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1.
Computers, Materials and Continua ; 72(3):5059-5078, 2022.
Article in English | Scopus | ID: covidwho-1836524

ABSTRACT

The main objective of this study is to comprehensively investigate individuals' vaccination intention against COVID-19 during the second wave of COVID-19 spread in Vietnam using a novel hybrid approach. First, the Decision-Making Trial and Evaluation Laboratory based on Grey Theory (DEMATEL-G) was employed to explore the critical factors of vaccination intention among individuals. Second, Partial Least Squares-Structural Equation Modeling (PLS-SEM) was applied to test the hypotheses of individual behavioral intention to get the vaccine to prevent the outbreak of COVID- 19. A panel of 661 valid respondents was collected from June 2021 to July 2021, and confidentiality was maintained for all data obtained. The results identified that perception of COVID-19 vaccination and trust in vaccination strategy directly associated with individuals' COVID-19 immunization. Hence, the perceived severity of COVID-19 has an indirect impact onCOVID- 19 vaccination intentions via the perception of the COVID-19 vaccine. These findings indicated that the government's information about vaccines is necessary for the new phase of vaccination intervention strategies in Vietnam. Therefore, the study suggests that the government needs to give complete information about the role of vaccines prioritizes transparency in official information about COVID-19 vaccines to allay concerns about side effects, allowing for the most appropriate policy formulation and implementation to encourage public vaccination. Future studies can apply PLS-SEM and other MCDMmodels with the fuzzy, hesitant numbers to re-evaluate the feasibility, validity and reliability of this research's proposed model. © 2022 Tech Science Press. All rights reserved.

2.
Green Energy and Technology ; : 187-203, 2022.
Article in English | Scopus | ID: covidwho-1826224

ABSTRACT

Recently, the Covid-19 pandemic has become very complicated and seriously affecting the economy as well as society in every countries in the world. In this chapter, we explore the solution of Computer Vision for handling the Covid-19 pandemic situation. The given scenarios based on deep learning techniques are used to monitor the traffic of people and vehicles through the checkpoints to control the in-out movement in significant areas. In addition, we also need to pay attention to complying with the regulations on wearing masks and ensuring a safe social distance in public places. From there, the proposed system will effectively support organizations to deal with the Covid-19 pandemic. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

3.
Clinical Cancer Research ; 27(6 SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1816895

ABSTRACT

Background: Cancer therapy may put patients at risk of mortality from COVID-19. The impact of abbreviated treatment courses on outcomes in the setting of COVID-19 is unknown. We incorporated COVID-19-associated risks in re-analysis of practice-defining randomized trials in oncology that compared different radiation therapy (RT) regimens. Methods: We extracted individual patient level data (IPLD) from published survival curves from randomized trials in rectal cancer (Dutch TME, TROG 01.04), early stage breast cancer (CALGB 9343, OCOG hypofractionation trial, FAST-Forward, NSABP B-39), and localized prostate cancer (CHHiP, HYPO-RT-PC). Trials were simulated with incorporation of varying risk of SARS-CoV-2 infection and mortality associated with receipt of therapy. Results: IPLD from 14,170 patients were re-analyzed. In scenarios with low COVID-19-associated risks (0.5% infection risk per fraction [IRF], 5% case fatality rate [CFR]), fractionation did not significantly affect outcomes. In locally advanced rectal cancer, short-course RT appeared preferable to long-course chemoradiation (TROG 01.04) or RT omission (Dutch TME) in most settings. While moderate hypofractionation in early stage breast cancer (OCOG hypofractionation trial) and prostate cancer (CHHiP) was not associated with survival benefits in the setting of COVID-19, more aggressive hypofractionation (FAST-Forward, HYPO-RT-PC) and accelerated partial breast irradiation (NSABP B-39) were associated with improved survival in higher risk scenarios (≥5% IRF;≥ 20% CFR). In settings where RT can be omitted, such as favorable early stage breast cancer in the elderly (CALGB 9343), RT was associated with worse survival in higher risk pandemic scenarios (≥5% IRF, ≥ 20% CFR). Conclusions: Our framework, which can be adapted to dynamic changes in COVID-19 risk, provides a flexible, quantitative approach to assess the impact of treatment recommendations across oncology. The magnitude of potential benefit from abbreviated RT courses depends on the degree of hypofractionation and local COVID-19-associated risk. Abbreviated RT courses should be prioritized when possible and are increasingly beneficial in higher risk pandemic settings. With increased understanding and precautions against COVID-19 that can minimize risks for patients, our results support the continued use of evidence-based treatments for cancer patients in the COVID-19 era.

