COVID-19 in Mass Media: Manufacturing Mass Perceptions of the Virus among Older Adults

According to the latest The Global Risks Report (2022) of World Economic Forum, the large-scale coronavirus disease 2019 (COVID-19) threat creates various tensions that might lead to unexpected cascading impacts in various domains. Nevertheless, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, about 120 nm in diameter, remains invisible to people whose cognition, emotions, and health-related behaviors are driven primarily by the subjective perception of the virus. Mass media communicating information, symbols, beliefs, and codes of conduct to the population contribute widely to the socially constructed representations of the new SARS-CoV-2 virus. Thus, the aim of the current research is to investigate the impacts of the common COVID-19 mass media image of the "ball with spikes"representing the SARS-CoV-2 virus on older adults particularly vulnerable to the COVID-19 coronavirus disease and fake news dissemination. This research is based on an innovative mixed-methods research design that combines questionnaires (N = 144), semi-structured research interviews, and pictographic measures (N = 26). The primary results demonstrate that individuals' perceptions of and emotional reactions to the invisible SARS-CoV-2 virus are shaped by mass media exposure, as the "ball with spikes"became a familiar symbol of the COVID-19 virus, marked by the symbolism of dangerousness and mystery with a divisive aesthetic. The current research that aims to highlight the role of mass media as the vector of an icon image of the new SARS-CoV-2 virus provides additional elements that may contribute to improved crisis management effectiveness of future pandemic outbreaks. © 2023 the author(s), published by De Gruyter.

Covid-19 Infection Segmentation Using Deep Learning Techniques

The rapid spread of the disease after COVID-19's emergence in 2019 has presented enormous problems to medical institutions. The diagnosis process will go more rapidly if the infected region in the COVID-19 CT image can be automatically segmented, which will aid clinicians in promptly identifying the patient's illness. Automated lung infection identification using computed tomography scans is a more general approach. However, segmenting sick areas from CT slices is quite difficult. In this work, a diagnosis system based on deep learning methods is being created to identify and quantify COVID-19 infection and screen for pneumonia using CT imaging. Here, Unet++ approaches, U-net architecture based on CNN encoder and CNN decoder, and Attention Unet segmentation techniques are used. These methods are applied for quick and accurate picture segmentation to produce segmentation models for lung and infection. Fourfold cross-validation has been used as a re-sampling method to improve skill estimate on unseen data. To enable volume ratio calculating and determine infection rate, the lung and infection volumes have been reconfigured. 20 CT scan cases were used in this study, and the data were split into two, training dataset 70% and a validation dataset 30%. In this study with three architectures it shows that basic Unet performs well compared to other two architectures. © 2022 IEEE

Ensuring safety from COVID-19 in arthroscopic surgery

In the current time of coronavirus disease-2019 (COVID-19) pandemic, orthopedic procedures have been shelved and guidelines to establish the safety of medical professionals and patients are still evolving. Although sports injuries are not life threatening, a spectrum of these injuries requires urgent intervention. To ensure the safety of medical professionals and patients of sports injuries in COVID times, the following guidelines are suggested. Such surgery needs to be performed only in COVID-free facility (green zone). Patients from red zone and containment zone should be avoided. Young, fit individuals without medical comorbidities should be considered. Wherever possible, regional anesthesia should be used. As COVID virus is present in all body fluids, aerosol generation (coughing, sneezing, intubation, use of power instruments, and cautery) should be minimized. Operation theater (OT) should be fumigated on the prior night and ideally between the cases. The number of cases per OT should be kept under three to get adequate time in-between for sterilization. The ventilation setup of OT should be negative pressure in addition to positive pressure. If there are hindrances in setting up negative pressure, a simple exhaust can be added to the existing setup. The ventilation system should ideally provide more than 20 air changes per hour. During surgery, movement of doors of OT and OT personnel should be minimal so as to minimize the air turbulence and eddy current. This will reduce the risk of infection. Surgical team should wear personal protective equipment (PPE) and helmet hood to reduce the chances of respiratory droplet infection. The doffing of helmet and PPE should be done with utmost care and should be discarded in a chloro-derivate solution. The motorized drill used for surgical procedure should be used at low revolution per minute (RPM). Usage of sterile transparent polythene hood while irrigating during drilling and sequential drilling will help in minimizing aerosol generation. Spillage of arthroscopic fluid should be avoided at all times. These basic norms will minimize the chance of accidental spread of COVID.

Telemedicine-Rehabilitation and Virtual Reality in Orthopaedics and Sports Medicine.

