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1.
IEEE Transactions on Engineering Management ; : 1-15, 2022.
Article in English | Scopus | ID: covidwho-2107855

ABSTRACT

COVID-19 pandemic has created disruptions and risks in global supply chains. Big data analytics (BDA) has emerged in recent years as a potential solution for provisioning predictive and pre-emptive information to companies in order to preplan and mitigate the impacts of such risks. The focus of this article is to gain insights into how BDA can help companies combat a crisis like COVID-19 via a multimethodological scientific study. The advent of a crisis like COVID-19 brings with it uncertainties, and information processing theory (IPT) provides a perspective on the ways to deal with such uncertainties. We use IPT, in conjunction with the Crisis Management Theory, to lay the foundation of the article. After establishing the theoretical basis, we conduct two surveys towards supply chain managers, one before and one after the onset of the COVID-19 pandemic in India. We follow it up with qualitative interviews to gain further insights. The application of multiple methods helps ensure the triangulation of results and, hence, enhances the research rigor. Our research finds that although the current adoption of BDA in the Indian industry has not grown to a statistically significant level, there are serious future plans for the industry to adopt BDA for crisis management. The interviews also highlight the current status of adoption and the growth of BDA in the Indian industry. The article interestingly identifies that the traditional barriers to implementing new technologies (like BDA for crisis management) are no longer present in the current times. The COVID-19 pandemic has hence accelerated technology adoption and at the same time uncovered some BDA implementation challenges in practice (e.g., a lack of data scientists). IEEE

2.
IoT-Based Data Analytics for the Healthcare Industry: Techniques and Applications ; : 277-284, 2020.
Article in English | Scopus | ID: covidwho-2094911

ABSTRACT

The Internet of Things (IoT) consists of three major components: perception or idea generation, secure transmission, and intelligent data analysis. These core components can be applied in different formats for the prevention and control of infectious diseases. The procedure relies on the combination of sensors, artificial intelligence (AI), information technology, and available dynamic networking devices. The IoT networks can establish long-distance communication among hospitals, patients, and medical equipment, which could ultimately improve current medical conditions. The IoT has found many applications in infectious disease management that include early prediction, accurate diagnosis, suggestions on therapeutic intervention, and sharing of research data and policy making. All the components of IoT network gets integrated into skeletal framework and can help in control and prevention of infectious diseases. © 2021 Elsevier Inc. All rights reserved.

3.
Bulletin of Electrical Engineering and Informatics ; 11(6):3509-3520, 2022.
Article in English | Scopus | ID: covidwho-2080906

ABSTRACT

Infectious diseases are a group of medical conditions caused by infectious agents such as parasites, bacteria, viruses, or fungus. Patients who are undiagnosed may unwittingly spread the disease to others. Because of the transmission of these agents, epidemics, if not pandemics, are possible. Early detection can help to prevent the spread of an outbreak or put an end to it. Infectious disease prevention, early identification, and management can be aided by machine learning (ML) methods. The implementation of ML algorithms such as logistic regression, support vector machine, Naive Bayes, decision tree, random forest, K-nearest neighbor, artificial neural network, convolutional neural network, and ensemble techniques to automate the process of infectious disease diagnosis is investigated in this study. We examined a number of ML models for tuberculosis (TB), influenza, human immunodeficiency virus (HIV), dengue fever, COVID-19, cystitis, and nonspecific urethritis. Existing models have constraints in data handling concerns such data types, amount, quality, temporality, and availability. Based on the research, ensemble approaches, rather than a typical ML classifier, can be used to improve the overall performance of diagnosis. We highlight the need of having enough diverse data in the database to create a model or representation that closely mimics reality. © 2022, Institute of Advanced Engineering and Science. All rights reserved.

