Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 34
Filter
Add filters

Journal
Year range
1.
Homeopathy ; 2022.
Article in English | PubMed | ID: covidwho-2000974

ABSTRACT

BACKGROUND/OBJECTIVE:  Most of the symptoms of coronavirus disease 2019 (COVID-19) are covered by large repertory rubrics and hence many remedies have been proposed as "genus epidemicus". The aim of this study was to combine the information from various data collections to prepare a COVID-19 Bayesian mini-repertory/an algorithm-based application (app) and test it. METHODS:  In July 2021, 1,161 COVID-19 cases from 100 practitioners globally were combined. These data were used to calculate "condition-confined" likelihood ratios (LRs) for 59 symptoms of COVID-19. Out of these, 35 symptoms of the 11 medicines that had at least 20 cases each were considered. The information was entered in a spreadsheet (algorithm) to calculate combined LRs of specific combinations of symptoms. The algorithm contained the medicines Arsenicum album, Belladonna, Bryonia alba, Camphora, Gelsemium sempervirens, Hepar sulphuris, Mercurius solubilis, Nux vomica, Phosphorus, Pulsatilla and Rhus toxicodendron. To test concordance, the doctors were then invited to re-enter the symptoms of their cases into this algorithm. RESULTS:  The algorithm was re-tested on 358 cases, and concordance was seen in 288 cases. On analysis of the data, bias was noticed in the Merc group, which was therefore excluded from the algorithm. The remaining 10 medicines, representing 81.8% of all cases, were included in the preparation of the next version of the homeopathic mini-repertory and app. CONCLUSION:  The Bayesian mini-repertory and app is based on qualitative clinical experiences of various doctors in COVID-19 and gives indications for specific medicines for common COVID-19 symptoms. It is freely available [English: https://hpra.co.uk/;Spanish: https://hpra.co.uk/es ] for further testing and utilization by the profession.

2.
2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022 ; : 442-447, 2022.
Article in English | Scopus | ID: covidwho-1992619

ABSTRACT

With COVID-19, more than millions of people from all over the world got infected due to this pandemic disease, has wrought havoc. Due to delay in detection of presence of COVID-19 in human body, it infected large number of people all around the globe. Besides all the available manual methods, Artificial Intelligence (AI) and Machine Learning (ML) can help in detecting, treating and monitoring the sternness of COVID-19. This paper intends to provide a complete overview of the role of AI and ML as one important tool for COVID-19 and associated epidemic screening, prediction, forecasting, contact tracing, and therapeutic development. AI is a game-changer in terms of disease diagnosis speed and accuracy. It's a promising technique for a fully transparent and autonomous monitoring system that can follow and cure patients remotely without transmitting the infection to others. AI Application areas in the field of health care are also identified. This paper examines the role of AI in combating the COVID-19 epidemic. We attempt to present a medical network architecture based on AI. The architecture employs artificial intelligence (AI) to efficiently and effectively carry out patient monitoring, diagnosis, and their cure. © 2022 IEEE.

3.
2nd FICR International Conference on Rising Threats in Expert Applications and Solutions, FICR-TEAS 2022 ; 434:229-235, 2022.
Article in English | Scopus | ID: covidwho-1971600

ABSTRACT

Online study is not a new technology it was used since 2013 but become popular during the Corona virus. This research articles contain the study of the comparison between study through virtual platform and study by physical medium. Our study involves how the both traditions are different from each other. In this review paper we will also discuss the different online tools and methods used by the particular organisation for taking online classes. The advantage and disadvantage of online education and how it has changed the perspective of learning are also discussed. We will also discuss the importance of campus learning for improving the social skills and technical skills. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

4.
2nd International Conference on Mechanical and Energy Technologies , ICMET 2021 ; 290:529-538, 2023.
Article in English | Scopus | ID: covidwho-1958920

ABSTRACT

The purpose of the study is to examine the perceptions of people on the effect of lockdown and outbreak of COVID-19 in the National Capital Region (NCR) area of India. In this survey, the two cities of the NCR area, i.e., Delhi and Guru gram are selected for the collection of primary data. The primary data have been collected through the questionnaire. A total of 204 respondents have answered the pre-framed questionnaire. Five-point Likert Scales have been used to judge the degree of agreement with the statements. Descriptive statistics are used to analyze the data. The findings suggest that people pay more attention to personal hygiene during the pandemic time and they feel that working from home is a challenge in India due to bandwidth and technological issues. Job security is a big concern in front of people due to lockdown. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