Introduction: Tele-rehabilitation is a method of delivering rehabilitation services using information, technology and communication to everyone, irrespective of their geographic location. National zeal for competitive sports and COVID pandemic has led to an increase in its demand and popularity worldwide. The athletes need immediate treatment and correct rehabilitation to keep them in their game. This review aims to bring into perspective the importance of telemedicine and telerehabilitation in orthopaedics and sports medicine with a focus on virtual reality. Methods: Articles were searched based on suitable keywords 'telemedicine', 'telerehabilitation' 'orthopedics', 'orthopaedics', 'sports' and 'India*' which were combined using suitable boolean operators in PubMed, Scopus and Web of Science. Government guidelines and laws were also reviewed in view of telehealth and telemedicine. Conclusion: Tele-rehabilitation and virtual physical therapy are innovative and cost-effective ways to provide the best rehabilitative services to the patients at their doorstep. Virtual reality should be incorporated into the Indian telehealth delivering system with a special focus on the remote athlete population.

Capsule Networks with Chest X-Ray Enhancement for Detection of COVID-19

Corona virus was declared a global pandemic that has affected people worldwide. It is critical to diagnose corona virus-infected individuals to restrict the virus's transmission. Recent research indicates that radiological methods provide valuable information in identifying infection using deep learning algorithms. Deep learning has contributed to large-scale medical data research, providing new ways and chances for diagnostic tools. This research attempted to investigate how the Capsule Networks leverage chest X-ray scans to identify the infected person. We suggest Capsule Networks identify the illness using chest X-ray data. The proposed approach is rapid and robust, classifying scans into COVID-19, No Findings, or any other issue in the lungs. The study can be used as a preliminary diagnosis by medical practitioners, and the study focuses on the COVID-19 class, a minority class in all public data sets accessible, and ensures that no COVID-19 infected individual is identified as Normal. Even with a small dataset, the model provides 96.37% accuracy for COVID-19 and for the non-COVID-19, and on multi-class classification, it provides an accuracy of 95.12%. © 2022 IEEE.

Stunted Growth of Employment in MSME

The MSMEs in India constitute roughly 98% as micro enterprises and hardly 1% as medium enterprises. During COVID, it was observed that the MSMEs in India were in financial distressand the MSMEs roughly around 45lacs linked to the bank were given working capital up to Rs3 lac crores. But some of them could not extended their financial assistance as they must have not been seriously affected. It is on record that roughly 60 lacs MSMEs have been closed down because of the non-availability of financial assistance. Which they needed after the reopening started. The unemployment rate for the semi-skilled workers in the age group of 18 to 25 is very-very alarming. Unless there is a proper main streaming of the MSMEs, the struggle of MSMEs will appears to be continuing for long. Of late, the government has revised the policy of special economic zones. Which were expected to contribute towards export. But they couldnot enhance the SEZ in any state where they are located can contribute in the domestic production. The Government is facing difficulty in deciding a policy by which the global supply chain could be strengthen and the companies leaving china could also be attracted in India. The paper has pointed out that the manufacturing in India is not so healthy because of complication in labour laws, cost reducing logistics and the hassle full environment in customs.In case these issue are tackled on piecemeal basis the result cannot be so cherish able. But in case the states like Rajasthan and Chhattisgarh, they developed their own policy and indulge in appropriate reforms of labour. The result can be favourable and the issue of employment will be taken as solved. © 2022

Coronavirus Detection Using Computer Vision

The coronavirus disease (COVID-19) also known as SARS-Cov-2 has largely impacted the entire globe physically, economically, and psychologically. The detection of the virus in early stages is extremely crucial for faster recovery in patients and curbing its spread as its nature is highly contagious. Although several techniques are present today for the detection of coronavirus, they are laborious in nature, costly, require experts from medical science, and the accuracy is questionable in some of the traditional methods. This brings the need to search for a faster and reliable technique. Computer vision produced remarkable results in predicting the onset of various diseases, and the use of machine learning in healthcare has increased tremendously owing to the fast speed and high accuracy of results with minimal human intervention. Hence, this research paper aims to develop a computer vision-based artificial intelligence model that can predict the occurrence of coronavirus using electron microscopic images of the samples. In order to achieve the goal, YOLO v3 object detection algorithm using non-maxima suppression is used to classify whether a particular sample has coronavirus or not. It is proved that the proposed algorithm works faster than existing methodologies with considerably higher accuracy for detection of coronavirus. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Third Wave Prediction Analysis for Kerala in India

