Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 226
Filter
1.
Problems and Perspectives in Management ; 20(2):161-174, 2022.
Article in English | Scopus | ID: covidwho-1893549

ABSTRACT

The COVID-19 pandemic has made many companies in China adopting telecommuting to continue their operations. Like traditional office work, telecommuting requires communication and cooperation to complete the work, and getting along with others means the possibility of conflict. Therefore, conflict can also occur in telecommuting. The purpose of this paper is to analyze telecommuting based on conflict process theory and build a model to test the hypothesis. Quota sampling and convenience sampling are used to conduct online questionnaires, and quantitative research methods are used to analyze the collected data and provide solutions. To this end, 282 Chinese respondents from different service industries completed online questionnaires. Through empirical analysis, the results show that telecommuting has a significant negative relationship with inter-role conflict and interpersonal conflict but has a significant positive effect on stress. In addition, interpersonal conflict, stress, and inter-role conflict have significant positive impacts on affective conflict. Similarly, interpersonal conflict and stress have significant positive effects on cognitive conflict. However, the relationship between inter-role conflict and cognitive conflict, cognitive conflict, and affective conflict is not significant. Thus, the results provide suggestions for managers on how to manage telecommuters and key factors that need to be considered. It also provides a new way for other scholars to study telecommuting. © Junjun Li, Zhongwu Li, 2022

2.
Traitement du Signal ; 39(2):701-710, 2022.
Article in English | Scopus | ID: covidwho-1893498

ABSTRACT

As Covid-19 plagues the world, a clean environment helps to control the factors and risks that threaten health, and curb the spread of the epidemic. However, the quality evaluation of environmental health faces some problems and challenges in actual management and practice. Firstly, the classification, identification, and quantification of road garbage are mainly done manually, because of the diversity of road garbage, as well as their sharp differences in geometry, color, and texture. Secondly, it is labor-intensive to manually manage the large operation areas on the wide urban roads. Thirdly, the accuracy of statistical indices is affected by the time-varying road environment, making the quality evaluation of environmental health untimely and inaccurate. To solve these problems, this paper proposes an intelligent image classification and evaluation method for urban environmental health. Specifically, an environmental garbage recognition and semantic segmentation approach was designed based on UNet++, and combined with the vehicle-mounted machine vision system to automatically identify the typical targets among the road waste control indices. Next, an image attention quantitative evaluation method was developed based on the eye tracking analyzer, and the quantified attention was fused with the statistical features for road garbage classification, forming an attention-based evaluation method for environmental quality. The proposed approach supports the automatic recognition and semantic segmentation of the garbage on urban roads, and realizes the identification of complex targets in different scenes through transfer learning. In addition, the attention-based evaluation method for environmental quality provides environmental management departments with visual basis for quantitative decision-making. © 2022 Lavoisier. All rights reserved.

3.
Engineering, Construction and Architectural Management ; 2022.
Article in English | Scopus | ID: covidwho-1891305

ABSTRACT

Purpose: This study aims to focus on the sustainability of prefabricated medical emergency buildings (PMEBs) renovation after the epidemic, to address the problem that large numbers of PMEBs may be abandoned for losing their original architectural functions. This study develops an evaluation system to identify and measure sustainable factors for PMEBs’ renovation schemes. Qualitative and quantitative analysis of PMEBs’ renovation scheme was conducted based on cloud model evaluation method and selected the renovation scheme in line with sustainable development. The study promotes evaluation methods and decision-making basis for the renovation design of global PMEBs and realizes the use-value of building functions again. Design/methodology/approach: By referring to the existing literature, design standards and expert visiting a set of evaluation index systems which combines the renovation of the PMEBs and the sustainability concept has been established, which calculates the balanced optimal comprehensive weight of each indicator utilizing combination weighting method, and quantifies the qualitative language of different PMEBs’ renovation schemes by experts through characteristics of the cloud model. This paper takes Huoshenshan hospital a representative PMEB during the epidemic period as an example, to verify the feasibility of the cloud model evaluation method. Findings: The research results of this paper are that in the PMEBs’ renovation scheme structural reformative (T11) and corresponding nature with the original building (T13) have the most important influence;the continuity of architectural cultural value (T22) and regional development coherence (T23) are the key factors affecting the social dimension;the profitability of renovated buildings (T34) is the key factor affecting the economic dimension;the environmental impact (T41), resource utilization (T42) and ecological technology (T43) are the key factors in the environmental dimension. Originality/value: This study contributes to the existing body of knowledge by supplementing a set of scientific evaluation methods to make up for the sustainability measurement of PMEBs’ renovation scheme. The main objective was to make renovated PMEBs meet the needs of urban sustainable development, retain the original cultural value of the buildings, meanwhile enhance their social and economic value and realize the renovation with the least impact on the environment. © 2022, Emerald Publishing Limited.

