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.)

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.

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.

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.

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).

Demonstrating a Nurse-Driven Model for Interprofessional Academic-Practice Partnerships

The World Health Organization (WHO) describes interprofessional practice (IPP) as "...multiple health workers from different professional backgrounds working] together with patients, families, caregivers, and communities to deliver the highest quality of care" (WHO. 2010. The WHO deemed that interprofessional education and practice (IPEP) is vital to attain a workforce that Is ready and able to care for local health needs through teamwork and collaboration (WHO. 201 Oh Interprofessional teams are critical in the care of acute, chronic, and complex health and social support needs of COVID-19 patients (Michalec & Lamb. 20201.1 PE and IPP are so essential to care that accreditation bodies have come together to provide guidance about how to embed these activities throughout all health professions programs (Health Professions Accreditors Collaborative. 2019). When delivered Intentionally, IPEP has the potential to achieve the Quadruple Aim (i.e., Improved quality, Increased population health, reduced costs, and improved clinician experience), with teamwork playing a large part In the achievement of the fourth aim: addressing the needs of healthcare workers, and reducing stressors experienced by the past, current, and future healthcare workforce, including nurses (Bachvnskv. 2020: Nurses have demonstrated that they are In an ideal position on the healthcare team to meet the additional demands placed on health services (e.g., contact tracing, testing, vaccine administration) and increased demand for staff, resources, policies, and supplies by the COVID-19 pandemic, all of which threaten an already overtaxed system (Diabv et al„ 2021).

Real-Time and Accurate Monitoring of Social Distance and Contact Tracing during COVID-19 Situation

In recent years, a lot of research works have been done on object detection using various machine learning models. However, not many works have been done on detecting and tracking humans in particular. This study works with the YOLOv4 object detector to detect humans to use the detections for maintaining social distance. For this study, the YOLOv4 model is trained on only one class named 'Person'. This is done to improve the speed of detecting humans in real time scenario with satisfying accuracy of 97% to 99%. These detections are then tracked to build a system for maintaining social distance and alerting the authority if a breach in the social distance is detected. This system can be applied at ticket counters, hospitals, offices, factories etc. It can also be used for maintaining social distance among the students and the teachers in the classroom for their safety. © 2022 IEEE.

Interpersonal Distance Tracking with mmWave Radar and IMUs

Tracking interpersonal distances is essential for real-time social distancing management and ex-post contact tracing to prevent spreads of contagious diseases. Bluetooth neighbor discovery has been employed for such purposes in combating COVID-19, but does not provide satisfactory spatiotemporal resolutions. This paper presents ImmTrack, a system that uses a millimeter wave radar and exploits the inertial measurement data from user-carried smartphones or wearables to track interpersonal distances. By matching the movement traces reconstructed from the radar and inertial data, the pseudo identities of the inertial data can be transferred to the radar sensing results in the global coordinate system. The re-identified, radar-sensed movement trajectories are then used to track interpersonal distances. In a broader sense, ImmTrack is the first system that fuses data from millimeter wave radar and inertial measurement units for simultaneous user tracking and re-identification. Evaluation with up to 27 people in various indoor/outdoor environments shows ImmTrack's decimeters-seconds spatiotemporal accuracy in contact tracing, which is similar to that of the privacy-intrusive camera surveillance and significantly outperforms the Bluetooth neighbor discovery approach. © 2023 Owner/Author.

Effectiveness of different measures in reducing the daily number of moderate to severe cases of COVID-19

Objectives: Interventions for controlling COVID-19 can be classified into case-based (e.g., contact tracing and quarantining) and population-based (e.g., using masks and receiving vaccines) measures. The objective of pandemic control has now shifted from reducing the daily number of cases to reducing that of hospitalizations through vaccination. COVID-19 has started exhibiting flu-like characteristics. Therefore, in this study, we compared different measures in terms of their effectiveness in reducing the daily number of moderate to severe cases of COVID-19. Methods: The branching model developed by Hellewell (2020) was used for simulation. The epidemiological data of the Omicron variant and various hypothetical scenarios were analyzed. The outcome variable of our study was the daily number of hospitalizations under different measures and their combinations. Results: Population-based measures were more effective than case-based measures;however, their combination led to the best outcomes. If vaccination reduced the number of COVID-19-related hospitalizations, the focus was on increasing vaccine coverage to increase medical capacity rather than enhancing vaccine efficacy. Conclusions: While loosening case-based measures, the government must consider whether population-based measures can support this change. Furthermore, to reduce the daily number of moderate to severe cases of COVID-19, vaccine coverage, rather than vaccine efficacy, must be improved. (Taiwan J Public Health. 2023;42(1):32-41)

Close Contact Individual Monitoring Based on Prescribed Social Distance Using Computer Vision

Contact tracing is one of the methods used by the government and organizations for controlling viral diseases like COVID-19, which claimed many human lives. Social distancing is advised to everyone to minimize the virus from spreading. This study aims to build a contact tracing tool that monitors social distancing individually using computer vision in real-time. Object tracking by detection is used for individual monitoring with YOLOv4 (You Only Look Once) as the object detector and SORT (Simple Online and Real-time Tracking) as the object tracker. The combination gained an average streaming and detection frame rate of 26 FPS and 10 FPS on NVIDIA's GTX 1650, respectively. It is expected to have more frame rate when used in a more powerful device. Moreover, the system obtained 98.2% accuracy in measuring the distance between individuals. Furthermore, the performance of the QR scanner used in the study attains a 100% success rate and a 98% accuracy in allocating the QR code to the correct owner from the video stream. © 2022 IEEE.

