ABSTRACT
COVID-19 began in 2019, and by the advent of 2020, it had become widespread and adversely affected the world. In this work-Covid Live, COVID-19 data is scraped from an online website, which gives an overview of the status of the pandemic in the desired format. The authors built an application interface using a Python micro web Flask framework. The data scraping uses a multi-threading concept to reduce the program's runtime error, resulting in receiving the data quickly, and faster than existing web crawlers and scrapers. This paper focuses on dealing with storing scraped data in the desired format. It also provides options to hear the audio of the scraped data and to download the scraped data. The authors present visualizations of current trends with scraping period details and demonstrate an efficient application that does the data scraping quickly and efficiently. © 2023, IGI Global. All rights reserved.
ABSTRACT
The purpose of the present study is to examine the effect of stress induced by coronavirus (COVID-19), telecommuting, and work orientation on work engagement among employees in the Information Technology (IT) sector. Using a structured survey instrument, data were collected from 285 respondents from four cosmopolitan cities in the southern part of India-Chennai, Coimbatore, Tiruchirappalli, and Madurai using a structured instrument. The hierarchical regression results reveal that (i) stress induced by COVID-19 was negatively related to work engagement, (ii) work orientation is positively associated with work engagement, and (iii) telecommuting is positively associated with work engagement. The results also reveal that (i) telecommuting weakened the relationship between stress induced by COVID-19 and work engagement and (ii) strengthened the positive relationship between work orientation and work engagement. These results are consistent with Job Demands and Resources (JDR), Conservation of Resources Theory (COR), and Career Construction Theory (CCT). The study highlights the importance of telecommuting as a strategic move on the part of the companies to reduce stress and enhance work engagement. Considering the global pandemic situation, employees in the IT sector would find it comfortable to work from their homes and contribute their best for the success of organizations. The present study also suggests ways for the organizations to promote work engagement and remain committed to performing during stressful situations like a global pandemic. The theoretical and practical implications are discussed.
ABSTRACT
Introduction: The Covid-19 pandemic was a disruptor to teaching and learning activity in many medical schools all over the world. The pandemic resulted in the need to move rapidly to online platforms with a steep learning curve. Moving forward it appears likely that online teaching, learning and assessment will form a significant portion of delivery. Objective: The purpose of this study was to look at student perceptions towards online instruction and assessment in the obstetrics and gynaecology. Methods: This was a questionnaire based study. Results: A total of 113 completed questionnaires were received, 64.6% were female. 66.4% described themselves as average performers. Online teaching and learning was not acceptable as an adequate substitute, though many felt that there were better opportunities to achieve their learning outcomes and also to learn at their own pace. There was good interaction between them and the instructors during these sessions. In terms of instructor preparedness and availability as well as the clarity of instructions to prepare for these sessions the responses were positive. Students felt it was an appropriate platform for formative assessment. In terms of preparing for the future, the general perception was that this method of instruction should be retained. Students felt that it was an acceptable medium for teaching history taking but not adequate to teach examination and clinical reasoning. Conclusions: Online teaching and learning was a useful medium of instruction. It allowed paced learning and useful for formative assessment. It should be part of instructional methods moving forward.
ABSTRACT
Public health agencies advocate the use of contact tracing procedures to deal with pandemics such as COVID-19 to prevent the infection of a vast population. Although several mobile applications have been developed previously for contact tracing, they typically require collection of privacy-intrusive information such as GPS locations, personal data, or require infrastructures such as WiFi APs. In this paper, we introduce CONTAIN, an early proposal for privacy-sensitive contact tracing. CONTAIN is a privacy-oriented bluetooth-based mobile digital contact tracing framework that does not rely on any infrastructure-based location sensing, nor the continuous logging of personally identifiable information. The goal of CONTAIN is to allow users to determine with complete privacy if and when they have been within a short distance of someone that is infected. We identify and prove the privacy guarantees provided by CONTAIN. We also present a simulation study utilizing an empirical trace dataset which shows that users can maximize their possibility of identifying if they were near an infected user by turning on the app in more crowded settings. © 2021 IFIP.
ABSTRACT
Contagious diseases such as COVID-19 spread rapidly, forcing governments and policymakers to employ corrective measures. Contact tracing is one of the critical tools to identify whether individuals came into contact with infected persons. Many countries, including Australia, Singapore, and India, have released contact tracing apps to reduce the community spread. Such apps follow either a centralized or decentralized architecture;the former lets government agencies store and manage the user's data without privacy support, while the latter allows the user more control over their information, providing privacy. We analyze how the GDP and the democracy index influence the adoption of contact tracing applications. Our study analyzes COVID-19 contact tracing projects announced between February 2020 and August 2020 from 63 countries. The data indicates that countries with high GDP and democracy index tend to opt for decentralized architectures, while autocratic and low GDP countries tend to adopt centralized architectures. © 2020 ACM.
ABSTRACT
Policy-makers require data-driven tools to assess the spread of COVID-19 and inform the public of their risk of infection on an ongoing basis. We propose a rigorous hybrid model-and-data-driven approach to risk scoring based on a time-varying SIR epidemic model that ultimately yields a simplified color-coded risk level for each community. The risk score tt that we propose is proportional to the probability of someone currently healthy getting infected in the next 24 hours based on their locality. We show how this risk score can be estimated using another useful metric of infection spread, Rt, the time-varying average reproduction number which indicates the average number of individuals an infected person would infect in turn. The proposed approach also allows for quantification of uncertainty in the estimates of Rt and tt in the form of confidence intervals. Code and data from our effort have been open-sourced and are being applied to assess and communicate the risk of infection in the City and County of Los Angeles. © 2020 ACM.