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1.
Brain ; 2022.
Article in English | PubMed | ID: covidwho-2017745

ABSTRACT

Different neurological manifestations of COVID-19 in adults and children and their impact have not been well characterized. We aimed to determine the prevalence of neurological manifestations and in-hospital complications among hospitalized COVID-19 patients and ascertain differences between adults and children. We conducted a prospective multicenter observational study using the International Severe Acute Respiratory and emerging Infection Consortium cohort across 1507 sites worldwide from January/30th/2020 to May/25th/2021. Analyses of neurological manifestations and neurological complications considered unadjusted prevalence estimates for predefined patient subgroups, and adjusted estimates as a function of patient age and time of hospitalization using generalized linear models. Overall, 161,239 patients (158,267 adults;2,972 children) hospitalized with COVID-19 and assessed for neurological manifestations and complications were included. In adults and children, the most frequent neurological manifestations at admission were fatigue (adults: 37.4%;children: 20.4%), altered consciousness (20.9%;6.8%), myalgia (16.9%;7.6%), dysgeusia (7.4%;1.9%), anosmia (6.0%;2.2%), and seizure (1.1%;5.2%). In adults, the most frequent in-hospital neurological complications were stroke (1.5%), seizure (1%), and central nervous system (CNS) infection (0.2%). Each occurred more frequently in ICU than in non-ICU patients. In children, seizure was the only neurological complication to occur more frequently in ICU vs. non-ICU (7.1% vs. 2.3%, P < .001). Stroke prevalence increased with increasing age, while CNS infection and seizure steadily decreased with age. There was a dramatic decrease in stroke over time during the pandemic. Hypertension, chronic neurological disease, and the use of extracorporeal membrane oxygenation were associated with increased risk of stroke. Altered consciousness was associated with CNS infection, seizure, and stroke. All in-hospital neurological complications were associated with increased odds of death. The likelihood of death rose with increasing age, especially after 25 years of age. In conclusion, adults and children have different neurological manifestations and in-hospital complications associated with COVID-19. Stroke risk increased with increasing age, while CNS infection and seizure risk decreased with age.

2.
Current Medical Issues ; 20(3):172-176, 2022.
Article in English | EMBASE | ID: covidwho-2010409

ABSTRACT

Background: N95 respirators have prevented transmission among health-care workers during the COVID-19 pandemic. During times of intense shortage of respirators and border closures during the pandemic, re-use strategies with available decontamination methods were necessitated. This in-house experimental study evaluated the effect of hydrogen peroxide gas-plasma sterilization on respirators and helped establish an evidence-based protocol for their re-use in a resource-poor setting. Materials and Methods: A three-dimensional experimental model using saline nebulization as the aerosol exposure and a particle counter to measure the filtration of particles through the mask pre- and post-sterilization was used. Multiple cycles of plasma sterilization were done till the physical integrity/fit was lost. Total filtration volume was used as a surrogate marker to assess the filtration efficiency (FE). Results: The total volume of particles filtered on a 3M respirator was 99.9%. Unused Halyard and Venus respirators were compared against 3M and found to have FE of 99.9% and 60.5%, respectively. After repeated sterilization cycles, the total volume of particles filtered was 59.3% for Halyard in the seventh cycle and 36.2% for Venus in the fifth cycle. When the physical integrity and fit was tested, the appropriate fit was lost after eight cycles of sterilization for Venus and was not lost for Halyard even after the tenth cycle. Conclusion: This low-cost experimental study helped implement an effective and safe decontamination strategy for safe re-use of N95 respirators in an emergent situation with no access to commercial testing in a resource poor health-care setting during the pandemic.