4.
Kidney international reports ; 7(9):S473-S473, 2022.
Article in English | EuropePMC | ID: covidwho-2034435
5.
Lessons from COVID-19: Impact on Healthcare Systems and Technology ; : 263-287, 2022.
Article in English | Scopus | ID: covidwho-2027812

ABSTRACT

Machine learning (ML) and artificial intelligence (AI) approaches are prominent and well established in the field of health-care informatics. Because they have a more productive ability to predict, they are successfully applied in several health-care applications. ML approaches are needed thanks to the unsatisfactory experience of the novel virus, considerable ambiguity, complicated social circumstances, and inadequate accessible data. Several approaches have been applied as a tool to combat and protect against the new diseases. The COVID-19 outbreak has rapid growth, so it is not easy to predict the patients and resources within a specified time. ML is a strong approach in the fighting against the pandemic such as COVID-19. It is found significant to predict the susceptible, infected, recovered, or exposed persons and can assist the control strategies to block the spread of infections. This study critically examines the appropriateness and contribution of AI/ML methods on COVID-19 datasets, enhancing the understanding to apply these methods for quick analysis and verification of pandemic databases. © 2022 Elsevier Inc. All rights reserved.

6.
Indian Journal of Environmental Protection ; 42(6):694-702, 2022.
Article in English | Scopus | ID: covidwho-2011708

ABSTRACT

Due to the strict enforcement of lockdown, the air quality index improved drastically in the cities across the globe within a few days of lockdown globally. The present study was conducted in Jaipur city to evaluate the effect of lockdown phases on the concentrations of PM10, PM1 # NO2, SO2, CO and O3. Among the selected pollutants PM1 (-61.15%) and PM10 (-40.50%) witnessed the maximum reduction in the lockdown phase 1. Among others, gaseous pollutants also showed a declining trend, as N02(-69.61 %) witnessed maximum reduction followed by CO (-25%) and SO2(-13.74%). In contrast to this, the O3(+24.26%) showed the opposite trend. The decreasing trend of pollutant concentrations continued upto the 2nd phase of lockdown, after which conditional relaxations in restrictions led to an increase in pollutants. In comparison to last year (that is 2019) during the same period, the concentration of atmospheric pollutants in 2020 was found to be very low. Ultrafine particulate matter showed a decreasing trend throughout the study whereas coarse mode particles shows a decreasing trend till the 3rd phase of lockdown and increased later on. Whereas, most of the gaseous pollutants show a decreasing trend in almost all phases except O,showing a reverse trend. © 2022 Scientific Publishers. All rights reserved.

7.
International Journal of Academic Medicine and Pharmacy ; 4(3):45-51, 2022.
Article in English | EMBASE | ID: covidwho-1998207

ABSTRACT

Background: Amid this escalating pandemic crisis, adequate awareness about spread, control and prevention of COVID 19 is of utmost importance. As there is an emerging evidence on the presence of viable viral particles in the secretions and excreta of patients, untreated sewage, surfaces, it has become indispensable concern for the health care providers to be aware about the WASH (water, sanitation and hygiene) risks and practices. Hand hygiene is the leading measure for reducing healthcare-associated infections (HCAIs) and preventing the spread of antimicrobial resistance. Objective: The objective of this study was to evaluate the knowledge, attitude and practices of hand hygiene among housekeeping staff, technicians and attendants working in COVID-19 tertiary health care Centre. Materials and Methods: The study was conducted for the then present staff in JK hospital, COVID centre, Bhopal in the month of July, 2020. A standard form for recording the data was made. Housekeeping staff and attendants were involved from all the clinical departments. The tools for the data collection were: questionnaires including multiple choices, yes/no answers. A prior orientation was provided to the respondents regarding how to fill the questionnaire. The questions were verbally asked by the researcher and the responses were sought. Result: A total of 83 health care workers participated in the study. Amongst the total participants, 37.34% were males and 65.65% were females. Most of the participants were in the age group of 18-39 years, 69.88% of them had gained knowledge about infection control in COVID-19 through hospital, 74.70% of them had received training about hand hygiene in past 6 months. Comparing the pre and post training responses, it was observed that the knowledge component significantly increased on post training evaluation regarding correct steps of hand hygiene (90.31% from 55.01%). There was remarkable increment from 55.16% to 95.54% in the practice element of hand hygiene on post training evaluation for all the five moments. Women showed 42% improvement in their knowledge, attitude and practice of hand hygiene after training in comparison to men who did not show a significant habit change. Conclusion: Our study portrays moderate level of knowledge regarding many aspects of hand hygiene among health care workers. Education plays an important role in overcoming these barriers and makes it easy to incorporate changes in hand hygiene habits of healthcare workers. Middle aged workers show more sense of responsibility towards habit change as compared to the young.

