Forecasting COVID-19 Pandemic using Prophet, LSTM, hybrid GRU-LSTM, CNN-LSTM, Bi-LSTM and Stacked-LSTM for India

The COVID-19 Pandemic has been around for four years and remains a health concern for everyone. Although things are somewhat returning to normal, increased incidence of COVID-19 cases in some regions of the world (such as China, Japan, France, South Korea, etc.) has bred worry and anxiety in world, including India. The scientific community, which includes governmental organizations and healthcare facilities, was eager to learn how the COVID-19 Pandemic would develop. The current work makes an attempt to address this question by employing cutting-edge machine learning and Deep Learning algorithms to anticipate the daily incidence of COVID-19 for India over the course of the next six months. For the purpose famous timeseries algorithms were implemented including LSTM, Bi-Directional LSTM and Stacked LSTM and Prophet. Owing to success of hybrid algorithms in specific problem domains- the present study also focuses on such algorithms like GRU-LSTM, CNN-LSTM and LSTM with Attention. All these models have been trained on timeseries dataset of COVID-19 for India and performance metrics are recorded. Of all the models, the simplistic algorithms have performed better than complex and hybrid ones. Owing to this best result was obtained with Prophet, Bidirectional LSTM and Vanilla LSTM. The forecast reveals flat nature of COVID-19 case load for India in future six months. . © 2023 IEEE.

Knowledge, attitude, and oral hygiene practices among law students in Davangere City: A cross-sectional study

Aim: The aim of this study was to assess dental health awareness and oral hygiene practice among law students of R L Law College, Davangere, Karnataka. Materials and Methods: A questionnaire containing 30 questions, regarding basic knowledge, attitude, and practice was distributed among 150 Law students of R L Law college of Davangere, Karnataka, India. The data obtained were tabulated in Microsoft Excel and statistically analyzed in the Statistical Package for the Social Sciences (IBM Corporation) software. Results: In the present study, only 39.4% of the participants were aware of routine dental check-ups. 8.5% of the participants visited the dental clinic twice a year and 57% of the participants had never visited a dental clinic. 37.3% of the participants were aware of oral hygiene aids. 62% of the participants used a tongue cleaner routinely and 55.5% brushed their teeth using only horizontal brushing technique. 48.6% were aware that consuming tobacco causes cancer. Only 9.2% consumed tobacco in various forms. 49% of the participants felt that all dental procedures were painful and expressed fear. 81% of the students were unaware of dental fluorosis. 65.5% of the participants agreed that dental health education is important and 21.8% thought that it might be important. Inferential statistics using the Pearson Chi-square test showed that there was a statistically significant correlation between the responses and the Year of law degree the participant was pursuing. Conclusion: In the present study, law students have satisfactory knowledge about good oral hygiene practices and oral health care. However, the knowledge acquired must be transferred into daily practice. This can be achieved by a change in their attitude toward oral hygiene maintenance. The inclusion of oral health-oriented education programs in their curriculum would improve their knowledge along with behavior, and they would be a good model to the community. This study will help us in devising an outline for the oral hygiene education of Law students of our country based on their current attitude, knowledge, and oral hygiene practice.

Severity in schizophrenia patients receiving atypical antipsychotic medications

Atypical antipsychotic drugs are nowadays the mainstay of treatment of schizophrenia due to their lesser extrapyramidal symptoms (EPS) as adverse effects. However, these drugs have different profiles of adverse drug reactions (ADRs). Here, the objective of this study was to analyze the probability, occurrences, and more significant involvement of various risk factors. A prospective observational study was carried out on a patient with schizophrenia who has prescribed atypical antipsychotic drugs for their treatment. The probability of the ADR was analyzed by using the Naranjo causality assessment scale. While Glasgow antipsychotic Side effect Scale (GASS) was used to estimate the severity of side effects. Statistical software for social science (SPSS) ver 25;was used for different descriptive statistics and chi-square analysis. A total of 140 patients were included in the study of which the majority (58.57 %) was male. However, atypical antipsychotic drugs were primarily prescribed to the patient as mono therapy (81.43 %). Interestingly, COVID-19 infections were reported as positive in 39.29 % of total patients. Probability assessment of ADRs revealed that most (55 %) were "Probable". Subsequently, the GASS score was evaluated for severity, the majority (55.71 %) were reported as "Mild". The statistically significant association between gender and severity of side effects &duration of illness and severity of side effects were found (P>0.5).The Present study aids in knowing the risk factors and improving the management practices of ADR, thereby improving the guidelines in terms of safe clinical approaches for psychiatric patients.