3.
Indian Journal of Critical Care Medicine ; 26:S94, 2022.
Article in English | EMBASE | ID: covidwho-2006381

ABSTRACT

Aim and background: COVID-19 was a new disease-causing a pandemic and hence generated uncertainty, and a great deal of anxiety with regard to appropriate therapeutic interventions. Many treatment regimens were tried with no evidence supporting the same. Critical and fatal COVID-19 due to immune dysregulation results in severe inflammation or a cytokine storm with markedly elevated pro-inflammatory cytokines like interleukin-6 (IL-6). Tocilizumab, an IL-6 receptor antagonist, is reported to prevent disease progression. However, since this is an expensive intervention, it is important that evidence is reviewed systematically regarding its utility. The India COVID guidelines is a group of experts and methodologists who came together to use a process of evidence synthesis to inform treatment guidelines using an evidence to decision framework (www.indiacovidguidelines.org). We report the data regarding tocilizumab in severe to critical COVID-19 infection. Objectives: To assess the efficacy and safety of tocilizumab in patients with COVID-19. Materials and methods: Search methods: We performed a systematic search till 15.10.2021 of the following databases: Pubmed, WHO ICTRP, L.OVE platform, Cochrane library, and COVID-NMA. Selection criteria: We selected only randomised controlled trials (RCT) evaluating tocilizumab use in COVID-19. Data collection and analysis: Two review authors independently screened and identified studies using Rayyan, did a risk of bias assessment using the Cochrane ROB 2 tool and extracted numerical data from studies for outcomes like all-cause mortality, disease progression, clinical improvement, and adverse events. Meta-analysis was performed using Review Manager 5.4. I2 statistics were used to measure residual heterogeneity. Certainty of evidence was evaluated using GRADE methodology. A group of experts then used the WHO evidence to decision framework to judge values and preferences, and a recommendation for tocilizumab applicable to a lower-middle-income country was generated. Results: Our search retrieved 1408 s from various databases. Twenty-three RCTs were included in this systematic review with 10,583 participants. All participants were hospitalised adults with moderate to severe disease with an average age of 54-65 years. Median C-reactive protein was ≥ 100 mg/L indicating significant systemic inflammation. Prevalence of comorbidities varied and tocilizumab was initiated in rapidly worsening patients within 24-48 hours of admission to intensive care in most trials. More than 80% of participants were administered corticosteroids. Tocilizumabtreated patients showed a significant reduction in mortality with RR 0.88 (95% CI 0.81, 0.94) and reduced disease progression with RR 0.87 (95% CI 0.72, 1.06) with moderate certainty of the evidence, increased clinical improvement with RR 1.04 (95% CI 1.00, 1.09), and reduced time to clinical improvement with HR 1.22 (95% CI 1.14, 1.30) with low certainty of evidence. There was very low certainty in the evidence for adverse events and serious adverse events. Secondary infections were uncommon in most trials with follow-up till 14 or 28 days, which may have been too early to detect the same. Conclusion: A systematic review and meta-analysis which generated efficacy data of tocilizumab was then applied to an evidence to decision framework by subject experts resulting in a robust evidence-informed guideline applicable to any Indian secondary or tertiary healthcare setting.

5.
7th IEEE International conference for Convergence in Technology, I2CT 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1992610

ABSTRACT

The SARS-CoV-2 has a confirmed case count of about 11.3 million and a death count of about 158,000 in India as of March 13th, 2021. Despite the early social distancing and lockdown measures imposed by the government, these counts have continued to rise. Mathematical models prove extremely useful to predict the course of the pandemic and for the government to strategize accordingly. Over due course several models have emerged to predict the number of COVID-19 cases, but a thorough comparison among them is lacking. In this paper, we propose three novel Hybrid Models based on the compartment-based modeling over data from January 22nd, 2020 to December 3rd 2020 and then make comparisons among them and show through experiments that each performs a better fitting and prediction on the Johns Hopkins COVID-19 dataset pertaining to India than all other benchmark models discussed. Comparison of our proposed Hybrid models with the existing compartment models like SIR, SIRD and SEIRD demonstrates that our proposed Hybrid models not only overcome the performance inefficiencies related to the existing compartmental models but also achieve a better fitting on the Johns Hopkins COVID-19 dataset. © 2022 IEEE.