5.
International Journal of Molecular Epidemiology and Genetics ; 13(1):1-14, 2022.
Article in English | EMBASE | ID: covidwho-1955716

ABSTRACT

Some blood group antigens are reported as a susceptibility marker for some diseases. For instance, HBGA (Histo-blood group antigen) which is controlled by gene FUT2 also considered as a susceptible marker. The FUT2 gene which exhibits the expression of alpha-1, 2-L-fucosyltransferase enzyme also leads to HBGA expression for the gut, and it provides a composition of the phenotypical profile that exists in some populations with unique histories of evolution and it can be considered as a marker of the genetic population. It is found to have an association with many diseases which is discussed in this review. Polymorphic mutations are known to inhibit and reduce its function which are population specific. Detailed understanding and deeper knowledge of its role in the pathogenesis and prevention of many diseases is required. FUT2 may also have a potential role in the case of COVID-19 as a susceptible marker due to its association with respiratory diseases and the ABO blood group. There is an utmost need for this kind of review knowing its importance and owing to limited collective information.

6.
Asian Biotechnology and Development Review ; 23(3):23-53, 2021.
Article in English | Scopus | ID: covidwho-1897899

ABSTRACT

Synthetic biology is an emerging area of research representing one of the finest example of culmination of various engineering principles to biology resulting in multi-dimensional implications for humans. In other terms, as with any technology, synthetic biology presents plausible opportunities as well as potential risks. Commercialisation of synthetic biology- oriented products requires critical analysis to outweigh the probable risks. Synthetic biology based processes and products have been considered to be regulated under biotechnology regulatory framework due to existing overlap at various levels in the two fields. However, with ever widening scope and impact of synthetic biology, several nations have enacted various guidelines to regulate synthetic biology research. Outbreak of COVID-19 and various speculations about its origin has further attracted global attention to address bio risk concerns of synthetic biology. Therefore, the present study focuses on biosecurity, bioterrorism, and ethical aspects of synthetic biology, emphasising the urgent need for policymaking in this regard in India. In addition, role of various agencies in regulating synthetic biology has been reviewed. Furthermore, position of India in the synthetic biology race has been also assessed towards the end of the study.. © 2021, RIS.

7.
Journal of Obstetric Anaesthesia and Critical Care ; 12(1):5-16, 2022.
Article in English | Web of Science | ID: covidwho-1887285

ABSTRACT

Assisted reproductive technology (ART) is used primarily to address the treatment of infertility which includes medical procedures such as in vitro fertilisation (IVF), intra-cytoplasmic sperm injection (ICSI), gamete intra-fallopian transfer (GIFT) or zygote intra-fallopian transfer (ZIFT). IVF has revolutionised infertility treatment and is nowadays widely accepted all over the world. The IVF is carried out as a daycare procedure and many anaesthetic regimens have been studied, tried and tested so far. An anaesthesiologist's role mainly comes into play during trans- vaginal oocyte retrieval and embryo transfer (ET) process of IVF. Various techniques of anaesthesia are practised which include general or regional anaesthesia, conscious sedation or monitored anaesthesia care, patient-controlled analgesia, acupuncture and transcutaneous electrical nerve stimulation (TENS). The anaesthetic management needs careful consideration of the effect of drugs on the maturation of oocytes or embryonic development, fertilisation and pregnancy rates. In view of the Coronavirus disease-19 (COVID-19) pandemic, ART clinics have been affected and due to the ambiguity of its effects on the reproductive outcome, anaesthesiologists need to be vigilant and cautious with anaesthetic management during pandemic times. This review includes a discussion of various anaesthetic options and agents along with their advantages or disadvantages if any. The literature sources for this review were obtained via PubMed, Medline, Cochrane Library and Google Scholar. The results of 82 out of 110 articles discussing different methods of anaesthesia for ART procedures over 25 years were compiled.

8.
1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021 ; 107:6889-6903, 2022.
Article in English | Scopus | ID: covidwho-1874800

ABSTRACT

This study examines the effect of strategies adopted by Chitkara International School for the continuous improvement of online learning of kindergarten students, during the transition of classes from offline mode to online mode. The objective of this study is to increase the interest of the students in online classes, to increase the engagement of the parents in the child's learning process and upskilling the teachers for handling online classes during COVID-19 time. The study was conducted on 373 kindergarten students, parents and 25 teachers of Chitkara International School. The study was conducted using Pre-test-post-test single group design. The sample was analysed based on the qualitative and quantitative data. The findings of the study reported that there was significant improvement in the attendance of the students of the kindergarten classes, the cooperation and involvement of the parents increased and there was a significant increase in the participation of the students in all the activities. This study was conducted with a purpose of providing Quality Education to students even during Covid times and all efforts were made in sync with the Sustainable Development Goal 4 which focusses on Quality Education. © The Electrochemical Society

