Social Distancing Protocols Research Articles

Promotion of Physical Activity through Health Applications among Students of Selected Universities – a Preliminary Study

Mobile health applications provide individuals with a mobile tool that can be tailored to meet various health needs and physical activity goals, which is particularly important during the Covid-19 pandemic and the associated social distancing protocols. The consequence that the pandemic has on the mental health of university students has prompted and increased the demand of physical activity interventions. The aim of this study was to determine the self-perceived effects of mobile health applications on physical activity participation among university students. Participants included students registered in one of the faculties at a university in Johannesburg. Data collection took place by means of an electronic questionnaire using Google Forms as a platform, completed by a sample of 192 students. The findings in the study reflected that majority of university students use health applications to increase physical activity levels or to track current activity levels. Participants also indicated that specific health applications were used to set goals, monitor progress and receive feedback. Aerobic activities proved to be the more popular type of physical activity in comparison to anaerobic activity. This study concluded that health applications can be used as a tool to facilitate and promote physical activity participation in the university student population.

Can We Replace Our Human Connection With Technology?

The COVID-19 pandemic has led to social distancing protocols, subsequently increasing social isolation for older adults. The purpose of this study was to explore the relationship between social connectedness and mental health outcomes. Leveraging NHATS, a nationally representative study (n = 2,558, Mage = 79.20, SDage = 6.25), we examined the association between the method of social connectedness and mental health outcomes. Descriptive analyses revealed older adults are using various methods (e.g., in-person, phone, and video calls) to remain connected with their social networks during COVID-19. Findings from all of the linear regression analyses indicated phone or video calls are associated with negative affect, whereas in-person visits are associated with lower levels of negative affect. These findings suggest substituting in-person visits with video calls or phones may not be sufficient to relieve their loneliness and negative affect. Future studies should investigate this effect on physical or emotional health outcomes.

Human Mobility to Parks Under the COVID-19 Pandemic and Wildfire Seasons in the Western and Central United States.

In 2020, people's health suffered a great crisis under the dual effects of the COVID‐19 pandemic and the extensive, severe wildfires in the western and central United States. Parks, including city, national, and cultural parks, offer a unique opportunity for people to maintain their recreation behaviors following the social distancing protocols during the pandemic. However, massive forest wildfires in western and central US, producing harmful toxic gases and smoke, pose significant threats to human health and affect their recreation behaviors and mobility to parks. In this study, we employed the geographically and temporally weighted regression (GTWR) Models to investigate how COVID‐19 and wildfires jointly shaped human mobility to parks, regarding the number of visits per capita, dwell time, and travel distance to parks, during June ‐ September 2020. We detected strong correlations between visitations and COVID‐19 incidence in southern Montana, western Wyoming, Colorado, and Utah before August. However, the pattern was weakened over time, indicating the decreasing trend of the degree of concern regarding the pandemic. Moreover, more park visits and lower dwell time were found in parks further away from wildfires and less air pollution in Washington, Oregon, California, Colorado, and New Mexico, during the wildfire season, suggesting the potential avoidance of wildfires when visiting parks. This study provides important insights on people's responses in recreation and social behaviors when facing multiple severe crises that impact their health and wellbeing, which could support the preparation and mitigation of the health impacts from future pandemics and natural hazards.

Join the Holy Spirit on Zoom

The COVID-19 global pandemic impacted all social relations, including the way religious communities engage in worship services. Due to strict social distancing protocols, the only viable solution for many congregations was online worship. This article investigates how platforms in cyberspace, such as Zoom, can provide a substitute for the core religious practices found in physical worship services, particularly for African Pentecostal believers who rely heavily on the aesthetic and sensory experience of their religious environment. Drawing on the theoretical concept of affordance, it is argued that digital affordances such as the chat box and emojis are used by believers to communicate affective moments arising from the sensory experience of worship. Members of the congregation become ‘digital spiritual hype people’ who render support to leaders in order to create and regenerate an affective environment where the presence of the Holy Spirit can be felt. The Holy Spirit, a fundamental pillar for Evangelical Christians, is understood as an embedded presence within the digital infrastructure. The internet connection, the phone and computers and screens are all re-appropriated as spiritual tools through which miraculous healing can be dispensed to believers in need. This research stands at a critical juncture between what might be termed the ‘pre-COVID era’ and the ‘post-COVID era’. As vaccination plans continue to roll out and social distancing measures are slowly being lifted, a ‘post-COVID era’ for African Pentecostals means negotiating the boundaries between online and offline spaces to fulfil core religious practices.