6.
Frontiers in Environmental Science ; 10:13, 2022.
Article in English | Web of Science | ID: covidwho-1979034

ABSTRACT

The COVID-19 pandemic that emerged in Wuhan city of China in December 2019 has adversely impacted the health and the economy, society, and other significant spheres of the human environment. The pandemic has severely impacted economic activities, especially the industrial production, transportation, tourism, and hoteling industries. The present study analyses the impact of varying severity of lockdowns of economic activities during various phases of the pandemic on the water quality of the Yamuna river on parameters like pH values, biological oxygen demand, chemical oxygen demand, dissolved oxygen, total suspended solids, and electrical conductivity. The study has found a significant improvement in water quality parameters with closing economic activities during lockdowns. The average levels of concentration of these parameters of water quality were quite low during the lockdown period at 7.26 (pH value), 31.32, 136.07, 7.93, 30.33 mg/L, and 1500.24 mu S/cm compared to pre lockdown periods levels at 7.53 (pH), 39.62, 116.52, 6.1, 57.2 mg/L and 1743.01 mu S/cm for biological oxygen demand, chemical oxygen demand, dissolved oxygen, total suspended solids, and electrical conductivity, respectively. In addition, the study has found a strong significant positive correlation between COD with BOD and TSS during the lockdown period. The major findings from the present study could be instrumental in making environmentally sustainable policies for the country's economic development. There is also a huge scope of scaling up of the study at the national level to analyze the health of the rivers in the backdrop of lockdowns.

7.
Emergencias ; 34(4):305-307, 2022.
Article in Spanish | Web of Science | ID: covidwho-1976283
8.
BMJ Global Health ; 7:A7, 2022.
Article in English | EMBASE | ID: covidwho-1968251

ABSTRACT

Introduction The onset of the COVID-19 pandemic in early 2020 triggered reorganisation of hospital departments around the world as resources were configured to prioritise critical care. In spring 2020, NHS England issued national guidance proposing acceptable time intervals for postponing different types of surgical procedures for patients with cancer and other conditions. The 'Consider-19' study sought to investigate prioritisation decisions in practice, with in-depth examination of colorectal cancer surgery as a case-study, given recommendations that these procedures could be delayed by up to 12 weeks. Methods Twenty-seven semi-structured interviews were conducted with healthcare professionals between June - November 2020. A key informant sampling approach was used, followed by snowballing to achieve maximum regional variation across the UK. Data were analysed thematically using the constant comparison approach. Results Interviewees reported a spectrum of perceived disruption to colorectal cancer surgery services in the early phase of the pandemic, with some services reporting greater scarcity of resources than others. Nonetheless, all reported a need to prioritise patients based on local judgments. Prioritisation was framed by many as unfamiliar territory, requiring significant deliberation and emotional effort. Whilst national guidance provided a framework for prioritising, it was largely left to local teams to devise processes for prioritising within surgical specialities and then between different specialities, resulting in much local variation in practice. Discussion The pandemic necessitated a significant change in practice as surgeons, in a tense and uncertain situation, found themselves having to navigate clinically, emotionally, and ethically- charged decisions about how best to use limited surgical resources. Whilst unavoidable, many felt uncomfortable with the task and the consequences for their patients. The findings point to a need to better support surgeons tasked with prioritising patients and raise questions about who should be involved in this activity.

9.
Big Data and Cognitive Computing ; 6(2):15, 2022.
Article in English | Web of Science | ID: covidwho-1928471

ABSTRACT

The novel coronavirus disease (COVID-19) has dramatically affected people's daily lives worldwide. More specifically, since there is still insufficient access to vaccines and no straightforward, reliable treatment for COVID-19, every country has taken the appropriate precautions (such as physical separation, masking, and lockdown) to combat this extremely infectious disease. As a result, people invest much time on online social networking platforms (e.g., Facebook, Reddit, LinkedIn, and Twitter) and express their feelings and thoughts regarding COVID-19. Twitter is a popular social networking platform, and it enables anyone to use tweets. This research used Twitter datasets to explore user sentiment from the COVID-19 perspective. We used a dataset of COVID-19 Twitter posts from nine states in the United States for fifteen days (from 1 April 2020, to 15 April 2020) to analyze user sentiment. We focus on exploiting machine learning (ML), and deep learning (DL) approaches to classify user sentiments regarding COVID-19. First, we labeled the dataset into three groups based on the sentiment values, namely positive, negative, and neutral, to train some popular ML algorithms and DL models to predict the user concern label on COVID-19. Additionally, we have compared traditional bag-of-words and term frequency-inverse document frequency (TF-IDF) for representing the text to numeric vectors in ML techniques. Furthermore, we have contrasted the encoding methodology and various word embedding schemes, such as the word to vector (Word2Vec) and global vectors for word representation (GloVe) versions, with three sets of dimensions (100, 200, and 300) for representing the text to numeric vectors for DL approaches. Finally, we compared COVID-19 infection cases and COVID-19-related tweets during the COVID-19 pandemic.