4.
Engineering, Construction and Architectural Management ; 2022.
Article in English | Scopus | ID: covidwho-1891304

ABSTRACT

Purpose: The impacts of COVID-19 on construction projects have attracted much attention in the construction management research community. Nevertheless, a systematic review of these studies is still lacking. The purpose of this paper is to systematically analyze the impacts of COVID-19 on the different stages of a project life-cycle, and comprehensively sort out the epidemic response measures adopted by project participants. In addition, the study also attempts to explore the challenges and opportunities faced by project management practitioners under the context of COVID-19. Design/methodology/approach: This study comprehensively demonstrates the systematic review process of COVID-19 related research in the construction industry, systematically summarizes the research status of the impact of COVID-19 on construction projects, and defines the strategies to deal with COVID-19 in project management;and through the visualization research, determines the current key research topics and future research trends. Findings: This study identifies 11 construction activities in the project management life cycle that are affected by COVID-19 and finds that the COVID-19 epidemic has the greatest impact on construction workers, construction standards, construction contracts and construction performance. The study further summarizes the six main epidemic countermeasures and mitigation measures taken within the construction industry following the arrival of the epidemic. In addition, the results of this study identify opportunities and future trends in intelligent construction technology, rapid manufacturing engineering and project management in the construction industry in the post-epidemic era through literature results, which also provide ideas for related research. Practical implications: COVID-19 has brought severe challenges to society. It is of great significance for the future sustainable development of the construction industry to identify the impact of COVID-19 on all phases of the project and to promote the development of coping strategies by project stakeholders. Originality/value: First of all, there is little study comprehensively reviewing the impacts of COVID-19 on the different stages of construction projects and the strategies to deal with the negative impacts. In addition, from a life cycle perspective, the used articles in this study were grouped into different categories based on project stages. This promotes an integrated and comprehensive understanding of historical studies. Moreover, on the basis of a comprehensive review, this paper puts forward future research directions to promote the sustainable development of the construction sector. © 2022, Emerald Publishing Limited.

5.
International Journal of Low-Carbon Technologies ; 17:678-685, 2022.
Article in English | Web of Science | ID: covidwho-1886438

ABSTRACT

Windows are the communication medium between indoor and outdoor, but their influence and the corresponding landscape outside the window are often ignored due to the outdoor frequent activities of people. The coronavirus disease 2019 (COVID-19) has been a better choice to show the window performance, especially for the anxiety level alleviation of people isolated at home. A national survey was conducted on the anxiety of self-separation people and the window influence. The results showed that the average anxiety level was 1.54, between a little anxious and anxious, due to the COVID-19. The best satisfaction with the landscape outside the window was waterscape (2.98), followed by green plants (2.33) and buildings (0.83). During the COVID-19, the average number of overlook times increased by 1.49 times/day, which is higher 0.42 ties/day than the normal condition. The landscape types had the certain influence on the overlook frequency, the window opening times and even the anxiety level. The average anxiety levels are 1.36 and 1.68 with natural landscapes and human landscapes, respectively. Optimizing the landscapes outside the window plays an important role in alleviating the anxiety of residents and improving their mental health.