4.
Epidemics ; 39: 100569, 2022 Apr 28.
Article in English | MEDLINE | ID: covidwho-1804061

ABSTRACT

The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more. In addition to numerous challenges in epidemiology, healthcare, biosciences, and social sciences, there has been an urgent need to develop and provide visualisation and visual analytics (VIS) capacities to support emergency responses under difficult operational conditions. In this paper, we report the experience of a group of VIS volunteers who have been working in a large research and development consortium and providing VIS support to various observational, analytical, model-developmental, and disseminative tasks. In particular, we describe our approaches to the challenges that we have encountered in requirements analysis, data acquisition, visual design, software design, system development, team organisation, and resource planning. By reflecting on our experience, we propose a set of recommendations as the first step towards a methodology for developing and providing rapid VIS capacities to support emergency responses.

5.
International Journal of Qualitative Methods ; 21:13, 2022.
Article in English | Web of Science | ID: covidwho-1799145

ABSTRACT

Doing remote fieldwork is a 'new normal' in the COVID-19 pandemic era. It is challenging, but not impossible. With planning and preparation, comprehensive training and ongoing support for Research Assistants (RAs), researchers can overcome the challenges of remote fieldwork. In this article, we reflect on the experience of employing local RAs to support doctoral research involving in-depth household interviews and focus group discussions with ethnic minority people in upland Vietnam. The challenge of adapting to this 'new normal' provided us with an opportunity for a critical appraisal of the researcher-RA relationship. The approach to remote fieldwork we developed centres on frequent communication, feedback and building trusting team dynamics. We argue that this approach can overcome some of the power hierarchies between global north researchers and local RAs, and therefore, should not simply be seen as a temporary or inferior 'Plan B' for researchers, but should be embraced as a way of reimagining knowledge production. We discuss lessons learned in how to carry out remote fieldwork, present practical strategies and recommendations, and consider the strengths of this approach for knowledge production and the empowerment of researchers in the global south.

6.
Journal of Asian Finance Economics and Business ; 9(4):367-380, 2022.
Article in English | Web of Science | ID: covidwho-1798662

ABSTRACT

Using an extended unified theory of acceptance and use of technology, the goal of this paper is to investigate the antecedents of behavioral intention towards mobile money, as well as the mediating effect of trust between behavioral intention and financial inclusion in Vietnam during the COVID-19 period (UTAUT2). The data for this study was obtained via an online self-administered questionnaire, which was then analyzed using the SmartPLS 3.3.3 program. For the purpose of determining the relevance and performance of the exogenous constructs, an importance-performance matrix analysis was performed. The findings of this study suggest that knowledge, structural assurance, habit, and performance expectancy are the most important factors influencing users' behavioral intention to use mobile money. In the case of mobile money adoption, the behavioral intention has a significant influence, and trust does not mediate between behavioral intention and financial inclusion. For the first time in Vietnam, the extended UTAUT2 is being used to investigate mobile money usage and adoption patterns. The current study, however, focuses on users' financial inclusion goals rather than their intended behavior.

7.
IEEE Transactions on Services Computing ; 2022.
Article in English | Scopus | ID: covidwho-1788797

ABSTRACT

We present the design and development of a data visualization service (RAMPVIS) in response to the urgent need to support epidemiological modeling workflows during the COVID-19 pandemic. Facing a set of demanding requirements and several practical challenges, our small team of volunteers had to rely on existing knowledge and components of services computing, while thinking on our feet in configuring services composition and adopting suitable approaches to services engineering. Through developing the RAMPVIS service, we have gained useful experience of ensuring conformation to services computing standards, enabling rapid development and early deployment, and facilitating effective and efficient maintenance and operation with limited resources. This experience can be valuable to the ongoing effort for combating the COVID-19 pandemic, and provides a blueprint for visualization service development when future needs for visual analytics arise during emergency response. IEEE

8.
6th IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2021 ; : 117-118, 2021.
Article in English | Scopus | ID: covidwho-1759015

ABSTRACT

This work introduces a low-latency, searchable web tool for biologist and healthcare researchers to quickly explore a large number of host-pathogen interactions (HPI) reported in scientific publication. Our database contains 23,581 generic HPI and 257 COVID-19 related HPI extracted from 32 million PubMed s. The data was automatically collected by running our high-precision biomedical text mining system, which consumes much less effort than manual curation while still provides reliable output. Web URL: philm2web.live © 2021 IEEE.