10.
International Journal of Indian Culture and Business Management ; 26(2):145-165, 2022.
Article in English | Web of Science | ID: covidwho-1925463

ABSTRACT

This research paper is a step towards the study to see how Vedic Homa Therapy is an effective natural approach for treatment of any pollution, heavy PM 2.5 and PM 10 particles and the use of mango wood, cow dung and bargad wood in the cure of ailment, depression, pollution control by just focusing on its lyrics, sound, diction when done continuously. By performing Yagya, two energies are produced. Heat energy from fire of Yagya and the sound energy from vibration of the Vedic mantras;both the energies are combined to give self-healing results on any disease and its ionisation produces a vital role in curbing polluting particles. The study has done comparative analysis on emission of gaseous particles after Yagya post-second wave of COVID-19 and also through ML algorithms and statistical analysis;it demonstrates the auto correlation and high correlation on different parameters responsible for pollution measurement and for AQI.

11.
6th International Conference on Intelligent Computing and Control Systems, ICICCS 2022 ; : 1214-1219, 2022.
Article in English | Scopus | ID: covidwho-1922685

ABSTRACT

Covid-19 has disrupted lives throughout the world. It has spread all over the world and detection of the virus is an imperative step in beating the virus. Methods such as the RTPCR and Rapid antigen tests are not only time consuming but also complex and expensive. Since the virus attacks the lungs, the Xray images of the chest can be used for the detection of coronavirus. This paper summarizes as well as gives a detailed study of the research and various techniques used for this subject. Methods used for COVID-19 detection using medical imaging using Chest X-Ray (CXR) and CT scan images as well as role and usage of GANs in tackling this problem have been summarized. © 2022 IEEE.

12.
2nd International Conference on Electronic Systems and Intelligent Computing, ESIC 2021 ; 860:635-641, 2022.
Article in English | Scopus | ID: covidwho-1919740

ABSTRACT

COVID-19 is a pandemic that affected the majority of countries of the world. After the COVID-19 outburst, the Indian Government declared the complete lockdown starting on the night of 24 March 2020. The lockdown period is in its 4th phase. In the recent year it has been very fascinating to remind that the behaviour in the environment is vastly optimistic and all layers of the earth are under the repairing mode during the lockdown. With these healing environments, the conditions of the Yamuna River water in Mathura (polluted river) have also been found to be upgrading. In this present concern, we work on the concentration of BOD, COD, pH, and other physicochemical parameters for the study, i.e. TDS, Chlorides, Alkalinity, Magnesium, Calcium, Fluoride, Sulphate, Nitrate, Hardness and Total Coliform of Yamuna River (Mathura), respectively, which was found to be reduced as compared to pre-lockdown concentration, i.e. 57, 57, 3.6, 11.7, 5.1, 7.4, 9.5, 4.2, 62.5, 14.8, 33.3, and 4.5%. In the present work, the water of Yamuna River was analysed during the lockdown phase in ITL Labs Pvt. Ltd., Delhi (India). Yamuna River showed a better quality of water during the lockdown. As per results and trend analysis, the value was reducing in this lockdown phase, which is a matter of concern. Major locations of Yamuna water sample collection are Mathura region, i.e. adjacent to the road 50 m from Adda village in Naujheel of Mathura district in Uttar Pradesh. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

13.
2nd International Conference on Biologically Inspired Techniques in Many Criteria Decision Making, BITMDM 2021 ; 271:191-201, 2022.
Article in English | Scopus | ID: covidwho-1919732