6.
Traitement Du Signal ; 39(2):701-710, 2022.
Article in English | English Web of Science | ID: covidwho-1884816

ABSTRACT

As Covid-19 plagues the world, a clean environment helps to control the factors and risks that threaten health, and curb the spread of the epidemic. However, the quality evaluation of environmental health faces some problems and challenges in actual management and practice. Firstly, the classification, identification, and quantification of road garbage are mainly done manually, because of the diversity of road garbage, as well as their sharp differences in geometry, color, and texture. Secondly, it is labor-intensive to manually manage the large operation areas on the wide urban roads. Thirdly, the accuracy of statistical indices is affected by the time-varying road environment, making the quality evaluation of environmental health untimely and inaccurate. To solve these problems, this paper proposes an intelligent image classification and evaluation method for urban environmental health. Specifically, an environmental garbage recognition and semantic segmentation approach was designed based on UNet++, and combined with the vehicle-mounted machine vision system to automatically identify the typical targets among the road waste control indices. Next, an image attention quantitative evaluation method was developed based on the eye tracking analyzer, and the quantified attention was fused with the statistical features for road garbage classification, forming an attention-based evaluation method for environmental quality. The proposed approach supports the automatic recognition and semantic segmentation of the garbage on urban roads, and realizes the identification of complex targets in different scenes through transfer learning. In addition, the attention-based evaluation method for environmental quality provides environmental management departments with visual basis for quantitative decision-making.

7.
Acm Transactions on Spatial Algorithms and Systems ; 8(2):35, 2022.
Article in English | English Web of Science | ID: covidwho-1883319

ABSTRACT

Infectious diseases are caused by pathogenic microorganisms, such as bacteria, viruses, parasites or fungi, which can be spread, directly or indirectly, from one person to another. Infectious diseases pose a serious threat to human health, especially COVID-19 that has became a serious worldwide health concern since the end of 2019. Contact tracing is the process of identifying, assessing, and managing people who have been exposed to a disease to prevent its onward transmission. Contact tracing can help us better understand the transmission link of the virus, whereby better interrupting its transmission. Given the worldwide pandemic of COVID-19, contact tracing has become one of the most critical measures to effectively curb the spread of the virus. This paper presents a comprehensive survey on contact tracing, with a detailed coverage of the recent advancements the models, digital technologies, protocols and issues involved in contact tracing. The current challenges as well as future directions of contact tracing technologies are also presented.

8.
Australasian Journal of Dermatology ; 63(SUPPL 1):52, 2022.
Article in English | EMBASE | ID: covidwho-1883172

ABSTRACT

Aims: The landscape of health service delivery has changed significantly in the wake of the COVID-19 pandemic. The Australian Institute of Health and Welfare reports that health practitioners have delivered an increasing number of consultations via telehealth. To understand how this shift has manifested in dermatology, we present an audit of the Royal Melbourne Hospital dermatology telehealth service, comparing data collected between 2020 and 2021, and discuss factors affecting sustainability of clinics, the challenges faced, and lessons learnt. Methods: We performed a retrospective audit of all telehealth consultations (both telephone and video-conference) at the Royal Melbourne Hospital Department of Dermatology between February to September in 2020 and 2021. Data was manually extracted from electronic medical records. We collected data for the total number of visits, rural vs metropolitan status, rural health region if applicable, and Pharmaceutical Benefits Scheme billing data for each month. Results: 1,056 telehealth consults were conducted in the 2021 period, comprising 28% of the 3,795 total Dermatology consults performed. 31% of these telehealth visits (330 consults) were with rural patients, representing a 42% increase from 2020 (233 consults). Review consults for patients on biologic therapy were particularly amenable to telehealth delivery within this rural cohort, experiencing a 141% growth from 49 consultations in 2020 to 118 in 2021. The most common reason for telehealth appointment was for inflammatory conditions (50% of all consults), followed by biologics reviews (37%), immunobullous conditions (6%), vascular anomalies and infective conditions (3% each), and benign and malignant skin lesions (2%). Conclusions: Telehealth consultations have proved essential in the delivery of many dermatological services throughout the COVID-19 pandemic. Rural populations demonstrate an increasing benefit from telehealth services. Inflammatory and biologics reviews are visit indications which may be particularly amenable to telehealth delivery.