Real-Time Infoveillance of Moroccan Social Media Users' Sentiments towards the COVID-19 Pandemic and Its Management.

The impact of COVID-19 on socio-economic fronts, public health related aspects and human interactions is undeniable. Amidst the social distancing protocols and the stay-at-home regulations imposed in several countries, citizens took to social media to cope with the emotional turmoil of the pandemic and respond to government issued regulations. In order to uncover the collective emotional response of Moroccan citizens to this pandemic and its effects, we use topic modeling to identify the most dominant COVID-19 related topics of interest amongst Moroccan social media users and sentiment/emotion analysis to gain insights into their reactions to various impactful events. The collected data consists of COVID-19 related comments posted on Twitter, Facebook and Youtube and on the websites of two popular online news outlets in Morocco (Hespress and Hibapress) throughout the year 2020. The comments are expressed in Moroccan Dialect (MD) or Modern Standard Arabic (MSA). To perform topic modeling and sentiment classification, we built a first Universal Language Model for the Moroccan Dialect (MD-ULM) using available corpora, which we have fine-tuned using our COVID-19 dataset. We show that our method significantly outperforms classical machine learning classification methods in Topic Modeling, Emotion Recognition and Polar Sentiment Analysis. To provide real-time infoveillance of these sentiments, we developed an online platform to automate the execution of the different processes, and in particular regular data collection. This platform is meant to be a decision-making assistance tool for COVID-19 mitigation and management in Morocco.

COVID-19’s Social Ecological Impacts on Health and Human Services Worker Well-being

ABSTRACT Health and human services workers (HHS; e.g., child welfare, physical and mental healthcare) engage with clients facing heightened vulnerability during the COVID-19 pandemic. Under typical circumstances, HHS workers face a host of challenges in carrying out their job responsibilities such as high caseloads and burnout, and now navigate new challenges such as social distancing protocols and protecting their own health and that of their families and clients. This study explored the experiences of 531 HHS workers in Florida to understand well-being impacts of COVID-19 on the HHS workforce. Using a social ecological framework, we analyzed open-ended responses from HHS workers to better understand the multi-level and frequently intertwined impacts of COVID-19. Participants reported numerous proximal factors (i.e., intrapersonal, interpersonal, organizational) impacting their well-being but fewer distal factors (i.e., community, public policy). Agencies should work to understand the intersecting vulnerabilities of their workers and implement safety protocols to preserve workers’ well-being.

The use of e-commerce and the COVID-19 outbreak: A panel data analysis in Japan

This study analyzes the changes in Japanese consumers' psychological intentions toward the use of e-commerce and the corresponding reasons before and after the COVID-19 outbreak using panel data. Several insights emerge on changes in consumers’ fundamental behaviors. First, the share of e-commerce use differs across the types of goods. Grocery goods showed a significant increase immediately after the COVID-19 outbreak. In contrast, machinery/PC applications and book/DVD/software showed only a slight increase immediately after the outbreak. However, only a slight decrease was observed during the third survey. Overall, consumers recognized the importance of e-commerce immediately after the pandemic, with no subsequent significant decline. Second, there may be a positive relationship between the time spent at home and the importance of e-commerce One reason is that an increase in stay-at-home duration decreases the opportunity to shop at retail stores. Consequently, trips to stores decreased during the initial spread of COVID-19. The modes of transportation for shopping and in the living area (infection status) were not significant factors of e-commerce usage. Finally, if consumers recognize its usefulness, they continued to consider e-commerce as important. However, their attitudes toward e-commerce improved after the COVID-19 outbreak because they wanted to avoid infection risks and follow social distancing and safety protocols.

