Change in anti‐COVID‐19 behaviour and anti‐immigrant prejudice during the COVID‐19 pandemic: Longitudinal evidence from five European countries

During a pandemic, it is vital to identify factors that motivate individuals to behave in ways that limit virus transmission (i.e., anti‐COVID‐19 behaviour). Fear has been suggested to motivate health‐oriented behaviour, yet fear of the virus (i.e., fear of COVID‐19) could have unintended consequences, such as an increase in anti‐immigrant prejudice. In a three‐wave longitudinal study (NT1 = 4275) in five European countries from April to October 2020, we investigated how social norms, the impact of the pandemic on individuals, and intergroup contact affected fear of COVID‐19 and—or in turn—anti‐COVID‐19 behaviour and prejudice towards immigrants. A latent change score model—distinguishing between intra‐ and inter‐individual changes in outcomes—indicated that fear of COVID‐19 influenced neither anti‐COVID‐19 behaviour nor prejudice. Anti‐COVID‐19 behaviour was increased by anti‐COVID‐19 norms (i.e., belief that others perform anti‐COVID‐19 behaviours), while prejudice was influenced by positive and negative direct and mass‐mediated intergroup contact.

Path planning research for mobile robots in dynamic environments

At present, due to the COVID-19, China's social and economic development has slowed down. Some life service e-commerce platforms have successively launched "contactless delivery" services, which can effectively curb the spread of the epidemic. Robot distribution is the current mainstream, but robots are different from people and need to have accurate program settings. Both path planning and obstacle avoidance are currently top issues. This requires the mobile robot to successfully arrive at the destination while minimizing the impact on the surrounding environment and pedestrians, and avoiding encroachment on the movement space of pedestrians. Therefore, the mobile robot needs to be able to actively avoid moving pedestrians in a dynamic environment, in addition to avoiding static obstacles, and safely and efficiently integrate into the pedestrian movement environment. In this paper, the path planning problem of unmanned delivery robot is studied, and the path of mobile robot in the crowd is determined by global planning and local planning, and the matlab simulation is used for verification. © The Authors. Published under a Creative Commons Attribution CC-BY 3.0 License.

Design and Implementation of Intelligent Truck Based on Azure Kinect

In recent years, due to the impact of COVID-19, the market prospect of non-contact handling has improved and the development potential is huge. This paper designs an intelligent truck based on Azure Kinect, which can save manpower and improve efficiency, and greatly reduce the infection risk of medical staff and community workers. The target object is visually recognized by Azure Kinect to obtain the center of mass of the target, and the GPS and Kalman filter are used to achieve accurate positioning. The 4-DOF robot arm is selected to grasp and transport the target object, so as to complete the non-contact handling work. In this paper, different shapes of objects are tested. The experiment shows that the system can accurately complete the positioning function, and the accuracy rate is 95.56%. The target object recognition is combined with the depth information to determine the distance, and the spatial coordinates of the object centroid are obtained in real time. The accuracy rate can reach 94.48%, and the target objects of different shapes can be recognized. When the target object is grasped by the robot arm, it can be grasped accurately according to the depth information, and the grasping rate reaches 92.67%. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

The impact of source credibility and risk perception attitudes on Americans' willingness to participate in contact tracing applications

Contact tracing has emerged as one tool to communicate infection risks with the public during the COVID-19 pandemic. This study uses source credibility and the risk perception attitude framework to interpret how Americans responded to contact tracing messages from a technology company, employer, physician, or state government. Survey participants (n = 245) were generally positive towards a contact tracing message regardless of source. Participants with high risk perceptions and low efficacy beliefs responded more strongly to appeals from their company and their physician while the low risk-low efficacy group found the state government appeal more compelling. The results suggest that several sources delivering the same health message could engage people with different risk perceptions and efficacy beliefs. [ FROM AUTHOR] Copyright of Journal of Applied Communication Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Face Recognition Attendance System

The conventional procedure used in all of India's major regions is attendance monitoring on paper with pens. Although the final data is computerized, it takes a long time to get from a classroom to a database. The effectiveness of the classes is directly impacted by the number of absences. The attendance takes up almost half of the lecture's allotted time. The alternative method that is being used involves using fingerprints, but even this approach is ineffective since it takes so long. Due to the illnesses (COVID-19) spreading over the world, however, the situation as it stands right now does not make this the best course of action. Therefore, it will be advisable to develop a contactless and more efficient. © 2023 IEEE.