9.
5th International Conference on Vision, Image and Signal Processing (ICVISP) ; : 206-211, 2021.
Article in English | English Web of Science | ID: covidwho-1883123

ABSTRACT

With increasing physical threats in recent years targeted at critical infrastructures, it is crucial to establish a reliable threat monitoring system integrating video surveillance and digital sensors based on cutting-edge technologies. A physical threat monitoring solution unifying the floorplan, cameras, and sensors for smart buildings has been set up in our study. Computer vision and deep learning models are used for video streams analysis. When a threat is detected by a rule engine based on the real-time analysis results combining with feedback from related digital sensors, an alert is sent to the Video Management System so that human operators can take further action. A physical threat monitoring system typically needs to address complex and even destructive incidents, such as fire, which is unrealistic to simulate in real life. Restrictions imposed during the Covid-19 pandemic and privacy concerns have added to the challenges. Our study utilises the Unreal Engine to simulate some typical suspicious and intrusion scenes with photorealistic qualities in the context of a virtual building. Add-on programs are implemented to transfer the video stream from virtual PTZ cameras to the Milestone Video Management System and enable users to control those cameras from the graphic client application. Virtual sensors such as fire alarms, temperature sensors and door access controls are implemented similarly, fulfilling the same programmatic VMS interface as real-life sensors. Thanks to this simulation system's extensibility and repeatability, we have consolidated this unified physical threat monitoring system and verified its effectiveness and user-friendliness. Both the simulated Unreal scenes and the software add-ons developed during this study are highly modulated and thereby are ready for reuse in future projects in this area.

10.
Ieee Access ; 10:53640-53651, 2022.
Article in English | English Web of Science | ID: covidwho-1883114

ABSTRACT

Recently, the Healthcare Internet of Things (H-IoT) has been widely applied to alleviate the global challenge of the coronavirus disease 2019 (COVID-19) pandemic. However, security and limited energy capacity issues remain the two main factors that prevent the large-scale application of the H-IoT. Therefore, a permissioned blockchain and deep reinforcement learning (DRL)-empowered H-IoT system is presented in this research to address these two issues. The proposed H-IoT system can provide real-time security and energy-efficient healthcare services to control the propagation of the COVID-19 pandemic. To address the security issue, a permissioned blockchain method is adopted to guarantee the security of the proposed H-IoT system. As for handling the limited energy constraint, we employ the mobile edge computing (MEC) method to offload the computing tasks to alleviate the computational burden and energy consumption of the proposed H-IoT system. We also adopt an energy harvesting method to improve performance. In addition, a DRL method is employed to jointly optimize both the security and energy efficiency performance of the proposed system. The simulation results demonstrate that the proposed solution can balance the requirements of security and energy efficiency issues and hence can better respond to the COVID-19 pandemic.

11.
Frontiers in Earth Science ; 10:14, 2022.
Article in English | Web of Science | ID: covidwho-1869357

ABSTRACT

The research of atmospheric aerosol in mountain glacier areas has attracted more and more people's attention. For the first time, a field observation study of total suspended particles (TSPs) for four seasons from September 2019 to August 2020 was carried out at the Tianshan Glaciological Station in the source area of Urumqi River, East Tianshan Mountains, China. The TSPs presented typical seasonal characteristics of high in autumn and low in winter, with the annual average value of 181 +/- 170 mu g m(-3). Concentrations of Ca2+, SO42-, NO3-, Cl-, NH4+ and K+, OC, EC were elevated in autumn. The influence of stationary source emissions was stronger than mobile sources, which was explained by the average ratio of NO3-/SO42- (0.31 +/- 0.17). The concentration of secondary organic carbon (SOC) was higher in summer and autumn, especially in summer, indicating that secondary formation processes of organic aerosols were frequent in summer. Impact of fossil fuel combustion sources were evident over the Glaciers, corroborated by the diagnostic mass ratios of OC/EC (0-21.4, 3.38) and K+/EC (0-0.31, 0.08). The factor analysis illustrated that aerosols were mainly affected by rock salt, dust, coal combustion, and automobile exhaust. The local sources made significant contributions to TSPs in the source of Urumqi River by the results of Results of Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and potential source contribution function (PSCF).