COVID-19 is spreading widely across the globe right now. India just went through the second wave of COVID-19 pandemic and has lost more than 425,000 people to this pandemic till date. Most of the other countries have gone through the second wave, with some countries experiencing third and fourth waves. In such difficult times, there is a shortage of resources everywhere. Planning is the need of the hour, and all the countries are expanding their resources, keeping future demands in mind. Some of the states of India, like Kerala, are also expecting imminent danger of the third wave. In this study, we are predicting the arrival and peak of the third wave in Kerala. We also provide the mathematical models and theoretical background to reach such expected dates. Prediction of this type helps to suggest the preparation needed to tackle the upcoming disaster. Governments can prepare themselves so that there is minimal damage to life in future. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

In silico screening of phytochemicals as potential inhibitors of sars-cov-2 mpro and human ace-2

Background and Objective: An enzyme that inhibits the receptor could make it more difficult for coronavirus to reach cells. The key protease necessary for coronavirus proteolytic maturation is the recognized coronavirus 3-chymotrypsin-like protease 3CLpro, also known as Mpro. This Mpro is needed for immune control and the cleavage of the polyproteins pp1a and pp1ab, making it a promising target for anti-COVID-19 drugs. As a result, inhibiting the Mpro enzyme inhibits viral maturation. Bioactive constituents obtained from some selected indigenous plants of India, which have been reported to have antiviral potential, were subjected to virtual screening against ACE-2 and Mpro in the current study. Materials and Methods: Cresset's Flare 4.0 was used to establish the 3-D structure of all the compounds. Complete optimizations of these constructed structures were carried out. While performing the minimization, the spin state of the wave function was set to the singlet and standard SCF convergence was used for optimization, all other parameters were left at their default values. The Protein Data Bank (https://www.rcsb.org) was used to download the 3-D structures of Mpro from COVID-19 (PDB ID 6LU7) and ACE-2 receptor from Human (PDB ID 1R4L). Results: The findings show that these phytochemicals can bind to ACE-2 and Mpro more effectively as compared to reference compounds and act as inhibitors. Conclusion: The findings of virtual screening of these bioactive constituents revealed that most of them are more active than the reference compounds. Therefore, they could be used to produce antiviral drugs against Coronavirus in the future.

Characteristics of mild to moderate COVID-19 infection from an urban ambulatory COVID-19 clinic-a guide to triage patients in the clinic

Introduction:Since the start of the pandemic, COVID-19 has spread rapidly. It presents with flu-like symptoms and can cause serious complications in high-risk individuals. Here, we discuss the presentation of COVID-19 infection in an ambulatory setting. Method:Data was collected from all patients who visited the COVID-19 clinic from 03/11/2020- 06/14/2020. Testing was done based on the CDC guidelines at the time using a PCR method. Medical records were reviewed and captured on a RedCap database. Statistical analysis was performed using both univariate and bivariate analysis using Fischer's exact test with 2-sided p values. All analyses were done in person with a high predictive valve per CDC guidelines for testing, and not in general population. Results:Of the 2471 total evaluated patients, 846 (34.2%) were positive for COVID-19. The mean age was 43.4 years (SD+/-15.4), 60.1% were female and 48.4% were Black. There was known exposure to COVID-19 in 58.7% of all people tested, and amongst those with exposure, 33.3% were positive. Hospitalization occurred in 101 patients (11.1%), with a median number of days from testing to hospitalization of 2 (range 0-25) and the median length of stay of 6 days (range 1-51). A total of 22 patients (23.4% of hospitalized patients) required ICU admission and 10 patients died. The overall death rate of patients presenting to COVID clinic was 0.4%, or 1.2% amongst those who tested positive. When compared to patients without COVID-19 infection, the symptoms significantly associated with COVID-19 positivity included anosmia, subjective fever, change in taste, anorexia, objective fever, myalgias, cough, chills and fatigue (Figure 1). No significant differences were noted in other presenting symptoms and vital signs. An increased risk for COVID-19 infection was seen in diabetics [OR 1.39, CI1.09-1.77]. Whereas, individuals with lung disease, asthma and malignancy were not associated with increased risk of COVID-19 infection. No statistically significant association with COVID-19 infection was found in individuals with hypertension, heart failure, COPD, HIV, CKD, ESRD and immunocompromised state. Discussion:Blacks and females had the highest infection rates. Most patients with mild to moderate disease did not require hospitalization. The hospitalization rate was 11.1%, while the death rate for patients who visited COVID-19 clinic was <1%. This suggests there is a broad gap in mortality of those who are very ill and require hospitalization to those who remain ambulatory. The above data could assist health care professionals perform a targeted review of systems and co-morbidities, allowing for appropriate patient triage.

