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1.
Jundishapur Journal of Microbiology ; 15(1):4845-4882, 2022.
Article in English | GIM | ID: covidwho-2124596

ABSTRACT

'Corona', this alarming word comes from the 'Latin' word 'Crown' that protects the virus. On Dec, 19, firstly, this virus was isolated from three patients having pneumonia connected to a cluster of acute illnesses. WHO declared it a 'pandemic' in Jan, 20 but later in Feb, WHO's general director Tedros Adhanom Ghebreyesus named the virus nCOVID-19. It was first identified in Wuhan, China, as a respiratory illness causing novel diseases (SARS and MERS). CDC informed corona primarily causes mild to moderate upper RTI and, in a few cases, lower RTI (pneumonia, bronchitis). Transmission occurs through direct contact or air droplets of sneezing, coughing, etc. The origin is not clear, but recent studies reported that ACE 2, a membrane exopeptidase receptor, was used to enter the human cell. The primary symptoms are fever above 104 degrees F, shortness of breath, pneumonia, throat soreness, diarrhea, etc. Available approved therapeutics include hydroxychloroquine. This current review updates about the viral transmission and main effect of this virus on children, pregnant women, diabetic, and cancer patients.

2.
12th Annual International Research Conference of Symbiosis Institute of Management Studies, SIMSARC 2021 ; : 1-17, 2022.
Article in English | Scopus | ID: covidwho-2094562

ABSTRACT

The outbreak of Covid-19 has brought a thrift in the lives of people, business, and the shoppers. As this disease was declared pandemic, the Indian government declared lockdown to break the chain of coronavirus. Due to this, people were locked in their homes and the world was come to stake. This resulted in the anxiety and fear among the people. This lockdown and social distancing guidelines have unsettled the buying habits of the consumers, and it has drastically transformed the shopping habits also. Shoppers are learning to devise and understand new practices. The new normal has become the part of lives of every individual. The study basically aims in identifying the relationship between self-care measure and hygiene practices adopted by the shoppers while they go out for shopping. A total of 236 respondents were administered in Smart PLS version 3.3.2. The results imply that there is a significant relationship between self-care measures and hygiene practices. In addition, the findings prove a mediating role for social distancing, self-care measures, and hygiene practice. The findings of the study can be useful to shoppers and retailers in the devising guidelines to be followed while shopping keeping in lieu of the protection of spreading coronavirus during pandemic. These findings can provide insight to consumer behaviour comprehensively, help companies agreement with similar status quo as well as suggestions for the government to aid businesses effectively in the future. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

3.
Travel Behaviour and Society ; 30:41-59, 2023.
Article in English | Web of Science | ID: covidwho-2069717

ABSTRACT

Ride-hailing services (RHS) are rapidly transforming the urban transportation landscape, and subsequently, users' perception of mobility services. Hence, it is of utmost importance to understand the perceptual and latent attitudinal factors that drive such service usage. This gains more relevance in the context of a developing nation both because of its characteristically different transport environment-lifestyle interaction, and relatively fewer studies investigating RHS utilization. The present research uses revealed preference data from household surveys (N = 418) to estimate the usage propensity of RHS services in Kolkata, as it has the highest share of commuters among the four large metropolitan areas in India. A SEM-MIMIC Ordered Probit modelling framework has been developed, as it extracts the advantages of exploring latent constructs through a structural equation model (SEM) and examines their interaction with demographics and trip-specific factors with the Multiple Indicator Multiple Cause Model (MIMIC). This study relies on the confirmatory approach to establish the latent attitudinal factors which stem from accepted theories in travel behaviour, i.e., Theory of Planned Behaviour (TPB) and Technology Acceptance Model (TAM). Subsequently, the Ordered Probit model estimates RHS use-frequency. The results highlight that the latent variables (LVs), viz., ride-hailing attitude and perceived usefulness, are the most significant while estimating RHS utilization. These findings encourage RHS providers to focus on service aspects (for example, security during rides, clean vehicles, reliability of rides, less wait time between booking and ride arrival), instead of only emphasizing on (cosmetic) changes to the booking interface. Besides, in contrast to the developed countries, subjective norms were found to have an inverse relationship with RHS usage, suggesting inhibition among the public, which is probably arising from the dearth of customer-friendly service, especially after being comparatively expensive. The model also suggests the supplementary role of RHS to public transit, which could be pivotal in its integration into mobility-as-a-service (MaaS) and also calls for regulatory actions. The demographics (e.g., age, gender, household income) and trip-specific (e.g., trip purpose, trip length, time-of -day) covariates add further meaning to the relationships among latent constructs. The results suggest a higher preference for RHS among non-car-owners, whereas frequent use of ride-hailing is observed to have a likely positive association with longer trip lengths. Overall, this research brings valuable and first-of-its-kind insights into attitudinal factors and their interaction with demographics and trip-specific covariates facilitating RHS utilization in the context of a developing nation.