12.
Advanced Engineering Informatics ; 52, 2022.
Article in English | Scopus | ID: covidwho-1859243

ABSTRACT

Emergencies, such as pandemics (e.g., COVID-19), warrant urgent production and distribution of goods under disrupted supply chain conditions. An innovative logistics solution to meet the urgent demand during emergencies could be the factory-in-a-box manufacturing concept. The factory-in-a-box manufacturing concept deploys vehicles to transport containers that are used to install production modules (i.e., factories). The vehicles travel to customer locations and perform on-site production. Factory-in-a-box supply chain optimization is associated with a wide array of decisions. This study focuses on selection of vehicles for factory-in-a-box manufacturing and decisions regarding the optimal routes within the supply chain consisting of a depot, suppliers, manufacturers, and customers. Moreover, in order to contrast the options of factory-in-a-box manufacturing with those of conventional manufacturing, the location of the final production is determined for each customer (i.e., factory-in-a-box manufacturing with production at the customer location or conventional manufacturing with production at the manufacturer locations). A novel multi-objective optimization model is presented for the vehicle routing problem with a factory-in-a-box that aims to minimize the total cost associated with traversing the edges of the network and the total cost associated with visiting the nodes of the network. A customized multi-objective hybrid metaheuristic solution algorithm that directly considers problem-specific properties is designed as a solution approach. A case study is performed for a vaccination project involving factory-in-a-box manufacturing along with conventional manufacturing. The case study reveals that the developed solution method outperforms the ε-constraint method, which is a classical exact optimization method for multi-objective optimization problems, and several well-known metaheuristics. © 2022 Elsevier Ltd

13.
Modern Pathology ; 35(SUPPL 2):1099, 2022.
Article in English | EMBASE | ID: covidwho-1857726

ABSTRACT

Background: Digital pathology adoption for clinical diagnostics continues to increase due to favorable regulatory environment and need for remote diagnosis during COVID-19 pandemic. Whole slide imaging (WSI) scan failure is fairly uncommon. However, there is limited literature about the true incidence of WSI scan failure rates and the impact on the daily operations in a setting of complete digital workflow. Our digital pathology scanning facility is one of the largest clinical digital pathology operating the world. Our facility routinely monitors scan failure data as a part of quality control and quality assurance. This study was undertaken to address the issues related to scan failure and to assess impact on turn-around times (TATs). This data would be beneficial to health care providers considering transition to a complete digital work-flow. Design: In 2017, we transitioned from scanning of archival slides to mostly new slides for primary diagnosis. We have operated 13 different Philips UFS scanners and scanned 2,289,266 slides representing nearly 233,864 cases. Scan failure data was collected from 3 resources (1) Errors detected by machine, (2) Retrospective quality control review and (3) Errors reported by pathologists. Every slide image is appraised by the scanner for defects including failed region of interest (ROI) detections, slides skipped, slides dropped, tissue not detected, and other faults. Each image is also checked by scan technician to determine if the ROI was correctly captured or not. Routinely 1.5% of the daily scans are inspected by senior staff for quality assurance. Slides are scored on a scale of 1 to 10 using different parameters and scans scoring <8 are designated as failed scans and slides typically get rescan. Total scan failure rates, re-scan (since 2019) rates were recorded and monitored. Results: Table 1 summarizes WSI scan failure data at our facility. Overall scan failure rate was just 1.19% with majority of the failures were attributable to machine error followed by failures due to slide preparation features. Most common machine error was failed ROI followed by skipped tissue error. Conclusions: WSI scan failure is extremely uncommon (1.19%) in a facility with experienced slide scanning staff and optimal slide preparations. Re-scanning was requested only for 1.19% cases and was feasible in 100% cases. Scanning of archival versus newly prepared slides did not have an impact on scan failure rates. Scan failure is not frequent enough to impact TATs and therefore need not be a concern for institutions considering transitioning to digital workflow. (Table Presented).