Recent diagnostic techniques for COVID-19

An outbreak of coronavirus pneumonia was firstly documented in Wuhan, Hubei Province, China (December 2019), with an indication of human-to-human transmission. The causative agent identified for coronavirus disease 2019 (COVID-19) is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). America, Italy, India, and Africa became new venues of COVID infection;the overall data of patients and death is increasing day by day. Generally inplace of most of the infected people develop respiratory symptoms (throat pain, cough, etc.), fever, and chest opacity on CT scan and X-ray. A few numbers of suspected persons are found asymptomatic;they may serve as carriers for infection. As a point of care, the patient diagnosis is compulsory, and only the diagnosis can provide a real-time condition of patients and can be helpful in arresting the spreading of the infection. In the present chapter, we focused on illustrating various diagnostic techniques that have been employed by the world for the detection of the coronavirus. The diagnostic techniques are categorized into molecular and serologic assay techniques. The nucleic acid is detected in molecular assay, whereas the serologic assay uses antigen-antibody reaction. © Springer Nature Switzerland AG 2021.

Healthcare workers with COVID-19 infection: Experience from a designated COVID-19 clinic

Background: Healthcare workers (HCW) are at the frontline of the COVID- 19 pandemic, risking infection through hospital contacts. Data regarding predisposing factors in the healthcare field is limited. In this study, we characterized presenting symptoms, occupation and hospitalizations for HCW who tested COVID-19 positive. Methods: This is a retrospective study of HCW who presented for screening to a designated COVID-19 clinic at the largest hospital in Washington, DC between 3/13/20 - 5/28/20. Variables extracted included profession, exposure, presenting symptoms, past medical history and outcomes. Univariate analysis was performed using Fischer's exact tests, with significance defined as p < 0.05. IRB approval was obtained. Results: There were a total of 881 HCW who presented for COVID-19 testing: 316 (35.8%) tested positive;216 (68.4%) were female, mean age was 39. Cough was the most common presenting symptom (92.7%), followed by subjective fever (63.3%), myalgia (57.9%), and chills (46.8%)(Fig 1). RNs [110 (34.8%)] and physicians [39 (12.3%)] accounted for nearly 50% of cases. Hospitalizations occurred in 22(6.9%);2(0.6%) died from COVID-19. See Fig 2 for symptoms associated with hospitalizations. African Americans (OR 4.52, CI95 1.54-12.50), and those with hypertension (3.14, 1.32-7.23) and obesity (2.98, 1.25-6.89) were more likely to be hospitalized. Conclusion: HCW remain at risk for COVID-19 infection with respiratory and constitutional symptoms as the most common presentation. RNs were among the most affected. This study supports other reports that African Americans and those with pre-existing comorbidities have greater morbidity with COVID-19 - we have documented that these inequities are also prevalent amongst HCW. This should be considered when testing for and implementing practices to avoid risk of COVID-19 among HCW. (Figure Presented).

Genomic variations of sars-cov-2 and effect of various factors on covid-19

Introduction: COVID-19 (SARS-CoV-2) is a disease caused by the newly discovered novel Coronavirus. The first case of SARS-CoV-2 was reported in Wuhan, China in December 2019 which later turned out pandemic affecting large population across the world till now. Aim: This study aimed to review morphological differences of SARS-CoV-2 with other viruses belongs to beta coronaviruses and to analyze the effect of various factors on the spread of disease. Conclusion: SARS-CoV-2 causes a severe acute respiratory illness with morbidity rate up to 3%. Despite 79% similarity with SARS-CoV, key differences have been observed in spike glycoprotein, 2 accessory proteins and 2 non-structural proteins (nsp). High transmissibility of SARS-CoV-2 across the globe may be associated with these genetic differences. However, geographical differences in cases also suggest the influence of natural immunity, climatic conditions on disease spread. Unavailability of an effective vaccine and antiviral therapy left only social distancing and lockdown as an option to minimize disease spread. Further investigations are needed to know the mode of transmission, resistance to environmental factors. The developments of vaccine for SARS-CoV-2 in many countries are in Phase II & III of clinical trial whereas many drugs have been repurposed to check their efficacy in combating SARS-CoV-2 infections. . © IJCRR.