4.
Medical Journal of Dr. D.Y. Patil Vidyapeeth ; 15(7):S24-S29, 2022.
Article in English | Scopus | ID: covidwho-2024847

ABSTRACT

Background: Continuing Medical education during the COVID-19 Pandemic has been a great challenge to Medical educators, especially teaching clinical skills online. Aims: The study aims too study the efficacy of teaching ECG in online mode to first MBBS students in the Department of Physiology. Materials and Methods: There are 200 students in the first MBBS batch at Burdwan Medical College. Our method of teaching was flipped classroom-assisted self-directed learning. For teaching ECG to our students we had first arranged for presession MCQ to assess the initial level of knowledge. We had then provided the students with PowerPoint presentations with voice narrations for their self-study, following which the students were divided into batches of twenty and each batch had a team leader and a facilitator. These small batches were shown videos of instruments, methods of recording ECG, normal and abnormal ECG along with explanations in multiple sessions (10). Doubt clearing sessions were arranged for each batch and these sessions were brainstorming. The students were assessed with MCQs (10 marks each Session), oral questions, short answer type questions, spots, and problem-based questions. We also took a feedback survey from the students and provided the students with feedback regarding their performance. Results: MCQ assessments of students in Pre and Posttest session on ECG teaching classes were 50.39 ± 19.41 vs. 65.25 ± 9.14;P ≤ 0.001FNx08. Students performed significantly better in MCQ assessments of students on Normal parameters of ECG assessment as compared to Abnormal ECG parameters: 67.25 ± 10.98 vs. 63.157 ± 7.399;P = 0.000424FNx08. Results of Written Examination and Viva Examination of students in ECG classes were 64.844 ± 9.923 vs. 71.89 ± 10.49;P ≤ 0.001FNx08. Conclusions: The online method of teaching ECG was a success in the institution as observed in this study as observed in the assessment. Students performed better in viva in online exam for ECG and students were satisfied with online delivery. © Medical Journal of Dr. D.Y. Patil Vidyapeeth 2022.

5.
Journal of Health and Translational Medicine ; 25(1):145-153, 2022.
Article in English | EMBASE | ID: covidwho-1979857

ABSTRACT

Viral diseases are the most devastating health concern worldwide. Outbreaks of coronavirus (CoVs)-related acute respiratory diseases are responsible for the massive health/socio-economic breakdown in the last two decades including the Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), the third reported spillover SARS-CoV-2 from an animal coronavirus to humans. After the H1N1 pandemic influenza (2009), SARS-CoV-2 (novel-beta coronavirus) causing COVID-19 has stretched across 215 countries in 5 major continents with 200,523,190 confirmed cases (4 August 2021;https://www.worldometers.info/coronavirus/). COVID-19 patients had cough, fever, dyspnea, headache, and respiratory failure, as well as shock, acute respiratory distress syndrome, and sepsis in severe instances. Independent of two preceding epidemics, SARS (2002) and MERS (2012), a knowledge gap about the emerging medical manifestations as well as complications of SARS-CoV-2 (2019-2020) infections in humans must be filled, with a focus on immunological complications and computational genomics for forecasting/preparedness for a similar outbreak in the future. This paper aims to address aspects of this gap.