14.
Modern Pathology ; 35(SUPPL 2):1079-1081, 2022.
Article in English | EMBASE | ID: covidwho-1857341

ABSTRACT

Background: Digital pathology has enormous potential to make routine pathology practice more efficient and accurate, however, full adoption has been slow. We aimed to identify driving factors that encourage pathologists to adopt digital pathology for their daily practice at our institution. Design: We have collected data on four indicators of pathologist adoption since the implementation of digital pathology: (1) number of pathologists receiving training and certification for primary diagnosis using digital whole slide images (WSI);(2) average daily number of users logged in imaging managing system (IMS);(3) average daily number of primary diagnosis slides scanned;and (4) average daily number of slides scanned for immediate pathologist use (including consultation, urgent cases, etc.) Since adoption of digital workflow was voluntary and slides were only scanned for pathologists who have indicated to use WSIs for routine practice, these are accurate indicators of pathologists' transition from glass slides to digital workflow. These data were correlated with potential events during the study period. Results: The data of four indicators were summarized in the table. We observed two spikes: the first one was from July to September 2019 and the second was from March to May 2020 (Figure 1). The first spike correlates with our pathology laboratory information system (LIS) transition from Sunquest Copath to Epic Beaker, which enables single-click access to WSIs in IMS from case working drafts. Previously, pathologists had to switch from pathology LIS to IMS and type in case numbers in order to access WSIs. The second spike correlates with the beginning of COVID-19 pandemic when many academic activities transitioned from live to remote using digital platforms. The need to work remotely, conduct education and consultation at distance, and minimize interaction with others appears to have driven many fence-sitting pathologists to adopt digital pathology. CMS waiver to loosen regulatory requirements during this pandemic has hastened pathologists' decision to switch to digital pathology for primary diagnosis. Conclusions: Our data suggests that ease of use and the ability to work remotely are the most powerful drivers of digital pathology adoption. (Table Presented).

15.
Frontiers in Marine Science ; 9:22, 2022.
Article in English | Web of Science | ID: covidwho-1855364

ABSTRACT

Using AIS data to mine the dynamic characteristics of fishery resource exploitation helps to carry out scientific management of fishery and realize the sustainable development of marine resources. We proposed a framework that integrates multiple AIS data processing and analysis modules, which can efficiently divide fishing voyages, determine the fishing activities and identify fishing types, and provide near real-time analysis results on the number of fishing vessels, fishing duration, voyages and so on. The framework was applied to 1.68 billion AIS trajectory data points of approximately 588,000 fishing vessels. We selected China's sea areas overall and six fishing grounds as the research area, explored the characteristics of fishing vessel activities in winter and spring of 2019, and analyzed the impact of COVID-19 on winter-spring fishing in China in 2020. In 2019, our results showed that the number of fishing vessels in China's sea areas gradually increased over time, with the Chinese New Year holiday affecting fishing activities at the corresponding time but having little impact on the entire month. We found that the changing laws of the fishing duration and voyages in the inshore fishing grounds were similar to those of the number of fishing vessels, which increased to varying degrees over time. Gillnetters were the most numerous fishing vessel type operating in the inshore fishing grounds with increased in spring, while seiners had an absolute advantage in the Xisha-Zhongsha fishing ground. In 2020, during the occurrence period of COVID-19, the fishing activities in China's sea areas was almost unaffected. During the outbreak period, the number, distribution range, activity intensity, and fishing duration of fishing vessels all experienced a relatively large decline. After the epidemic was effectively controlled, they were rapidly increased. In addition, we found that compared with the Government Response Stringency Index, the number of fishing vessels and the number of new confirmed cases showed a more obvious negative correlation. By processing, mining and analyzing AIS data with high spatial-temporal granularity, this study can provide data support for the reasonable development of fishery resources, and help fishery practitioners make wise decisions when responding to unexpected emergencies (e.g. pandemics).

