Role of perceived social support in COVID-19 vaccine uptake among U.S. adults

Background Vaccine uptake concerns in the Unites States were at the forefront of public health discussions during the COVID-19 pandemic. By the end of 2022, approximately 80% of the U.S. population was vaccinated against the virus. This study examined the relationship between perceived social support and COVID-19 vaccine uptake among U.S. adults. Methods Using nationally representative cross-sectional data on 21,107 adults from the 2021 National Health Interview Survey, we assessed the COVID-19 vaccination rates across individuals with strong, some, and weak levels of social support. Multivariable logistic regression models were estimated to obtain the odds of being vaccinated in adults with different levels of perceived social support for the full sample and sub-samples of age groups. Results We found that compared to adults with perceived strong social support, adults with weak social support were 21.1% less likely to be vaccinated against COVID-19. Apart from the age 18-24 years group, the lower likelihood of being vaccinated for adults with weak social support was evident in age 24-49 years (AOR=0.66, 95% CI: 0.52-0.85), age 50-64 years (AOR=0.67, 95% CI: 0.50-0.90), and age 65+ years (AOR=0.56, 95% CI: 0.41-0.75) groups. Conclusions These findings are consistent with a broader literature indicating that social support increases the likelihood of healthy behaviors and decreases risky behaviors. Interventions designed to improve the perception of social support, particularly among those at high risk of mortality from COVID-19 may be a promising tactic for increasing COVID-19 vaccine uptake. Graphical Image, graphical

Oversampling techniques for predicting COVID-19 patient length of stay

COVID-19 is a respiratory disease that caused a global pandemic in 2019. It is highly infectious and has the following symptoms: fever or chills, cough, shortness of breath, fatigue, muscle or body aches, headache, the new loss of taste or smell, sore throat, congestion or runny nose, nausea or vomiting, and diarrhea. These symptoms vary in severity;some people with many risk factors have been known to have lengthy hospital stays or die from the disease. In this paper, we analyze patients' electronic health records (EHR) to predict the severity of their COVID-19 infection using the length of stay (LOS) as our measurement of severity. This is an imbalanced classification problem, as many people have a shorter LOS rather than a longer one. To combat this problem, we synthetically create alternate oversampled training data sets. Once we have this oversampled data, we run it through an Artificial Neural Network (ANN), which during training has its hyperparameters tuned by using bayesian optimization. We select the model with the best F1 score and then evaluate it and discuss it. © 2022 IEEE.

Communicating Mental Health Coping Resources Among College Students of Color: A Resilience Approach to COVID-19 Response

The COVID-19 pandemic has disproportionately affected African American college students and put them at high risk of mental health concerns. Guided by the community resilience model, this study examined how Historically Black Colleges and Universities (HBCUs) communicated mental health resources during the COVID-19 pandemic. An analysis of HBCUs' website-based communication showed that mental health received minimal importance in response to the ongoing pandemic. Although larger and advanced degree-granting institutions provided a relatively greater amount of mental health resources than smaller institutions, those resources might not be sufficient to buffer against the COVID-19 induced stressors. Providing such inadequate mental resources indicate that many HBCU institutions were unable to provide a necessary supportive environment for the campus communities. HBCUs may establish formal and informal networks with local and regional mental health support organizations and share resources. Specifically, smaller institutions would benefit from such networked support. Additionally, HBCUs need to prioritize mental health in their response to COVID-19 to promote resilience among the student community. Copyright 2022 Authors.

A Video-based Physiotherapy Exercise Dataset

A patient recovering from a stroke, injury, or physical pain needs continuous physiotherapy and rehabilitation to achieve a quick and complete recovery. It is often difficult for elderly people to visit clinics to undertake exercises. Finding physiotherapists and relevant treatments becomes more difficult, particularly in an epidemic condition like covid-19. AI-driven at-home physiotherapy exercise monitoring and assessment systems can be the straightforward feasible solution in this regard. Accurate recognition of particular exercises, exercise assessments, providing feedback, etc. are parts of the whole system, which a machine typically learns through a data-heavy training process. A key issue in this regard is the lack of specific training data for physiotherapy exercises. There exist only a few datasets in the literature that are designed for physiotherapy exercises;most of them however are based on multiple body sensors or Kinect device. Sensor devices are quite costly, and their availability is not guaranteed everywhere. In contrast, video data can be a better alternative, where video can be acquired easily from an available smartphone camera or desktop/laptop webcam. Addressing this issue, we present a new video-based physiotherapy exercise database containing 1237 video clips of 14 physiotherapy exercises that were carefully elicited from an extensively conducted survey from multiple physiotherapists. Exercises were recorded with 28 male and female subjects within various lighting conditions, camera angles, and camera jitters to simulate the real-world setting. Several machine learning algorithms were utilized to carry out an experimental study on the dataset, and the results are provided for future reference. © 2022 IEEE.