6.
4th International Conference on Computational Intelligence in Pattern Recognition, CIPR 2022 ; 480 LNNS:77-89, 2022.
Article in English | Scopus | ID: covidwho-1958945

ABSTRACT

The Covid-19 pandemic has had a profound effect on our daily lives. One of the most effective ways to protect ourselves from this virus is to wear face masks. This research paper introduces face mask detection that authorities can use to reduce and prevent COVID-19. The face mask recognition process in this research paper is done with a deep learning algorithm and image processing done using MobileNetV2. Steps to build the model are data collection, pre-processing, data classification, model training and model testing. The authors came up with this approach due to the recent Covid-19 situations for following specific guidelines and the uprising trend of Artificial Intelligence and Machine Learning and its real-world practices. This system has been made to detect more than one person whether they are wearing masks or not. This system also gives us the Covid cases-related worldwide updates as per our chosen country and type of cases like total cases, total deaths etc. Such systems are already available, but the efficiency of the available mask detection systems was not achieved thoroughly. This newly developed system proposes to take a step further, which recognizes more than one person at a time and increases the accuracy level to a much greater extent. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

7.
Medical Journal of Dr. D.Y. Patil Vidyapeeth ; 15(4):555-560, 2022.
Article in English | Scopus | ID: covidwho-1954414

ABSTRACT

Background: The COVID-19 pandemic has greatly impacted the progress of medical education. As the crisis continues, it is important to develop valid and reliable methods of assessment. Aims: To assess the impact of the competency-based medical education (CBME) implemented online in the department of physiology during this pandemic on the results of internal assessments conducted online. Materials and Methods: This pilot study was conducted on two hundred First-year MBBS students at Burdwan Medical College after taking Institutional clearance in 6 months. Two internal assessments had to be conducted online in 6 months. We divided our internal assessment sessions which were conducted at three monthly intervals into 4 compartments: multiple-choice questions, short answer type questions, orals, and spots. We conducted two surveys to assess the stress levels of the students and two feedback surveys to assess our teaching program. Statistical analysis: T-test and Chi-square test was used to analyze the data. Results: Assessments scores of students in the first session were 59.68 ± 10.91;assessment scores of students in the second session were 73.21 ± 8.66;P < 0.001 ∗∗ (highly significant). Perceived stress score (PSS) in the first survey was 21.36 ± 3.84 and PSS in the second survey was 20.77 ± 4.13;P = 0.144. Thirty students failed in the first session while 1 in the second session, χ 2 = 32.1;P < 0.0001∗∗. At the end of 3 months, 11.4% had difficulty in studying physiology, while at the end of 6 months, 8.5% had difficulty in studying physiology with online support. Conclusions: The first MBBS students were able to cope up better with the online mode of teaching with the passage of time and regular feedback provided to them. The results of the present study demonstrate that the department of physiology could implement CBME online and conduct internal assessments also. © 2022 Medical Journal of Dr. D.Y. Patil Vidyapeeth ;Published by Wolters Kluwer - Medknow

8.
Diabetes research and clinical practice ; 186:109317-109317, 2022.
Article in English | EuropePMC | ID: covidwho-1877214
9.
International Journal of Public Leadership ; 2022.
Article in English | Scopus | ID: covidwho-1741095

