Forecasting of Novel Corona Cases in India Using LSTM-Based Recurrent Neural Networks

Novel corona disease is spreading all over the world. The cases of the corona virus are increasing drastically day by day. Therefore, it is necessary to predict the cases in advance to handle the condition. Recently, machine learning comes into the picture of researchers to solve the problem in engineering. The present study is focused to the application of LSTM recurrent neural network to predict the Novel corona cases on the daily basis in India. Various RNN models are used in this study, and performance evaluation of each model is carried out using different statistical parameters such as mean absolute error (MAE), mean absolute percentage error (MAPE), route mean square error (RMSE), and coefficient of determination (r2-score) for regression problems. From the study, it is concluded that the LSTM RNN model can be utilized for the prediction of the novel corona cases. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

A new fractional mathematical model to study the impact of vaccination on COVID-19 outbreaks

This study proposes a new fractional mathematical model to study the impact of vaccination on COVID-19 outbreaks by categorizing infected people into non-vaccinated, first dose-vaccinated, and second dose-vaccinated groups and exploring the transmission dynamics of the disease outbreaks. We present a non-linear integer order mathematical model of COVID-19 dynamics and modify it by introducing Caputo fractional derivative operator. We start by proving the good state of the model and then calculating its reproduction number. The Caputo fractional-order model is discretized by applying a reliable numerical technique. The model is proven to be stable. The classical model is fitted to the corresponding cumulative number of daily reported cases during the vaccination regime in India between 01 August 2021 and 21 July 2022. We explore the sensitivities of the reproduction number with respect to the model parameters. It is shown that the effective transmission rate and the recovery rate of unvaccinated infected individuals are the most sensitive parameters that drive the transmission dynamics of the pandemic in the population. Numerical simulations are used to demonstrate the applicability of the proposed fractional mathematical model via the memory index at different values of 0.7,0.8,0.9 and 1. We discuss the epidemiological significance of the findings and provide perspectives on future health policy tendencies. For instance, efforts targeting a decrease in the transmission rate and an increase in the recovery rate of non-vaccinated infected individuals are required to ensure virus-free population. This can be achieved if the population strictly adhere to precautionary measures, and prompt and adequate treatment is provided for non-vaccinated infectious individuals. Also, given the ongoing community spread of COVID-19 in India and almost the pandemic-affected countries worldwide, the need to scale up the effort of mass vaccination policy cannot be overemphasized in order to reduce the number of unvaccinated infections with a view to halting the transmission dynamics of the disease in the population. © 2022 The Author(s)

A new fractional mathematical model to study the impact of vaccination on COVID-19 outbreaks

This study proposes a new fractional mathematical model to study the impact of vaccination on COVID-19 outbreaks by categorizing infected people into non-vaccinated, first dose-vaccinated, and second dose-vaccinated groups and exploring the transmission dynamics of the disease outbreaks. We present a non-linear integer order mathematical model of COVID-19 dynamics and modify it by introducing Caputo fractional derivative operator. We start by proving the good state of the model and then calculating its reproduction number. The Caputo fractional-order model is discretized by applying a reliable numerical technique. The model is proven to be stable. The classical model is fitted to the corresponding cumulative number of daily reported cases during the vaccination regime in India between 01 August 2021 and 21 July 2022. We explore the sensitivities of the reproduction number with respect to the model parameters. It is shown that the effective transmission rate and the recovery rate of unvaccinated infected individuals are the most sensitive parameters that drive the transmission dynamics of the pandemic in the population. Numerical simulations are used to demonstrate the applicability of the proposed fractional mathematical model via the memory index at different values of 0.7,0.8,0.9 and 1. We discuss the epidemiological significance of the findings and provide perspectives on future health policy tendencies. For instance, efforts targetting a decrease in the transmission rate and an increase in the recovery rate of non-vaccinated infected individuals are required to ensure virus-free population. This can be achieved if the population strictly adhere to precautionary measures, and prompt and adequate treatment is provided for non-vaccinated infectious individuals. Also, given the ongoing community spread of COVID-19 in India and almost the pandemic-affected countries worldwide, the need to scale up the effort of mass vaccination policy cannot be overemphasized in order to reduce the number of unvaccinated infections with a view to halting the transmission dynamics of the disease in the population.