16.
Embase; 2021.
Preprint in English | EMBASE | ID: ppcovidwho-335634

ABSTRACT

Background: Evaluating seroprevalence study risk of bias (RoB) is crucial for robust infection surveillance, but can be a time-consuming and subjective process. We aimed to develop decision rules for reproducible RoB assessment and an automated tool to implement these decision rules. Methods: We developed the SeroTracker-RoB approach to RoB assessment. To do so, we created objective criteria for items on the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Prevalence Studies and developed decision rules for RoB based on these items. The criteria and decision rules were based on published guidance for assessing RoB for prevalence studies and expert opinion. Decision rules were validated against the SeroTracker database of seroprevalence studies, which included consensus manual RoB judgements from two independent reviewers. We measured efficiency by calculating paired-samples t-test for time to judge RoB using the automated tool versus manually for 25 randomly selected articles from the SeroTracker database, coverage as the proportion of database studies where the decision rules could evaluate RoB, and reliability by calculating intraclass correlations between automated and manual RoB assessments. Results: We established objective criteria for seven of nine JBI items. We developed a set of decision rules with 61 branches. The SeroTracker-RoB tool was significantly faster than manual assessment with a mean time of 0.80 vs. 2.93 minutes per article (p<0.001), classified 100% (n = 2,070) of studies, and had good reliability compared to manual review (intraclass correlation 0.77, 95% confidence interval 0.74 to 0.80). The SeroTracker-RoB Excel Tool embeds this approach in a simple data extraction sheet for use by other researchers. Conclusions: The SeroTracker-RoB approach was faster than manual assessment, with complete coverage and good reliability compared to two independent human reviewers. This approach and tool enable rapid, transparent, and reproducible evidence synthesis of infection prevalence studies, and may support public health efforts during future outbreaks and pandemics.

17.
3rd International Conference on Internet Technology and Educational Informization, ITEI 2021 ; : 176-180, 2021.
Article in English | Scopus | ID: covidwho-1831835

ABSTRACT

Since the outbreak of COVID-19, it has had a direct and profound impact on social production and people's lives. The national economy has even stopped for a while, and the catering industry is one of the most obvious industries. This paper collects the store information and comments of the public comment platform from December 2019 to September 2020. In terms of comments, word vector is constructed by word 2vec algorithm, and the thesaurus of epidemic prevention measures is obtained by cluster analysis;In terms of data, in addition to obtaining the detailed page information of public comments, the time period for all catering stores to close down and the time interval for store reopening shall be determined according to the monthly comments. Finally, the mechanism of the number of online reviews, per price and epidemic prevention measures affecting the reopening time is discussed by using regression equation analysis. The results show that the number of online reviews represents that the stores have a certain anti risk ability to a certain extent, so that catering enterprises can resume business quickly;The higher price positioning of stores can meet the safety psychology of consumers during the epidemic. © 2021 IEEE.

18.
2nd International Conference on Electronics, Communications and Information Technology, CECIT 2021 ; : 298-303, 2021.
Article in English | Scopus | ID: covidwho-1831728