9.
Biophysical Journal ; 121(3):538A-538A, 2022.
Article in English | Web of Science | ID: covidwho-1755846
10.
Open Forum Infectious Diseases ; 8(SUPPL 1):S267, 2021.
Article in English | EMBASE | ID: covidwho-1746669

ABSTRACT

Background. The data on CAPA in the U.S. are limited to date and clinical characteristics unique to this phenomenon have not been widely reported. Methods. This retrospective observational study was conducted at multiple VA hospitals across southern California and Arizona. CAPA cases were identified in inpatients with laboratory-confirmed COVID-19 based on microbiologic or serologic evidence of aspergillosis and pulmonary abnormalities on imaging, and were classified according to ECMM/ISHAM consensus definitions. Characteristics of interest included immunosuppressive/modulatory agents used prior to onset of CAPA, COVID-19 disease course, length of hospitalization, and mortality. Results. Seventeen patients with probable (18%) or possible (82%) CAPA were identified from April 2020 to March 2021. Values below reported as medians. All patients were male and 13 (76%) were white, with age 74 years and BMI 26 kg/m2. Baseline comorbidities included diabetes mellitus (47%), cardiovascular disease (65%), and pulmonary disease (71%). Evidence of aspergillosis was mostly based on respiratory culture, with mainly A. fumigatus (75%). Systemic corticosteroids were used in 14 patients, with a total dose of 400 mg prednisone equivalents starting 10 days prior to Aspergillus detection. Patients also received tocilizumab (18%), leflunomide (6%), tacrolimus (6%), mycophenolate (6%), and investigational agent LSALT or placebo (6%);2 patients (12%) did not receive any immunosuppression/modulation. Length of hospitalization for COVID-19 was 22 days. Death occurred in 12 patients (71%), including all patients with probable CAPA, at 34 days after COVID-19 diagnosis and 16 days after CAPA diagnosis. Eight patients (47%) were treated for aspergillosis;mortality did not appear to differ with treatment (75% vs. 67%). Conclusion. This case series reports high mortality among patients with CAPA;the primary contributor to this outcome is unclear. Frequency of lower respiratory tract sampling in patients with COVID-19 may have limited diagnosis of CAPA. Interestingly, inpatient respiratory cultures with Aspergillus spp. increased compared to previous years. Future work will attempt to identify risk factors for CAPA and attributable mortality via comparison to inpatients with COVID-19 without CAPA.

11.
Open Forum Infectious Diseases ; 8(SUPPL 1):S367-S368, 2021.
Article in English | EMBASE | ID: covidwho-1746464

ABSTRACT

Background. Bamlanivimab and casirivimab/imdevimab were the first monoclonal antibodies (mAb) developed against SARS-CoV-2 and proved beneficial early in the course of infection. However, real-world administration of these therapies presents logistical challenges. We present our experience implementing mAb treatment at a large VA Medical Center and review the efficacy of therapy in preventing hospitalization from COVID-19 in a closed healthcare system. Methods. All positive outpatient COVID tests performed at VA Greater Los Angeles Healthcare System (GLA) were reviewed by the Emergency Medicine (EM) and Infectious Diseases (ID) Sections for mAb eligibility beginning 12/2/2020. Due to limited supply, treatment was prioritized for patients at highest risk of developing severe disease, as determined by EM/ID with input from a machine learning ensemble risk estimation model produced by VA National Artificial Intelligence Institute (Figure 1). If a patient declined or did not reply, treatment was offered to the next patient on a ranked eligibility list. Those who declined or were eligible but not treated were included in the analysis. Patients were excluded if they were hospitalized before treatment was offered. We collected data on age, comorbidities, date of diagnosis, and admission at 30 days after diagnosis. A multivariate log binomial regression was performed to determine the relative risk of admission within 30 days of diagnosis for those who received mAb therapy as compared to those who did not, adjusting for age and comorbidity. All analysis was done in R (version 4.0.5). Results. 139 patients met inclusion criteria. 45 (32%) received mAb therapy, 48 (35%) declined mAb therapy, and the remaining 46 (33%) either did not respond or were not offered mAb therapy. Hospitalizations following diagnosis in each group are illustrated in Figure 2. There was a trend towards reduced absolute and relative risk of hospitalization (Table 1). There were no anaphylactic events in patients who received mAb therapy. Conclusion. At our facility, a system for rapid identification of candidates and a coordinated distribution plan was essential in ensuring timely administration of mAb therapy to eligible patients. Administration of mAb showed a trend towards decreased risk of hospitalization due to SARS-CoV-2.

