried out, using SPSS22.0 as the statistical tool. Results: The total STAI score of the experimental group was significantly higher than that of the control group after ten weeks of treatment (t = 164.102, P < 0.001). After five weeks of treatment, the STAI score of the experimental group decreased significantly compared with that before treatment (t = 56.742, P < 0.001). After ten weeks of treatment, the STAI score of the experimental group decreased significantly compared with that after five weeks of treatment (t = 71.155, P < 0.001). Conclusions: Music Therapy improves the patients' physical conditions such as sleep and energy, eating, movement and feeling. It is pain-free, low-cost, simple and easy to implement. Furthermore, it can also improve patients' interpersonal skills, work and study efficiency, as well as leisure and entertainment life satisfaction. It is worthy of promotion in the treatment of patients with generalized anxiety disorders.

15.
Zhonghua Liu Xing Bing Xue Za Zhi ; 43(4): 460-465, 2022 Apr 10.
Article in Chinese | MEDLINE | ID: covidwho-1810383

ABSTRACT

Objective: To understand the research progresses of economic evaluation of COVID-19 vaccination strategies both at home and abroad, and provide reference for the economic evaluation of COVID-19 vaccination strategies using real word data in China. Methods: Literature retrieval was conducted for related papers published from January, 2020 to December, 2021 in Chinese and English databases, including the economic evaluation of COVID-19 vaccination, and the results of the related literatures were narratively integrated. Results: A total of 16 English literatures (including 3 reviews) were included, and it was found that the COVID-19 vaccination was cost-effective or cost-saving regardless of the vaccine types, while the cost-effectiveness in different population and under different vaccination dose strategies varied due to vaccine efficacy, vaccine price, duration of natural immunity, duration of vaccination campaign, vaccine supply, and vaccination pace. Conclusions: China lacks suitable evidences of economic evaluation of COVID-19 vaccination strategies based on real-world data in the context of long-term epidemic. Therefore, further researches of suitable strategies of booster COVID-19 vaccination are needed.


Subject(s)
COVID-19 Vaccines , COVID-19 , COVID-19/prevention & control , China/epidemiology , Cost-Benefit Analysis , Humans , Vaccination
16.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333600

ABSTRACT

OBJECTIVE: Identifying symptoms highly specific to COVID-19 would improve the clinical and public health response to infectious outbreaks. Here, we describe a high-throughput approach - Concept-Wide Association Study (ConceptWAS) that systematically scans a disease's clinical manifestations from clinical notes. We used this method to identify symptoms specific to COVID-19 early in the course of the pandemic. METHODS: Using the Vanderbilt University Medical Center (VUMC) EHR, we parsed clinical notes through a natural language processing pipeline to extract clinical concepts. We examined the difference in concepts derived from the notes of COVID-19-positive and COVID-19-negative patients on the PCR testing date. We performed ConceptWAS using the cumulative data every two weeks for early identifying specific COVID-19 symptoms. RESULTS: We processed 87,753 notes 19,692 patients (1,483 COVID-19-positive) subjected to COVID-19 PCR testing between March 8, 2020, and May 27, 2020. We found 68 clinical concepts significantly associated with COVID-19. We identified symptoms associated with increasing risk of COVID-19, including "absent sense of smell" (odds ratio [OR] = 4.97, 95% confidence interval [CI] = 3.21-7.50), "fever" (OR = 1.43, 95% CI = 1.28-1.59), "with cough fever" (OR = 2.29, 95% CI = 1.75-2.96), and "ageusia" (OR = 5.18, 95% CI = 3.02-8.58). Using ConceptWAS, we were able to detect loss sense of smell or taste three weeks prior to their inclusion as symptoms of the disease by the Centers for Disease Control and Prevention (CDC). CONCLUSION: ConceptWAS is a high-throughput approach for exploring specific symptoms of a disease like COVID-19, with a promise for enabling EHR-powered early disease manifestations identification.

17.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333514

ABSTRACT

BACKGROUND: The novel human coronavirus disease 2019 (COVID-19) pandemic has claimed more than 240,000 lives worldwide, causing tremendous public health, social, and economic damages. While the risk factors of COVID-19 are still under investigation, environmental factors, such as urban air pollution, may play an important role in increasing population susceptibility to COVID-19 pathogenesis. METHODS: We conducted a cross-sectional nationwide study using zero-inflated negative binomial models to estimate the association between long-term (2010-2016) county-level exposures to NO2, PM2.5 and O3 and county-level COVID-19 case-fatality and mortality rates in the US. We used both single and multipollutant models and controlled for spatial trends and a comprehensive set of potential confounders, including state-level test positive rate, county-level healthcare capacity, phase-of-epidemic, population mobility, sociodemographic, socioeconomic status, behavior risk factors, and meteorological factors. RESULTS: 1,027,799 COVID-19 cases and 58,489 deaths were reported in 3,122 US counties from January 22, 2020 to April 29, 2020, with an overall observed case-fatality rate of 5.8%. Spatial variations were observed for both COVID-19 death outcomes and long-term ambient air pollutant levels. County-level average NO2 concentrations were positively associated with both COVID-19 case-fatality rate and mortality rate in single-, bi-, and tri-pollutant models (p-values<0.05). Per inter-quartile range (IQR) increase in NO2 (4.6 ppb), COVID-19 case-fatality rate and mortality rate were associated with an increase of 7.1% (95% CI 1.2% to 13.4%) and 11.2% (95% CI 3.4% to 19.5%), respectively. We did not observe significant associations between long-term exposures to PM2.5 or O3 and COVID-19 death outcomes (p-values>0.05), although per IQR increase in PM2.5 (3.4 ug/m3) was marginally associated with 10.8% (95% CI: -1.1% to 24.1%) increase in COVID-19 mortality rate. DISCUSSIONS AND CONCLUSIONS: Long-term exposure to NO2, which largely arises from urban combustion sources such as traffic, may enhance susceptibility to severe COVID-19 outcomes, independent of long-term PM2.5 and O3 exposure. The results support targeted public health actions to protect residents from COVID-19 in heavily polluted regions with historically high NO2 levels. Moreover, continuation of current efforts to lower traffic emissions and ambient air pollution levels may be an important component of reducing population-level risk of COVID-19 deaths.