9.
2020 National Conference on Advances in Applied Sciences and Mathematics, NCASM 2020 ; 2357, 2022.
Article in English | Scopus | ID: covidwho-1873614

ABSTRACT

Data science is emerging as a novel domain in the area of not only computers but also medical, agriculture, machine learning, social networking, and health care. As the data increases every second, the success of any real-world data analytical application majorly depends on the type and efficiency of its storage and management system. In these applications where there is difficulty in organizing the data in structured form materializes the role of Graph databases. Graph databases are well-organized to manage and store the data in the real world. Often, the graph databases have the capability of representing trillions of relationships which exist in any of the web or social networking dataset. The world is suffering from COVID-19 pandemic. Many researchers are working on post lockdown strategies that will control the spread of the coronavirus as well as unlock some of our freedoms. This situation is quite tricky, but data science as technology can probably provide a solution. One of the major objectives of this paper is that how graph database like Neo4j can help us information of policies which leads to achieve social isolation and to provide a solution for contact tracing problems which is a hurdle to social isolation [18]. © 2022 Author(s).

10.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-337490

ABSTRACT

Background: India experienced the second wave of the COVID-19 pandemic in March 2021, driven by the delta variant. Apprehensions around the usefulness of vaccines against delta variant posed a risk to the vaccination program. Therefore, we estimated the effectiveness of two doses of the ChAdOx1 nCoV-19 (Covishield) vaccine against COVID-19 infection among individuals ≥45 years in Chennai, India. Methods: A community-based cohort study was conducted from May to September 2021 in a selected geographic area in Chennai, Tamil Nadu. The estimated sample size was 10,232. We enumerated individuals from all eligible households and periodically updated vaccination and COVID-19 infection data. We computed vaccine effectiveness with its 95% confidence interval for two doses of the Covishield vaccine against any COVID-19 infection. Results: We enrolled 69,435 individuals, of which 21,793 were above 45 years. Two dose coverage of Covishield in the 18+ and 45+ age group was 18% and 31%, respectively. The overall incidence of COVID-19 infection was 1099 per 100,000 population. The vaccine effectiveness against COVID-19 disease in the ≥45 age group was 61.3% (95% CI: 43.6 - 73.4) at least two weeks after receiving the second dose of Covishield. Genomic analysis of 74 (28 with two doses, 15 with one dose, and 31 with zero dose) out of the 90 aliquots collected from the 303 COVID-19 positive individuals in the 45+ age group showed delta variants and their sub-lineages. Conclusion: We demonstrated the effectiveness of two doses of the ChAdOx1 vaccine against the delta variant in the general population of Chennai. We recommend similar future studies considering emerging variants and newer vaccines. Two-dose vaccine coverage could be ensured to protect against COVID-19 infection.

11.
Indian Pediatr ; 59(4):343-344, 2022.
Article in English | PubMed | ID: covidwho-1782005
12.
Australasian Journal of Information Systems ; 25:1-27, 2021.
Article in English | Scopus | ID: covidwho-1745161

ABSTRACT

The highly infectious nature of the COVID-19 virus has made the use of contactless payment methods a health exigency. Yet, consumers are resisting using mobile payments (m-payments) during the pandemic, a confounding behavior that needs to be better understood. The present study explicates this behavior by examining consumer resistance to m-payments during the COVID-19 pandemic. In addition, it provides more granular findings by measuring three levels of resistance/non-adoption, namely, postponement, opposition, and rejection. In this way, the study adds depth to the literature, which has largely examined resistance at an aggregate level to yield generic findings. Toward this end, the study draws upon the Innovation Resistance Theory (IRT) to propose that usage, value, risk, tradition, and image barriers influence the three levels of resistance/non-adoption differently. An artificial neural network analysis (ANN) of the data collected from 406 non-users of m-payments confirmed that the influence of the five barriers varies for the three levels of resistance/non-adoption. The results further suggest that the usage barrier is the most significant contributor to opposition and rejection intentions toward m-payments, whereas the image barrier is the most influential for postponement intentions. This study thus makes a useful contribution to theory and practice. © 2021. authors.