Online Detection of Attentiveness of Students with Special Needs

In this COVID-19 pandemic era, students with Autism Spectrum Disorder (ASD) are struggling to adapt to classes in the online environment using Google Meet or Zoom. Failing to keep sustained attention in the class is a common problem for students with ASD. In face-to-face classes, teachers can track a student's behavior and activity to infer the student's attentiveness level and act accordingly. However, it becomes difficult for a teacher to monitor the attentiveness level of multiple students simultaneously on online platforms like Zoom. Detecting the attentiveness level of a student and notifying the teacher in an automated way can play a crucial role in improving the learning outcome. In this paper, we propose the first deep learning based attentiveness level prediction technique for students with ASD. Our model detects the behavior (e.g., unusual movement, gaze etc.) and activities from real-time videos and uses them as features to classify the attentiveness level as low, mid and high. Existing state-of-the-art techniques to detect the attentiveness level of typically developed students using gaze or facial expression cannot be trivially extended for students with ASD as they do not exhibit regular and consistent behavior. We collect video data belonging to different classes covering various types of activities over a long period, train our classifier, and run extensive experiments to validate the prediction performance. Our solution outperforms existing baselines by a large margin.

Pre and Present COVID-19 Situation: A Framework of Educational Transformation in South Asia Region

This study is designed to support the development of strategies to recover from the disrupted impact of COVID-19 on HE institutes of the South Asian Region (SAR), as the nations in this region are severely cursed by poverty and unemployment. During the unusual phase of the COVID-19 pandemic, the face-to-face learning method is no longer appropriate, and the crisis leads to force on distance learning instead of physical learning. Like all other educational institutions, HE institutions are also in big trouble. Changes in educational structure change the pattern of academic work, which may have an inverse impact on acquiring knowledge and improving skills. Not only students but also a greater number of teachers at the HE institutions required to continue their service through online during this closure period. However, well digital infrastructure and digital contents appear to be the prime requirements for this educational transmission, which are extensively accessible in SAR countries. By following a mixed-methods strategy, the study specifically examines the impact of the pandemic on higher education in the South Asian Region, with an emphasis on the impact on learners, educators, and institutions, and to identify the measures that have been taken by these countries to survive and continue the education system with all the obstacles of the crisis. It concludes with some vital suggestions that may be applied to mitigate the crisis moment and assist in moving forward with more technological advancements for a new future. © 2023 by the authors. Licensee ESJ, Italy.

Human Resource Skill Adjustment in Service Sector: Predicting Dynamic Capability in Post COVID-19 Work Environment

The havoc caused by the COVID-19 pandemic on hospitality businesses across the world affected the human resource skills of the industry to the extent that managers and industry experts are still finding difficult how best to upgrade the skills of their workforce and enhance their capability to withstand future disruptions. It is based on this problem that this research investigated the effect of human resource skill adjustment on the dynamic capability of hospitality businesses in sub-Saharan Africa post the COVID-19 work environment. The study employed cross-sectional survey design with a total population of two hundred and twenty participants drawn from sixty hospitality businesses in the south-eastern part of Nigeria. Formulated research hypotheses were analysed with linear regression. The results of the research demonstrated that human resource skill adjustment predicted the dynamic capability of hospitality businesses. The study concludes that human resource skill adjustment measured with upskilling and reskilling methodologies predicted the dynamic capability. The implication of the finding is that managers and operators of hospitality businesses should implement human resource skill adjustment in all the functional areas of their management to enable each section or department to attain its goals equally, and enhance the dynamic capability of the industry.