18.
4th Artificial Intelligence and Cloud Computing Conference, AICCC 2021 ; : 208-215, 2021.
Article in English | Scopus | ID: covidwho-1789021

ABSTRACT

English Teachers resource allocation problem (TRAP) which is a highly complex multi-level system is a talent scheduling problem (TSP) with limited human, material and financial resources. It is of great significance to study the allocation of teacher resource in a century-long plan based on education. In this paper, under the effective control of COVID-19, taking the Bayannur City of Inner Mongolia as an example, teaching sites are set up to study the TRAP for the resumption of classes in the graduating grade. In order to minimize the total cost of the whole distribution system, a multi-objective linear hybrid model (MOLHM) is proposed based on the fact about different demands on the number of teachers in each site, the different daily salary of teachers with different teaching experience and degree level, and the different cost of transporting teachers to respective destination. And three heuristic algorithms, ant colony optimization algorithm (ACOA), tabu search algorithm (TSA) and particle swarm optimization algorithm (PSOA) are used to solve the model. Through numerical experiments, the feasibility of them is verified, and the performances of them is compared in terms of optimization results and running time. In the system of the paper, the optimization result of ACOA is optimal, and TSA has better performance of running time. Under the condition that the equal number of ants and particles, the running time of PSOA is better than that of ACOA. © 2021 ACM.

19.
International Journal of Emerging Markets ; 2022.
Article in English | Scopus | ID: covidwho-1788589

ABSTRACT

Purpose: This paper investigates the current psychological state of Chinese tourism practitioners and their career resilience during the ongoing COVID-19 pandemic. It empirically examines the effects of COVID-19 on Chinese tourism practitioners' professional attitudes and their career belief in the future. The study is intended to guide enterprises and governments to design effective strategies/policies to deal with the effect of this unfavorable environment. Design/methodology/approach: The sample consists of 442 tourism practitioners in 313 tourism enterprises in China. The data were collected via a targeted online survey based on a well-structured questionnaire. The data were analyzed using statistical procedures including multilevel regression analysis. Findings: The study results show that Chinese tourism practitioners have strong career resilience in the face of current turbulent time. After testing, the model shows that career beliefs and social support have a significant positive impact on the professional attitudes of tourism practitioners, and that career resilience has a partial mediating effect on their career beliefs, social support and professional attitude. Originality/value: This study enriches the existing literature on career belief, social support and career resilience. It provides a new interpretation on how career belief and social support impact career resilience and thus shape tourism practitioners' professional attitudes during pandemics. © 2022, Emerald Publishing Limited.

20.
Review of Behavioral Finance ; : 26, 2022.
Article in English | Web of Science | ID: covidwho-1784472

ABSTRACT

Purpose The paper provides new evidence for Bitcoin's safe-haven property by examining the relationship between currency price, return and Bitcoin trading volume. Design/methodology/approach A unique dataset from a person-to-person (p2p) exchange is used to investigate association between Bitcoin trading volume and currency prices. Currency returns are used to identify local economic crises, the 8 crisis affected currencies are Venezuela Bolivar (VES), Iranian Rial (IRR), Ukrainian Hryvnia (UAH), Argentine Peso (ARS), Egyptian Pound (EGP), Nigerian Naira (NGN), Turkish Lira (TRY) and Kazakhstani Tenge (KZT). Findings The paper demonstrates that local economic crises are positively associated with increased Bitcoin trading. There is a negative association between trading volume and currency value (and return), suggesting low currency price and currency depreciation are accompanied with increased Bitcoin trading. The results not only hold for the crisis affected currencies but also currencies of advanced economies. Granger causality test also reinforces the negative association results. Originality/value The finding indicates some forms of flight-to-safety have occurred during local market crises when capital flight from domestic markets to Bitcoin, strengthening Bitcoin's hedging asset status. However, total global trading volume declines after the start of the COVID pandemic, suggesting that Bitcoin is still regarded as a speculative asset. Overall, the findings show that Bitcoin is a hedging asset to protect against local currency depreciation, but not a safe-haven asset for the global crisis.

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