13.
3rd International Conference on Data and Information Sciences, ICDIS 2021 ; 318:121-129, 2022.
Article in English | Scopus | ID: covidwho-1718598

ABSTRACT

Artificial Intelligence (AI) is playing a significant role in shaping the world. The most significant change can be seen in the healthcare sector. The world nowadays is suffering from the deadly pandemic known as coronavirus (COVID-19) and scientists in the whole world are finding ways to combat this disease. Since, Artificial Intelligence has made remarkable changes in the healthcare system, the main goal of our study is to review the applications of Artificial Intelligence in controlling the spread of the COVID-19. This study is organized into different parts consisting of a background of Artificial Intelligence, followed by the application of AI that can help in deprivation of coronavirus. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

14.
2021 International Conference on Smart Systems and Advanced Computing, SysCom 2021 ; 3080, 2021.
Article in English | Scopus | ID: covidwho-1695850

ABSTRACT

The epidemic COVID-19 has shaken the globe through its cruelty, and its spread rate continues to rise daily. This paper highlights the clinical stance in the COVID-19 research studies, where time-series statistical analysis has been performed by using Prophet Model. It is widely used to understand the trend of the current epidemic after 2nd May 2020 with data at the worldwide state. The prophet model is an open-source model obtained by the data science panel on Facebook for performing predicting operations. It assists to make fast and accurate predictions for existing data samples. The Prophet model is simple to implement because its open authorized repository exists on GitHub. The time-series data analysis refers to the confirmed, recovered, and death rates for the time of 2nd May 2021 to 17th January 2022. The statistical validation strategy is followed by the implementation of a T-test on the evaluated time-series data. The expected data generated by the predictive model can be further used by the official authorities, medical departments of various countries. Moreover, the model is used to provide new graphical insights into past, present, and future trends. © 2021 Copyright for this paper by its authors.

15.
Paediatrics and Child Health (Canada) ; 26(SUPPL 1):e7-e8, 2021.
Article in English | EMBASE | ID: covidwho-1584152

ABSTRACT

BACKGROUND: The COVID-19 pandemic has impacted every facet of society but has been particularly disastrous for families of children with developmental disabilities (DD) living on the margins. The unprecedented repercussions of COVID-19, including quarantine, social distancing, and service restrictions, continue to disproportionately impact these families. This is a pattern observed in previous humanitarian crises, where there has been a lack of response for children with DD. There is an urgent need to understand the experiences of families of children with DD in order to develop a community-driven model of service provision. OBJECTIVES: This study aims to identify the experienced impact of COVID-19 on families of children with DD who have significant needs and social barriers. DESIGN/METHODS: This was a community-based participatory study using a formative research framework in accordance with COREQ guidelines. In-depth interviews (IDIs) were conducted with caregivers and care providers of children with DD. Data were recorded, transcribed, and coded using deductive and inductive coding methods by three independent coders. A peer debriefing strategy was used to verify the coding approach and interpretation of findings in accordance with the RATS (relevancy, appropriateness, transparency, and soundness) guidelines for qualitative research. Perceived parental stress and social support were explored using the Perceived Stress Scale (PSS-10) and Multidimensional Scale of Perceived Social Support (MSPSS). RESULTS: A total of 25 IDIs were conducted. Of the 15 caregivers interviewed, five were new to Canada. Results suggested both newcomer and non-newcomer families of children with DD are in crisis, reporting high stress and low social support, with increased difficulties navigating and accessing therapies and programs, including those offered virtually. Participants reported behavioural regressions and increased anxiety among their children with DD, as well as caregiver mental health challenges. Providers reported having to change their service delivery model in accordance with public health recommendations, but caregivers said that they were not included in these decisions. CONCLUSION: Families of children with DD face extraordinary barriers to care, which may be further compounded by the COVID-19 pandemic. Our study demonstrates the value of community-informed design, particularly in the setting of the COVID-19 pandemic. To deliver truly patient-centred services during the pandemic, there is an urgent need for responsive programming that is built with patients, for patients.