8.
International Journal of Early Childhood Special Education ; 14(4):2603-2611, 2022.
Article in English | Web of Science | ID: covidwho-1979674

ABSTRACT

Individual awareness of the disease and adherence to preventative measures are essential for a successful response to the COVID-19 pandemic. Early media portrayals of COVID-19 health information may have an impact on public attitudes and behavior. To urge people to respond correctly, the media should ensure that its coverage is relevant, timely, and actionable. We looked at internet reportage in India to see how well the media conveyed health information regarding COVID-19 by WHO's Strategic Risk Communication standards Sixty-seven percent of publications that cited sources of information did so from reliable sources, including public health agencies and scholars. In addition, media coverage did not appear to reflect WHO changes promptly, with most of the material coming before the updates. According to the results, Indian media should focus on actionable and relevant news that gives individual reaction recommendations. To combat the spread of disinformation, the media should report on evidence-based preventive and treatment methods.

9.
Neurology ; 98(18 SUPPL), 2022.
Article in English | EMBASE | ID: covidwho-1925485

ABSTRACT

Objective: To explore various post covid immune mediatedneurological manifestations in children Background: The neurological manifestation following a SARS-CoV2 infection is varied and till now there are only few studies reported regarding the same. Our study aimed to identify the varied spectrum of neurological manifestation following SARS-CoV2 infection. Design/Methods: Retrospective data were collected from May 2021 to September 2021, including all children aged from 1month to 18 years of age who presented to our pediatric emergency or OPD (a tertiary care center from western Rajasthan, India) with the neurological manifestation with history of COVID-19 infection or exposure and positive SARS-CoV-2 serology. Those who are RT PCR positive were excluded. The neurological manifestations were further categorized in a pre-designed proforma. Results: Case records of the 18 children who fulfilled the criteria were included in the study, among them 7 (38.8%) were male and 11 (61.1%) were female. Predominant presentation in our study group was seizures (6/18) and Gullian Barre Syndrome (5/18). Other manifestations included stroke (2/18), ADEM (1/18), MS (1/18), LETM (1/18), Autoimmune encephalitis[NMDAR](2/18). In our study group, 13/18 (72.2%) required immunomodulatory therapy either IVIG or high dose methylprednisolone pulse therapy. Steroids were used upfront in patients with elevated inflammatory markers. Cerebrovascular complications in children were less common compared to adults. Most of the children had favourable outcomes except for one mortality in our cohort. Conclusions: Delayed complications following SARS-CoV2 infection with varied manifestations are seen in children. A temporal correlation between the COVID 19 infection and the increasing number of neurological cases after the second wave was noted. Steroids are beneficial while treating such patients. Testing for SARS-CoV2 serology during the pandemic can give a clue to the underlying etiology. However, further studies are required to understand the CNS effects of SARS-CoV2 infection in children.

10.
Journal of Communicable Diseases ; 2022:15-23, 2022.
Article in English | Scopus | ID: covidwho-1904117

ABSTRACT

Introduction: As new strains of SARCOV2 virus emerge across the world, it is imperative to investigate measures which restrict the movement of the general population such as social and travel restrictions by lockdowns to mitigate the effects of COVID-19. Thus, our paper helps in two ways: 1) Drastic measures like lockdown are essential but cannot be a feasible long-term intervention. Therefore, it is crucial to understand if the same unlock down can be reversed without compromising public health needs. Our paper provides evidence on the same;and 2) Our report also provides an insight into the trends of disease transmission during different phases of the un-lockdown. Methods: We examine the spread of pandemic during different phases of Un-lockdown (8th June to 31st October 2020). Since Rt calculation takes into consideration numerous factors, we use β, the transmission coefficient that governs the transition of population from Susceptible to Exposed pool, to examine the effect of public heaThelth interventions on disease spread. Results: The comparison of the distribution of fitted β values, thus calculated using SEIR model and GLM have been done and a Welch Two Sample t-test suggests that the GLM fitted β and SEIR β data sets are not significantly different from one another. Conclusion: We provide evidence that un-lockdown can be achieved without increasing the transmission of disease disproportionately. Thus, a phased wise approach to un-lockdown is encouraged. We also provide the rationale for using β over Rt values to specifically assess the effect of public health interventions designed to decrease exposure. Copyright (c) 2022: Author(s).