40.2 Psychological IMPACT of Remote Learning in Children and Adolescents With Mental Health Disorders in the Community New York City Area

The global crisis of COVID-19 demanded that schools adapt to online education at an unprecedented pace. Remote learning has followed social distancing protocols and helped in continuation of education. However, in children with mental health disorders (C-MHD), the outcomes of online learning are not similar to normal individuals. The primary objective of this study is to determine the prevalence of psychological distress of transitioning to remote learning in C-MHD. The secondary objective is to provide directions to increase student satisfaction for online education.

COVID-19’s Negative Mental Health Impact Goes Well Beyond Standard At-Risk Populations: Action Needs To Be Taken to Combat Long-term Nationwide Emotional Disruption

The current Coronavirus pandemic has changed the lives of many. Everyday, new information about the virus emerges from the many studies taking place across the globe. Many countries have enacted social distancing and quarantine protocols to slow the spread of the virus. However, these restrictions have had a severe impact on the mental health of many individuals across the globe. Substance use has been on a rise since the onset of restrictions in March 2020. An increase in depression and anxiety has been correlated with the increase in substance use. This correlation points to the use of substances as a coping mechanism in many people to combat the negative feelings associated with the pandemic. Continued use of drugs to cope with the pandemic has long-lasting impacts on social functioning as well as the possibility for future substance abuse problems. The Canadian mental health system is not equipped to effectively treat a surge in mental health issues and needs help. Increased funding of the Canadian mental health system and increased importance placed on mental health issues is imperative to ensuring all Canadians receive the help they need.

Social Distancing for Covid-19 Monitoring System

The battle of corona-virus and mankind is possible to be tackled as long as we maintain the basic norm of social distancing and wearing masks amongst ourselves as it is through our droplets from the respiratory tract that the virus spreads. With the increasing demand for man-force and people requiring to go to their workplaces post lockdown, it is very necessary that we save each other from the virus. In this project, we will go through a detailed explanation of how we can use Python, AI and Deep Learning to monitor social distancing at public places and workplaces are keeping a safe distance from each other by analyzing real-time video streams from the camera and also detect facial mask monitoring using OpenCV and Python. To ensure if people are following social distancing protocols in public places and workplaces, we wanted to develop a tool that can monitor if people are keeping a safe distance from one another, wearing masks or not by processing real-time video footage from the camera. People at workplaces, factories, shops can integrate this tool into their security camera systems and can monitor whether people are keeping a safe distance from each other or not along with that we detect facial mask monitoring using Python with help of haar-cascade algorithm to see whether a person is wearing a mask or not. We are also planning to include thermal screening detection to measure the temperature of the subjects, a dashboard which will display a live report of corona cases around the world. We will also include an alert system that will send a notification to the authorities if the social distancing is not followed or if the temperature exceeds the threshold. The authorities can take suitable measures to isolate the subject and thus prevent the spread of Covid-19.

Crash Patterns in the COVID-19 Pandemic: The Tale of Four Florida Counties

This study investigates the impacts of the noticeable change in mobility during the COVID-19 pandemic with analyzing its impact on the spatiotemporal patterns of crashes in four demographically different counties in Florida. We employed three methods: (1) a Geographic Information System (GIS)-based method to visualize the spatial differences in crash density patterns, (2) a non-parametric method (Kruskal–Wallis) to examine whether the changes in crash densities are statistically significant, and (3) a negative binomial regression-based approach to identify the significant socio-demographic and transportation-related factors contributing to crash count decrease during COVID-19. Results confirm significant differences in crash densities during the pandemic. This may be due to maintaining social distancing protocols and curfew imposement in all four counties regardless of their sociodemographic dissimilarities. Negative binomial regression results reveal that the presence of youth populations in Leon County are highly correlated with the crash count decrease during COVID-19. Moreover, less crash count decrease in Hillsborough County U.S. Census blocks, mostly populated by the elderly, indicate that this certain age group maintained their mobility patterns, even during the pandemic. Findings have the potential to provide critical insights in dealing with safety concerns of the above-mentioned shifts in mobility patterns for demographically different areas.