ABSTRACT

Purpose: The purpose of the article is to examine the interplay between charismatic leadership and two follower characteristics in predicting safety behaviors during the Covid-19 pandemic in two distinct countries. Design/methodology/approach: The quantitative investigation was conducted during the first wave of the Covid-19 crisis in India and Germany. Given the importance of safety behaviors during the pandemic, the authors proposed high charismatic public leadership, the perception of crisis and belief in science of the constituent influence safety behaviors. Findings: Consistent with the hypothesis, the authors found that there was a positive relationship between charismatic leadership and safety behaviors. Contrary to the expectations, belief in science did not moderate the relationship between charisma and safety behaviors. Opposite to the hypotheses, the relationship between charisma and crisis was stronger under followers' low in perception of crisis. Originality/value: The findings contribute to the understanding of charisma during a crisis and the role of followers' perceptions. Implications include raising awareness about the importance of charismatic leadership in encouraging critical safety behaviors during a crisis, but these effects depend in part on the followers' attributions of the public leader. © 2022, Emerald Publishing Limited.

10.
Icaart: Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Vol 2 ; : 1066-1072, 2021.
Article in English | Web of Science | ID: covidwho-1296116

ABSTRACT

Due to the increasing number of users in social media, news articles can be quickly published or share among users without knowing its credibility and authenticity. Fast spreading of fake news articles using different social media platforms can create inestimable harm to society. These actions could seriously jeopardize the reliability of news media platforms. So it is imperative to prevent such fraudulent activities to foster the credibility of such social media platforms. An efficient automated tool is a primary necessity to detect such misleading articles. Considering the issues mentioned earlier, in this paper, we propose a hybrid model using multiple branches of the convolutional neural network (CNN) with Long Short Term Memory (LSTM) layers with different kernel sizes and filters. To make our model deep, which consists of three dense layers to extract more powerful features automatically. In this research, we have created a dataset (FN-COV) collecting 69976 fake and real news articles during the pandemic of COVID-19 with tags like social-distancing, covid19, and quarantine. We have validated the performance of our proposed model with one more real-time fake news dataset: PHEME. The capability of combined kernels and layers of our C-LSTM network is lucrative towards both the datasets. With our proposed model, we achieved an accuracy of 91.88% with PHEME, which is higher as compared to existing models and 98.62% with FN-COV dataset.

11.
ICAART - Proc. Int. Conf. Agents Artif. Intell. ; 2:1066-1072, 2021.
Article in English | Scopus | ID: covidwho-1184227

ABSTRACT

Due to the increasing number of users in social media, news articles can be quickly published or share among users without knowing its credibility and authenticity. Fast spreading of fake news articles using different social media platforms can create inestimable harm to society. These actions could seriously jeopardize the reliability of news media platforms. So it is imperative to prevent such fraudulent activities to foster the credibility of such social media platforms. An efficient automated tool is a primary necessity to detect such misleading articles. Considering the issues mentioned earlier, in this paper, we propose a hybrid model using multiple branches of the convolutional neural network (CNN) with Long Short Term Memory (LSTM) layers with different kernel sizes and filters. To make our model deep, which consists of three dense layers to extract more powerful features automatically. In this research, we have created a dataset (FN-COV) collecting 69976 fake and real news articles during the pandemic of COVID-19 with tags like social-distancing, covid19, and quarantine. We have validated the performance of our proposed model with one more real-time fake news dataset: PHEME. The capability of combined kernels and layers of our C-LSTM network is lucrative towards both the datasets. With our proposed model, we achieved an accuracy of 91.88% with PHEME, which is higher as compared to existing models and 98.62% with FN-COV dataset. © 2021 by SCITEPRESS - Science and Technology Publications, Lda.

13.
National Journal of Physiology, Pharmacy and Pharmacology ; 11(1):62-67, 2021.
Article in English | EMBASE | ID: covidwho-1041467