ABSTRACT

With the in-depth integration of information technology and human life, the Internet has gained rapid popularity, and global data shows the characteristics of explosive growth and massive aggregation. The outbreak of COVID-19 makes online learning popular and universal. Different from the traditional way of education, online learning allows learners to have access to complexity and diversity as well as varying levels of knowledge mastery. For the current mainstream personalized education, making good use of education data for learning analysis is an important direction to solve the problem. This paper finds that learning platform has just begun to rise on a large scale, but there are still some problems, such as the confusion of learning resources, the unreasonable setting of the question bank and the unclear classification of the difficulty of knowledge points. Most of the platforms do not divide the knowledge points and difficulty of the questions, therefore, students cannot find the key points, and some of them fill in the difficulty directly according to subjective judgment, which is not scientific nor objective. This paper analyzes students' historical answer data, classifies and divides the difficulty of knowledge points by clustering algorithm, then verifying it on the Istudy education platform which is developed by our laboratory. The experimental results show that this labeling system is more objective and effective, contributing to improving the efficiency of online learning. For students, they can adjust their own learning plans while understanding the difficulty of knowledge points. Teachers can also modify their teaching focus and assist the teaching design according to the difficulty classification of knowledge points. © 2021 IEEE.

19.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-334805

ABSTRACT

Omicron sub-lineage BA.2 has rapidly surged globally, accounting for over 60% of recent SARS-CoV-2 infections. Newly acquired RBD mutations and high transmission advantage over BA.1 urge the investigation of BA.2's immune evasion capability. Here, we show that BA.2 causes strong neutralization resistance, comparable to BA.1, in vaccinated individuals' plasma. However, BA.2 displays more severe antibody evasion in BA.1 convalescents, and most prominently, in vaccinated SARS convalescents' plasma, suggesting a substantial antigenicity difference between BA.2 and BA.1. To specify, we determined the escaping mutation profiles1,2 of 714 SARS-CoV-2 RBD neutralizing antibodies, including 241 broad sarbecovirus neutralizing antibodies isolated from SARS convalescents, and measured their neutralization efficacy against BA.1, BA.1.1, BA.2. Importantly, BA.2 specifically induces large-scale escape of BA.1/BA.1.1effective broad sarbecovirus neutralizing antibodies via novel mutations T376A, D405N, and R408S. These sites were highly conserved across sarbecoviruses, suggesting that Omicron BA.2 arose from immune pressure selection instead of zoonotic spillover. Moreover, BA.2 reduces the efficacy of S309 (Sotrovimab)3,4 and broad sarbecovirus neutralizing antibodies targeting the similar epitope region, including BD55-5840. Structural comparisons of BD55-5840 in complexes with BA.1 and BA.2 spike suggest that BA.2 could hinder antibody binding through S371F-induced N343-glycan displacement. Intriguingly, the absence of G446S mutation in BA.2 enabled a proportion of 440-449 linear epitope targeting antibodies to retain neutralizing efficacy, including COV2-2130 (Cilgavimab)5. Together, we showed that BA.2 exhibits distinct antigenicity compared to BA.1 and provided a comprehensive profile of SARS-CoV-2 antibody escaping mutations. Our study offers critical insights into the humoral immune evading mechanism of current and future variants.

20.
Chinese Journal of Disease Control and Prevention ; 26(3):343-346 and 356, 2022.
Article in Chinese | EMBASE | ID: covidwho-1822640

ABSTRACT

Objective To analyze the utilization of HIV testing services and related influencing factors among men who have sex with men (MSM) on COVID-19. Methods From September to November 2020, an electronic questionnaire survey was conducted on MSM in the AIDS Vct of Longhua CDC and the Third People's Hospital of Shenzhen, The rank sum test was used to compare the changes in the utilization of HIV testing services in different situations of various factors, and ordinal multinomial logistic regression model was established to analyze the influencing factors of the utilization of HIV testing services. Results A total of 30.4% MSM were reported reduction in the use of HIV testing services. Logistic regression analysis showed that highly panic of COVID-19 reducing the frequency of anal sex (OR=0.056, 95% CI: 0.021-0.150, P < 0.001), being advised not going to testing agency (OR=0.538, 95% CI: 0.297-0.975, P=0.041), and being infected of COVID-19 (OR=21.979, 95% CI: 4.369-110.559, P < 0.001) had higher chance of reduction in the used of HIV testing services. Conclusion The HIV testing service utilization is decreased in MSM during COVID-19. It is necessary to pay more attention to this convenience when formulating and implementing epidemic prevention and control measures.

SELECTION OF CITATIONS
SEARCH DETAIL