Novel social distancing detector using local binary pattern in comparison with principal component analysis to improve accuracy

The objective is to detect Novel Social Distancing using Local Binary Pattern (LBP) in comparison with Principal Component Analysis (PCA). Social Distance deduction is performed using Local Binary Pattern(N=20) and Principal Component Analysis(N=20) algorithms. Google AI open Images dataset is used for image detection. Dataset contains more than 10,000 images. Accuracy of Principal Component Analysis is 89.8% and Local Binary Pattern is 93.9%. There exists a statistical significant difference between LBP and PCA with (p<0.05). Local Binary Pattern appears to perform significantly better than Principal Component Analysis for Social Distancing Detection. © 2023 Author(s).

Infectious diseases and social distancing under state-dependent probabilities.

We analyze the implications of infectious diseases and social distancing in an extended SIS framework to allow for the presence of stochastic shocks with state dependent probabilities. Random shocks give rise to the diffusion of a new strain of the disease which affects both the number of infectives and the average biological characteristics of the pathogen causing the disease. The probability of such shock realizations changes with the level of disease prevalence and we analyze how the properties of the state-dependent probability function affect the long run epidemiological outcome which is characterized by an invariant probability distribution supported on a range of positive prevalence levels. We show that social distancing reduces the size of the support of the steady state distribution decreasing thus the variability of disease prevalence, but in so doing it also shifts the support rightward allowing eventually for more infectives than in an uncontrolled framework. Nevertheless, social distancing is an effective control measure since it concentrates most of the mass of the distribution toward the lower extreme of its support.

The spread of COVID-19 in stock returns along global value chains

This paper examines the performance of industries in the trade network in international stock markets during the onset of COVID-19. In general, the value of all industries in G20 countries declines significantly in the pandemic. Stock returns of industries in the central positions of global value chains exhibit remarkable resilience despite the economic hardship caused by COVID-19. This pattern is more pronounced when the disruptions caused by social distancing requirements are considered. We postulate that this is related to the essential services provided by the central industries.

Covid-19: Rest and PPE reassurance are needed before NHS services can restart, MPs hear

At a Health and Social Care Select Committee evidence session on 14 May the King's Fund, the Nuffield Trust, and the Health Foundation warned that it would take many more months before core health and care services were able to fully restart. Limited capacity Jennifer Dixon, chief executive officer at the Health Foundation, told the committee that capacity within hospitals would be severely limited because of the need for social distancing, separating out covid and non-covid patients, and more time for deep cleaning of equipment and facilities. Chris Hopson, chief executive officer at NHS Providers, told the committee that NHS staff had worked incredibly hard in the past few months, with leave cancelled, and were very tired as a result.

Providing culturally responsible health care to Pacific Islander communities: The creation of a cultural competency training for healthcare professionals

Cultural competency is the ability to respectfully engage, understand, and communicate through conscientious interaction, enabling effective work and meaningful relationships in cross-cultural situations. Cultural competency recognizes the importance for organizations of participants' diverse social and cultural values, beliefs, and behaviors, and has gained attention because it can bridge health perspectives, understanding, and respect between health professionals and patients. There remains a need for cultural competency in healthcare as disparities persist across the U.S. in racial and ethnic minority groups who experience worse health outcomes and lower healthcare quality than the general public. Therefore, a cultural competency training curriculum was created using various resources to improve interactions between Pacific Islander patients and healthcare professionals. This training helps to reduce racial/ethnic disparities in healthcare by encouraging mutual understanding and improving patient satisfaction, adherence to medical instructions, and overall health outcomes by highlighting patient-centered care as a result of utilizing components of cultural competency. To improve patient experiences in Hawai'i, healthcare professionals need the tools to better interact with patients from different cultures, such as Pacific Islanders. This training provides healthcare professionals with culturally-based content for improving cultural competence techniques for interacting with Pacific Island patients. This training was pilot tested with key stakeholders from community organizations and Cancer Center faculty/staff. Local health clinics, providers, and practices will have the opportunity to participate in this training through a Zoombased electronic training format and be provided with three continuing medical education credits. The initial delivery of the training was intended for in-person sessions;however, a virtual format was adapted due to the COVID-19 pandemic and subsequent social distancing regulations. Healthcare providers are provided pre-training resources, a pre- and post-test, and a course evaluation to determine the validity of training objectives. To date, two Federally Qualified Health Centers have been provided the training, n=60, as well as one Cancer Health Equity Partnerships' Scientific Workshop, n=40. For attendees, the analysis of correct responses from the pretest to post-test showed a significant improvement on 6 of the 12 questions. Respondents also agreed that the training resources aligned with the course objectives. Improved patient interactions from this training can help support better patient outcomes, adherence to medical advice regarding cancer screenings, and many other aspects of improving health equity for Pacific Islanders.