12.
2021 IEEE International Conference on Big Data, Big Data 2021 ; : 4387-4395, 2021.
Article in English | Scopus | ID: covidwho-1730874

ABSTRACT

COVID-19 is an air-borne viral infection, which infects the respiratory system in the human body, and it became a global pandemic in early March 2020. The damage caused by the COVID-19 disease in a human lung region can be identified using Computed Tomography (CT) scans. We present a novel approach in classifying COVID-19 infection and normal patients using a Random Forest (RF) model to train on a combination of Deep Learning (DL) features and Radiomic texture features extracted from CT scans of patient's lungs. We developed and trained DL models using CNN architectures for extracting DL features. The Radiomic texture features are calculated using CT scans and its associated infection masks. In this work, we claim that the RFs classification using the DL features in conjunction with Radiomic texture features enhances prediction performance. The experiment results show that our proposed models achieve a higher True Positive rate with the average Area Under the Receiver Curve (AUC) of 0.9768, 95% Confidence Interval (CI) [0.9757, 0.9780]. © 2021 IEEE.

13.
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-329605

ABSTRACT

Microglia, the innate immune cells of the brain, are exquisitely sensitive to dynamic changes in the neural environment. Using single cell RNA sequencing of the postnatal somatosensory cortex during topographic remapping, we identified a type I interferon (IFN-I) responsive microglia population that expanded with this developmental stressor. Using the marker gene IFITM3 we found that IFN-I responsive microglia were engulfing whole neurons. Loss of IFN-I signaling ( Ifnar1 -/- ) resulted in dysmorphic 'bubble' microglia with enlarged phagolysosomal compartments. We also observed a reduction in dead cells and an accumulation of neurons with double strand DNA breaks, a marker of cell stress. Conversely, IFN-I gain of function in zebrafish was sufficient to drive microglial engulfment of whole neurons. We identified IFITM3+ microglia in two murine disease models: SARS-CoV-2 infection and the 5xFAD model of Alzheimer's disease. These data reveal a novel role for IFN-I signaling in regulating efficient neuronal clearance by microglia.

14.
Accounting Research Journal ; 34(3):279-289, 2021.
Article in English | Web of Science | ID: covidwho-1703301

ABSTRACT

Purpose - Coronavirus (COVID-19) has caused upheaval in university teaching practices. This paper aims to document how the teaching team on a large third-year undergraduate financial accounting course in an Australian university coped with the impact of the virus. Changes in teaching practices when classes shifted from face-to-face to online instruction during the COVID-19 crisis are described and examined using the crisis management process framework of Pearson and Clair (1998). Teaching team members were asked to write brief reflections on their experiences teaching the course during the period from February to July 2020. These were then thematically analysed and included as outcomes within the Pearson and Clair (1998) framework. Design/methodology/approach - Description of COVID-19 induced changes to teaching a large undergraduate financial accounting course at an Australian university. Findings - Six outcomes emerged: learning new technology;collegiality;the course review;the online delivery experience;redesigning assessments and;time investment;conjectures are offered about the survival of some of the changes made during the year. Research limitations/implications - The research only covers one teaching team's experience but that is the purpose of the special issue. Practical implications - Lessons for the future are explored. Social implications - The implications of online teaching are explored. Originality/value - The paper provides a historical record of how the teaching team on a large undergraduate financial accounting course coped with an unexpected, major event that necessitated rapid and radical changes to teaching methods.

15.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-308226

ABSTRACT

The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more. In addition to numerous challenges in epidemiology, healthcare, biosciences, and social sciences, there has been an urgent need to develop and provide visualisation and visual analytics (VIS) capacities to support emergency responses under difficult operational conditions. In this paper, we report the experience of a group of VIS volunteers who have been working in a large research and development consortium and providing VIS support to various observational, analytical, model-developmental and disseminative tasks. In particular, we describe our approaches to the challenges that we have encountered in requirements analysis, data acquisition, visual design, software design, system development, team organisation, and resource planning. By reflecting on our experience, we propose a set of recommendations as the first step towards a methodology for developing and providing rapid VIS capacities to support emergency responses.