ABSTRACT

The COVID-19 epidemic continues to have a devastating influence on the global population's well-being and economy. One of the most important advances in the fight against COVID-19 is thorough screening of infected individuals, with radiological imaging using chest radiography being one of the most important screening methods. Early studies revealed that patients with abnormalities in chest radiography images were infected with COVID-19. Persuaded by this, a variety of computerized reasoning and simulated intelligence frameworks based on profound learning have been suggested, with promising results in terms of precision in differentiating COVID-infected individuals. COVID-Net, a neural system configuration custom-fit for the recognition of COVID-19 instances from chest radiography photographs that is open source and accessible to the general public, is presented in this study. Many techniques have been used for the detection of COVID-19, but here we are going to focus on the chest radiography technique with the application of machine learning and image processing concepts. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

14.
Journal of Paediatrics and Child Health ; 58(SUPPL 2):97-98, 2022.
Article in English | EMBASE | ID: covidwho-1916250

ABSTRACT

Background: COVID-19 trials took <1 year to identify therapies reducing death in >30,000 patients but the Australian Placental Transfusion Study took >12 years to show that delaying cord clamping reduced death or major disability (cerebral palsy, severe visual loss, deafness, or cognitive delay) in 1,531 preterm infants. What can this teach us? Further, as composite outcomes of death or major disability can be inconclusive if each is unequally affected (as in the NeOProM Collaboration1) 2 important aims are (i) global co-operation (https://www.alphacollaboration.com/) to identify core Participant-Intervention-Comparator-Outcome questions for trials assessing mortality, a key outcome, and (ii) to answer those questions in much larger, faster trials. Such trials will also yield much more precise estimates of disability in survivors than was previously typical - a major benefit. Method: To inform these aims we compared enrolment in 2 COVID-19 trials and in 10 trials by IMPACT collaborators with samples >1,500 in high- or low-or-middle-income countries (HIC/LMIC). Results: The COVID-19 trials took 3-9 months, enrolling 13 - 219 per-site-per-year. Perinatal trials took 16-86 months, enrolling 5 - 1,700 per site per year. Trials in pregnant women or LMIC (n = 53,092) enrolled 5 times more than trials in newborns or restricted to HIC (n = 9,014). (Table) Conclusions: Greater international collaboration could resolve questions of shared relevance and priority more rapidly. Megatrials addressing mortality may benefit from highly streamlined processes for enrolment and minimal data collection, e.g., RECOVERY's one-page outcome form.

15.
Pantnagar Journal of Research ; 20(1):71-75, 2022.
Article in English | GIM | ID: covidwho-1904833

ABSTRACT

COVID-19 pandemic has disrupted the Indian agricultural system extensively. SAMETI (State Agricultural Management and Extension Training, GBPUA&T, Pantnagar, Uttarakhand) has adapted to the changed circumstances and has taken up the mandate of trainings in the online mode with very interesting and encouraging outcomes. The study has revealed that more subjects have been covered in online trainings as compared to offline training. Remoteness does not discourage people from availing online trainings on diverse subjects. Observations of extension professionals have put forth the pros and cons of both online and offline mode of trainings. The learning experience is that conducting trainings in HYBRID (both online and offline) mode will defenitely have better outcome.

16.
Journal of Clinical and Diagnostic Research ; 16(6):QC01-QC05, 2022.
Article in English | EMBASE | ID: covidwho-1897155