Sampling and analytical techniques for COVID-19

In March 2020, the novel corona virus disease 2019 was declared as pandemic as the disease had started transmitted rapidly, worldwide many death cases were reported due to the fast-spreading of virus. Plenty of researches were carried out and some are still in progress to know the causative agent of SARS-CoV-2 and also on antiviral treatment to cure this disease. Many sample specimens such as Nasopharyngeal specimens, nasal wash, saliva, sputum, Oropharyngeal specimens, blood, tracheal aspirate, Bronchoalveolar lavage fluid, urine and environmental sampling were used to detect corona virus, while several analytical techniques such as nucleic acid based techniques which are RT-PCR, and RT-LAMP as well as immunological assays such as ELISA, LFIA, neutralization assays, and luminescent immunoassays were used to detect Corona virus from the sample and a vibrant understanding about the sampling and analytical technique is of paramount significance. In this chapter, the different human sample collection method with their merits such as ease to collect, prominent result and many more as well as their demerits are discussed. Apart from that, the immunological assays to detect the cause of past infection and antibodies and also the most commonly used RT-PCR method for COVID-19 and limitation of this technique along with other alternative techniques are also discussed in detail. © 2022 Elsevier Inc. All rights reserved.

Analysis of the Adomian decomposition method to estimate the COVID-19 pandemic

Several techniques, including mathematical models, have been explored since the onset of COVID-19 transmission to evaluate the end outcome and implement drastic measures for this illness. Using the currently infected, noninfected, exposed, susceptible, and recovered cases in the Indian community, we created a mathematical model to describe the transmission of COVID-19. In particular, we used the semianalytical Adomian decomposition method without considering any discretization to perform the first-order differential equations related to COVID-19 cases. According to our early findings, rigorous initial isolation for 22-25days would reduce the number of exposed and newly infected people. As a result of the downstream effect, the number of suspected and recovered persons would remain stable, assuming that social distance is properly recognized. In a larger sense, the parameters established by our mathematical model may aid in the refinement of future pandemic tactics. © 2022 Elsevier Inc. All rights reserved.

Can new education policy 2020 serve as a paradigm shift to the employability gap in India? A viewpoint

Employment and employability have lately surfaced as a significant concern for India that stands as the world's second central higher education system. The post-COVID-19 era further demanded a comprehensive policy at the national level. The Indian government approved the new education policy (NEP), bringing changes to higher education in the country on 29th July 2020. After an exhaustive reading of all education policies published in Indian literature, the authors present this viewpoint chapter, contributing to the extant literature on education policies in the following three ways. The first purpose is to evaluate and compare the current NEP 2020 to the last two educational policies of 1968 and 1986 to understand how far each policy could realize the goal of employability. The second purpose is to adumbrate the gaps between industry and academia in the proposed NEP 2020 to propose some transformative steps to fill the outlined gap. Thirdly, the main findings are depicted through a graphical representation to give some directions for future policy and research in employability. © 2022, IGI Global. All rights reserved.

Evaluation of some plant-derived natural ingredients against SARS-CoV-2: an in-silico approach

Background: The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), infected by a new strain of human coronavirus, has engulfed the whole globe with its vicious potential to eradicate humankind. The pandemic has emerged from the Wuhan provinces of China with high transmissibility. Researchers are rushing to discover vaccines and drugs for the disease, which is not known yet. In this study, we have focused on the in-silico screening of phytochemicals occurring naturally in plant extracts that could possibly interact with receptor binding motif (RBM) of spike protein and thereby inhibit virus-cell interaction. Materials and Methods: In this study, we have taken 100 phytochemicals that have been studied in various viral interactions and have shown antiviral properties. Initially, these compounds were analyzed on the basis of their physicochemical and pharmacokinetic properties, biological activities, possible target interactions, similar compounds in humans, and gene regulations using bioinformatic tools, namely Swiss-ADME, PASS (prediction of activity spectra for substances), SwissTargetPrediction, similar ensemble approach (SEA) search server, DIEGP-pred, respectively and were filtered out on the basis of immunobiological activities and expression of genes involved in cytokine storm regulation and immunostimulation. Further, they were docked with the receptor-binding domain (RBD) of spike protein in the SARS-CoV-2 using SwissDock and analyzed by UCSF Chimera.