16.
Paediatrics and Child Health (Canada) ; 26(SUPPL 1):e104, 2021.
Article in English | EMBASE | ID: covidwho-1584131

ABSTRACT

BACKGROUND: With more than 28 million individuals of refugee or asylum-seeking background globally, the current situation has been described as one of the largest humanitarian crises of all time. Families of refugee background have complex, multigenerational mental health and developmental needs that are not accounted for in current programming frameworks. Difficulties in resettlement have been further compounded by COVID-19-related lockdowns, straining parental mental health and placing children at an increased risk for developmental or behavioural problems. Providing appropriate support services and educational resources that address the multigenerational concerns of families of refugee background will address these challenges, allowing for improved parental mental health, family cohesion, and developmental outcomes for children. OBJECTIVES: To gather data about the experiences, resources, referral pathways and barriers that impact the experience of parents of refugee background in the Greater Toronto Area (GTA) and to develop a novel, multi-dimensional parenting program model using Community-Based Participatory Research (CBPR) principles. DESIGN/METHODS: This was a qualitative community-based participatory study using a formative research framework, in accordance with COREQ guidelines. In-depth interviews (IDIs) were conducted with parents of refugee background and care providers that work closely with this population. Data were recorded, transcribed, and coded using deductive and inductive coding methods by two independent coders. A peer debriefing strategy was used to verify the coding approach and interpretation of findings in accordance with the RATS (relevancy, appropriateness, transparency and soundness) guidelines for qualitative research. RESULTS: A total of 20 IDIs were conducted (7 parents and 13 care providers). The main topics that were identified to be incorporated into the program include features of child development, how to address resettlement issues, child advocacy, and parenting in the Canadian context. Participants felt that tackling the language barriers, addressing the overlapping responsibilities of the mothers attending the sessions, providing incentives, increasing awareness of the program, and using an anti-racist and anti-oppressive approach is key to the program's success. Participants emphasized the need for trauma-informed mental health support within the program model. CONCLUSION: This study describes the key considerations for a novel parenting program for families of refugee background, by engaging them as key stakeholders in the program design process. Future iteration of this project would involve a pilot and evaluation of the program.

17.
4th IEEE International Conference on Computing, Power and Communication Technologies, GUCON 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1526276

ABSTRACT

COVID-19 has acted as a roadblock to mental health services across the globe, and the isolation because of the lockdowns has caused various depressive problems. Through this paper, we aim to determine the effect of COVID-19 on the public's mental health. Data obtained from some specific subreddits helps us identify a pool of users whose mental condition was affected by the pandemic. Using transformer-based classification models on the selected users' Reddit activity, we found 6.4% of our user base to be free from any mental issues before the pandemic. Further experiments show that most of the users posted about their struggles due to the pandemic during the March-May period. © 2021 IEEE.

18.
Lecture Notes in Bioengineering ; : 125-152, 2022.
Article in English | Scopus | ID: covidwho-1353681

ABSTRACT

Dental profession is at a very critical conjecture owing to novel coronavirus sickness, COVID-19. Dentistry is a profession where healthcare professionals are extremely susceptible of being infected as well as retain a high susceptibility to cross infect and transmit the contagious viral sickness among general public attending dental clinics. The grounded reality for an average dental practitioner is that walking back to operative clinical work in dentistry post-pandemic is quite tedious. Most of the safeguards and practices recommended in the current COVID-19 pandemic phase need significant alterations in the ways to practice clinical dentistry in terms of prevention and transmission of cross infection. 3D printing or additive manufacturing is the most upcoming surge of technology in the field of health care. Many novel research-driven and technology-based interventions from 3D printing technologies must be exploited and adapted to find ways and means to fight out the outburst of the pandemic. Many such 3D printed mass produced and cost-effective tools, equipments, and barrier materials instilled in clinical dental practice shall prevent or minimize COVID-19 cross contamination and transmission by ensuring safe clinical practices. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

19.
Big Data, Iot, and Ai for a Smarter Future ; 185:135-143, 2021.
Article in English | Web of Science | ID: covidwho-1353373

ABSTRACT

The devastating impacts of coronavirus have recently shaken up the world. This pandemic has changed every individual's life, forcing them to adapt to a new normal to survive the deadly disease. With these adjustments, technology has never been more needed than today to stay connected, stay productive, and receive important news. Though people are getting used to the new normal, it is essential to understand technology's role. Resiliency is an important concept to look at during the pandemic. It is crucial to understand how technology has helped individuals, communities, and infrastructures become more resilient. The purpose of this paper is to gain a deeper understanding of resiliency through previous literature. Though resiliency has become a study over the years, it is relatively new in artificial intelligence (AI). By reviewing different resilient models and systems from preceding literature and their impact on various kinds of situations, there will be an understanding of the term resilience and how various frameworks and scales will help create a pandemic management model. Discussing how the various kinds of resilience have helped people and Infrastructure during the pandemic will allow researchers and other professionals to understand resiliency and prepare for future disturbances. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Complex Adaptive Systems Conference, June 2021.

20.
Hematology Transfusion and Cell Therapy ; 43(2):214-218, 2021.
Article in English | Web of Science | ID: covidwho-1293815
SELECTION OF CITATIONS
SEARCH DETAIL