ABSTRACT

Introduction: Coronavirus Disease-2019 (COVID-19) pandemic has led to devastating and unprecedented health crises especially in the vulnerable population, ever since its origin in 2019. COVID-19 management in pregnant women had been a matter of controversy before the introduction of the standard protocols by the various international bodies. A lot of concern still prevails around the adverse foeto-maternal outcomes such as preterm birth, stillbirth, increased caesarean rates, maternal morbidity and mortality. Furthermore, uncertainty about the duration of the COVID-19 pandemic had also increased anxiety among pregnant women, particularly during the first wave. Aim: To find out the knowledge and beliefs of pregnant women towards the COVID-19 infection in first wave and to know whether it had increased anxiety among non infected pregnant women before the advent of the COVID-19 vaccination. Materials and Methods: A cross-sectional study was conducted on the 280 asymptomatic pregnant women attending the Department of Obstetrics and Gynaecology, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India, over four months (10th October 2020 to 10th February 2021). These women were provided with a questionnaire and a Generalised Anxiety Disorder Score-7 (GAD-7) chart. Statistical analysis was performed using the Pearson Chi-square analyses with p<0.05 considered statistically significant. Results: The total number of participants were 280. Majority of them were in their 20s and were primigravida. The mean GAD-7 score for the study population was 4.642 and the overall prevalence of anxiety in this study was 34.3% (n=96). GAD-7 score chart showed 65.7% (n=184) had 0-4 levels (minimal) while severe scores ≥15 were noted in 2.9% (n=8). In the current study, greater anxiety scores were found in the homemakers. A high prevalence of anxiety was seen in primigravida and during the third trimester. About 37.5% of the participants believed that COVID-19 could transmit to the foetus-in-utero, if infected and 50.36% felt being pregnant could increase the risk of contracting COVID-19 infection. Conclusion: The present findings suggest that pregnant women showed a lot of concerns and significant anxiety due to COVID-19 during the study period.

17.
Topics in Antiviral Medicine ; 30(1 SUPPL):332, 2022.
Article in English | EMBASE | ID: covidwho-1880610

ABSTRACT

Background: Accurate and reliable serological assays are essential for epidemiological surveillance of SARS-CoV-2. Several commercial anti-SARS assays are available and use cases for serological testing includes surveillance. However, there is growing evidence of varying performance of SARS-CoV-2 assays dependent of their format. We compare the performance of 3 different assays used in a national serosurvey undertaken between April and June 2021, in South Africa before widescale vaccination roll out. Methods: Venous blood samples from participants ≥12 years were transported under cold chain to a central testing laboratory within 24 hours of collection. Samples were tested for SARS CoV-2 antibodies with the Abbott nucleocapsid (NC)-based Architect anti-SARS CoV-2 chemiluminescent microparticle immunoassay (CMIA), the EuroImmun Spike (S)-based assay and the Roche total IgG NC-based Elecsys Anti-SARS-CoV-2 electrochemiluminescence immunoassay (ECLIA) on the Cobas e411 platform. We compared antibody detection proportions. Results: 8146 participants (median age 40 years, IQR 26-55) 5.6% of whom reported ≥1 SARS-CoV-2 symptom in the preceding 3 months gave a blood sample. Samples were tested on the Abbott assay with different cut-offs:-15.5% tested positive at the 1.40 cut-off and 26.8% at the 0.49 lower cut-off. 21.6% of the samples tested positive on the Euroimmun and 39.0% tested positive on the Roche assay (Table). 286 samples were from respondents self-reporting a prior positive PCR test, and among them 149(52.1%), 156(54.6%), and 206(72.3%) were positive on the Abbott (1.40 cut-off), Euroimmun and Roche assays respectively. 116/286(40.6%) of these were positive on all three assays and with 21(7.3%) positive on Roche only. 224/286(78.3%) of those reporting prior PCR test positivity were positive at the lower Abbott cut-off, with 47(16.4%) positive on Abbott only. Conclusion: These samples collected before wide scale vaccination roll out in South Africa show variable performance of these assays with the Roche NC assay detecting more infections that both the Abbott NC assay(0.40 cut-off) and the Euroimmun S assay.This could be reflective of seroreversion previously reported with Abbott and Euroimmun, and the greater sensitivity of Roche assay targeting the more abundant NC as an epitope. Use of direct, double Antigen-sandwich-based assays that are stable and have increased sensitivity over time may be optimal to detect both natural and vaccine-induced immunity in serosurveys.