Associations between older African academics' physical activity, walkability and mental health: a social distancing perspective.

SummaryThis study aimed to assess the moderating influence of neighborhood walkability on the association between physical activity (PA) and mental health among older African academics aged 50 years or more in cities with social distancing protocols in response to the Coronavirus disease 2019 (COVID-19). A total of 905 volunteer academics participated in the study. A hierarchical linear regression analysis was employed to conduct sensitivity analyses and test the study hypotheses. After controlling for sex, education and age, there was a positive association between PA and mental health. Neighborhood walkability moderated the relationship between PA and mental health, which suggests that during the pandemic PA was associated with higher mental health scores in more walkable neighborhoods. The study concludes that PA was beneficial to mental health in the social distancing context and was associated with higher mental health in more walkable neighborhoods, particularly in a social distancing context.

Human mobility impacts on the surging incidence of COVID‐19 in India

Human mobility triggers how fast and where infectious diseases spread and modelling community flows helps assess the impact of social distancing policies and advance our understanding of community behaviour in such circumstances. This study investigated the relationship between human mobility and the surging incidence of COVID‐19 in India. We performed a generalised estimating equation with a Poisson log‐linear model to analyse the daily mobility rate and new cases of COVID‐19 between 14 March and 11 September 2020. We found that mobility to grocery and retail locations was significantly associated (p < 0.01) with the incidence of COVID‐19, these being crowded and unorganised in most parts of India. In contrast, visits to parks, workplaces, and transit stations did not considerably affect the changing COVID‐19 cases over time. In particular, workplaces equipped with social distancing protocols or low‐density open spaces are much less susceptible to the spread of the virus. These findings suggest that human mobility data, geographic information, and health geography modelling have significant potential to inform strategic decision‐making during pandemics because they provide actionable knowledge of when and where communities might be exposed to the disease.

Monocular Pedestrian 3D Localization for Social Distance Monitoring.

Social distancing protocols have been highly recommended by the World Health Organization (WHO) to curb the spread of COVID-19. However, one major challenge to enforcing social distancing in public areas is how to perceive people in three dimensions. This paper proposes an innovative pedestrian 3D localization method using monocular images combined with terrestrial point clouds. In the proposed approach, camera calibration is achieved based on the correspondences between 2D image points and 3D world points. The vertical coordinates of the ground plane where pedestrians stand are extracted from the point clouds. Then, using the assumption that the pedestrian is always perpendicular to the ground, the 3D coordinates of the pedestrian’s feet and head are calculated iteratively using collinear equations. This allows the three-dimensional localization and height determination of pedestrians using monocular cameras, which are widely distributed in many major cities. The performance of the proposed method was evaluated using two different datasets. Experimental results show that the pedestrian localization error of the proposed approach was less than one meter within tens of meters and performed better than other localization techniques. The proposed approach uses simple and efficient calculations, obtains accurate location, and can be used to implement social distancing rules. Moreover, since the proposed approach also generates accurate height values, exclusionary schemes to social distancing protocols, particularly the parent-child exemption, can be introduced in the framework.

Patchy signals: capturing women’s voices in mobile phone surveys of rural India

Phone surveys are a rapid and cost-effective way to collect primary data for research, monitoring and evaluation purposes. But for these data to be precise, reliable and unbiased, women’s perspectives...

Can blockchain help food supply chains with platform operations during the COVID-19 outbreak?

Food selling platforms are facing both challenges and opportunities during the COVID-19 outbreak as the enforcement of social distancing protocols has pushed consumers with serious health and safety concerns to shop online. Observing that platforms and their suppliers have adopted blockchain technologies and linked selected information nodes separately to foster consumers’ trust, we establish a game-theoretic model to study the operations decisions and blockchain adoption strategies for a food supply chain consisting of one platform and one supplier. We explore the values and impacts of blockchain on the retailing platform, supplier, and consumers, respectively. An all-win situation is achieved when both members of the supply chain adopt blockchain. We further propose that not all prevalent supply chain contracts can achieve supply chain coordination in the presence of blockchain. In extended studies, we examine the incentives of the supply chain members’ blockchain implementation with consideration of the fixed cost of such adoption, product infection, and tampered information.