Evaluation of the impact of guideline communication from the Centers for Disease Control and Prevention and the Centers for Medicare and Medicaid Services among US healthcare providers: COVID-19 prevention counselling guidance.

AIM: To evaluate healthcare provider awareness and uptake of the Centers for Medicare & Medicaid Services (CMS) billing for coronavirus disease 2019 (COVID-19) prevention counselling and the delivery of prevention counselling to patients awaiting severe acute respiratory syndrome coronavirus 2 test results. DESIGN: Cross sectional survey of US-based healthcare providers in February 2021. METHODS: Analysis of associations with healthcare provider-reported awareness of CMS prevention counselling guidance and billing with provider type, specialty, and work setting. RESULTS: A total of 1919 healthcare providers responded to the survey. Overall, 38% (726/1919) of providers reported awareness of available CMS reimbursement for COVID-19 patient counselling and 29% (465/1614) of CMS billing-eligible providers reported billing for this counselling. Among physicians, those aware of CMS guidance were significantly more likely to bill (58%) versus those unaware (10%). Among RNSights respondents eligible for CMS billing (n = 114), 31% of those aware of the guidance reported billing as compared to 0% of those not aware.

Use of Bluetooth contact tracing technology to model COVID-19 quarantine policies in high-risk closed populations.

Containment measures in high-risk closed settings, like migrant worker (MW) dormitories, are critical for mitigating emerging infectious disease outbreaks and protecting potentially vulnerable populations in outbreaks such as coronavirus disease 2019 (COVID-19). The direct impact of social distancing measures can be assessed through wearable contact tracing devices. Here, we developed an individual-based model using data collected through a Bluetooth wearable device that collected 33.6M and 52.8M contact events in two dormitories in Singapore, one apartment style and the other a barrack style, to assess the impact of measures to reduce the social contact of cases and their contacts. The simulation of highly detailed contact networks accounts for different infrastructural levels, including room, floor, block, and dormitory, and intensity in terms of being regular or transient. Via a branching process model, we then simulated outbreaks that matched the prevalence during the COVID-19 outbreak in the two dormitories and explored alternative scenarios for control. We found that strict isolation of all cases and quarantine of all contacts would lead to very low prevalence but that quarantining only regular contacts would lead to only marginally higher prevalence but substantially fewer total man-hours lost in quarantine. Reducing the density of contacts by 30% through the construction of additional dormitories was modelled to reduce the prevalence by 14 and 9% under smaller and larger outbreaks, respectively. Wearable contact tracing devices may be used not just for contact tracing efforts but also to inform alternative containment measures in high-risk closed settings.

Exploring the psychological impact of contact tracing work on staff during the COVID-19 pandemic.

BACKGROUND: Contact tracing is a key control measure in the response to the COVID-19 pandemic. While quantitative research has been conducted on the psychological impact of the pandemic on other frontline healthcare workers, none has explored the impact on contact tracing staff. METHODS: A longitudinal study was conducted using two repeated measures with contact tracing staff employed in Ireland during the COVID-19 pandemic using two-tailed independent samples t tests and exploratory linear mixed models. RESULTS: The study sample included 137 contact tracers in March 2021 (T1) and 218 in September 2021 (T3). There was an increase from T1 to T3 in burnout related exhaustion (p < 0·001), post-traumatic stress disorder (PTSD) symptom scores (p < 0·001), mental distress (p < 0·01), perceived stress (p < 0·001) and tension and pressure (p < 0·001). In those aged 18-30, there was an increase in exhaustion related burnout (p < 0·01), PTSD symptoms (p < 0·05), and tension and pressure scores (p < 0·05). Additionally, participants with a background in healthcare showed an increase in PTSD symptom scores by T3 (p < 0·001), reaching mean scores equivalent to those of participants who did not have a background in healthcare. CONCLUSIONS: Contact tracing staff working during the COVID-19 pandemic experienced an increase in adverse psychological outcomes. These findings highlight a need for further research on psychological supports required by contact tracing staff with differing demographic profiles.

COVICT: an IoT based architecture for COVID-19 detection and contact tracing.

The world we live in has been taken quite surprisingly by the outbreak of a novel virus namely SARS-CoV-2. COVID-19 i.e. the disease associated with the virus, has not only shaken the world economy due to enforced lockdown but has also saturated the public health care systems of even most advanced countries due to its exponential spread. The fight against COVID-19 pandemic will continue until majority of world's population get vaccinated or herd immunity is achieved. Many researchers have exploited the Artificial intelligence (AI) knacks based IoT architecture for early detection and monitoring of potential COVID-19 cases to control the transmission of the virus. However, the main cause of the spread is that people infected with COVID-19 do not show any symptoms and are asymptomatic but can still transmit virus to the masses. Researcher have introduced contact tracing applications to automatically detect contacts that can be infected by the index case. However, these fully automated contact tracing apps have not been accepted due to issues like privacy and cross-app compatibility. In the current study, an IoT based COVID-19 detection and monitoring system with semi-automated and improved contact tracing capability namely COVICT has been presented with application of real-time data of symptoms collected from individuals and contact tracing. The deployment of COVICT, the prediction of infected persons can be made more effective and contaminated areas can be identified to mitigate the further propagation of the virus by imposing Smart Lockdown. The proposed IoT based architecture can be quite helpful for regulatory authorities for policy making to fight COVID-19.