11.
Acta Neurologica Taiwanica ; 31(4):167-170, 2022.
Article in English | Scopus | ID: covidwho-1877042

ABSTRACT

Purpose: To highlight the factors leading to the delayed diagnosis of basilar artery occlusion and poor outcome in the postpartum period during the prevailing Corona Virus Disease-2019 (COVID-19) pandemic. Case report: We here report a case of a 34-year female who presented with a headache localized to the occipital region after cesarean section under spinal anesthesia. Her headache severity increased over time, and she developed a generalized seizure episode and became unconscious. Subsequently, basilar artery thrombosis was diagnosed. Despite all efforts, she succumbed to death. We believe that we might have saved the patient's life if we could have made the diagnosis beforehand. Conclusion: We recommend that unless shown otherwise, postpartum headache and neck discomfort, even in individuals with no known risk factors, should have a low index of suspicion, early diagnosis using non-invasive radiological study such MRI to rule out this uncommon but deadly illness quickly. © 2022, Neurological Society R.O.C (Taiwan). All rights reserved.

12.
International Journal of Ayurvedic Medicine ; 13(1):191-198, 2022.
Article in English | Web of Science | ID: covidwho-1848780

ABSTRACT

The rampant destruction due to COVID is going on. So far, in modern medical system, there is no proven cure for COVID-19. The only relevant literature on the treatment of corona virus disease comes from Traditional Chinese Medicine (TCM). TCM, which is widely used to control epidemics in China, is also composed of kinds of herbs similar to Ayurveda. There is reportedly a high death rate from severe COVID-19 infection requiring oxygen support. The chest severity score as assessed by computed tomography has predictive value for future outcomes in such situations. This paper is an observational (retrospective) study of COVID-19 condition of three patient receiving Ayurvedic treatment entirely without use of any allopathic drug. There is this case series of 3 patients, 32 years old male, 38 years old female and 70 years old female. These cases were managed on the principle of Sannipatika Jwar (type of fever) along with Shwas (type of respiratory illness) with administration of Hirak bhasma, Trailokya chintamani ras, Maha lakshmi vilas ras, Abhrak bhasma, Shwaskas chintamani ras, Praval pishti, Chandramrita ras, Sitopladi churna, Mahalaxmivilas ras, Sameerpannag ras, Tab Shwas kalpa and Syp Whooping for about 10 days in different combination in these patients. The treatment resulted in complete remission of almost all the signs and symptoms. The cases were followed up after next 15 days and there were no remnant symptoms. The cases also advocated for an early Ayurvedic intervention institution for COVID-19 in prevention, deterioration and complications.

13.
5th International Conference on Information Systems and Computer Networks, ISCON 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1759111

ABSTRACT

Today's generation wants everything easier, faster and automatic. During this corona pandemic, health and safety of each and every individual, either who is traveling through flights or working at an airport is a big issue. Usually, when we go to an airport, we go through many checks, and before boarding the flight, the security check-in, our luggage bags are counted and tagged by the person working at the counter of the airport. The luggage bags are put on the conveyor belt and the person working at the counter has to count the luggage bags by himself, he has to stick the tags on the luggage bags. None of the airports provides the facility of automatic counting of the luggage bags and sticking tags on them. And during this COVID-19 pandemic, we should avoid touching maximum things. This research paper provides a new technique for the same and that in a smart way. In this research, we are providing a novel approach to create an automatic system which will help to make the airport a smart one with IOT sensors and devices. Smart Airport also provides the counting of the luggage bags, tagging of the luggage bags, checking the presence of metallic objects in the luggage bags in a single embedded system. This approach will help the human society in maintaining social distancing and help them to save their time. © 2021 IEEE.