ABSTRACT

Background: Coronavirus disease (COVID)-19 pandemic has brought a sudden change in education across the globe. To ensure social distancing, Medical Colleges in India also started online medical teaching since Nation Wide lockdown from 24 March 2020. Aim and Objective: To assess the impact and effectiveness of online teaching program provided by the Department of Physiology in Burdwan Medical College, West Bengal, among the first Prof. M.B.B.S students. Materials and Methods: This pilot study was conducted in a time span of 3 months after obtaining Institutional ethical clearance. Two hundred students enrolled in 1st year participated in this study. Mode of teaching was Flipped Class Room Assisted Self-directed Learning. Multiple assessments were conducted. Two surveys to assess stress level with the perceived stress scale of Sheldon Cohen and three feedback surveys to assess and modify the online teaching program were conducted. Results: Academic activities carried by the majority of students were 5 h or more. About 77.1% were satisfied with the online support, 86.1% felt that regular assessment and feedback provided to them were beneficial, and 11.4% had difficulty in studying physiology in online mode. About 87% students wanted the online support to continue along with offline mode in the near future. Students performed significantly better in post-test sessions (65.155 ± 4.74 vs. 53.378 ± 5.4;P = 0.0045**) as compared to pre-test sessions. There was no significant difference in performance between traditional lecture (even with revision) classes and online sessions. No significant difference in stress scores was observed between two surveys conducted in consecutive 2 months. Conclusions: It is evident that online teaching is an effective tool in teaching physiology to undergraduate medical students and may be taken into consideration in future teaching-learning and assessment program.

14.
ACM Int. Conf. Proc. Ser. ; : 437, 2020.
Article in English | Scopus | ID: covidwho-1021133

ABSTRACT

During the pandemic of COVID-19, the propagation of fake news is spreading like wildfire on social media. Such fake news articles have created confusion among people and serious social disruptions as well. To detect such news articles effectively, we propose a generalized classification model (MCNNet) having the power of learning across different kernel-sized convolutional layers in different parallel channel network. The capability of MCNNet is lucrative towards any real-world fake news dataset. Experimental results have demonstrated the performance of our model with different real-world fake news datasets. © 2021 Owner/Author.

15.
Asia Pacific Journal of Health Management ; 15(3), 2020.
Article in English | Scopus | ID: covidwho-827903

ABSTRACT

Global health systems are under immense pressure with the exponential growth and spread of COVID-19. Public health and health system responses to the pandemic have relied on health information reporting, visualisation, and projections of incidence, morbidity, and mortality. This commentary aims to explore how health information has been used to inform the public, manage risk, understand capacity, prepare the health system and to plan public health strategy. We also aim to share the health information challenges and our insights to inform future debate and strategic investment. This paper will be relevant to health service and health information managers wanting to understand vulnerabilities and focus for future health information initiatives. © Asia Pacific Journal of Health Management 2020. All rights reserved.

16.
International Journal of Pharmaceutical Research ; 12(4):237-243, 2020.
Article in English | EMBASE | ID: covidwho-708874

ABSTRACT

The novel coronavirus (COVID-19) is a pandemic of the new millennium. It was first reported in the Wuhan city, a huge metropolis of 11 million people in central China. The World Health Organization (WHO) declared the COVID-19 outbreak as a pandemic. The virus became named Severe Acute Respiratory Syndrome coronavirus 2 (SARS-Cov-2), which was nomenclature by the International Committee on Taxonomy of Viruses. Coronavirus is polymorphic spherical particles with spike like surface projections. The envelope of coronavirus consists of a lipid bilayer, where the four membrane protein is anchored i.e. S – spike, E – envelope, M – membrane, N – nucleocapsid. Inside envelop the N protein bound to the positive sense single stranded RNA (+ssRNA) genome. The size of the ssRNA genome is ̴30000 nucleotide long. The coronavirus probably originated in bats, although it was not clear that how it was transmitted from bats to humans. In keeping with current evidence, coronavirus is transmitted between people through respiratory droplets and close contacts. RT-PCR is the most unique and sensitive for the detection of coronavirus and it is more beneficial for detecting the virus in the primary phase of the infection. It has been observed that there is no vaccine available for the treatment of coronavirus till now, but the S protein is presently considered to be one of the maximum promising targets for coronavirus vaccine development. Here, we review that the biology of the coronavirus in the term of an epidemiology, multiplication, diagnosis, transmission, prevention, treatment.

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