The UK's public health response to covid-19

Too little, too late, too flawed

A survey of automatic contact tracing approaches using bluetooth low energy

To combat the ongoing Covid-19 pandemic, many new ways have been proposed on how to automate the process of finding infected people, also called contact tracing. A special focus was put on preserving the privacy of users. Bluetooth Low Energy as base technology has the most promising properties, so this survey focuses on automated contact tracing techniques using Bluetooth Low Energy. We define multiple classes of methods and identify two major groups: systems that rely on a server for finding new infections and systems that distribute this process. Existing approaches are systematically classified regarding security and privacy criteria.Copyright © 2021 ACM.

COVID-19 and dermatology

The aim of this manuscript is to investigate skin diseases associated with COVID-19 under three main headings: skin problems related to personal protective equipment and personal hygiene measures, skin findings observed in SARS-CoV-2 virus infections, and skin findings due to COVID-19 treatment agents. In PubMed and Google Scholar databases, publications on skin lesions related to personal protective equipment and personal hygiene measures, skin findings observed in SARS-CoV-2 virus infections and skin findings due to COVID-19 treatment agents subjects were searched in detail. Pressure injury, contact dermatitis, pruritus, pressure urticaria, exacerbation of preexisting skin diseases, and new skin lesion occurrence/new skin disease occurrence may be due to personal protective equipment. The incidence of skin lesions due to COVID-19 was reported to be between 0.2% and 29%. Many skin lesions including maculopapular, urticarial, vesicular, chilblain-like, thrombotic/ischemic, etc., are observed in COVID-19 patients. Some authors have stated that there is an absence of SARS-CoV-2 virus infection-specific skin rashes. Many skin lesions may appear as a result of COVID-19. Even in the absence of a COVID-19 diagnosis, skin findings should be evaluated carefully in the pandemic period.

Digital Contact Tracing for COVID-19: Overview of Existing Systems and Framework for Future Innovation

Background: The COVID-19 pandemic catalyzed innovation in infection control measures, including widespread deployment of digital contact tracing systems. However, these technologies were not well understood by the general public and were complex for the public health community to implement, hampering adoption. Objective(s): To provide an overview of existing digital contact tracing systems, creating a framework for understanding design elements that impact their effectiveness as public health tools and offering a rubric for decision-makers to evaluate different systems for selection and implementation. Method(s): Scientific literature and publicly available information from relevant health authorities and other stakeholders was reviewed. Information was synthesized to develop a conceptual framework explaining how key design elements impact effectiveness of digital contact tracing systems and highlighting opportunities for future improvement. Result(s): A range of digital contact tracing interventions were deployed by governments worldwide and several professional sports leagues. Key design elements of the systems include: (1) data architecture (i.e., centralized versus decentralized systems, impacting privacy guarantees and data availability);(2) proximity detection technology (e.g., type of device signaling);(3) alert logic and timing (e.g., time- and distance-based criteria affecting sensitivity and specificity of alerts;real-time proximity alerts and/or bidirectional contact tracing, determining scope of infection prevention);(4) population (eligibility and availability);and (5) the structural and public health context of intervention (e.g., availability and timeliness of testing). Several systems demonstrated effectiveness in preventing transmission during COVID-19, though numerous limitations have also been documented in the literature. Conclusion(s): Digital contact tracing systems have the potential to mitigate the economic and public health impact of future infectious disease outbreaks, reducing community transmission and detecting potential cases earlier in the disease course. Lessons learned from solutions deployed during the COVID-19 pandemic provide an opportunity to improve multiple aspects of these systems, enhancing preparedness for future outbreaks.Copyright © 2023

Getting it right in the pandemic

In a research paper that warrants close scrutiny by hospital administrators everywhere, Min Liu and colleagues find that none of 420 healthcare workers deployed to a hospital in Wuhan were infected with the virus, despite caring for severely ill patients and performing aerosol generating procedures over 6-8 weeks.3 The workers wore surgical masks and N95 respirators as well as protective suits and gowns, goggles, gloves, and face shields. The US and the UK missed the just right "Goldilocks zone” of hospital capacity by building temporary hospitals that remained mostly empty.6 How did this happen? "Bad modelling based on insufficient data,” says one expert. Missing the Goldilocks zone of hospital capacity during covid-19.