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.

Control System for Indoor Safety Measures Using a Faster R-CNN Architecture

This paper presents a control system for indoor safety measures using a Faster R-CNN (Region-based Convolutional Neural Network) architecture. The proposed system aims to ensure the safety of occupants in indoor environments by detecting and recognizing potential safety hazards in real time, such as capacity control, social distancing, or mask use. Using deep learning techniques, the system detects these situations to be controlled, notifying the person in charge of the company if any of these are violated. The proposed system was tested in a real teaching environment at Rey Juan Carlos University, using Raspberry Pi 4 as a hardware platform together with an Intel Neural Stick board and a pair of PiCamera RGB (Red Green Blue) cameras to capture images of the environment and a Faster R-CNN architecture to detect and classify objects within the images. To evaluate the performance of the system, a dataset of indoor images was collected and annotated for object detection and classification. The system was trained using this dataset, and its performance was evaluated based on precision, recall, and F1 score. The results show that the proposed system achieved a high level of accuracy in detecting and classifying potential safety hazards in indoor environments. The proposed system includes an efficiently implemented software infrastructure to be launched on a low-cost hardware platform, which is affordable for any company, regardless of size or revenue, and it has the potential to be integrated into existing safety systems in indoor environments such as hospitals, warehouses, and factories, to provide real-time monitoring and alerts for safety hazards. Future work will focus on enhancing the system's robustness and scalability to larger indoor environments with more complex safety hazards.

Efficient Centroid Based Distance Monitoring System Using Deep Learning

COVID-19 virus spread very rapidly if we come in contact to the other person who is infected, this was treated as acute pandemic. As per the data available at WHO more than 663 million infected cases reported and 6.7 million deaths are confirmed worldwide till Dec, 2022. On the basis of this big reported number, we can say that ignorance can cause harm to the people worldwide. Most of the people are vaccinated now but as per standard guideline of WHO social distancing is best practiced to avoid spreading of COVID-19 variants. This is difficult to monitor manually by analyzing the persons live cameras feed. Therefore, there is a need to develop an automated Artificial Intelligence based System that detects and track humans for monitoring. To accomplish this task, many deep learning models have been proposed to calculate distance among each pair of human objects detected in each frame. This paper presents an efficient deep learning monitoring system by considering distance as well as velocity of the object detected to avoid each frame processing to improve the computation complexity in term of frames/second. The detected human object closer to some allowed limit (1m) marked by red color and all other object marked with green color. The comparison of with and without direction consideration is presented and average efficiency found 20.08 FPS (frame/Second) and 22.98 FPS respectively, which is 14.44% faster as well as preserve the accuracy of detection. © 2023 IEEE.

Immersive Technologies - The future for tracheostomy education?