Alleviating the click fatigue on clinicians to improve referrals for colorectal cancer screening

Background: The impact of clinician burnout on patient care is pervasive across medical delivery systems. The effects are also felt in preventive care where cancer screening efforts rely on clinician referrals through the electronic medical records (EMRs). Though designed to support healthcare, EMRs are a significant source of clinician burnout given the number of clicks or navigation time needed to refer a patient. This is a barrier to Patient Navigation (PN) when ordered tests do not materialize into screenings or when clinicians order labs/imaging and the pending orders are not created. This causes frustration for all clinical staff involved, delays the workflow processes, and leads to missed opportunities for PN. We implemented an 'order set' intervention to reduce the click burden linked to colorectal cancer (CRC) screening referral among clinicians in South Georgia. Methods: The 'order set' intervention was developed to facilitate PN for a Colorectal Cancer Control Program (CRCCP) aimed at implementing Evidence- Based Interventions to increase CRC screening rates in Georgia. The 'order set' was designed to address workflow issues by consolidating steps associated with CRC screening. This reduced typing input and the need to click between multiple windows within the EMR while making a referral to PN. The intervention was piloted in the Albany Area Primary Health Care (AAPHC) system after modifications were made to the EMR and clinician workflows. The monthly CRC screening rates continue to be generated and tracked post-implementation. Results: The use of the 'order set' reduced the click burden from 78 to 7 inputs and clinician EMR interaction time from 110 seconds to 29 seconds. Providers from 4/7 clinics have adopted the 'order sets' when making referrals for CRC screening. Two clinics provided post-implementation screening data. The pre-implementation screening rates for one clinic were comparable (August = 59.3%, September = 57.6%) to post-implementation (October = 56.3%, November = 56.6%, December = 57.2%), while the second clinic showed some increase (August = 58.6%, September = 60%) vs. (October = 61%, November = 62.1%, December = 62.8%). Conclusions: The 'order sets' intervention reduced the time clinicians spent creating referrals for CRC screening, including fecal immunochemical tests (FIT) and colonoscopies. Additional follow-up and rollout to clinics participating in the program is underway to evaluate further the impact of the order sets on CRC screening outcome and process measures, including qualitative interviews with clinicians. There is significant potential in the application of order sets to various workflow processes to aid in preventative health efforts. Challenges linked to the COVID-19 pandemic and staff turnover affected acquisition of patient referral data.

Novel Lung Targeting Cell Penetrating Peptides as Vectors for Delivery of Therapeutics

Rationale: Cell-penetrating peptides are able to cross membranes and deliver cargoes in a functional form. Our prior work identified a 12-amino acid, cardiac targeting peptide (APWHLSSQYSRT). Studies into its mechanism of transduction led to the identification of two lung targeting peptides (LTPs), S7A and R11A. Here we report on a) the comparative lung uptake of S7A versus R11A, b) complete biodistribution of R11A, c) show that cyclic versions are -100-fold more efficient than linear counterparts, d) uptake is via a non-endocytic pathway, and e) cyclic R11A's (cR11A) ability to deliver siRNA targeting structural proteins of SARS-CoV-2 and act as an anti-viral. Methods: Linear LTPs were synthesized with N-terminal labeled with Cyanine 5.5 (Cy5.5). Cyclic versions were synthesized with lysine added to the N-terminus, cyclized through a peptide bond, with a side NH-group labeled with Cy5.5. cR11A was conjugated to siRNA duplexes via a DTME linker. Wild-type, CD1 mice, were injected with S7A or R11A at 10, 5, and 1mg/Kg, peptides allowed to circulate for 15mins, mice euthanized, lung along with multiple other organs dissected and imaged using In Vivo Imaging Systems (IVIS, Perkin-Elmer) followed by confocal microscopy. CD1 mice were injected with R11A, 5mg/Kg, and euthanized at different time intervals for biodistribution studies. Endocytosis studies were done using serum-starved human bronchial epithelial cells (HBEC) incubated with fluorescently labeled transferrin and LTP-S7A or LTP- R11A. Lastly, anti-viral activity was tested in HBECs pre-treated with cR11A-siRNA followed by viral infection. Results: Mice injected with LTP-S7A or LTP-R11A showed robust uptake of the peptides by lung tissue, with R11A showing an increasingly favorable lung:liver ratio with decreasing dose. Lung uptake of R11A peaked at 120mins with complete dissipation of fluorescence by 24 hours. In Vitro studies in HBECs showed no co-localization of transferrin with LTPs, ruling out endocytosis as a mechanism of uptake. Comparison of linear versus cyclic peptides using FACS showed cyclic peptides had -100-fold increased transduction efficiency over their linear counterparts. cR11A conjugated to ant-spike, and anti-envelop proteins showed an anti-viral effect with EC90 of 0.6uM and 1.0μM, respectively. Conclusions: We have identified two novel lung-targeting peptides capable of acting as delivery vectors. Peak uptake of R11A occurred at 120mins. Furthermore, this uptake was not via endocytosis, and cyclic versions were -100-fold more efficiently taken up. Lastly, as proof of concept, we show cR11A acts as a vector and delivers siRNA to HBECs in a functional form, and act as anti-virals.