Assessment of RT PCR diagnostic assays for SARS CoV-2 detection in a Molecular diagnostic & Research Lab

Background: SARS CoV-2 infection took the whole world by storm in the final month of 2019.Different measures have been taken to reduce its spread by timely and accurate detection of COVID 19(coronavirus disease 2019) infection in suspected patients and theircontacts. Aim: This study was conducted to assess commercially available five Rt pcr (reverse transcriptase polymerase chain reaction) kits from different manufacturers available in our center for diagnostic testing ofSARS CoV-2 infection .94 oropharyngeal clinical samples, previously confirmed as 64 positive and 30 negative for SARS CoV-2 were extracted and amplified separately by each of the five Rt pcr kitsand the results compared. Results:The performance of different kits was in was satisfactory and above 90 percent in agreement with the standard kit for samples (n=47) with low Ct values (Ct values<30) . There was a significant variation in performance among the five kits while testing high Ct values (Ct value >30) samples (n=17).Significant variation in Ct values of E gene ,RdRp gene and N gene was observed in the Rt pcr kits results . Conclusion: We conclude that it is necessary to assess the diagnostic performance of different Rt pcr kits for COVID 19 clinical samples from time to time to study the variation in Ct values, sensitivity of different gene targets of SARS CoV2 virus, with proper co -ordination with other laboratories , for development of reliable COVID 19 diagnostic centers at every level.

Parameter Estimation and Early Dynamics of COVID-19 Disease

In this article, we have considered nine countries where the epidemic shows steady state or has a rising trend and used the traditional SEIR model to estimate the parameter for COVID-19 disease. These parameters are contact rate, removal rate, basic reproduction number, initial doubling time, point of inflection, and epidemic rate. In another part of the work, we have considered five countries where the epidemic trend has not settled and used exponential smoothing technique to forecast the infected cases. The study reports a magnifiable concern for reducing the transmission rate in order to combat the disease. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Modeling and analysis on the transmission of covid-19 Pandemic in Ethiopia

The newest infection is a novel coronavirus named COVID-19, that initially appeared in December 2019, in Wuhan, China, and is still challenging to control . The main focus of this paper is to investigate a novel fractional-order mathematical model that explains the behavior of COVID-19 in Ethiopia. Within the proposed model, the entire population is divided into nine groups, each with its own set of parameters and initial values. A nonlinear system of fractional differential equations for the model is represented using Caputo fractional derivative. Legendre spectral collocation method is used to convert this system into an algebraic system of equations. An inexact Newton iterative method is used to solve the model system. The effective reproduction number (R0) is computed by the next-generation matrix approach. Positivity and boundedness, as well as the existence and uniqueness of solution, are all investigated. Both endemic and disease-free equilibrium points, as well as their stability, are carefully studied. We calculated the parameters and starting conditions (ICs) provided for our model using data from the Ethiopian Public Health Institute (EPHI) and the Ethiopian Ministry of Health from 22 June 2020 to 28 February 2021. The model parameters are determined using least squares curve fitting and MATLAB R2020a is used to run numerical results. The basic reproduction number is R0=1.4575. For this value, disease free equilibrium point is asymptotically unstable and endemic equilibrium point is asymptotically stable, both locally and globally.

AVA - A Cloud-based Banking Virtual Assistant

The world is embracing a digital revolution and entering a millennial generation of banking. However, the literal and conservative bounds of the society who choose to stick to a traditional banking approach, prefer the in-person experience for banking. The staff at any bank undergo tremendous pressure doing trivial tasks to offer basic services like balance inquiry and fixed deposits, loan inquiries, etc. Given the limited time of banking hours and the highly dense population of India, it has been a burden, especially during the COVID-19 pandemic. This motivates us to introduce Ambar Virtual Assistant (AVA), which will take care of the trivial tasks aforementioned. The ability of AVA to converse in the national language (Hindi) along with English, will ensure better customer satisfaction to bridge the gap between diversity, education, and innovation. © 2021 IEEE.