The epidemiological characteristics of the admitted cases of COVID-19 in a tertiary hospital in India

Introduction: COVID -19 disease broke out in Wuhan, China at the end of 2019 and the deadly virus spread out rapidly worldwide by the end of March 2020. India has the second largest number of cases in the world with 1,05,95,660 COVID 19 cases and has had 1,52,718 deaths at the end January 2021.3 As it is a new emerging infectious disease, it is a challenging task for the health system to manage the pandemic. This study will provide epidemiological characteristics of COVID-19 in Indian population which will help to make new policies and programs. Aim and Objective: To study the epidemiology of COVID-19 cases in a tertiary care hospital in North India. Material(s) and Method(s): This Retrospective study included 2985 patients treated as COVID -19 positive cases admitted in AIIMS Trauma centre-JPNATC (Jai Prakash Narayan Apex Trauma Centre - JPNATC). The patient's data were collected between 1st April 2020 to 30th October 2020 from AIIMS -EWD and CPRS platform were COVID 19 data recorded. Demographic details such as age, gender, date of admission for COVID-19 and the outcome were collected and analyzed. Result(s): A total number of 2985 cases were included in this study. The mean+/-SD age of the male patients were 44.37 +/-19.65 and mean+/-SD female patients were 45.75 +/- 19.58. The majority were male patients constituted 62.5% of the sample. The mean+/-SD age of the male patients were died during the treatment 51.75 +/-18.68 and female 51.31 +/- 18.71. The death ratio of male: female was 1.78Copyright © 2020 Ubiquity Press. All rights reserved.

Structure Based Drug Design Approach to Identify Potential SARS-CoV-2 Polymerase Inhibitors

Aims: The research work aims to apply the current virtual screening approaches for rapid screening of available compounds as inhibitors of the novel coronavirus (COVID-19). Background(s): The worldwide pandemic, uncontrolled spread, and lack of effective therapeutics demand novel SARS-CoV-2 inhibitory anti-viral agents. Objective(s): The major objectives of the present work are - i) effective utilization of open-source com-puter-aided drug design (CADD) tools;ii) to prepare a database according to chemical structure similarity to the reported anti-viral drug, Favipiravir;and iii) to investigate potential inhibitors of the novel coronavirus. Method(s): The dataset was prepared based on the chemical structure similarity feature of ChemSpider. The virtual screening was carried out using molecular docking and ADMET properties. For performing molecular docking studies, the standard docking protocol of iGEMDOCK was used. Result(s): Based on chemical structure similarity search to Favipiravir, a small library of 40 compounds was designed. The docking score and ADMET properties were analyzed to prioritize the compounds. Conclusion(s): The virtual screening resulted in the identification of potential anti-viral compounds. Among the designed library of compounds based on structural similarity to Favipiravir, 70% of compounds were found to possess docking scores more than that of Favipiravir. The amino acid residues involved in binding at the RNA dependent RNA polymerase (RdRp) were identified. The compounds have shown acceptable ADME properties and are potentially non-toxic. Other: The study has successfully applied the open-source CADD tools to investigate the novel SARS-CoV-2 polymerase inhibitors.Copyright © 2021 Bentham Science Publishers.

Acute motor and sensory axonal neuropathy in a patient with undiagnosed mixed connective tissue disease