Food Insecurity, Dietary Diversity, and Coping Strategies in Jordan during the COVID-19 Pandemic: A Cross-Sectional Study.

The 2019 coronavirus disease (COVID-19) is an emerging respiratory infection with severe impacts on the nutritional status of the worldwide population. This cross-sectional study was conducted to assess the food insecurity, dietary diversity, and food-related coping strategies in Jordan during the pandemic using an online, self-administered questionnaire. Among the 740 adults who completed the survey, the prevalence of food security was 84.1%, whereas 2% and 13.9% were moderately and severely food-insecure, respectively. The determinants of food insecurity were educational level, monthly income, marital status, availability of health insurance, and type of residence. In addition, food insecurity was significantly higher among the participants who consumed two or fewer meals per day (p = 0.015). Moreover, an acceptable food consumption score was shown among 76.2% of the participants, and the remaining participants were at borderline (14.1%) or had poor scores (9.7%), with a significant association between food insecurity and food consumption scores (p < 0.001). The food-related coping strategies studied were significantly associated with food insecurity at both levels (p < 0.001) and were more evident in the severely food-insecure group. These findings highlight the adverse effects of COVID-19 restrictions on nutritional status, especially among food-insecure households, which might reduce food accessibility due to economic difficulties.

Crisis communication and learning: The US higher education's response to a global pandemic

Purpose This study investigates the processes that the US universities and colleges used to learn during the COVID-19 pandemic and the factors that facilitated and impeded their learning processes. Design/methodology/approach To address this study's research questions, this study used a crisis communication and learning lens to interview crisis response team members from 30 US higher education institutions in May 2020 (the first pandemic semester). In October 2020 (the second pandemic semester), this study conducted follow-up interviews with 25 of the original interviewees. Overall, this study conducted 55 interviews. Findings Learning during the COVID-19 pandemic is facilitated by a recognition of a serious deficiency in the current system and impeded by the need to act quickly. The findings demonstrate the process by which decisions, actions and strategies emerged during crises. Originality/value This investigation illustrates how crises can prompt organizational learning while demonstrating the critical role of internal and external resources in the learning process.

Behavioral intention and continued adoption of Facebook: An exploratory study of graduate students in Bangladesh during the Covid-19 pandemic

Behavioral intention and continued adoption of Facebook: An exploratory study of graduate students in Bangladesh during the Covid-19 pandemicThis study is designed to find out the fundamental reasons for students’ social media adoption during the Covid 19 epidemic in Bangladesh. The research object is to build a perceptual picture of the factors that will encourage and impact Facebook’s continued acceptance during this crisis. The sample was taken from 400 students from different universities in Bangladesh. Nine indicators (Trust, Perceived Usefulness, Privacy, Perceived Ease of Use, Subjective Norms, Educational Compatibility, Behavioral Intention, Personal Needs, and Continued Facebook Adoption) were used to experiment. The study results show that the fit indices of measurement model (fit /df = 1.436;GFI = 0.958;AGFI = 0.960;NFI = 0.947;CFI = 0.977;TLI = 0.978;SRMR = 0.031;RMSEA = 0.027;P-close = 1.00) are suitable and appropriate within their prescribed ranges. The mean, standard deviation, internal consistency (Cronbach Alpha > 0.7), composite reliability (CR > 0.8), and average variance extracted (AVE > 0.5) of each constructs are well and appropriate their recommended level which determine the designs of validity. The coefficient of all factors like Trust (0.29), Perceived Usefulness (0.19), Privacy (0.17), Perceived Ease of Use (0.26), Educational Compatibility (0.13), Behavioral Intention (0.45), Personal Needs (0.16), except subjective norms (0.01) have a meaningful and positive effect on the behavioral intention of Facebook that satisfactorily affects continued adoption behavior during covid-19. These observations illustrate the scientific rationale and views relevant to emerging economies like Bangladesh in the context of social media. Several implications have been presented based on the results.

