Build an Agent-Based Model for COVID-19 Effect of Mitigation Policies

Non-Drug Intervention (NDI) is one of the important means to prevent and control the outbreak of coronavirus disease 2019 (COVID-19), and the implementation of this series of measures plays a key role in the development of the epidemic. The purpose of this paper is to study the impact of different mitigation measures on the situation of the COVID 19, and effectively respond to the prevention and control situation in the "post-epidemic era". The present work is based on the Susceptible-Exposed-Infectious-Remove-Susceptible (SEIRS) Model, and adapted the agent-based model (ABM) to construct the epidemic prevention and control model framework to simulate the COVID-19 epidemic from three aspects: social distance, personal protection, and bed resources. The experiment results show that the above NDI are effective mitigation measures for epidemic prevention and control, and can play a positive role in the recurrence of COVID-19, but a single measure cannot prevent the recurrence of infection peaks and curb the spread of the epidemic;When social distance and personal protection rules are out of control, bed resources will become an important guarantee for epidemic prevention and control. Although the spread of the epidemic cannot be curbed, it can slow down the recurrence of the peak of the epidemic;When people abide by social distance and personal protection rules, the pressure on bed resources will be eased. At the same time, under the interaction of the three measures, not only the death toll can be reduced, but the spread of the epidemic can also be effectively curbed. © 2022 ACM.

Social Distance and Face Mask Detection using vision-based sensors and IP cameras

Healthcare systems all over the world are strained as the COVID-19 pandemic's spread becomes more widespread. The only realistic strategy to avoid asymptomatic transmission is to monitor social distance, as there are no viable medical therapies or vaccinations for it. A unique computer vision-based framework that uses deep learning is to analyze the images that are needed to measure social distance. This technique uses the key point regressor to identify the important feature points utilizing the Visual Geometry Group (VGG19) which is a standard Convolutional Neural Network (CNN) architecture having multiple layers, MobileNetV2 which is a computer vision network that advances the-state-of-art for mobile visual identification, including semantic segmentation, classification and object identification. VGG19 and MobileNetV2 were trained on the Kaggle dataset. The border boxes for the item may be seen as well as the crowd is sizeable, and red identified faces are then analyzed by MobileNetV2 to detect whether the person is wearing a mask or not. The distance between the observed people has been calculated using the Euclidian distance. Pretrained models like (You only look once) YOLOV3 which is a real-time object detection system, RCNN, and Resnet50 are used in our embedded vision system environment to identify social distance on images. The framework YOLOV3 performs an overall accuracy of 95% using transfer learning technique runs in 22ms which is four times fast than other predefined models. In the proposed model we achieved an accuracy of 96.67% using VGG19 and 98.38% using MobileNetV2, this beats all other models in its ability to estimate social distance and face mask. © 2023 IEEE.

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.

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.

85 - Chemical, Biological, Radiological, and Nuclear Quarantine

Quarantine is a public health measure used to control the spread of contagious disease or environmental toxins within a population. Quarantine can be a helpful tactic in the setting of chemical, biological, radiological, or nuclear disasters. The success of quarantine demands tailoring preventative measures to the specific features of a given exposure. The criteria for initiating quarantine is clearly delineated in federal, state, and local laws, regulations, and policies. Successful quarantine and mitigation of risk depends on a complex interplay between first responders, affected individuals, and local, state, and federal services and authorities. As was seen in the current COVID-19 pandemic, there are many potential pitfalls that can be encountered during initiation and sustaining a quarantine effort.