Case Report: Acute motor and sensory axonal neuropathy (AMSAN) syndrome is a rare subtype of Guillain-Barre syndrome (GBS) with poor recovery [1]. While respiratory and gastrointestinal infections may precipitate AMSAN, an underlying autoimmune disorder is seldom reported in literature. We herein report the complex case of a patient with undiagnosed, asymptomatic mixed connective tissue disease (MCTD) who developed AMSAN syndrome. Case: A 44-year-old Asian male without medical history presented with progressively worsening weakness of both upper and lower extremities and inability to perform daily activities. His symptoms started 12 weeks prior with difficulty standing from a seated position. He felt subjectively better for some time until a week prior, when he became bedbound. He had diarrhea 6 months ago, with 5-6 loose bowel movements a day for a few weeks. Vital signs on admission was normal. On neurological examination, he was alert and oriented, with bilateral upper and lower extremity flaccid paralysis, diffuse muscle atrophy, bilateral hand and foot drop, negative Hoover sign, diffuse areflexia, and intact sensation. Cerebrospinal fluid (CSF) analysis showed WBC 0 and protein level 136. MRI cervical, thoracic, and lumbar spine were normal. EMG revealed sensory involvement with positive sharp waves in proximal muscles along with fibrillations. Intravenous immunoglobulin (IVIG) was initiated at 0.4 mg/kg for 5 days. Infectious workup for COVID-19, stool culture, HIV, TB, RPR and campylobacter jejuni antibody (Ab), was negative. ANA was positive in a speckled pattern with titres 1:1280, with a positive RNP Ab, SS-A, and RF IgM, IgG and IgA. Rest of the autoimmune workup (anti-dsDNA, anti-CCP, SS-B, aldolase, anti-Jo-1, anti-Scl-70, p-ANCA, c-ANCA, anti-GM1, anti-GQ1b, and anti-GD1a ganglioside Ab) was negative. The myositis specific 11 Ab panel was negative. Despite IVIG therapy, he developed dysphagia, respiratory distress, with a negative inspiratory force of -0, requiring intubation. He had a tracheostomy and PEG tube placed and remains quadraplegic nearly 120 days later. Discussion(s): The authors report a unique case of a patient who became progressively weak over 3 months, leading to complete quadriplegia. Interestingly, this is more consistent with chronic inflammatory demyelinating poly-neuropathy (CIDP), as AMSAN typically develops over a short period of 2 to 4 weeks [2]. Despite having negative anti-GM1 and anti-GD1a Ab (in which positive Ab are pathognomonic but not always present in AMSAN syndrome), the patient had weakness that began in the lower extremities, progressing to paralysis, along with albuminocytological dissociation on CSF analysis, pointing to a GBS diagnosis [3]. He had sensory involvement in the EMG, thus making the diagnosis as AMSAN. He had an undiagnosed, asymptomatic autoimmune process most consistent with MCTD. Whether the two disease processes are related to each other is a concept that has not yet been investigated. Pediatric Clinical Case Reports Concurrent Session Saturday February 4, 2023 1:00 PM Copyright © 2023 Southern Society for Clinical Investigation.

Smart Contract-Based Secure Decentralized Smart Healthcare System

Social distancing has been imposed to prevent substantial transmission of the COVID-19 outbreak, which is presently a global public health issue. Medical healthcare providers rely on telemedicine to monitor their patients, particularly those with chronic conditions. However, telemedicine faces many implementation-related risks, including data breaches, access restrictions within the medical community, inaccurate diagnosis, fraud, etc. The authors propose a transparent, tamper-proof, distributed, decentralized smart healthcare system (DSHS) that uses blockchain-based smart contracts. The authors use an immutable modified Merkel tree structure to hold the transaction for viewing contracts on a public blockchain, updating patient health records (PHR), and exchanging PHR to all entities. It is verified by a performance evaluation based on the Ethereum platform. The simulation results show that the proposed system outperforms existing approaches by enhancing transparency, boosting efficiency, and reducing average latency in the system. The proposed system improves the functionality of the SHS environment.

Predicting COVID-19 Fourth Wave Incidence in India Using Machine Learning Algorithms and SEIR Model

The world is witnessing COVID - 19 Pandemic for quite some time now. India has seen three waves of COVID-19 in the last 700 days. The curiosity still lies in the occurrence and timing of the fourth wave. The current study tries to solve this and predicts the COVID-19 daily incidence in India in the future. State-of-the-art methodologies both from Machine learning (LSTM, KNN, SVR, Random Forest, and Multi Linear Regressor) and Mathematical models (SEIR) have been tried out to train and predict the Daily New Cases of COVID19 in India. Further prediction for the next 200 days has been tried out using the trained models. As per the forecast from most of the models, it is evident that no fourth wave is going to be witnessed in India in the next 200 days. © 2022 IEEE.