14.
New Mathematics & Natural Computation ; : 1-41, 2022.
Article in English | Academic Search Complete | ID: covidwho-1752910

ABSTRACT

Classical automata, fuzzy automata, and rough automata with input alphabets as numbers or symbols are formal computing models with values. Fuzzy automata and rough automata are computation models with uncertain or imprecise information about the next state and can only process the string of input symbols or numbers. To process words and propositions involved in natural languages, we need a computation model to model real-world problems by capturing the uncertainties involved in a word. In this paper, we have shown that computing with word methodology deals with perceptions rather than measurements and allows the use of words in place of numbers and symbols while describing the real-world problems together with interval type-2 (IT2) fuzzy sets which have the capacity to capture uncertainties involved in word using its footprint of uncertainty. The rough set theory, which has potential of modeling vagueness in the imprecise and ill-defined environment, introduces a computation model, namely, IT2 fuzzy rough finite automata, which is efficient to process uncertainties involved in words. Further, we have shown the application of introduced IT2 fuzzy finite rough automaton in the medical diagnosis of COVID-19 patients. [ FROM AUTHOR] Copyright of New Mathematics & Natural Computation is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

15.
Indian Pediatrics ; 59(1):58-62, 2022.
Article in English | Web of Science | ID: covidwho-1694234

ABSTRACT

Justification Recent research has provided evidence for lack of transmission of SARS-CoV-2 through human milk and breastfeeding. Updating the practice guidelines will help in providing appropriate advice and support regarding breastfeeding during the coronavirus 2019 (COVID-19) pandemic. Objectives To provide evidence-based guidelines to help the healthcare professionals to advise optimal breastfeeding practices during the COVID-19 pandemic. Process Formulation of key questions was done under the chairmanship of President of the IAP. It was followed by review of literature and the recommendations of other international and national professional bodies. Through Infant and Young child (IYCF) focused WhatsApp group opinion of all members was taken. The final document was prepared after the consensus and approval by all members of the committee. Recommendations The IYCF Chapter of IAP strongly recommends unabated promotion, protection and support to breastfeeding during the COVID-19 pandemic with due precautions.

16.
Journal of Pharmaceutical Research International ; 33(57B):178-188, 2021.
Article in English | Web of Science | ID: covidwho-1614276

ABSTRACT

COVID-19 patients have lower immunosuppressive CD4+ T and CD8+ T cells and henceforth patients in intensive care units (ICU) need mechanical ventilation, henceforward they stay in hospitals. These patients have been exposed to advances in fungal co-infections. COVID-19 patients progress towards mucormycosis a black fungal infection that is deadly leading to loss of sight and hearing and eventually death. This article discusses the clinical manifestations, risk factors and emphases on virulence traits and management of black fungus.

17.
Indian Pediatrics ; 22:22, 2021.
Article in English | MEDLINE | ID: covidwho-1527228

ABSTRACT

JUSTIFICATION: Recent research has provided evidence for lack of transmission of SARS-CoV-2 through human milk and breastfeeding. Updating the practice guidelines will help in providing appropriate advice and support regarding breastfeeding during the COVID-19 pandemic. OBJECTIVES: To provide evidence-based guidelines to help the healthcare professionals to advise optimal breast feeding practices during the COVID-19 pandemic. Process: Formulation of key question was done under the chairmanship of President of the IAP. It was followed by review of literature and the recommendations of other international and national professional bodies. Through Infant and Young child (IYCF) Powered by Editorial Manager R and ProduXion Manager R from Aries Systems Corporation focused WhatsApp group opinion of all members was taken. The final document was prepared after the consensus and approval by all members of the committee. RECOMMENDATIONS: The IYCF Chapter of IAP strongly recommends unabated promotion, protection and support to breastfeeding during the COVID-19 pandemic with due precautions.