Voting with Their Feet: Coronavirus Pandemic Refugees and the Future of American Cities

Paralleling crisis behavior in prior pandemics and continuing a contemporary migration trend already underway, wealthy individuals and families as well as remote workers in a host of other demographic groups are fleeing major, high cost, densely settled urban centers in response to the COVID-19 pandemic. These coronavirus pandemic refugees are relocating to less densely settled suburbs, exurbs, and rural areas-creating, in some instances, new "Zoom Towns.” The implications for the future viability of large cities are far ranging if, unlike prior pandemics, the social distance moves of coronavirus pandemic refugees and the aversion to dense urban living continue post-COVID-19. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Social Distancing and Politeness: Hungarian Emailing Practices During the Coronavirus Epidemic

With its outbreak and quick spread in early 2020, the COVID-19 epidemic brought rapid and sweeping changes in its wake in all walks of life. As measures were being imposed to contain the spread of the virus, emailing practices, including patterns of polite behaviour, were re-evaluated. Based on a corpus of emails comprising more than 250 texts, collected by various methods and showcasing personal, official and business correspondence alike, our paper presents linguistic features of emailing practices characterizing the first two and a half months of the global epidemic. Our pragmatic analysis uses the criteria of politeness theories to explore and classify novel emailing formulas indexically referring to the speech situation, and to interpret the functions of particular linguistic devices. The results point to the existence of a social distance-reducing strategy underlying varied patterns of expression. Social distance is offset, as it were, by linguistic means, distance being restricted to the spatial domain and solidarity taking centre stage in language activity. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

The Impact and Complex Effects of the COVID-19 Pandemic on the Working Environment and the Use of Coworking Spaces in Malta

Coworking spaces in Malta have grown in their presence and use only within the last decade, yet the COVID-19 pandemic may have altered the cultural working office norms of Maltese society. Indeed, this chapter, using in-depth interviews with different groups of people, that is, co-worker owners, employees, traditional employers and members of an employment association, aims to explore how the pandemic may be impacting the coworking industry in complex ways. From the narratives, it emerged that the soft lockdown measures related to the pandemic had caused immediate negative effects due to the fear of contagion on the use of coworking spaces in Malta and the limitations related to social distances in workspaces. However, the pandemic itself may have created a shift within the Maltese context where the idea of remote working is perceived as beneficial and may become more popular. The pandemic may have contributed to the revision of the Maltese employers' priorities, such as the importance of owning or renting a permanent office space or giving permission to employees to work from home or renting a coworking space for socialisation at work. Therefore, the pandemic may have caused damaging short-term effects to the coworking industry in Malta yet possibly beneficial long-term effects. © 2023, The Author(s).

Rethinking Distance and Presence Conceptions in Times of COVID-19 and Post-COVID-19: The Search for a New Educational Literacy

This work aims to deepen etymological, semantic, sociocultural and philosophical issues in relation to the concepts of distance and presence for their understanding of relevance and pertinence in the context of the current scenario of the COVID-19 pandemic. To this end, it is intended to argue that the radical dichotomies of common sense around such concepts do more harm than good in the clarification necessary for taking decisions and attitudes that protect individuals and collective health and life. The coronavirus pandemic requires the need for a clear discernment, supported by philosophical and scientific knowledge, which lead to a change in a set of attitudes, values, perceptions and sensitivities in relation to responsible social distancing, often contaminated by discourses without argument or a solid knowledge base. From a methodological point of view, this work performs a reflexive theoretical incursion in an essay style form, whose objective is to formulate hypotheses about the role that the concepts of distance and presence acquire from the context of COVID-19 onward, and how they should also be positioned in the context of future pandemics that may happen. Of course, this requires a re-education in the treatment of such concepts in light of the act of caring, as well as concerns about health, well-being, the individual and social life. To deepen these aspects, the spirit of this work will be supported by theoretical references that intertwine philosophical questions about presence and distance associated with human values, such as: affection, ethics and solidarity, philosophical questions about the use of face masks, and how such concepts are discussed and related with the idea of caring for and protecting the health in the context of COVID-19. The goal of these reflective support structures is to deepen our discussion of philosophical issues in the face of attitudinal challenges, which will result from new social relations demanded during the COVID-19 pandemic period as well as the challenges that will emerge in response to the social habits that will have to become naturalized, with greater frequency, in the post-COVID-19 period. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