Contact Tracing over Uncertain Indoor Positioning Data

Pandemics often cause dramatic losses of human lives and impact our societies in many aspects such as public health, tourism, and economy. To contain the spread of an epidemic like COVID-19, efficient and effective contact tracing is important, especially in indoor venues where the risk of infection is higher. In this work, we formulate and study a novel query called Indoor Contact Query (<sc>ICQ</sc>) over raw, uncertain indoor positioning data that digitalizes people's movements indoors. Given a query object <inline-formula><tex-math notation="LaTeX">$o$</tex-math></inline-formula>, e.g., a person confirmed to be a virus carrier, an <sc>ICQ</sc> analyzes uncertain indoor positioning data to find objects that most likely had close contact with <inline-formula><tex-math notation="LaTeX">$o$</tex-math></inline-formula> for a long period of time. To process <sc>ICQ</sc>, we propose a set of techniques. First, we design an enhanced indoor graph model to organize different types of data necessary for <sc>ICQ</sc>. Second, for indoor moving objects, we devise methods to determine uncertain regions and to derive positioning samples missing in the raw data. Third, we propose a query processing framework with a close contact determination method, a search algorithm, and the acceleration strategies. We conduct extensive experiments on synthetic and real datasets to evaluate our proposals. The results demonstrate the efficiency and effectiveness of our proposals. IEEE

Engineering care in pandemic technogovernance: The politics of care in China and South Korea's COVID-19 tracking apps

This article critically examines South Korea and China's COVID-19 tracking apps by bridging surveillance studies with feminist technoscience's understanding of the "politics of care". Conducting critical readings of the apps and textual analysis of discursive materials, we demonstrate how the ideological, relational, and material practices of the apps strategically deployed "care" to normalize a particular form of pandemic technogovernance in these two countries. In the ideological dimension, media and state discourse utilized a combination of vilifying and nationalist rhetoric that framed one's acquiescence to surveillance as a demonstration of national belonging. Meanwhile, the apps also performed ambivalent roles in facilitating essential care services and mobilizing self-tracking activities, which contributed to the manufacturing of pseudonormality in these societies. In the end, we argue that the Chinese and South Korean governments managed to frame their aggressive surveillance infrastructure during COVID-19 as a form of paternalistic care by finessing the blurred boundaries between care and control. [ FROM AUTHOR] Copyright of New Media & Society is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Social Distancing Monitoring and Contact Tracing on CCTV Footage

Social distancing is one of the most effective measures to prevent the spread of the COVID-19 disease. Most methods of enforcing this in the Philippines resort to manual methods. As such, a video-based social distancing monitoring tool can help ensure constant enforcement of social distancing due to the availability and up-time of CCTV cameras in various areas. This can be achieved by using object detection and tracking techniques. Object detection can be used to detect people within an area, and tracking can be used to watch people who get into close contact with one another. Contact tracing can also be performed by processing the social distancing measurements and tracking information. This information can be stored to keep a record of who has a high risk of infection based on who they came into contact with and for how long. We introduce a social distancing monitoring and contact tracing framework using the EfficientDet object detector and DeepSORT tracker. This framework is used to monitor social distancing violations and keep a record of violations associated to the tracked people. © 2022 IEEE.

The Impact of COVID-19 Routine Life - A Survey

The COVID-19 pandemic, caused by the novel coronavirus, has had a significant impact on daily life, education, business, and trade. The virus spreads quickly through direct contact with droplets, fecal-oral transmission, and water contamination. The consequences of the pandemic can be classified into three categories: health, economic, and social. The physical, mental, and psychological behaviors of individuals have also changed due to the pandemic. This study aimed to assess the impact of COVID-19 on the general population. A survey questionnaire with ten questions was distributed through an online portal, and the responses were analyzed using SPSS software. The results showed that healthcare workers were among the most affected, with the primary impact on their social and psychological well-being. Although previous research suggested that all fields were equally affected, this study found that healthcare workers were the most impacted group. The study concluded that the COVID-19 pandemic had a significant impact on the social and psychological well-being of the general population, with healthcare workers being the most affected. © 2023 IEEE.