16.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326914

ABSTRACT

The BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) vaccines generate potent neutralizing antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the global emergence of SARS-CoV-2 variants with mutations in the spike protein, the principal antigenic target of these vaccines, has raised concerns over the neutralizing activity of vaccine-induced antibody responses. The Omicron variant, which emerged in November 2021, consists of over 30 mutations within the spike protein. Here, we used an authentic live virus neutralization assay to examine the neutralizing activity of the SARS-CoV-2 Omicron variant against mRNA vaccine-induced antibody responses. Following the 2nd dose, we observed a 30-fold reduction in neutralizing activity against the omicron variant. Through six months after the 2nd dose, none of the sera from naïve vaccinated subjects showed neutralizing activity against the Omicron variant. In contrast, recovered vaccinated individuals showed a 22-fold reduction with more than half of the subjects retaining neutralizing antibody responses. Following a booster shot (3rd dose), we observed a 14-fold reduction in neutralizing activity against the omicron variant and over 90% of boosted subjects showed neutralizing activity against the omicron variant. These findings show that a 3rd dose is required to provide robust neutralizing antibody responses against the Omicron variant.

17.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326782

ABSTRACT

SARS-CoV-2 is the highly transmissible etiologic agent of coronavirus disease 2019 (COVID-19) and has become a global scientific and public health challenge since December 2019. Several new variants of SARS-CoV-2 have emerged globally raising concern about prevention and treatment of COVID-19. Early detection and in depth analysis of the emerging variants allowing pre-emptive alert and mitigation efforts are thus of paramount importance. Here we present ClusTRace, a novel bioinformatic pipeline for a fast and scalable analysis of sequence clusters or clades in large viral phylogenies. ClusTRace offers several high level functionalities including outlier filtering, aligning, phylogenetic tree reconstruction, cluster or clade extraction, variant calling, visualization and reporting. ClusTRace was developed as an aid for COVID-19 transmission chain tracing in Finland and the main emphasis has been on fast and unsupervised screening of phylogenies for markers of super-spreading events and other features of concern, such as high rates of cluster growth and/or accumulation of novel mutations.

18.
Journal of Asian Finance Economics and Business ; 8(10):119-128, 2021.
Article in English | Web of Science | ID: covidwho-1560678

ABSTRACT

In the era of industry 4.0 with the robust digital transformation, especially under the trigger of the Covid-19 pandemic, the process of transforming businesses to achieve the desired business performance depends much on the mindset transformation of each member of the organization, beginning with the thoughts of leadership and stakeholders. This study will evaluate the relationship between leadership's strategic reasoning perspectives on employee engagement or commitment and the company's reputation, thereby directly or indirectly affecting organizational performance. The study examines data from 382 companies out of 500 samples in typical industries in Vietnam using the exploratory factor analysis (EFA) and partial least squares structural equation modeling (PLS-SEM) techniques. The results show that holistic thinking is closely related to employee retention and corporate reputation, thereby increasing the business outcomes of the organization, whereas there was no evidence to support analytical thinking in this study. As a consequence, transforming the business to achieve the desired business performance is heavily reliant on changing the mindset of each member of the organization, beginning with the top leaders and influencers of the business. This will assist Vietnamese leaders in gaining a comprehensive understanding of corporate governance and controlling the relationships between organizational constructs.

19.
Journal of Distribution Science ; 19(10):17-22, 2021.
Article in English | Scopus | ID: covidwho-1538917

ABSTRACT

Purpose: Covid-19 has caused an unprecedented situation for the tourism industry with slumping demand during the outbreak and many uncertainties about tourist behavior in the post-pandemic. This study is aimed to discover the distribution in the behavior of tourists in Vietnam, whose government has taken serious and early actions towards the health crisis and among the earliest to reopen the economy. Research design, data, and methodology: We adopted a mixed-method approach - combining qualitative interviews with quantitative research using a questionnaire survey. Through the form of the online survey through social networking channels: Facebook, Gmail. The study received 261 valid responses for analysis. Multivariate analysis techniques were used: descriptive statistics, exploratory factor analysis (EFA). Results: From the data and result of EFA, the result showed that the distribution of tourist behavior could be grouped into four main factors, including (1) the general impacts, (2) travel-related behaviors;(3) attitudes and preferences regarding modes of tours and destinations;(4) awareness of safety and hygiene. Conclusions: These results highlighted the importance of the theory of perceived risks in explaining the travelers’ prudent decisions. In addition, this study provides practical implications for policymakers and various stakeholders of Vietnam’s tourism industry in formulating the recovery strategy. © 2021. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://Creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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