A Smart Social Distance Monitoring System

The entire world is affected by Covid-19 pandemic. One of the major reasons is that it is contagious and a minimum distance should be maintained to stay safe. Social distancing might be a difficult task to implement effectively. Social distancing plays a pivotal role in curbing diseases that are contagious like Covid-19.Now that situations are returning to normal, the risk of getting infected is still high. Governments are deciding to ease lockdown regulations, as part of the unlocking public places, workspaces and educational institutions started to resume their activities. Considering the current scenario, the public has to strictly follow all the necessary Covid-19 protocols to reduce the spike in the number of Covid cases. This project aims to develop a prototype device that helps in implementing social distancing using Ultra-Wide Band (UWB) wireless technology based solution. Prototype issues an alert signal when the distance between individuals is less than the prescribed threshold distance. If the protocol is breached, the user is alarmed through an LED. UWB is known for its advantages as it has greater signal strength compared to Bluetooth. The design of the prototype enables implementation as wearable such as an ID card. © 2022 IEEE.

Covid -19 Social Distance Analysis Using Machine Learning

According to the Ministry of Global Health, social distance is one of the most effective defenses against COVID-19 and helps to prevent its spread. Governments have imposed many safety orders on citizens and facilities to limit social distancing and slow the spread of the virus. As a result, there has been an increase in interest in technologies to research and control the spread of COVID-19 in various settings. This research aims to investigate the results of several machine learning approaches to find cases when the physical distance between people has been violated. The method first identifies the instance of the human in the video frame, tracks the movements, computes the distance with other humans on the same frame and thus estimates the number of people who violate the social distance. Compares the approach to performing the performance using Yolo, SSD and Faster R- CNN. Videos that are used in this approach are collected from the wild, considering different camera settings, indoor and outdoor scenes, and recorded from various angles. Comparing the three methods Yolo, SSD and Faster RNN, the results show Yolo has a better performance in detecting humans from the current videos and thus in determining the violation of the distance between humans. © 2023 IEEE.

Resilient and social health service network design to reduce the effect of COVID-19 outbreak.

With the severe outbreak of the novel coronavirus (COVID-19), researchers are motivated to develop efficient methods to face related issues. The present study aims to design a resilient health system to offer medical services to COVID-19 patients and prevent further disease outbreaks by social distancing, resiliency, cost, and commuting distance as decisive factors. It incorporated three novel resiliency measures (i.e., health facility criticality, patient dissatisfaction level, and dispersion of suspicious people) to promote the designed health network against potential infectious disease threats. Also, it introduced a novel hybrid uncertainty programming to resolve a mixed degree of the inherent uncertainty in the multi-objective problem, and it adopted an interactive fuzzy approach to address it. The actual data obtained from a case study in Tehran province in Iran proved the strong performance of the presented model. The findings show that the optimum use of medical centers' potential and the corresponding decisions result in a more resilient health system and cost reduction. A further outbreak of the COVID-19 pandemic is also prevented by shortening the commuting distance for patients and avoiding the increasing congestion in the medical centers. Also, the managerial insights show that establishing and evenly distributing camps and quarantine stations within the community and designing an efficient network for patients with different symptoms result in the optimum use of the potential capacity of medical centers and a decrease in the rate of bed shortage in the hospitals. Another insight drawn is that an efficient allocation of the suspect and definite cases to the nearest screening and care centers makes it possible to prevent the disease carriers from commuting within the community and increase the coronavirus transmission rate.

Adherence to Online Nutritional Monitoring Was Associated with Better Food Habits in People with T1DM during the COVID-19 Pandemic in Brazil.

Until this moment, no research has been found that has assessed adherence to online nutritional monitoring by adults with Diabetes Mellitus Type 1 (T1DM) during the pandemic. This article aims to analyze the association between eating habits and adherence to nutritional online care by adults with T1DM during social distancing because of the COVID-19 pandemic in Brazil. A cross-sectional study was carried out in July 2020. An online form was used to collect sociodemographic data, financial status, eating habits, carrying out online nutritional monitoring, and adherence to social distancing. Pearson's chi-squared test was performed with adjusted residual analysis and binomial logistic regression analysis (p < 0.05). Out of the 472 adults, only 8.9% had consulted with a nutritionist. Doing nutritional monitoring online during social distancing was associated with a reduction in the consumption of ultra-processed foods (p = 0.021), eating more servings of fruit (p = 0.036), and doing carbohydrate counting (CC) more frequently (p = 0.000). Doing nutritional monitoring online increased adherence to carbohydrate counting by 2.57 times and increased the consumption of fruits by 0.423 times. Therefore, nutritional monitoring, even if performed remotely, can influence the acquisition and maintenance of healthier eating habits, in addition to assisting adherence to the practice of CC.