Halting the COVID-19 Widespread: A Audit on the Progresses of Determination, Treatment, and Control Measures

Efforts to prevent the transmission of the SARS-CoV-2 infection are critical in light of the ongoing worldwide spread of COVID-19. Recently developed diagnostic tools include CRISPR, IgG tests, spike protein detection, and artificial intelligence. RT-PCR has been replaced with point-of-care assays, which may be performed at the patient's bedside (RT-PCR). All of these options are available to treat the disease: antivirals and other antiparasitic agents, anti-inflammatory medications like interferon or convalescent plasma, monoclonal antibodies like gamma-globulin, and RNAi treatments like mesenchymal stem cell therapy are among the options (ECMO). More than a dozen different types of vaccines are now being tested in clinical studies. Furthermore, breakthrough technologies that are easily deployable and transportable.In addition, vaccination delivery technologies are being developed. The threat of a second wave of infection needs strict and reasonable control mechanisms to keep mortality to a minimal when governments begin to loosen their lockdown tactics. Research into COVID-19's advances in diagnostics and treatment may serve as a platform for future research that can lead to improved containment strategies. Copyright © 2023 Ubiquity Press. All rights reserved.

Smart Contract-Based Secure Decentralized Smart Healthcare System

Social distancing has been imposed to prevent substantial transmission of the COVID-19 outbreak, which is presently a global public health issue. Medical healthcare providers rely on telemedicine to monitor their patients, particularly those with chronic conditions. However, telemedicine faces many implementation-related risks, including data breaches, access restrictions within the medical community, inaccurate diagnosis, fraud, etc. The authors propose a transparent, tamper-proof, distributed, decentralized smart healthcare system (DSHS) that uses blockchain-based smart contracts. The authors use an immutable modified Merkel tree structure to hold the transaction for viewing contracts on a public blockchain, updating patient health records (PHR), and exchanging PHR to all entities. It is verified by a performance evaluation based on the Ethereum platform. The simulation results show that the proposed system outperforms existing approaches by enhancing transparency, boosting efficiency, and reducing average latency in the system. The proposed system improves the functionality of the SHS environment. © 2022 Taru Publications. All rights reserved.

An inexpensive and rapid diagnostic method for detection of SARS-CoV-2 RNA by loop-mediated isothermal amplification (LAMP).

SARS-CoV-2 is a public pandemic health concern globally. Nasopharyngeal and oropharyngeal swab samples are used for Covid-19 viral detection. Sample collection procedure was tedious and uncomfortable and unsuitable for biochemical and CBC analysis in swab samples. Biochemistry and CBC tests are key determinant in management of Covid-19 patients. We developed a LAMP test to detect viral RNA in blood samples. LAMP is required four specific primers targeting the internal transcribed S-region and loop primers for viral RNA amplification. RNA was extracted from blood samples by TRIzol method. LAMP reaction was performed at 60 °C for 1 hour and amplicons were visualized in HNB dye. No cross-reactivity was seen with HBV, HCV, and HIV infected sample. Out of 40 blood samples, 33 samples were positive for LAMP and Q-PCR analysis, one sample was positive for LAMP and negative for Q-PCR, two samples were negative for LAMP but positive for Q-PCR, and four blood samples were negative for LAMP and Q-PCR. LAMP method has an accuracy of 92.50%, with sensitivity and specificity of 94.28% and 80%, respectively. Thus, LAMP diagnostic test has proved reliable, fast, inexpensive and can be useful for detection where the limited resources available.•LAMP method is a potential tool for detection of SARS-CoV-2.•Blood samples are the key determinant for routine diagnostics as well as molecular diagnostics.•LAMP assay is an appropriate diagnostics method which offers greater simplicity, low cost, sensitivity, and specificity than other methods in molecular diagnostics.