A study on requirement of cold chain maintenance for reliable testing of SARS-CoV-2 samples

Introduction: Coronavirus Disease 2019 (COVID-19) has been haunting the world since December 2019 and has grown to pandemic proportions from March 2020. Even after a full year of research and study, the most effective way to control the spread of this infection is early diagnosis and isolation of the cases. Real-time Reverse Transcription Polymerase Chain Reaction (RT-PCR) is considered the standard test all over the world for the diagnosis of Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) infection. All the sample collection guidelines have recommended stringent maintenance of the cold chain for the sample transport. However, it is not possible for the resource constrained developing countries with inadequate infrastructure to comply with these guidelines all the time. Aim: To determine necessity of these stringent transport criteria and the effect of temperature on the clinical sensitivity of a RT-PCR assay for diagnosis of SARS-CoV-2 infection. Materials and Methods: In this prospective experimental study conducted in November 2020, 49 positive samples were kept at ambient room temperature and were tested everyday with RT-PCR for the detection of SARS-CoV-2 Ribonucleic Acid (RNA). The samples were also kept under refrigeration at the 4°C and were also tested by RT-PCR and the results were compared with their respective counterparts kept at room temperature till nine days. Python Jupiter notebook SciPy and Anaconda software was used for statistical analysis. Results: It was observed that the positivity of the RT-PCR results were not deteriorated till five days and there was no significant deterioration even after nine days of samples being stored at room temperature suggesting that even if the viral RNA itself is not stable outside strict temperature control but small fragment or target genetic sequences are enough for detection of virus by RT-PCR. Conclusion: It is possible to keep samples at this ambient temperature for five days without any loss of positivity in RT-PCR.

Effective Teaching Practices for Success During COVID 19 Pandemic: Towards Phygital Learning

Following the outbreak of COVID 19 in February 2020, Indian universities were shut down and used digital platforms to teach their students since then. Drawing from Kolb’s Learning Theory, John Dewey’s theory, Jack Mezirows transformative learning theory, and Jean Piaget’s theory, the authors in this paper offer a viewpoint on some of the practical teaching practices which can be adapted in business schools in India to be successful in this emerging blended or phygital environment. Using a Community of Inquiry (CoI) framework, the authors reflect on the effective teaching practices based on their own experience, theoretical knowledge gained from an exhaustive web search of various databases of the period, particularly from February to August 2020. The authors performed a careful manual content analysis of the selected research papers. They concluded seven principal teaching methods to create an effective blended environment for students and faculties in Indian business schools: a) reframing virtual spaces in India through online knowledge repository and virtual labs b) using reflective thinking for andragogical and pedagogical Indian approach c) Indian teachers’ readiness to offer various genres of courses on demand d) reinforcing resilience in Indian schools through meaningful participation and conflict resolution e) purposeful learning and inquiry-based learning for Indian students f) experiential learning through an inclusive online pivot in India g) useful apps are discussed to reach out to Indian parents community. These initiatives can influence academicians, educationists, podcasters, and the entire teacher fraternity to design an efficient and adequate teaching plan for the student community in India. © Copyright © 2021 Chaturvedi, Purohit and Verma.

A nonlinear epidemiological model considering asymptotic and quarantine classes for SARS CoV-2 virus.

In this article, we develop a mathematical model considering susceptible, exposed, infected, asymptotic, quarantine/isolation and recovered classes as in case of COVID-19 disease. The facility of quarantine/isolation have been provided to both exposed and infected classes. Asymptotic individuals either recovered without undergo treatment or moved to infected class after some duration. We have formulated the reproduction number for the proposed model. Elasticity and sensitivity analysis indicates that model is more sensitive towards the transmission rate from exposed to infected classes rather than transmission rate from susceptible to exposed class. Analysis of global stability for the proposed model is studied through Lyapunov's function.