Routine blood report and common laboratory parameters in COVID-19: Experience from Bangladesh

Background: The present study aimed to describe the association of hematological parameters and common clinico-epidemiological features wit hdisease severity among COVID-19 patients. Methods: This is a hospital based observational study done in Dhaka Medical College Hospital from 01 July 2020 to 15 September 2020. Findings from hematological tests along with patient clinic-pathological features were recorded from a total of 309 COVID-19 patients. All the data were analyzed by SPSS 23.0 software. Results: Among the studied hematological parameters hemoglobin percentage, total WBC count, lymphocyte percentage, platelet count, CRP, serum ferritin, d-dimer, and ESRwere significantly associated with disease severity (p<0.05). Association was found between disease severity and other biochemical markers, such as AST, ALT, LDH, and serum bilirubin. Conclusion: With limited resources these cheap, yet highly indicative biochemical markers could be used to assess, treat, and prognose COVID-19 patients in Bangladesh.

Factors associated with SARS-CoV-2 infection amongst healthcare workers in a COVID-19 designated hospital.

BACKGROUND: Understanding the risk factors responsible for the increased infection among HCWs can mitigate the transmission of COVID-19 among HCWs and patients alike. The aim of this study is to evaluate factors associated with SARS-CoV-2 infection among healthcare Workers. METHODS: Healthcare workers and hospital administrators were asked to participate in this cross-sectional survey study that was conducted in Jaber Al Ahmad Hospital (JAH) between August to October 2020. Participants were invited to undergo SARS-CoV-2-specific antibody testing and to complete a questionnaire targeted to factors that may be associated with acquisition of SARS-CoV-2. Descriptive analysis and multivariate logistic regression were done. RESULTS: 847 healthcare workers participated in the study and 20.5% of them had previous SARS-CoV-2 infection. The average age of participants was 35.7 years (SD = 7.9); 52.4% were female, and 55.8% were doctors. Multivariate analysis showed that working as a nurse (adjusted OR 1.77, 95% CI = 1.15, 2.71), and wearing gloves (adjusted OR 2.93, 95% CI = 1.19, 7.22) were significantly associated with an increased likelihood of contracting SARS-CoV-2 infection while controlling for other factors. Most personal protective equipment (PPE) were reported to be available always or most of the time, with the least available PPE item being coveralls (74.4%). CONCLUSIONS: After adjusting for confounding factors, being a nurse and prolonged glove use were associated with increased likelihood of SARS-CoV-2 infection. Prospective cohort studies are required to further elucidate the reasons for our findings in order to minimize the transmission of infection among healthcare workers.