Cross-National Study of Mental Health and Employment Status Nine Months Post Social Distancing Implementation Practices

This cross-national study examined the mental health between those individuals working and those not working nine months post initial COVID-19 social distancing implementation. Respondents (N = 3,474) were recruited through social media (e.g. Facebook, Twitter) and completed an online survey in October/November 2020. The respondents were from Norway, the UK, the USA and Australia. The mental health of those working and not working were analysed using t tests and socio-demographics were compared using one-way analysis of variance. Respondents who were working were significantly more likely to experience better mental health, were younger, report higher levels of education, and significantly less likely to worry about their own situation, health or financial situation than respondents who were not employed. Respondents who were retired reported better mental health than respondents who were not working for other reasons (laid off/dismissed, receiving benefits, studying, other). These findings raise the importance for social workers and other health service providers to monitor the overall mental health of individuals especially when social distancing protocols are in place and as countries begin to recover from the pandemic.

Maintaining Social Distancing: Video and Just-in-Time In Situ Simulation During the COVID-19 Pandemic.

Summary StatementRespiratory failure and cardiopulmonary arrest in patients with SARS-CoV-2 infection require life-saving procedures that aerosolize virus and increase risk of transmission. To educate faculty, trainees, and staff on safe practices, a video with embedded questions was created demonstrating intubation and cardiopulmonary resuscitation in pediatric SARS-CoV-2+ patients. Just-in-time in situ simulations of these scenarios were also carried out while adhering to isolation and social distancing protocols. We demonstrated that use of simulation to train physicians and staff during the COVID-19 pandemic is possible and effective in improving confidence in performance of the procedures.

Research Challenges for Nigerian Road Transportation Sector in Covid-19 Pandemic Era

The COVID-19 pandemic created an enormous disruption to the everyday life of the modern society. Among the various urban systems, transportation services were among those that suffered the most significant impacts, particularly severe in the case of urban transportation and highways. Using the Nigerian experience in the COVID-19 era, it is seen that a lot of city/urban and even rural challenges have to do with coping with peak hour traffic periods when workers have to go to work and student/school children commuting to school, and later return to their homes. With COVID-19 pandemic and social distancing consequences, mass transportation is actually the main barrier for students and workers dependent on transport to go back to their daily routines with comfort and safety. It is implied that the objective of a good research would be to determine a demand control able to equalize the number of passengers in each car but respecting the COVID-19 social distancing protocols with the number of passengers in each time-of-day range being combined into suitable predictive models that include independent variables related to passenger’s behavior so that almost 90% of all passengers are follow very strict and straight daily routine that can be coordinated and scheduled creating enough time space one from the other to avoid undesirable concentrations inside buses and bus stops.

Examining User Engagement in AI-based Interactional Tools: Valorizing the Essence of Human-Beings

As the COVID-19 pandemic batters the world and disrupts the economic activities globally, companies are attempting to reshape the future by swiftly turning to use AI-based interactional tools to comply with the mandated social-distancing protocols. However, practitioners are unsure about the efficacy of AI-based interactional systems in facilitating the desired user engagement. Turing test premises user engagement in AI-tools based on the “indistinguishability” of AI-tools from human-beings. Such a user engagement approach for AI-tools is very different from the dominant user-engagement approach employed in prior IS research focusing on the “instrumental” value of technologies. Rooting our arguments in “human competency” and “media naturalness” literature, we theorize the significant role of the three human-like interactional competencies —cognitive, relational, and emotional competencies in interactional-AI tools, for fostering the desired user engagement with AI. We also hypothesize the mediating role of user trust in the relationship between ‘human-like interactional competencies in AI tools’ and ‘user engagement’. The theorized model is tested through a sequential mixed-methods approach comprising a quantitative two-wave survey followed by qualitative interviews with a sampled set of AI users. Results from our study largely support the theorized model. The emerging theoretical and practical implications are also discussed.