Introduction: The need for standardised education on tracheostomy care is well recognised.1 Staff frequently report a lack of confidence in caring for those with tracheostomies, as well as the management of adverse events as they occur.2 Over the past decade, healthcare providers have developed strategies to educate staff, however, the covid-19 pandemic has severely hampered the ability to provide this necessary training due to restrictions on access to training rooms, the need for social distancing and the significant clinical demands placed on both trainers and trainees.3 The potential for immersive technologies to augment healthcare training is gaining interest exponentially.4 However, its effectiveness is yet to be clearly understood and as such it is not yet common within healthcare education.5 Based on the above, we aimed to explore the potential of these immersive technologies to overcome the current challenges of tracheostomy education, and to develop future strategies to use immersive technology in healthcare education. Method(s): We received a 400,000 grant from Cardiff Capital Region (CCR) to undertake a rapid innovation project overseen by the SBRI centre of excellence. The project consisted of 3 main phases: 1) feasibility;2) development;and 3) testing. The project was officially launched in April 2021 and lasted 12 months. Project governance was provided via the SBRI for clinical excellence, a project board with representation from Welsh Government, Cardiff University and Cardiff and Vale UHB, and a project team with clinical expertise in both the delivery of tracheostomy education and the provision of simulation training in healthcare. Result(s): Phase 1: During phase one 4 industries were successful and received up to 30,000 to explore the feasibility of immersive technology to support tracheostomy education. The industries were Rescape, TruCorp, Aspire2Be and Nudge Reality. During the feasibility phase all industries focused on the emergency management process utilising existing NHS Wales tracheostomy education resources and the national tracheostomy safety programme. Phase 2: For phase 2, Rescape and Nudge Reality were chosen to develop the technology. These industries continued to work in conjunction with the project team to capture the core elements of tracheostomy care, including multi-user emergency management scenarios. Additional content was also added for bronchoscopy and insertion of intercostal drains. Phase 3: Testing of both solutions was undertaken over an 8-week period, across 6 Health Boards in NHS Wales. The results of the testing will be analysed and available for presentation in due course. Provision findings demonstrate good face and content validity with high levels of user satisfaction. Discussion / Conclusion(s): The provision of essential tracheostomy education has been severely affected by the covid-19 pandemic. Evolving immersive technologies have the potential to overcome these challenges and improve the effectiveness and efficiency of education packages in tracheostomy care and wider. Through this CCR grant, in conjunction with industry, we have developed two solutions with the potential for widescale procurement and future research on the use of immersive technologies within healthcare.

Impact of COVID-19 Pandemic on Beach Tourism in India

COVID-19 Pandemic has a profound Impact on the Indian tourism sector, especially on beach tourism. Research shows significant changes in the pattern of the ecological terrain of coastal areas and on the community dependent on tourism business and marine life, due to the imposition of lockdown for several months. The paper discusses the change in behavioral patterns of people during Pre and Post COVID-19 for visiting any beach destination in near future in terms of preferences in accommodation, selection of beaches based on crowd and other factors that will be considered in post pandemic days. This study brings out various key indicators shaping the pattern of beach holidays in the future based on the survey conducted among tourists belonging to youth population. The survey considered the tourists preferences of visits and factors they would look upon to choose beach holidaying in the Post COVID-19 years. The influence of the pandemic on quality of beaches, visitors'willingness to visit beaches in future, Post Pandemic opportunities and strategies of destinations for shaping tourism further have also been examined. ©Copyright IJHTS.

Youth Compliance Level in Covid-19 Prevention Efforts in Bangkalan Regency

Introduction: The covid-19 disease can be prevented, including by knowledge and public compliance, especially with adolescents in efforts to prevent Covid-19 disease. A preliminary survey of 40 adolescents showed that 30% of teenagers are knowledgeable and 60% of teenagers in Bangkalan are non-compliant in covid-19 prevention efforts. This study aimed to determine the level of compliance to prevent Covid-19. Methods: This research was conducted using a quantitative descriptive survey method. The population and sample were taken by simple random sampling, namely, all adolescents aged 14-21 years in Bangkalan as many as 200 respondents. The instrument uses a questionnaire about Covid-19 prevention efforts. Quantitative data analysis by calculating the frequency of values in a variable. Results: The results showed that 66% of adolescents washed their hands, 95.5% stated that they already knew how to wash their hands properly, and 96.5% used clean water and soap to wash their hands. All adolescents still leave the house, 46% avoid crowds and 97% have kept their distance. 96.5% of adolescents used masks when leaving the house. 84.5% of respondents exercised during a pandemic. 64% of respondents consume nutritious food, exercise, and add vitamins to maintain their immunity, and 59% wear masks, wash their hands and keep a suitable distance health protocol as an effort to prevent Covid-19. Conclusion: The level of adolescent adherence is very good in terms of all aspects of the efforts to prevent Covid-19 except for the physical distancing aspect, so there is a need for increased socialization to eliminate the stigma about physical distancing. [ FROM AUTHOR] Copyright of Malaysian Journal of Medicine & Health Sciences is the property of Universiti Putra Malaysia 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.)