18.
Computers, Materials and Continua ; 71(1):423-438, 2022.
Article in English | Scopus | ID: covidwho-1515730

ABSTRACT

Corona is a viral disease that has taken the form of an epidemic and is causing havoc worldwide after its first appearance in the Wuhan state of China in December 2019. Due to the similarity in initial symptoms with viral fever, it is challenging to identify this virus initially. Non-detection of this virus at the early stage results in the death of the patient. Developing and densely populated countries face a scarcity of resources like hospitals, ventilators, oxygen, and healthcareworkers. Technologies like the Internet of Things (IoT) and artificial intelligence can play a vital role in diagnosing the COVID-19 virus at an early stage. To minimize the spread of the pandemic, IoT-enabled devices can be used to collect patient's data remotely in a secure manner. Collected data can be analyzed through a deep learning model to detect the presence of the COVID-19 virus. In this work, the authors have proposed a three-phase model to diagnose covid-19 by incorporating a chatbot, IoT, and deep learning technology. In phase one, an artificially assisted chatbot can guide an individual by asking about some common symptoms. In case of detection of even a single sign, the second phase of diagnosis can be considered, consisting of using a thermal scanner and pulse oximeter. In case of high temperature and low oxygen saturation levels, the third phase of diagnosis will be recommended, where chest radiography images can be analyzed through an AI-based model to diagnose the presence of the COVID-19 virus in the human body. The proposed model reduces human intervention through chatbot-based initial screening, sensor-based IoT devices, and deep learning-based X-ray analysis. It also helps in reducing the mortality rate by detecting the presence of the COVID-19 virus at an early stage. © 2022 Tech Science Press. All rights reserved.

19.
Cmc-Computers Materials & Continua ; 69(3):3459-3475, 2021.
Article in English | Web of Science | ID: covidwho-1389993

ABSTRACT

In March 2020, the World Health Organization declared the coronavirus disease (COVID-19) outbreak as a pandemic due to its uncontrolled global spread. Reverse transcription polymerase chain reaction is a laboratory test that is widely used for the diagnosis of this deadly disease. However, the limited availability of testing kits and qualified staff and the drastically increasing number of cases have hampered massive testing. To handle COVID19 testing problems, we apply the Internet of Things and artificial intelligence to achieve self-adaptive, secure, and fast resource allocation, real-time tracking, remote screening, and patient monitoring. In addition, we implement a cloud platform for efficient spectrum utilization. Thus, we propose a cloud based intelligent system for remote COVID-19 screening using cognitive radio-based Internet of Things and deep learning. Specifically, a deep learning technique recognizes radiographic patterns in chest computed tomography (CT) scans. To this end, contrast-limited adaptive histogram equalization is applied to an input CT scan followed by bilateral filtering to enhance the spatial quality. The image quality assessment of the CT scan is performed using the blind/referenceless image spatial quality evaluator. Then, a deep transfer learning model, VGG-16, is trained to diagnose a suspected CT scan as either COVID-19 positive or negative. Experimental results demonstrate that the proposed VGG-16 model outperforms existing COVID-19 screening models regarding accuracy, sensitivity, and specificity. The results obtained from the proposed system can be verified by doctors and sent to remote places through the Internet.

20.
Journal of Association of Physicians of India ; 69(7):14-18, 2021.
Article in English | Scopus | ID: covidwho-1359618

ABSTRACT

Introduction: Remdesivir and Tocilizumab are two experimental drugs used in severely ill COVID-19 patients. Various clinical trials studying these drugs are giving conflicting results. Our aim is to study these two drugs and share the experience in our setting. Methods: Our Study is a retrospective analysis of Clinico-laboratory details and outcome of three groups of patients who were given either (i) Remdesivir or (ii) Tocilizumab or (iii)both Remdesivir and Tocilizumab . We compared the outcome of these patients with other patients who did not receive either of these drugs, when it was not available or not introduced as experimental drugs earlier in treatment guidelines. Results: Out of a total of 521 patients, in the above three groups who received either or both Remdesivir or Tocilizumab, 334 survived. Out of 214 patients who did not receive any of the two drugs only 74 survived. The outcome was better individually for all the three groups of patients receiving either or both of the drugs as compared to neither of the drugs.(p <0.01) Conclusion: Remdesivir and Tocilizumab were useful drugs in treatment of severely ill covid -19 patients as compared with the patients who did not receive any of the above drugs. © 2021 Journal of Association of Physicians of India. All rights reserved.

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