18.
Journal International Medical Sciences Academy ; 34(4):318-321, 2021.
Article in English | EMBASE | ID: covidwho-1880046

ABSTRACT

Background: MIS-A, a hyperinflammatory condition in individual aged >21 years, is a rare condition seen in association with COVID-19 illness. Very few cases of MIS-A has been reported till date, and it still remains a box of mystery. Case Presentation: We report a case of 44 Year old male, with an evidence of prior COVID-19 illness, presented with 3 weeks of fever with polyarthralgia along with 3 days of palpitation, shortness of breath, conjunctivitis and soreness of mouth. Laboratory evidence of inflammation, features of myocarditis in 2D-Echocardiography was noted at the time of admission, with no evidence of any active infection and lung pathology. He was diagnosed as a case of MIS-A as per the CDC definition. Improvement in clinical and laboratory parameters and normalization of cardiac function was noted after treatment with IV methylprednisolone, and Intravenous Immunoglobulin. Conclusion: In adults presenting with fever and multisystem involvement, in Post-Covid period, with raised inflammatory markers, a high index of suspicion for MIS-A is required in order to start timely treatment and prevent potentially fatal outcome.

19.
Frontiers in Education ; 7, 2022.
Article in English | Scopus | ID: covidwho-1875401

ABSTRACT

In March 2020, the World Health Organization (WHO) declared the coronavirus disease 2019 (COVID-2019) epidemic a pandemic and whole education system came to a standstill. An immediate transformation from an offline mode to online mode of teaching learning was needed. Majority of teachers in India were not prepared for digital pedagogy. Regardless of serious difficulties and deep-rooted traditional teaching and learning methods, they quickly involved themselves in their professional learning virtually and adopted the online teaching methods to keep the system going on. Thus, the present study is focused to find the answers of the questions emerged out of this situation such as: (i) how teachers prepared themselves to come forward for gigantic initiative? (ii) How did they learn the digital online techniques? (iii) How the deficiencies of electronic gadgets, such as mobile phones and tablets were arranged in short span of time and made available to all the stakeholders? This is a qualitative study using phenomenological enquiry as an approach, participants were selected with purposive sampling technique and data were collected through the in-depth (semi-structured) interviews of 15 school teachers, 5 school heads, and 5 block education mentors from Punjab state of India. The findings of the study indicated that with continuous motivation, school teachers took the initiative to come forward for digital teaching and learning. Some teachers out of firm professional commitment managed to pursue their professional learning mainly through their own efforts. In addition, the Education Department provided online crash courses to teachers. The clusters of teachers having sound knowledge of technology collaboratively trained the teachers at block levels. Majority of teachers have their own gadgets but underprivileged sections were provided mobiles and tablets by the government and non-government agencies. A quick shift to virtual professional learning resulted in significant improvements in the learning outcomes of students. Hence, the study will motivate the teachers of other states to pursue virtual professional learning to update themselves. Additionally, it suggests that teachers ought to be part of forums, interest groups, and online professional communities to interact with peers and know how the rest of the world is doing with digital education. Copyright © 2022 Singh, Zamaletdinov, Kaur and Singh.

20.
6th International Conference on Computational Intelligence in Data Mining, ICCIDM 2021 ; 281:635-650, 2022.
Article in English | Scopus | ID: covidwho-1872358

ABSTRACT

COVID-19 (novel coronavirus disease) is a serious illness that has killed millions of civilians and affected millions around the world. Therefore, numerous technologies that enable both the rapid and accurate detection of COVID-19 illnesses will provide much assistance to healthcare practitioners. A machine learning-based approach is used for the identification of COVID-19. In general, artificial intelligence (AI) approaches have yielded positive outcomes in healthcare visual processing and analysis. CXR is the digital image processing method that plays a significant role in the analysis of corona disease. In this research article, at the initial phase of the process, a median filter is used for the noise reduction from the image. Edge detection is an essential step in the process of COVID-19 detection. The canny edge detector is implemented for the detection of edges in the CXR images. The principal component analysis (PCA) method is implemented for the feature extraction phase. There are multiple features extracted through PCA. The essential features are optimized by an optimization technique known as swarm optimization is used for feature optimization. For the recognition of COVID-19 through CXR images, a hybrid multi-class support vector machine technique is implemented. The particle swarm optimization (PSO) technique is used for feature optimization. The proposed system has achieved an accuracy of 97.51%, specificity (SP) of 97.49%, and 98.0% of sensitivity (SN). © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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