Evaluating the impact of Industry 4.0 technologies on medical devices manufacturing firm’s operations during COVID-19

There is a strong opinion about the impact of Industry 4.0 (I4.0) technologies on the operations performance of manufacturing firms. However, there are several challenges while evaluating such situations. Determining the significance of I4.0 technologies in the context of the pandemic situation must consider several criteria for exhaustive understanding. This study aims to determine the significance and impact of I4.0 technologies on medical devices manufacturing firms’ operations during the COVID-19 outbreak. The set of technologies of I4.0 is evaluated over productivity, quality, cost, delivery, health, and safety parameters using a fuzzy analytical hierarchy process. The study reveals that the significance of big data analytics, autonomous robotics, and industrial internet of things (IIoT) in the business continuity of medical device manufacturing operations during the COVID-19 outbreak is high. Cloud technologies, digital simulations and augmented reality follow the order. Copyright © 2022 Inderscience Enterprises Ltd.

Social Distance Monitoring to Enhance the Safety from COVID-19 Infection

The best precaution in the COVID-19 pandemic period is social distancing. Despite being aware of these, people often violate social distance and take down their masks in public places, knowingly or unknowingly. This unawareness is the primary reason for public places like retail shops, bus stops, public transport, educational institutions, hospitals, and clinics to become increasingly inaccessible and COVID-19 hotspots. It would be practically impossible for anyone to make sure everyone is following social distancing in a public place;a human will not be able to see beyond his field of view. An automated CCTV-based real-time system could help in monitoring the crowd. The proposed model takes a video stream as input, segments people using a CNN-object detection algorithm (YOLO), anchors objects' locations, and finds the distance between them. The system then marks bounding boxes around people who do not follow social distancing. Using pixel coordinates of violating people can accurately mark and alert security personnel or display wherever social distancing is violated. © 2022 IEEE.

Impact of aerosols and reactive trace gases concentrations in India

The concentration of reactive trace gases in the atmosphere affects the human health differently. This study presents the changes of aerosol and reactive gases load in the atmosphere from the recent past with the help of Copernicus Atmosphere Monitoring Service (CAMS) data in Indian domain. The EAC4 (ECMWF Atmospheric Composition Reanalysis 4) data sets were used to examine spatially the load of ambient trace gases (NO2, O3, SO2 & CO) and aerosol present in the atmosphere as aerosol optical depth(AOD). The four weekly phases of the study are for April, 2020 (01-07, 08-14, 15-21 & 22-30). It has been observed during the above said phases that the concentration of aerosols, chemically reactive gases and greenhouse gases shows appreciable reduction up to ~60-70 % from CAMS Long Period Average (LPA) 17 years (2003-2019) data over the entire Indian sub-continent, except few pockets of Central (Durg, Indore, Bilaspuretc.) and South West (Kolhapur, Gujaratetc.) India. These slightly higher values in 2nd and 3rd week of April-2020 are due to pre-monsoon dust storm activity and well captured in vertical air flow Omega at 850/NCAR reanalysis. Concentrations of reactive gases from 12 different Central Pollution Control Board (CPCB) stations of India with CAMS, LPA data of April-2019 & 2020 has been compared and show that aerosol load in terms of PM-2.5 & PM-10 is appreciably drop down (60-70 %) over IGP and 25-30 % in other parts of India. The concentration of other reactive gases (NO2, SO2 & CO) with actual data from the month of April, 2019 &2020 also decreases ~ 32 %, 7 %, 17 % over IGP and 16 %, 8 %, 9 % in other parts of India respectively. The concentration of Ozone shows slightly positive behaviour over IGP and negative at other parts of India. This study is further brought out a message for future that we should use the natural resources judiciously as their long term exposure can cause severe health problems and a psychological burden or stress globally during this COVID-19 spread period. © 2022, India Meteorological Department. All rights reserved.

A Comparative Study of Work Life Balance in Engineering Consultancies in NCR during COVID-19

The paper determines the level of work life balance (WLB) while work from home and while attending the office regularly. The participants were same and they have to rate the Work Life Balance assuming themselves in both the situations. The two groups compared were male employees and female employees. The participants were taken randomly from four engineering consultancies in NCR (Jacobs Engineering, Tractebel Engineering, Bechtel India Pvt. Ltd. and Ercom Engineers Pvt. ltd.). 124 completed responses found to be completed. Further the study compares the mean values of Work Life Balance while work from home and regular office among male and female employees. The results reveal that the employees can maintain the WLB level well while work from home. The hypothesis testing results show that there is no significant difference among the male and female employees in the level of Work Life Balance while work from home and regular office. © 2022 University of Stockholm. All rights reserved.