Using Absorbable Suture For Traumatic Wound Closure To Avoid Additional Hospital Visit For Suture Removal During The Covid 19 Pandemic: A Randomized Controlled Trial

Introduction: The COVID-19 pandemic worldwide forced governments to undertake intervention measures to encourage social distancing. Meanwhile, traumatic skin lacerations require multiple hospital visits for dressing, changings, and suture removal since they are usually repaired with non-absorbable sutures. In a matter of fact, these visits can be avoided by using absorbable sutures instead. However, absorbable sutures carry the theoretical risk of wound infection. In this study, our aim was to determine whether absorbable sutures are better than non-absorbable sutures in repairing lacerations during the COVID-19 pandemic. The first and second objectives were to assess the rate of infection and the number of postoperative hospital visits. Method(s): A sample of 469 patients with traumatic skin lacerations were analysed during the COVID-19 pandemic in April-July 2020. In the control group, wounds were repaired using non-absorbable sutures, while rapid-onset absorbable sutures were used in the treatment group. By conducting a phone call follow-up after 21 days, several parameters regarding infection signs and hospital visits were compared between both groups. Result(s): No statistically significant difference was observed between both groups regarding wound infection (p-value= 0.623). Using absorbable sutures resulted in fewer postoperative hospital visits than non-absorbable sutures (p-value= 0.001). This study is limited because the assessment of wound infection was subjective to the patient by a phone call follow-up. Conclusion(s): Using absorbable sutures to close traumatic skin lacerations is safe. They should be considered during a pandemic to reduce hospital visits for suture removal, which will subsequently enhance social distancing and relieve hospital load.

Effects of the Covid-19 Pandemic on Primary Education System of Lahore, Pakistan

Background: The pandemic of Covid-19 impeded all socio-economical, pedagogic, and recreational activities. Pakistan is facing an intensified educational crisis due to previous educational differences, so the era of the pandemic has shown difficulties in the educational framework. Aim(s): Awareness among parents and students to combat challenges of pandemic. Method(s): The current study is based on random quantitatively study which gathered data from 300 respondents assembled from different areas of Lahore, Pakistan from June 2020 to July 2021. The responses were collected from students, teachers, and parents that how homeschooling compromises student's physical, psychological, and emotional health. Result(s): About 76% of the students favoured traditional classes over online classes whereas only 20% of the students found the online session interactive. In the other section, only 15.33% of the teachers were satisfied by the online results and they complained about the poor performance and interaction with the students. Overall, 81.67% parents agreed that there is a decline in the physical activity of their children. The results of this study suggested that social distancing and the emerging challenges associated with Covid- 19 have entirely changed the education system that has caused number of problems for children, parents, and teachers in Pakistan. Practical implication: This study highlights pros and cons of online study;such studies give students and teachers a way to prepare for future challenges. Conclusion(s): Considering all outcomes of study, it is highlighted that policy-level interventions were needed, along with well-designed interactive courses. Hence, integrated approaches based on the mental as well as physical capabilities of the students must be executed, and e-tools must also be practiced in traditional classes to fill the gap of homeschooling.Copyright © 2023 Lahore Medical And Dental College. All rights reserved.