Unconstrained face mask and face-hand interaction datasets: building a computer vision system to help prevent the transmission of COVID-19.

Health organizations advise social distancing, wearing face mask, and avoiding touching face to prevent the spread of coronavirus. Based on these protective measures, we developed a computer vision system to help prevent the transmission of COVID-19. Specifically, the developed system performs face mask detection, face-hand interaction detection, and measures social distance. To train and evaluate the developed system, we collected and annotated images that represent face mask usage and face-hand interaction in the real world. Besides assessing the performance of the developed system on our own datasets, we also tested it on existing datasets in the literature without performing any adaptation on them. In addition, we proposed a module to track social distance between people. Experimental results indicate that our datasets represent the real-world's diversity well. The proposed system achieved very high performance and generalization capacity for face mask usage detection, face-hand interaction detection, and measuring social distance in a real-world scenario on unseen data. The datasets are available at https://github.com/iremeyiokur/COVID-19-Preventions-Control-System.

THE SOCIAL DISTANCE AND DAILY LIFE OF PEOPLE WITH DISABILITIES: Social distance and people with disabilities

Covid-19 has manifested itself as a highly infectious disease. In this sense, People with Disabilities were advised to redouble their precautions to prevent Covid-19, such as social withdrawal, because they are considered to be in the risk group. The purpose of this study was to understand the interference of social distancing in the daily lives of people with physical disabilities during the Covid-19 pandemic period. This study is of an applied nature and descriptive observational character. The data analysis and discussion was carried out under the qualitative paradigm. As for the technical procedures, it is characterized as a field research. The group of collaborators was composed of ten People with Disabilities. The results indicated that the greatest impacts of the distancing were the difficulties of access to health and rehabilitation activities, as well as the changes in hygiene habits due to the danger of contamination. On a personal level, some perceived the distance as a factor of introspection and reflection on the relationships with oneself and with others, putting into perspective the world in a post-pandemic future.

Social Distance – History and Presence of the Hygienic Consciousness

Social distancing – this is the formula to which pandemic daily life has had to adapt to in a very short time. In the public debate, however, it is often overlooked that this is not only a contemporary phenomenon. This article expands the discussion to include an historical perspective on social distancing, by focusing on scenes of hygiene and disease prevention from the 18th and 19th century. It becomes evident that socially distanced behaviors practiced during times with increased risks of infection is not just a product of medical progress, but is modelled on the growing middle-class lifestyle. © Leviathan (Germany). All rights reserved.

The Use of Public Space During the Epidemic

At the beginning of this article, it was shown that the indicators of the current so-called social distance determined by decision-makers at various stages of the epidemic development are imprecise, do not sufficiently take into account spatial relations, are unclear in public perception, and do not contain specific practical solutions. Therefore, this study undertakes the task of giving the term "social distancing"precise features, defined on the basis of geometry, and providing solutions in typical cases of the living space of the population. The geometry of the distribution of people in various situations of everyday life was considered: people standing during concerts or religious ceremonies, sitting during meals in collective catering rooms and participating in lectures, cultural, entertainment or sports events. In the latter group of tasks, the concept of building a people-distribution scheme must be adapted to the existing, arbitrary grid of real places of a lecture hall, theater hall, cinema, or stadium. The article contains some practical examples with comments and an evaluation of benefits, both in terms of ensuring safety and in terms of effective use of space. © 2023 Anna Marta Barańska et al., published by Sciendo.

YOLO KeepSafe: Utilization of YOLOv4-Based Algorithm to Employ a Real-time People Detection and Social Distance Monitoring System

This paper outlines the process used to create the social distance detection system - YOLO KeepSafe. The researchers discuss several calibration procedures, investigate the difficulties that arise when used in real-time situations, and offer potential solutions. © 2022 IEEE.