A critical review of literature to reveal Covid-19 effect on mental health

Over 26,13,73683 cases and 52,12,961 verified fatalities have been documented because of the Corona pandemic so far. As a result of such extensive epidemics, mental health issues are more likely to occur. Keeping this in mind, the medical databases were used to locate relevant research on the Corona epidemic and mental health. Classification and summarization of previously published articles were carried out in accordance with the articles' overarching topics. In the early stages of the Corona pandemic, symptoms of anxiety, sadness, and self-reported stress (ranging from 16–28 percent) are frequent and may be linked to disrupted sleep. Several factors, both personal and institutional, influence this risk. In designing services for these groups, consideration must be given to both the requirements of the individuals affected and the appropriate preventative recommendations. Only a handful of the impacted nations have been documented in the literature, which may not accurately reflect the experiences of people in other areas of the world. As a result of the Corona epidemic, many people have developed subsyndromal mental health issues. For disadvantaged communities in other nations, there is a need for more representative studies. However, the current study explores the four main studies undertaken in China, which were chosen out of a total of 28 articles and after careful selection were delineated for study, the methodology gives the selection criterion in detail. © MEDIC SCIENTIFIC, All rights reserved.

Human Computer Model for E-learning in Pandemic of Covid-19

The concept of e-learning is not new to the education sector. However, in the recent years, with the outbreak of COVID-19, the importance of e-learning has grown globally. It has completely transformed the way in which learning is imparted to students. Unlike traditional chalk and board method of teaching, e-learning makes learning simpler, easier, and more effective. Earlier the access to knowledge was not accessible to all. Students with economic constraints, geographical boundaries or physical disabilities had scarce opportunities in the academic province. The concept of online education has broken all these barriers. Today's learners are engaged in appropriate, mobile, self-paced, and customized content. This need is satisfied by the online style of learning, where students can study at their own convenience and demand. This research work has proposed an E-Learning Website for Beginners especially designed keeping in mind the students of rural areas and backward classes who may not have access to correct and sufficient resources to learn the tools which are required in day-to-day life. The web-application will provide the user a complete basic knowledge on the various Microsoft Office Tools through videos, images and text materials provided on the platform. There is a quiz at the end of every course, so that students can examine themselves. Students can also download the course material from the platform. Being an open-source platform, this e-learning website can be used by any school or college students. © 2022 IEEE.

Awareness and Skills of Modern Telemedicine Practice among Doctors in Kerala-A Cross-sectional Study

Introduction: In this modern era of technology, Information and Communication Technology (ICT) has made a very big revolution. Telemedicine is an emerging concept in health care services in Kerala, its implementation has not been satisfactory and successful. It is cost effective and provides easy access to healthcare services for people anywhere and especially during pandemic situations like this. A study is required in the domain of awareness and skill of doctors to facilitate its adoption and implementation. There was an urgent need to devise means for patients to consult doctors during Coronavirus Disease 2019 (COVID-19) pandemic. Aim: To assess the level of awareness and skill among doctors practicing modern medicine during COVID-19 pandemic. Materials and Methods: A cross-sectional study was conducted among 535 modern medicine doctors of Kerala from June 2020 to May 2021, using a structured self-administered questionnaire designed for the study. The total scores of awareness and skill calculated and categorised as poor, moderate, and good. Data was analysed by Statistical Package for the Social Sciences (SPSS) version 20.0 software by IBM. The Chi-square test/Fisher's-Exact test was used as test of significance. Results: Mean age of the study participants were 40.44±10.66 years, with majority 326 (60.94%) been females. Among the 535 doctors participated, 68.22% had moderate skill, 27.85% have good skill and only 3.92% have poor skill. Years of experience of doctors ranged from 1 to 48 with mean of 13.47±10.46 years. In majority, 431 (80.56%) of the participants, had moderate awareness about the telemedicine practice. Poor awareness was present in 19 (3.55%) doctors. 46.54% believes that specific software training is required for practicing telemedicine. Conclusion: The study showed that 15.89% had good awareness, while 80.56% of the participants had moderate awareness about the telemedicine. Only 27.85% of doctors had good skill, while 68.22% had moderate skill. Even though, awareness and skill of doctors practicing modern medicine are favourable, more webinars or workshops are needed to improve their knowledge.