Hygiene predictors among COVID-19 screened individuals during the first wave in Mumbai: a cross-sectional survey

Introduction: taught The most important lesson COVID-19 pandemic is basic hygiene practices. It is important to understand hygiene practices among patients during first wave, when meager knowledge about the management of COVID-19 was available. To assess the adopted behavioral practices Objective: and predictors for COVID-19 infection among screened individuals during the 1st wave. A cross- Method: sectional study included COVID-19 screened individuals attending COVID -19 screening OPD at Mumbai. Total 950 participants were interviewed telephonically using convenient sampling method. Logistic regression nanalysis was performed. A total 950 respondents participated, with median age of36 Results: years (range:18yrs to 83 years). Respondents, RTPCR positive or quarantined were 36%. Analysis concludes that practices of having seen or read about hand hygiene, face hygiene, maintaining social distancing, cough etiquettes and enforcement of strict lockdown were significantly associated with lower risk of COVID-19 infection (p value <0.05). Hygiene Practices were followed correctly by more than 50% of this Conclusion: cohort however few individuals were able to answer knowledge related questions correctly. Simple hygiene practices like face hygiene, cough etiquettes, social distancing, strict following of lockdown and having seen or read information on hand washing were predictors of COVID-19 infection. The study highlights the need for quick and rigorous attempts to educate people during a state of a health emergency.

COVID-19 and the family courts: key practitioner findings in children cases

In March 2020, stringent social distancing measures were introduced across England and Wales to reduce the spread of Covid-19. These measures have presented significant challenges for the family justice system. This article sets out the findings of interviews conducted with professionals in the North East of England who have represented or otherwise supported litigants in private and public children proceedings since social distancing measures were introduced. The findings reveal that whilst practitioners are broadly positive about their experiences of shorter non-contested hearings, they nonetheless have concerns about the effectiveness of remote/hybrid hearings in ensuring a fair and just process in lengthy and complex cases. In particular, the findings indicate that the move to remote hearings has exacerbated pre-existing barriers to justice for unrepresented and vulnerable litigants. The aims of this article are not to ‘name and shame' any particular court but to highlight evidence of good practice in the North East of England and provide scope for improving practitioners' and litigants' experiences within current restrictions.

Addressing the Need for Accountability in Public Health

The article calls for the public health community to examine who deter the issuance of deficiently supported recommendations by holding accountable public health officials who promote such recommendations. Topics discussed include advice public health advice that contradicts prevailing scientific evidence, mechanisms for accountability, and the need for self-regulation.

Traffic Impacts of the COVID-19 Pandemic: Statewide Analysis of Social Separation and Activity Restriction

The COVID-19 pandemic resulted in significant social and economic impacts throughout the world. In addition to the health consequences, the impacts on travel behavior have also been sudden and wide ranging. This study describes the drastic changes in human behavior using the analysis of highway volume data as a representation of personal activity and interaction. Same-day traffic volumes for 2019 and 2020 across Florida were analyzed to identify spatial and temporal changes in behavior resulting from the disease or fear of it and statewide directives to limit person-to-person interaction. Compared to similar days in 2019, overall statewide traffic volume dropped by 47.5%. Although decreases were evident across the state, there were also differences between rural and urban areas and between highways and arterials both in terms of the timing and extent. The data and analyses help to demonstrate the early impacts of the pandemic and may be useful for operational and strategic planning of recovery efforts and for dealing with future pandemics.

Tracking the Transit Divide: A Multilevel Modelling Approach of Urban Inequalities and Train Ridership Disparities in Chicago

Using a multilevel modelling approach, this study investigates the impact of urban inequalities on changes to rail ridership across Chicago's "L” stations during the pandemic, the mass vaccination rollout, and the full reopening of the city. Initially believed to have an equal impact, COVID-19 disproportionally impacted the ability of lower socioeconomic status (SES) neighbourhoods' to adhere to non-pharmaceutical interventions: working-from-home and social distancing. We find that "L” stations in predominately Black or African American and Hispanic or Latino neighbourhoods with high industrial land-use recorded the smallest behavioural change. The maintenance of higher public transport use at these stations is likely to have exacerbated existing health inequalities, worsening disparities in users' risk of exposure, infection rates, and mortality rates. This study also finds that the vaccination rollout and city reopening did not significantly increase the number of users at stations in higher vaccinated, higher private vehicle ownership neighbourhoods, even after a year into the pandemic. A better understanding of the spatial and socioeconomic determinants of changes in ridership behaviour is crucial for policymakers in adjusting service routes and frequencies that will sustain reliant neighbourhoods' access to essential services, and to encourage trips at stations which are the most impacted to revert the trend of declining public transport use.