Review of 5G Wireless Cellular Network on Covid-19 Pandemic: Digital Healthcare & Challenges

Since the coronavirus disease (COVID-19) began in 2020, it has changed the way people live such as social life and healthcare. One of the simplest ways to avoid wide spread of the virus is to minimize physical contact and avoid going to a crowded place. Besides that, it also has prompted countries across the world to employ digital technologies such as wireless communication systems to combat this global crisis. Digital healthcare is one of the solutions that play a crucial role to support the healthcare sector in order to prevent and minimize physical contact through telehealth and telemedicine such as monitoring, diagnosis and patient care. 5G network has the potential to advance digital healthcare along with its key technology such as enhanced Mobile Broadband (eMBB), Ultra Reliable and Low Latency Communication (URLLC), and massive Machine Type Communication (mMTC). Despite the benefits of digital healthcare by leveraging the 5G technology, there are still challenges to be overcome such as privacy protection issues, 5G deployment and limited connectivity. In this review, it highlights the relevance and challenges of 5G wireless cellular networks for digital healthcare during the COVID-19 pandemic. It also provides potential solutions and future research areas for researchers on 5G to reduce COVID-19 related health risks.

Less About Privacy: Revisiting a Survey about the German COVID-19 Contact Tracing App

The release of COVID-19 contact tracing apps was accompanied by a heated public debate with much focus on privacy concerns, e.g., possible government surveillance. Many papers studied people's intended behavior to research potential features and uptake of the apps. Studies in Germany conducted before the app's release, such as that by Häring et al., showed that privacy was an important factor in the intention to install the app. We conducted a follow-up study two months post-release to investigate the intention-behavior-gap, see how attitudes changed after the release, and capture reported behavior. Analyzing a quota sample (n=837) for Germany, we found that fewer participants mentioned privacy concerns post-release, whereas utility now plays a greater role. We provide further evidence that the results of intention-based studies should be handled with care when used for prediction purposes. © 2023 ACM.

On clinical manifestations of the new coronavirus infection in newborns.

The aim of the research. To study the specifics in manifestations of the new coronavirus infection in newborns. Material and methods. A retrospective analysis of observations of 28 newborns diagnosed with the new coronavirus infection SARS-CoV-2 dated from June to December 2020 was performed. The infants were transferred from the perinatal centre for hospitalisation to the infectious department of a children's hospital. The patients were born to mothers with COVID-19 as well as mothers discharged from hospital and hospitalised later due to COVID-19 acquired through family contact. Clinical and laboratory data of 12 female and 16 male children aged 1 to 28 days were studied. Results. Clinical symptoms of the new coronavirus infection in newborns tend to be different: from asymptomatic course in 46.5 % of the patients to evident pneumonia in 50 % of the children. The newborns admitted with COVID-19 acquired through family contact had more severe disease manifestations. Conclusion. Amidst the pandemic rise of its incidence, the new coronavirus infection COVID-19 is not rare among newborns. COVID-19 newborns did not have a registered severe nosocomial infection, sepsis, multisystem inflammatory syndrome.Copyright © 2022, Krasnoyarsk State Medical University. All rights reserved.

Covid-19: Testing testing

On its own it can't eliminate covid-19, but it buys a country time to prepare its health systems and to mount a public health response. The resulting loss to health and life will become clear, as will the impact on staff who have shouldered the covid burden. Failure to test patients transferred into the community fuelled the devastating outbreaks in care homes, and inability to test patients being admitted to hospital now makes it almost impossible to prevent hospital infection.

Covid-19: A wake-up call

Few can doubt the size of the government's challenge or the good faith and expertise of its chief advisers. Yes, writes Ali Mehdi (doi:10.1136/bmj.m1919), in the same way as did the planners of the welfare state during the second world war. After describing how covid-19 disproportionately affects the poorest people in our society, Adam Briggs and Harry Rutter say the pandemic can't become an excuse for worsening population health and widening inequalities (https://bit.ly/3e4PXnS).

Automated Contactless Continuous Temperature Monitoring System for Pandemic Disease Controlling Infrastructures

People are being thermally screened in hospitals and in such facilities, all the data collected must be stored and displayed. The person responsible for keeping track of people's body temperatures must put in more time and effort. This approach is a tedious task, especially during times of dealing with the pandemic diseases like Covid-19. Hence, in this paper, an automated contactless continuous temperature monitoring system is designed to eliminate this time-consuming process. If a person's temperature is too high, that is, higher than the usual temperature range, the system records it and monitors it continuously via a mobile application. In this paper, we present the development of an Automated contactless continuous body temperature monitoring system using a Raspberry Pi camera and mobile application. © 2023 IEEE.