Respiratory droplet resuspension near surfaces: Modeling and analysis

Knowing the environmental spreading pathway of COVID-19 is crucial for improving safety practices, particularly for health care workers who are more susceptible to exposure. This paper focuses on the possible secondary transmission due to resuspension of virus-laden droplets from common surfaces, which several studies have shown to be possible under external disturbances. Such disturbances could be body motion during walking, running, clothes removal, or airflow in the environment. In this paper, a three-dimensional two-phase model is utilized to study respiratory droplet resuspension dynamics on various surfaces due to sudden agitation. The velocity range and variation during walking, surgical glove removal, and dropping an object are studied experimentally. A parametric study is performed to characterize the effects of droplet size and surface wettability on the minimum initial droplet velocity required for detachment from surfaces. The results are reported as average droplet velocity during the detachment process, total detachment time, and detached droplet volume. The obtained results indicate that respiratory droplets larger than 200 μm can detach from typical surfaces due to normal daily activities. Droplets are partially separated from hydrophilic surfaces with contact angle Furthermore, the minimum initial droplet velocity to induce the resuspension depends on the droplet size. Droplet velocity immediately after detachment is a function of droplet size, initial droplet velocity, and surface wettability. Bigger droplets have larger detached volume percentage as well as higher velocity after detachment compared to smaller droplets. Finally, a higher initial velocity is needed to separate droplets from hydrophilic surfaces as compared to hydrophobic surfaces. In accordance with the results, the droplet minimum initial velocity to cause detachment is 2 m s−1, while our experiments show that surface velocity can reach up to 3 m s−1 during normal human activities. We also develop an analytical model to predict the required kinetic energy to detach droplets from different surfaces, which is in good agreement with numerical results. The mechanism of droplet detachment is dictated by a competition between droplet kinetic energy induced by surface motion and surface energy due to droplet-surface interaction as well as droplet-vapor and surface-vapor interactions. We believe that the results of this fundamental study can potentially be used to suggest proper surface wettability and safe motion that reduce respiratory droplet resuspension from various surfaces. © 2021 Author(s).

Association of ABO blood groups with presentation and outcomes of confirmed SARS CoV-2 infection: A prospective study in the largest COVID-19 dedicated hospital in Bangladesh.

BACKGROUND: Globally, studies have shown conflicting results regarding the association of blood groups with SARS CoV-2 infection. OBJECTIVE: To observe the association between ABO blood groups and the presentation and outcomes of confirmed COVID-19 cases. DESIGN, SETTING, AND PARTICIPANTS: This was a prospective cohort study of patients with mild-to-moderately severe COVID-19 infections who presented in the COVID-19 unit of Dhaka Medical College Hospital and were enrolled between 01 June and 25 August, 2020. Patients were followed up for at least 30 days after disease onset. We grouped participants with A-positive and A-negative blood groups into group I and participants with other blood groups into group II. RESULTS: The cohort included 438 patients; 52 patients were lost to follow-up, five died, and 381 completed the study. The prevalence of blood group A [144 (32.9%)] was significantly higher among COVID-19 patients than in the general population (p < 0.001). The presenting age [mean (SD)] of group I [42.1 (14.5)] was higher than that of group II [38.8 (12.4), p = 0.014]. Sex (p = 0.23) and co-morbidity (hypertension, p = 0.34; diabetes, p = 0.13) did not differ between the patients in groups I and II. No differences were observed regarding important presenting symptoms, including fever (p = 0.72), cough (p = 0.69), and respiratory distress (p = 0.09). There was no significant difference in the median duration of symptoms in the two group (12 days), and conversion to the next level of severity was observed in 26 (20.6%) and 36 patients (13.8%) in group I and II, respectively. However, persistent positivity of RT-PCR at 14 days of initial positivity was more frequent among the patients in group I [24 (19%)] than among those in group II [29 (11.1%)]. CONCLUSIONS: The prevalence of blood group A was higher among COVID-19 patients. Although ABO blood groups were not associated with the presentation or recovery period of COVID-19, patients with blood group A had delayed seroconversion.

A Web-Based System for Efficient Contact Tracing Query in a Large Spatio-Temporal Database

In this demonstration, we present a web based system for the novel contact tracing query (CTQ) that finds users who have come into direct contact with the query user or indirect contact via the already contacted users from a large spatio-temporal database. The CTQ is of paramount importance in the era of new COVID-19 pandemic world for identifying people who came into close spatial and temporal proximity with persons carrying an infectious disease. We demonstrate a multi-level index named QzR-tree, that considers the space coverage and the co-visiting patterns of the trajectories to group users who are likely to meet. More specifically, we use a quadtree to partition user movement traces along with a linear ordering and use the space-time mapping to group users with an R-tree. We develop a web-based demo system to show the effectiveness of the QzR-tree for the CTQ. The web-based system essentially uses a PostgreSQL database to store user trajectories, and indexes these trajectories using the QzR-tree, and finally uses a web interface to take user query and display the results in a map. © 2020 Owner/Author.